{ "01030000000187.pdf": { "elements": [ { "coordinates": [ { "x": 0.12233703583478928, "y": 0.08324472606182098 }, { "x": 0.8755038306117058, "y": 0.08324472606182098 }, { "x": 0.8755038306117058, "y": 0.16236083209514618 }, { "x": 0.12233703583478928, "y": 0.16236083209514618 } ], "category": "table", "id": 793, "content": { "text": "", "html": "
Properties Instruction Training Datasets Alignment
Alpaca-GPT4OpenOrcaSynth. Math-InstructOrca DPO PairsUltrafeedback CleanedSynth. Math-Alignment
Total # Samples52K2.91M126K12.9K60.8K126K
Maximum # Samples Used52K100K52K12.9K60.8K20.1K
Open SourceooOo
", "markdown": "" } }, { "coordinates": [ { "x": 0.11762748658657074, "y": 0.1743798404932022 }, { "x": 0.8825521320104599, "y": 0.1743798404932022 }, { "x": 0.8825521320104599, "y": 0.2718224301934242 }, { "x": 0.11762748658657074, "y": 0.2718224301934242 } ], "category": "paragraph", "id": 833, "content": { "text": "Table 1: Training datasets used for the instruction and alignment tuning stages, respectively. For the instruction\ntuning process, we utilized the Alpaca-GPT4 (Peng et al., 2023), OpenOrca (Mukherjee et al., 2023), and Synth.\nMath-Instruct datasets, while for the alignment tuning, we employed the Orca DPO Pairs (Intel, 2023), Ultrafeedback\nCleaned (Cui et al., 2023; Ivison et al., 2023), and Synth. Math-Alignment datasets. The 'Total # Samples indicates\nthe total number of samples in the entire dataset. The 'Maximum # Samples Used' indicates the actual maximum\nnumber of samples that were used in training, which could be lower than the total number of samples in a given\ndataset. 'Open Source indicates whether the dataset is open-sourced.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1179724857211113, "y": 0.30027636885643005 }, { "x": 0.4877632185816765, "y": 0.30027636885643005 }, { "x": 0.4877632185816765, "y": 0.42568156123161316 }, { "x": 0.1179724857211113, "y": 0.42568156123161316 } ], "category": "paragraph", "id": 834, "content": { "text": "pretraining to quickly recover performance. We\nattribute the success of DUS to reducing such dis-\ncrepancies in both the depthwise scaling and the\ncontinued pretraining steps. We also hypothesize\nthat other methods of depthwise scaling could also\nwork for DUS, as long as the discrepancy in the\nscaled model is sufficiently contained before the\ncontinued pretraining step.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11818179488182068, "y": 0.4381539821624756 }, { "x": 0.4877135455608368, "y": 0.4381539821624756 }, { "x": 0.4877135455608368, "y": 0.5965583026409149 }, { "x": 0.11818179488182068, "y": 0.5965583026409149 } ], "category": "paragraph", "id": 835, "content": { "text": "Comparison to other up-scaling methods. Un-\nlike Komatsuzaki et al. (2022), depthwise scaled\nmodels do not require additional modules like gat-\ning networks or dynamic expert selection. Conse-\nquently, scaled models in DUS do not necessitate\na distinct training framework for optimal training\nefficiency, nor do they require specialized CUDA\nkernels for fast inference. A DUS model can seam-\nlessly integrate into existing training and inference\nframeworks while maintaining high efficiency.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11835789680480957, "y": 0.6121742725372314 }, { "x": 0.2874200791120529, "y": 0.6121742725372314 }, { "x": 0.2874200791120529, "y": 0.6261339224874973 }, { "x": 0.11835789680480957, "y": 0.6261339224874973 } ], "category": "heading1", "id": 836, "content": { "text": "3\nTraining Details\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1179506778717041, "y": 0.6385002136230469 }, { "x": 0.4866051971912384, "y": 0.6385002136230469 }, { "x": 0.4866051971912384, "y": 0.6837581247091293 }, { "x": 0.1179506778717041, "y": 0.6837581247091293 } ], "category": "paragraph", "id": 837, "content": { "text": "After DUS, including continued pretraining, we\nperform fine-tuning of SOLAR 10.7B in two stages:\n1) instruction tuning and 2) alignment tuning.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11781125515699387, "y": 0.696702241897583 }, { "x": 0.4878057464957237, "y": 0.696702241897583 }, { "x": 0.4878057464957237, "y": 0.9189854860305786 }, { "x": 0.11781125515699387, "y": 0.9189854860305786 } ], "category": "paragraph", "id": 838, "content": { "text": "Instruction tuning. In the instruction tuning\nstage, the model is trained to follow instructions in\na QA format (Zhang et al., 2023b). We mostly use\nopen-source datasets but also synthesize a math QA\ndataset to enhance the model's mathematical capa-\nbilities. A rundown of how we crafted the dataset is\nas follows. First, seed math data are collected from\nthe Math (Hendrycks et al., 2021) dataset only, to\navoid contamination with commonly used bench-\nmark datasets such as GSM8K (Cobbe et al., 2021).\nThen, using a process similar to MetaMath (Yu\net al., 2023), we rephrase the questions and an-\nswers of the seed math data. We use the resulting\nrephrased question-answer pairs as a QA dataset\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5138390064239502, "y": 0.30028119683265686 }, { "x": 0.760803297162056, "y": 0.30028119683265686 }, { "x": 0.760803297162056, "y": 0.3128034770488739 }, { "x": 0.5138390064239502, "y": 0.3128034770488739 } ], "category": "paragraph", "id": 839, "content": { "text": "and call it 'Synth. Math-Instruct\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5121304392814636, "y": 0.3271423578262329 }, { "x": 0.8825632929801941, "y": 0.3271423578262329 }, { "x": 0.8825632929801941, "y": 0.4847298115491867 }, { "x": 0.5121304392814636, "y": 0.4847298115491867 } ], "category": "paragraph", "id": 840, "content": { "text": "Alignment tuning. In the alignment tuning stage,\nthe instruction-tuned model is further fine-tuned to\nbe more aligned with human or strong AI (e.g.,\nGPT4 (OpenAI, 2023)) preferences using direct\npreference optimization (DPO) (Rafailov et al.,\n2023). Similar to the instruction tuning stage, we\nuse mostly open-source datasets but also synthe-\nsize a math-focused alignment dataset utilizing the\n'Synth. Math-Instruct dataset mentioned in the\ninstruction tuning stage.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5119680762290955, "y": 0.489070862531662 }, { "x": 0.8829610347747803, "y": 0.489070862531662 }, { "x": 0.8829610347747803, "y": 0.7270951122045517 }, { "x": 0.5119680762290955, "y": 0.7270951122045517 } ], "category": "paragraph", "id": 841, "content": { "text": "The alignment data synthesis process is as\nfollows. We take advantage of the fact that\nthe rephrased question-answer pairs in Synth.\nMath-Instruct data are beneficial in enhancing the\nmodel's mathematical capabilities (see Sec. 4.3.1).\nThus, we speculate that the rephrased answer to the\nrephrased question is a better answer than the orig-\ninal answer, possibly due to the interim rephrasing\nstep. Consequently, we set the rephrased question\nas the prompt and use the rephrased answer as the\nchosen response and the original answer as the re-\njected response and create the {prompt, chosen,\nrejected} DPO tuple. We aggregate the tuples from\nthe rephrased question-answer pairs and call the\nresulting dataset 'Synth. Math-Alignment\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5131054520606995, "y": 0.7438886165618896 }, { "x": 0.6063991114497185, "y": 0.7438886165618896 }, { "x": 0.6063991114497185, "y": 0.7546981871128082 }, { "x": 0.5131054520606995, "y": 0.7546981871128082 } ], "category": "heading1", "id": 842, "content": { "text": "4 Results\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5131274461746216, "y": 0.7713144421577454 }, { "x": 0.7200952470302582, "y": 0.7713144421577454 }, { "x": 0.7200952470302582, "y": 0.7835732288658619 }, { "x": 0.5131274461746216, "y": 0.7835732288658619 } ], "category": "heading1", "id": 843, "content": { "text": "4.1\nExperimental Details\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5135653018951416, "y": 0.793268084526062 }, { "x": 0.8829649984836578, "y": 0.793268084526062 }, { "x": 0.8829649984836578, "y": 0.9184577912092209 }, { "x": 0.5135653018951416, "y": 0.9184577912092209 } ], "category": "paragraph", "id": 844, "content": { "text": "Training datasets. We present details regarding\nour training datasets for the instruction and align-\nment tuning stages in Tab. 1. We do not always\nuse the entire dataset and instead subsample a set\namount. Note that most of our training data is\nopen-source, and the undisclosed datasets can be\nsubstituted for open-source alternatives such as the\nMetaMathQA (Yu et al., 2023) dataset.\n", "html": "", "markdown": "" } } ] }, "01030000000049.pdf": { "elements": [ { "coordinates": [ { "x": 0.24129877984523773, "y": 0.05679428577423096 }, { "x": 0.8409502357244492, "y": 0.05679428577423096 }, { "x": 0.8409502357244492, "y": 0.07222497183829546 }, { "x": 0.24129877984523773, "y": 0.07222497183829546 } ], "category": "header", "id": 396, "content": { "text": "Overcoming Barriers to Filipino Women's Political Representation\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8883789777755737, "y": 0.05789290368556976 }, { "x": 0.9014906920492649, "y": 0.05789290368556976 }, { "x": 0.9014906920492649, "y": 0.07049464713782072 }, { "x": 0.8883789777755737, "y": 0.07049464713782072 } ], "category": "paragraph", "id": 397, "content": { "text": "9\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14520542323589325, "y": 0.10976089537143707 }, { "x": 0.8968019336462021, "y": 0.10976089537143707 }, { "x": 0.8968019336462021, "y": 0.3398113250732422 }, { "x": 0.14520542323589325, "y": 0.3398113250732422 } ], "category": "paragraph", "id": 398, "content": { "text": "The post-World War II period saw women participating in formal\npolitics and even attempting to form a political party and an alliance\nsupporting President Ramon Magsaysay's candidacy for the presidency\n(He served as president from 1953 to 1957), while the advent of the\nmartial law period in 1972 witnessed feminist movements. Roces (2012,\n6) attributes this to the burgeoning student movement and activism, SO\nmuch so that by the time Marcos declared martial law, women were\nprepared to take on the resistance. Though inspired by North America's\nsecond-wave feminists, Filipino women were also drawn to the era's\ndiscourses and contexts, such as the Vietnam War and the civil rights\nmovement.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14478325843811035, "y": 0.3610687553882599 }, { "x": 0.8962339162826538, "y": 0.3610687553882599 }, { "x": 0.8962339162826538, "y": 0.5945499688386917 }, { "x": 0.14478325843811035, "y": 0.5945499688386917 } ], "category": "paragraph", "id": 399, "content": { "text": "The women's movement continued to flourish in the Cory Aquino\nregime (1986-1992). The democratic transition provided political\nopportunity structures and venues ensuring women's access to the\nstate and nonstate spheres. The drafting of the 1987 Constitution\nwas one such opportunity. The movement managed to advocate for\nimportant provisions paving the way for women's rights legislation\nfrom the 1980s to the present. The provision in the 1987 Constitution\nmandates the state to recognize \"the role of women in nation building\nand shall ensure the fundamental equality before the law of men and\nwomen\" (Article 2, Section 14). This provision is said to be unique and\nis not even found in other countries' charters (Masilungan n.d.).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14308877289295197, "y": 0.6128485202789307 }, { "x": 0.8978015333414078, "y": 0.6128485202789307 }, { "x": 0.8978015333414078, "y": 0.8459727019071579 }, { "x": 0.14308877289295197, "y": 0.8459727019071579 } ], "category": "paragraph", "id": 400, "content": { "text": "The post-Marcos period advanced the participation of women\nnot only in civil society and nongovernment organizations but also in\nformal politics and bureaucracy. Several women from the movement\njoined formal politics, while others were invited by the Aquino and\nRamos governments (1992-1998) to executive posts. The entry of\nwomen activists, NGO leaders, and those from the academe ensured that\nthe new democracy would significantly help push measures promoting\nwomen's rights and gender equality. The House of Representative\n(HOR) and Philippine Commission on Women (PCW)'s \"How to Be\na Gender-Responsive Legislator\" (2021, 52) listed several recent laws\nresponding to women's empowerment and gender equality.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.19862568378448486, "y": 0.8643929958343506 }, { "x": 0.8285477161407471, "y": 0.8643929958343506 }, { "x": 0.8285477161407471, "y": 0.8814798966050148 }, { "x": 0.19862568378448486, "y": 0.8814798966050148 } ], "category": "paragraph", "id": 402, "content": { "text": "Republic Act No. 11313: Safe Spaces Act (April 17, 2019)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.19791695475578308, "y": 0.9003195762634277 }, { "x": 0.8954156935214996, "y": 0.9003195762634277 }, { "x": 0.8954156935214996, "y": 0.9388586208224297 }, { "x": 0.19791695475578308, "y": 0.9388586208224297 } ], "category": "paragraph", "id": 403, "content": { "text": "Republic Act No. 11210: 105-Day Expanded Maternity Leave\nLaw (March 11, 2019)\n", "html": "", "markdown": "" } } ] }, "01030000000013.pdf": { "elements": [ { "coordinates": [ { "x": 0.11483638733625412, "y": 0.04969889298081398 }, { "x": 0.1255482556298375, "y": 0.04969889298081398 }, { "x": 0.1255482556298375, "y": 0.058144026435911655 }, { "x": 0.11483638733625412, "y": 0.058144026435911655 } ], "category": "paragraph", "id": 422, "content": { "text": "o\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.7155578136444092, "y": 0.04984360560774803 }, { "x": 0.8968027234077454, "y": 0.04984360560774803 }, { "x": 0.8968027234077454, "y": 0.05852785427123308 }, { "x": 0.7155578136444092, "y": 0.05852785427123308 } ], "category": "header", "id": 423, "content": { "text": "AL-OGAYYEL AND OSKAY\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1118895635008812, "y": 0.0737309679389 }, { "x": 0.48739781230688095, "y": 0.0737309679389 }, { "x": 0.48739781230688095, "y": 0.6473607644438744 }, { "x": 0.1118895635008812, "y": 0.6473607644438744 } ], "category": "figure", "id": 424, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11178414523601532, "y": 0.6566758155822754 }, { "x": 0.466001495718956, "y": 0.6566758155822754 }, { "x": 0.466001495718956, "y": 0.6686947615817189 }, { "x": 0.11178414523601532, "y": 0.6686947615817189 } ], "category": "paragraph", "id": 425, "content": { "text": "IGURE\n8.7A-C A gazelle horn used in al-Sadu weaving.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14393244683742523, "y": 0.7043753862380981 }, { "x": 0.4640863388776779, "y": 0.7043753862380981 }, { "x": 0.4640863388776779, "y": 0.7186481636017561 }, { "x": 0.14393244683742523, "y": 0.7186481636017561 } ], "category": "heading1", "id": 426, "content": { "text": "Al-Sadu Symbols and Social Significance\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11063725501298904, "y": 0.7403568029403687 }, { "x": 0.4880388453602791, "y": 0.7403568029403687 }, { "x": 0.4880388453602791, "y": 0.9011487662792206 }, { "x": 0.11063725501298904, "y": 0.9011487662792206 } ], "category": "paragraph", "id": 427, "content": { "text": "erhaps the main reason for the uniqueness of\nl-Sadu weaving is that it was never mass-pro-\nluced for export in the same way other carpets\nwere. Although it was traded among tribes, due\no the length of time it takes to produce a tent,\nnd due to its particular function in the harsh\nlimate of the desert, it was not replicable in\nther geographies. Al-Sadu weaving could not\ne commercialized in the same way that other\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5112396478652954, "y": 0.07688446342945099 }, { "x": 0.8961632251739502, "y": 0.07688446342945099 }, { "x": 0.8961632251739502, "y": 0.2385886013507843 }, { "x": 0.5112396478652954, "y": 0.2385886013507843 } ], "category": "figure", "id": 428, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5126904249191284, "y": 0.24745388329029083 }, { "x": 0.8510917127132416, "y": 0.24745388329029083 }, { "x": 0.8510917127132416, "y": 0.275539293885231 }, { "x": 0.5126904249191284, "y": 0.275539293885231 } ], "category": "paragraph", "id": 429, "content": { "text": "FIGURE 8.8 Symbol of stars in contemporary al-Sadu\nweaving by Leila Yaser.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.511665403842926, "y": 0.3018326163291931 }, { "x": 0.8965682983398438, "y": 0.3018326163291931 }, { "x": 0.8965682983398438, "y": 0.481335312128067 }, { "x": 0.511665403842926, "y": 0.481335312128067 } ], "category": "paragraph", "id": 430, "content": { "text": "objects-such as kilims, clothes, bags, blankets,\nand tablecloths-were in other parts of the\nworld. Therefore, although the weaving practice\nand the symbols used may have changed, they\ndid not change as much as in other textiles, SO\nexamining the symbols embedded in these weav-\nings may yield a wealth of information about the\nlife of local populations. In the absence of writ-\nten records, al-Sadu weavings become, thus, re-\ncords of memories embodied in a thing.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5119345784187317, "y": 0.48500752449035645 }, { "x": 0.8965320587158203, "y": 0.48500752449035645 }, { "x": 0.8965320587158203, "y": 0.6641874611377716 }, { "x": 0.5119345784187317, "y": 0.6641874611377716 } ], "category": "paragraph", "id": 431, "content": { "text": "The natural environment of the nomadic tribe\ncan be seen in al-Sadu designs, which contain\nsymbols that reflect astronomical elements and\nthe desert environment. 24 Quite frequently, al-\nSadu symbols indicate constellations and stars\n(fig. 8.8). 25 In the vast sky of the pre-electric desert,\nthe stars, the moon, and the sun had a great signifi-\ncance, being the main sources of orientation. It is\nimportant to note that, currently, the weavers in\nKuwait explain these symbols simply as \"stars,\"\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5122129917144775, "y": 0.6937728524208069 }, { "x": 0.896626353263855, "y": 0.6937728524208069 }, { "x": 0.896626353263855, "y": 0.8525489717721939 }, { "x": 0.5122129917144775, "y": 0.8525489717721939 } ], "category": "paragraph", "id": 432, "content": { "text": "24\nFor more details on the symbols that appear in al-Sadu\nweavings, see also Altaf Salem Al-Ali Al-Sabah, Ibjad:\nOrnate Tent Dividers and Weavings of the Kuwait Desert\n(Kuwait: Al Sadu Society, 2006); Khawla Mohamed Ab-\ndel and Aziez Al Manai, Al Sadu (Doha: National Mu-\nseum of Qatar, 2013); and Ali S. Alnajadah, \"The Picto-\ngraphic Codes in Al-Sadu Weavings of Kuwait,'\nInternational Design Journal 8, no. 3 (2018): 63-74. In\nthis latter study, Alnajadah tracks changes in the mean-\nings of some al-Sadu symbols.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5128353238105774, "y": 0.8568351864814758 }, { "x": 0.8959129452705383, "y": 0.8568351864814758 }, { "x": 0.8959129452705383, "y": 0.9012698419392109 }, { "x": 0.5128353238105774, "y": 0.9012698419392109 } ], "category": "paragraph", "id": 433, "content": { "text": "25\nKhawlah M. Manna, Al-Sadu in Qatar: Traditional Tech-\nnical Values and Techniques (Doha: Qatar Museums\nAuthority, Qatar National Museum, 2013), 99-100.\n", "html": "", "markdown": "" } } ] }, "01030000000072.pdf": { "elements": [ { "coordinates": [ { "x": 0.21184834837913513, "y": 0.8090833425521851 }, { "x": 0.796335905790329, "y": 0.8090833425521851 }, { "x": 0.796335905790329, "y": 0.8387909196317196 }, { "x": 0.21184834837913513, "y": 0.8387909196317196 } ], "category": "table", "id": 275, "content": { "text": "", "html": "
Figure 4Komnas HAM's YouTube channel as of 1 December 2021
", "markdown": "" } }, { "coordinates": [ { "x": 0.180635467171669, "y": 0.09165783226490021 }, { "x": 0.8123466521501541, "y": 0.09165783226490021 }, { "x": 0.8123466521501541, "y": 0.3384377360343933 }, { "x": 0.180635467171669, "y": 0.3384377360343933 } ], "category": "figure", "id": 278, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.21452686190605164, "y": 0.3559819161891937 }, { "x": 0.7719407379627228, "y": 0.3559819161891937 }, { "x": 0.7719407379627228, "y": 0.38405271992087364 }, { "x": 0.21452686190605164, "y": 0.38405271992087364 } ], "category": "heading1", "id": 279, "content": { "text": "Distribution of Komnas HAM's YouTube Content (2019-\nDiagram 5\n2020)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11986948549747467, "y": 0.4070446491241455 }, { "x": 0.879678025841713, "y": 0.4070446491241455 }, { "x": 0.879678025841713, "y": 0.5353904366493225 }, { "x": 0.11986948549747467, "y": 0.5353904366493225 } ], "category": "paragraph", "id": 280, "content": { "text": "As of 1 December 2021, the Komnas HAM's YouTube channel has 2,290\nsubscribers with 185,676 total views. In the 2019-2020 period, content that specifically\ndiscusses the SDGs explicitly cannot be found on the Komnas HAM's YouTube.\nNevertheless, on 15 December 2021, the Tanggap Rasa Podcast with the title of\n\"Podcast #EP32: SDGs dan Anak Muda\" (Translation: \"Podcast #EP32: SDGs and\nYouth\") has been broadcast and can increase the awareness and understanding of\nthe citizen on the SDGs, especially towards young generations.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.13082605600357056, "y": 0.547085165977478 }, { "x": 0.878253698348999, "y": 0.547085165977478 }, { "x": 0.878253698348999, "y": 0.753590315580368 }, { "x": 0.13082605600357056, "y": 0.753590315580368 } ], "category": "figure", "id": 281, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.22222572565078735, "y": 0.8186702728271484 }, { "x": 0.28680142015218735, "y": 0.8186702728271484 }, { "x": 0.28680142015218735, "y": 0.8306497298181057 }, { "x": 0.22222572565078735, "y": 0.8306497298181057 } ], "category": "paragraph", "id": 282, "content": { "text": "Figure 4\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.34293535351753235, "y": 0.8125379085540771 }, { "x": 0.7542074620723724, "y": 0.8125379085540771 }, { "x": 0.7542074620723724, "y": 0.8365274760872126 }, { "x": 0.34293535351753235, "y": 0.8365274760872126 } ], "category": "paragraph", "id": 283, "content": { "text": "Komnas HAM's YouTube channel as of 1 December\n2021\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.4901881217956543, "y": 0.9322142601013184 }, { "x": 0.5066115856170654, "y": 0.9322142601013184 }, { "x": 0.5066115856170654, "y": 0.941533581353724 }, { "x": 0.4901881217956543, "y": 0.941533581353724 } ], "category": "paragraph", "id": 284, "content": { "text": "21\n", "html": "", "markdown": "" } } ] }, "01030000000099.pdf": { "elements": [ { "coordinates": [ { "x": 0.22625724971294403, "y": 0.0843815952539444 }, { "x": 0.7722651809453964, "y": 0.0843815952539444 }, { "x": 0.7722651809453964, "y": 0.5045662373304367 }, { "x": 0.22625724971294403, "y": 0.5045662373304367 } ], "category": "figure", "id": 204, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.21172726154327393, "y": 0.5192738175392151 }, { "x": 0.37678009271621704, "y": 0.5192738175392151 }, { "x": 0.37678009271621704, "y": 0.5303959893062711 }, { "x": 0.21172726154327393, "y": 0.5303959893062711 } ], "category": "paragraph", "id": 205, "content": { "text": "(Pope and Schweitzer 2011)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08965620398521423, "y": 0.5453158020973206 }, { "x": 0.9082312285900116, "y": 0.5453158020973206 }, { "x": 0.9082312285900116, "y": 0.6377086564898491 }, { "x": 0.08965620398521423, "y": 0.6377086564898491 } ], "category": "paragraph", "id": 206, "content": { "text": "To reiterate, this study's main econometric results reveal a negative effect on sinking a putt when\nthe typical golfer is putting for birdie, and a positive effect on putting for bogey. Consistent with the\nprevious graphs, these numerical results suggest that the typical professional golfer is more likely to\nsink a put for bogey and less likely to sink the putt for birdie (i.e., the typical golfer is indeed loss\naverse). 10\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09187865257263184, "y": 0.6600947380065918 }, { "x": 0.6848289966583252, "y": 0.6600947380065918 }, { "x": 0.6848289966583252, "y": 0.6711525181308389 }, { "x": 0.09187865257263184, "y": 0.6711525181308389 } ], "category": "heading1", "id": 207, "content": { "text": "ARE CIGARETTE SMOKERS HYPERBOLIC TIME DISCOUNTERS?\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08980368077754974, "y": 0.6900042295455933 }, { "x": 0.9073487967252731, "y": 0.6900042295455933 }, { "x": 0.9073487967252731, "y": 0.7442620433866978 }, { "x": 0.08980368077754974, "y": 0.7442620433866978 } ], "category": "paragraph", "id": 208, "content": { "text": "Recall from Chapter 4 the distinction between time-consistent exponential time discounters (Homo\neconomicus) and potentially time-inconsistent hyperbolic discounters (Homo sapiens). The discounting\ntime paths for exponential versus hyperbolic discounting looked like this:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.06999927014112473, "y": 0.9155927300453186 }, { "x": 0.9030833765864372, "y": 0.9155927300453186 }, { "x": 0.9030833765864372, "y": 0.9438757132738829 }, { "x": 0.06999927014112473, "y": 0.9438757132738829 } ], "category": "footer", "id": 209, "content": { "text": "10. A negative effect associated with putting for double bogey suggests that the typical golfer suppresses his inclination for loss\naversion when putting for a score worse than bogey.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.640755832195282, "y": 0.9514410495758057 }, { "x": 0.9061424732208252, "y": 0.9514410495758057 }, { "x": 0.9061424732208252, "y": 0.9586713355965912 }, { "x": 0.640755832195282, "y": 0.9586713355965912 } ], "category": "footer", "id": 210, "content": { "text": "BEHAVIORAL ECONOMICS PRACTICUM 193\n", "html": "", "markdown": "" } } ] }, "01030000000154.pdf": { "elements": [ { "coordinates": [ { "x": 0.08988052606582642, "y": 0.08341553062200546 }, { "x": 0.906297504901886, "y": 0.08341553062200546 }, { "x": 0.906297504901886, "y": 0.4139131233096123 }, { "x": 0.08988052606582642, "y": 0.4139131233096123 } ], "category": "table", "id": 146, "content": { "text": "", "html": "
66%
24%
18%
12%
6%8%
No textbook requiredAffordableZero costFreeLow costOER
", "markdown": "" } }, { "coordinates": [ { "x": 0.09278523921966553, "y": 0.07180226594209671 }, { "x": 0.9065304398536682, "y": 0.07180226594209671 }, { "x": 0.9065304398536682, "y": 0.4115651026368141 }, { "x": 0.09278523921966553, "y": 0.4115651026368141 } ], "category": "figure", "id": 189, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09220492094755173, "y": 0.4247712790966034 }, { "x": 0.577074371278286, "y": 0.4247712790966034 }, { "x": 0.577074371278286, "y": 0.43660150095820427 }, { "x": 0.09220492094755173, "y": 0.43660150095820427 } ], "category": "paragraph", "id": 190, "content": { "text": "Figure 7.1: Texas OER landscape survey results show terms used in course schedules\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0937090590596199, "y": 0.46145790815353394 }, { "x": 0.2663397565484047, "y": 0.46145790815353394 }, { "x": 0.2663397565484047, "y": 0.47283142898231745 }, { "x": 0.0937090590596199, "y": 0.47283142898231745 } ], "category": "heading1", "id": 191, "content": { "text": "IMPLEMENTATION\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09199462831020355, "y": 0.4906391203403473 }, { "x": 0.9073631018400192, "y": 0.4906391203403473 }, { "x": 0.9073631018400192, "y": 0.6045723855495453 }, { "x": 0.09199462831020355, "y": 0.6045723855495453 } ], "category": "paragraph", "id": 192, "content": { "text": "Locally, we implemented a quick and free solution that reflects the constraints of system capabilities,\nno financial support, and a local directive to vet every course to be tagged. Based on what was\nfeasible in the short term and conversations with key stakeholders (i.e., registrar, early OER adopters,\ncurriculum coordinators, student representatives, and the campus store), we incorporated an\n\"educational resources cost\" option into an existing \"course attribute\" drop-down menu under the\nsystem's advanced search options.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09275396913290024, "y": 0.9508891701698303 }, { "x": 0.10657139029353857, "y": 0.9508891701698303 }, { "x": 0.10657139029353857, "y": 0.9589489726349711 }, { "x": 0.09275396913290024, "y": 0.9589489726349711 } ], "category": "paragraph", "id": 193, "content": { "text": "18\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11287713795900345, "y": 0.9504043459892273 }, { "x": 0.9062606170773506, "y": 0.9504043459892273 }, { "x": 0.9062606170773506, "y": 0.9603010853752494 }, { "x": 0.11287713795900345, "y": 0.9603010853752494 } ], "category": "footer", "id": 194, "content": { "text": "BOYOUNG CHAE, KEVIN CORCORAN, MICHAEL DALY, ANN FIDDLER, JEFF GALLANT, JAMES GLAPA-GROSSKLAG, AMY HOFER, AND\n", "html": "", "markdown": "" } } ] }, "01030000000103.pdf": { "elements": [ { "coordinates": [ { "x": 0.12227077037096024, "y": 0.1542963981628418 }, { "x": 0.9471921995282173, "y": 0.1542963981628418 }, { "x": 0.9471921995282173, "y": 0.8161741495132446 }, { "x": 0.12227077037096024, "y": 0.8161741495132446 } ], "category": "table", "id": 215, "content": { "text": "", "html": "
- Open
o E R COMMONSStart by searching for information on platforms like OER Commons, where authors share their materials freely, ensuring no copyright issues.
02- Prepare Your Content Summarize or extract the key points from the materials you've found. This will be the content for your slides.
03- Generate Slides with ChatGPT Provide the summarized content to ChatGPT and instruct it to create a structured outline for Google Slides, including titles, main points, and any specific instructions for slide design.
04 - Create App Script Code After finalizing the slide structure, ask ChatGPT to generate a Google Apps Script code that can create these slides automatically.
05 - Execute in Google Apps Script Open Google Apps Script, start a new project, and paste the code provided by ChatGPT. Run the script to auto-generate your slide deck.
06 - Edit and Customize Once the slides are created, you can further edit and customize them in Google Slides according to your needs.
", "markdown": "" } }, { "coordinates": [ { "x": 0.40850692987442017, "y": 0.016087278723716736 }, { "x": 0.625423863530159, "y": 0.016087278723716736 }, { "x": 0.625423863530159, "y": 0.0333296786993742 }, { "x": 0.40850692987442017, "y": 0.0333296786993742 } ], "category": "header", "id": 231, "content": { "text": "WITH CHATGPT\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.17432253062725067, "y": 0.06695334613323212 }, { "x": 0.8258398026227951, "y": 0.06695334613323212 }, { "x": 0.8258398026227951, "y": 0.108063705265522 }, { "x": 0.17432253062725067, "y": 0.108063705265522 } ], "category": "heading1", "id": 232, "content": { "text": "CREATING SLIDES\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10242379456758499, "y": 0.13360367715358734 }, { "x": 0.24774008244276047, "y": 0.13360367715358734 }, { "x": 0.24774008244276047, "y": 0.2376473993062973 }, { "x": 0.10242379456758499, "y": 0.2376473993062973 } ], "category": "figure", "id": 233, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8359037637710571, "y": 0.0 }, { "x": 0.9979745149612427, "y": 0.0 }, { "x": 0.9979745149612427, "y": 0.18863096833229065 }, { "x": 0.8359037637710571, "y": 0.18863096833229065 } ], "category": "figure", "id": 234, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3070806562900543, "y": 0.14784696698188782 }, { "x": 0.7055140435695648, "y": 0.14784696698188782 }, { "x": 0.7055140435695648, "y": 0.16201092675328255 }, { "x": 0.3070806562900543, "y": 0.16201092675328255 } ], "category": "heading1", "id": 235, "content": { "text": "01 - Find Open Educational Resources\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.30695074796676636, "y": 0.17094068229198456 }, { "x": 0.927517294883728, "y": 0.17094068229198456 }, { "x": 0.927517294883728, "y": 0.2219901941716671 }, { "x": 0.30695074796676636, "y": 0.2219901941716671 } ], "category": "paragraph", "id": 236, "content": { "text": "Start by searching for information on platforms like OER\nCommons, where authors share their materials freely, ensuring\nno copyright issues.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09253992885351181, "y": 0.24691277742385864 }, { "x": 0.24930229038000107, "y": 0.24691277742385864 }, { "x": 0.24930229038000107, "y": 0.3508904352784157 }, { "x": 0.09253992885351181, "y": 0.3508904352784157 } ], "category": "figure", "id": 237, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.30710452795028687, "y": 0.26887401938438416 }, { "x": 0.5771201550960541, "y": 0.26887401938438416 }, { "x": 0.5771201550960541, "y": 0.2829838125035167 }, { "x": 0.30710452795028687, "y": 0.2829838125035167 } ], "category": "heading1", "id": 238, "content": { "text": "02- Prepare Your Content\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3064208924770355, "y": 0.29161056876182556 }, { "x": 0.9235560595989227, "y": 0.29161056876182556 }, { "x": 0.9235560595989227, "y": 0.3246648386120796 }, { "x": 0.3064208924770355, "y": 0.3246648386120796 } ], "category": "paragraph", "id": 239, "content": { "text": "Summarize or extract the key points from the materials you've\nfound. This will be the content for your slides.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10537830740213394, "y": 0.3688308298587799 }, { "x": 0.25194307416677475, "y": 0.3688308298587799 }, { "x": 0.25194307416677475, "y": 0.4619745910167694 }, { "x": 0.10537830740213394, "y": 0.4619745910167694 } ], "category": "figure", "id": 240, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3074057996273041, "y": 0.37218886613845825 }, { "x": 0.6771465241909027, "y": 0.37218886613845825 }, { "x": 0.6771465241909027, "y": 0.3840690543875098 }, { "x": 0.3074057996273041, "y": 0.3840690543875098 } ], "category": "heading1", "id": 241, "content": { "text": "03- Generate Slides with ChatGPT\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3071753978729248, "y": 0.39610156416893005 }, { "x": 0.9293132424354553, "y": 0.39610156416893005 }, { "x": 0.9293132424354553, "y": 0.4466363377869129 }, { "x": 0.3071753978729248, "y": 0.4466363377869129 } ], "category": "paragraph", "id": 242, "content": { "text": "Provide the summarized content to ChatGPT and instruct it to\ncreate a structured outline for Google Slides, including titles,\nmain points, and any specific instructions for slide design.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10359205305576324, "y": 0.4899180829524994 }, { "x": 0.246819868683815, "y": 0.4899180829524994 }, { "x": 0.246819868683815, "y": 0.5907450765371323 }, { "x": 0.10359205305576324, "y": 0.5907450765371323 } ], "category": "figure", "id": 243, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.30710938572883606, "y": 0.4979487955570221 }, { "x": 0.6054742336273193, "y": 0.4979487955570221 }, { "x": 0.6054742336273193, "y": 0.5123875038698316 }, { "x": 0.30710938572883606, "y": 0.5123875038698316 } ], "category": "heading1", "id": 244, "content": { "text": "04 - Create App Script Code\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.30626457929611206, "y": 0.5213486552238464 }, { "x": 0.9255204200744629, "y": 0.5213486552238464 }, { "x": 0.9255204200744629, "y": 0.5723966211080551 }, { "x": 0.30626457929611206, "y": 0.5723966211080551 } ], "category": "paragraph", "id": 245, "content": { "text": "After finalizing the slide structure, ask ChatGPT to generate a\nGoogle Apps Script code that can create these slides\nautomatically.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.30744919180870056, "y": 0.6083049774169922 }, { "x": 0.6813295185565948, "y": 0.6083049774169922 }, { "x": 0.6813295185565948, "y": 0.6227168394252658 }, { "x": 0.30744919180870056, "y": 0.6227168394252658 } ], "category": "heading1", "id": 246, "content": { "text": "05 - Execute in Google Apps Script\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09100880473852158, "y": 0.604003369808197 }, { "x": 0.2652270868420601, "y": 0.604003369808197 }, { "x": 0.2652270868420601, "y": 0.7135346159338951 }, { "x": 0.09100880473852158, "y": 0.7135346159338951 } ], "category": "figure", "id": 247, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3069574534893036, "y": 0.6324039101600647 }, { "x": 0.9469720423221588, "y": 0.6324039101600647 }, { "x": 0.9469720423221588, "y": 0.6803034394979477 }, { "x": 0.3069574534893036, "y": 0.6803034394979477 } ], "category": "paragraph", "id": 248, "content": { "text": "Open Google Apps Script, start a new project, and paste the\ncode provided by ChatGPT. Run the script to auto-generate your\nslide deck.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3074134588241577, "y": 0.7328197956085205 }, { "x": 0.5629608333110809, "y": 0.7328197956085205 }, { "x": 0.5629608333110809, "y": 0.7446707198396325 }, { "x": 0.3074134588241577, "y": 0.7446707198396325 } ], "category": "heading1", "id": 249, "content": { "text": "06 - Edit and Customize\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09052179008722305, "y": 0.7367880940437317 }, { "x": 0.2657202109694481, "y": 0.7367880940437317 }, { "x": 0.2657202109694481, "y": 0.8476699069142342 }, { "x": 0.09052179008722305, "y": 0.8476699069142342 } ], "category": "figure", "id": 250, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3075633943080902, "y": 0.7565896511077881 }, { "x": 0.9367015659809113, "y": 0.7565896511077881 }, { "x": 0.9367015659809113, "y": 0.7896079793572426 }, { "x": 0.3075633943080902, "y": 0.7896079793572426 } ], "category": "paragraph", "id": 251, "content": { "text": "Once the slides are created, you can further edit and customize\nthem in Google Slides according to your needs.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1726568341255188, "y": 0.8849180936813354 }, { "x": 0.8254963159561157, "y": 0.8849180936813354 }, { "x": 0.8254963159561157, "y": 0.931732852011919 }, { "x": 0.1726568341255188, "y": 0.931732852011919 } ], "category": "footer", "id": 252, "content": { "text": "INTERESTED IN FREE AI-CONSULTANCE OR\nCOLLABORATION WITH US?\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15766805410385132, "y": 0.9460690021514893 }, { "x": 0.8415380716323853, "y": 0.9460690021514893 }, { "x": 0.8415380716323853, "y": 0.9602243388071656 }, { "x": 0.15766805410385132, "y": 0.9602243388071656 } ], "category": "footer", "id": 253, "content": { "text": "EMAIL REBECCA.ALLEN@MSJ.EDU FOR MORE INFORMATION\n", "html": "", "markdown": "" } } ] }, "01030000000077.pdf": { "elements": [ { "coordinates": [ { "x": 0.1899181604385376, "y": 0.08350397646427155 }, { "x": 0.8809747099876404, "y": 0.08350397646427155 }, { "x": 0.8809747099876404, "y": 0.11644729226827621 }, { "x": 0.1899181604385376, "y": 0.11644729226827621 } ], "category": "paragraph", "id": 373, "content": { "text": "decline in 2020 in absolute numbers and as a percentage of 2019 deployment\n(Figure 1.9b).9\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1908283233642578, "y": 0.13135474920272827 }, { "x": 0.8808465600013733, "y": 0.13135474920272827 }, { "x": 0.8808465600013733, "y": 0.16376418247818947 }, { "x": 0.1908283233642578, "y": 0.16376418247818947 } ], "category": "paragraph", "id": 374, "content": { "text": "Figure 1.9b. Deployment of Overseas Foreign Workers by sex, new hires only\n(in thousands)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.18891552090644836, "y": 0.1747007966041565 }, { "x": 0.8809796869754791, "y": 0.1747007966041565 }, { "x": 0.8809796869754791, "y": 0.4078384190797806 }, { "x": 0.18891552090644836, "y": 0.4078384190797806 } ], "category": "figure", "id": 375, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.19023990631103516, "y": 0.42072582244873047 }, { "x": 0.5262030959129333, "y": 0.42072582244873047 }, { "x": 0.5262030959129333, "y": 0.43337497394531965 }, { "x": 0.19023990631103516, "y": 0.43337497394531965 } ], "category": "paragraph", "id": 376, "content": { "text": "Source: Philippine Statistics Authority (2022)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1432415097951889, "y": 0.4559457302093506 }, { "x": 0.6917935460805893, "y": 0.4559457302093506 }, { "x": 0.6917935460805893, "y": 0.47108236979693174 }, { "x": 0.1432415097951889, "y": 0.47108236979693174 } ], "category": "heading1", "id": 377, "content": { "text": "1.5. Migrant Workers More at Risk of COVID-19 Infection\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1895238608121872, "y": 0.4865959882736206 }, { "x": 0.8815876692533493, "y": 0.4865959882736206 }, { "x": 0.8815876692533493, "y": 0.6560332626104355 }, { "x": 0.1895238608121872, "y": 0.6560332626104355 } ], "category": "paragraph", "id": 378, "content": { "text": "COVID-19 infection among migrants appears to be higher than among\nnon-migrant groups (Hintermeier et al., 2020). Migrant workers are\ndisproportionately exposed to COVID-19 because of the nature of their\nwork and their living conditions. Many migrant workers performed essential\nservices, including jobs in healthcare, selected manufacturing, transportation,\nlogistics, construction, and maintenance, which continued during periods of\nmovement restrictions (OECD, ADBI and ILO, 2021). Many migrant workers\nalso have less access to personal protective equipment and testing and\ntreatment facilities (OECD, ADBI and ILO, 2021). The lack of access was\nespecially true for undocumented migrants.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.18941468000411987, "y": 0.670819878578186 }, { "x": 0.8807525038719177, "y": 0.670819878578186 }, { "x": 0.8807525038719177, "y": 0.7725658193230629 }, { "x": 0.18941468000411987, "y": 0.7725658193230629 } ], "category": "paragraph", "id": 379, "content": { "text": "Additionally, migrant workers employed in plantations far away from urban\ncentres had limited access to information and testing. High rates of infection\nwere also linked to overcrowded housing conditions, including shared facilities\nand sleeping areas, which increase the risk of transmission (ASEAN MP, 2021).\nMany workers in processing or assembly plants worked in conditions where\nphysical distancing was rarely observed.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.18995466828346252, "y": 0.7868915796279907 }, { "x": 0.8815793693065643, "y": 0.7868915796279907 }, { "x": 0.8815793693065643, "y": 0.8881495445966721 }, { "x": 0.18995466828346252, "y": 0.8881495445966721 } ], "category": "paragraph", "id": 380, "content": { "text": "In Malaysia, out of 2,188 positive cases recorded nationwide on 25 November\n2020, 1,511 were foreign workers employed by Top Glove Corporation Bhd.,\none of the world's largest personal protective equipment (PPE) manufacturers\n(The Straits Times, 2020; Ngui, 2020). Many other migrant workers were\nemployed as delivery agents, public transport drivers, or restaurant waiters,\nand are in constant contact with the general public. Infection risk is also higher\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1422392576932907, "y": 0.9065491557121277 }, { "x": 0.6799186319112778, "y": 0.9065491557121277 }, { "x": 0.6799186319112778, "y": 0.9190387511625886 }, { "x": 0.1422392576932907, "y": 0.9190387511625886 } ], "category": "footer", "id": 381, "content": { "text": "9\nKeeping in mind that for 2020 the figures are only up to October of the year.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14071707427501678, "y": 0.9516689777374268 }, { "x": 0.4201541990041733, "y": 0.9516689777374268 }, { "x": 0.4201541990041733, "y": 0.9669047528877854 }, { "x": 0.14071707427501678, "y": 0.9669047528877854 } ], "category": "footer", "id": 382, "content": { "text": "ASEAN Migration Outlook\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.9286197423934937, "y": 0.9526430368423462 }, { "x": 0.9490419086068869, "y": 0.9526430368423462 }, { "x": 0.9490419086068869, "y": 0.9637904735282063 }, { "x": 0.9286197423934937, "y": 0.9637904735282063 } ], "category": "paragraph", "id": 383, "content": { "text": "21\n", "html": "", "markdown": "" } } ] }, "01030000000039.pdf": { "elements": [ { "coordinates": [ { "x": 0.15873074531555176, "y": 0.07596137374639511 }, { "x": 0.9020787477493286, "y": 0.07596137374639511 }, { "x": 0.9020787477493286, "y": 0.08788005542010069 }, { "x": 0.15873074531555176, "y": 0.08788005542010069 } ], "category": "paragraph", "id": 307, "content": { "text": "Figure 9.4.1: Challenges in importing amongst tourism MSMEs who import - all survey phases (%)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.22292441129684448, "y": 0.0986485481262207 }, { "x": 0.8658657073974609, "y": 0.0986485481262207 }, { "x": 0.8658657073974609, "y": 0.33986927568912506 }, { "x": 0.22292441129684448, "y": 0.33986927568912506 } ], "category": "figure", "id": 308, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15794451534748077, "y": 0.36144527792930603 }, { "x": 0.5373168140649796, "y": 0.36144527792930603 }, { "x": 0.5373168140649796, "y": 0.40120936557650566 }, { "x": 0.15794451534748077, "y": 0.40120936557650566 } ], "category": "paragraph", "id": 309, "content": { "text": "There were very few tourism MSMEs that exported\nin each survey round. The base is too small for any\nconclusive analysis.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15829694271087646, "y": 0.41845935583114624 }, { "x": 0.5363636612892151, "y": 0.41845935583114624 }, { "x": 0.5363636612892151, "y": 0.4419354163110256 }, { "x": 0.15829694271087646, "y": 0.4419354163110256 } ], "category": "heading1", "id": 310, "content": { "text": "9.5. Adapting to the New Normal: Changing\nBusiness Models\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15832532942295074, "y": 0.4613450765609741 }, { "x": 0.5376155227422714, "y": 0.4613450765609741 }, { "x": 0.5376155227422714, "y": 0.5723016560077667 }, { "x": 0.15832532942295074, "y": 0.5723016560077667 } ], "category": "paragraph", "id": 311, "content": { "text": "In all survey phases, several MSMEs in the tourism\nsector reported changing their business models. In\nJuly 2020, 167 tourism MSMEs mentioned that they\nchanged their business model, in October 2020, 223\nmentioned the same, and in January 2021, it was 183\nMSMEs. Some changed models in more ways than\none. The main ways across all phases that MSMEs\nmade changes were:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.2034502476453781, "y": 0.5896275043487549 }, { "x": 0.4092555046081543, "y": 0.5896275043487549 }, { "x": 0.4092555046081543, "y": 0.6009865859523416 }, { "x": 0.2034502476453781, "y": 0.6009865859523416 } ], "category": "paragraph", "id": 312, "content": { "text": "Adapting to social distancing;\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.576119601726532, "y": 0.3615298569202423 }, { "x": 0.9313755035400391, "y": 0.3615298569202423 }, { "x": 0.9313755035400391, "y": 0.3862225655466318 }, { "x": 0.576119601726532, "y": 0.3862225655466318 } ], "category": "paragraph", "id": 314, "content": { "text": "Devising new ways to reach customers through\nonline markets or social media;\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5761610865592957, "y": 0.40416744351387024 }, { "x": 0.931136280298233, "y": 0.40416744351387024 }, { "x": 0.931136280298233, "y": 0.42968257516622543 }, { "x": 0.5761610865592957, "y": 0.42968257516622543 } ], "category": "paragraph", "id": 315, "content": { "text": "Moving into new products and services in high\ndemand during COVID-19;\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5766746401786804, "y": 0.44704970717430115 }, { "x": 0.798997089266777, "y": 0.44704970717430115 }, { "x": 0.798997089266777, "y": 0.4581797383725643 }, { "x": 0.5766746401786804, "y": 0.4581797383725643 } ], "category": "paragraph", "id": 316, "content": { "text": "Reducing employee salaries.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.552412748336792, "y": 0.4756021201610565 }, { "x": 0.9317962527275085, "y": 0.4756021201610565 }, { "x": 0.9317962527275085, "y": 0.6130807548761368 }, { "x": 0.552412748336792, "y": 0.6130807548761368 } ], "category": "paragraph", "id": 317, "content": { "text": "Compared to previous survey round results, in\nJanuary 2021, tourism MSMEs had increasingly\nshifted towards adapting to social distancing to\noperate (57%). 6 Starting online marketing remained a\npopular choice, as nearly a quarter (24%) mentioned\nit in January 2021, compared to 28% in July 2020 and\n31% in October 2020. Reducing employee salaries as\nan approach reduced considerably in January 2021 at\n8% of responses compared to 21% in July 2020 and\n24% in October 2020.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15867942571640015, "y": 0.8606281876564026 }, { "x": 0.5238825976848602, "y": 0.8606281876564026 }, { "x": 0.5238825976848602, "y": 0.8711791131645441 }, { "x": 0.15867942571640015, "y": 0.8711791131645441 } ], "category": "footer", "id": 318, "content": { "text": "6. Compared to 38% in July 2020 and 22% in October 2020.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.06518982350826263, "y": 0.9402389526367188 }, { "x": 0.0794128654524684, "y": 0.9402389526367188 }, { "x": 0.0794128654524684, "y": 0.9477090467698872 }, { "x": 0.06518982350826263, "y": 0.9477090467698872 } ], "category": "paragraph", "id": 319, "content": { "text": "39\n", "html": "", "markdown": "" } } ] }, "01030000000009.pdf": { "elements": [ { "coordinates": [ { "x": 0.10325287282466888, "y": 0.049902964383363724 }, { "x": 0.11974642984569073, "y": 0.049902964383363724 }, { "x": 0.11974642984569073, "y": 0.058081635273993015 }, { "x": 0.10325287282466888, "y": 0.058081635273993015 } ], "category": "paragraph", "id": 329, "content": { "text": "74\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.851375162601471, "y": 0.05034731701016426 }, { "x": 0.8960197865962982, "y": 0.05034731701016426 }, { "x": 0.8960197865962982, "y": 0.05798790883272886 }, { "x": 0.851375162601471, "y": 0.05798790883272886 } ], "category": "header", "id": 330, "content": { "text": "BAIRD\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11238103359937668, "y": 0.10741102695465088 }, { "x": 0.5861113592982292, "y": 0.10741102695465088 }, { "x": 0.5861113592982292, "y": 0.5806122422218323 }, { "x": 0.11238103359937668, "y": 0.5806122422218323 } ], "category": "figure", "id": 331, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.6236498951911926, "y": 0.5198641419410706 }, { "x": 0.8650058507919312, "y": 0.5198641419410706 }, { "x": 0.8650058507919312, "y": 0.588653452694416 }, { "x": 0.6236498951911926, "y": 0.588653452694416 } ], "category": "paragraph", "id": 332, "content": { "text": "FIGURE 4.3\nThe Honey-Moon [graphic]. Mezzotint,\nhand-colored.\nPRINTED FOR CARINGTON BOWLES,\nLONDON, JUNE 1777\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10334416478872299, "y": 0.6123700737953186 }, { "x": 0.4873029515147209, "y": 0.6123700737953186 }, { "x": 0.4873029515147209, "y": 0.7193570137023926 }, { "x": 0.10334416478872299, "y": 0.7193570137023926 } ], "category": "paragraph", "id": 333, "content": { "text": "this list, Richard Walker, apothecary to the Prince\nof Wales, adds Arabic henna, manna, and rhu-\nbarb.34 The influence of the Arabian medicine first\non the Greek, then on the French and English phy-\nsicians, although often decried, brought an influx\nof medicinal plants from or through the Arabian\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1445135772228241, "y": 0.7438521385192871 }, { "x": 0.4872005581855774, "y": 0.7438521385192871 }, { "x": 0.4872005581855774, "y": 0.8513738512992859 }, { "x": 0.1445135772228241, "y": 0.8513738512992859 } ], "category": "paragraph", "id": 334, "content": { "text": "Book. Interspersed with Some Occasional Observations\non Some of the Most Celebrated Modern Dispensatories,\nand the Present State of Pharmacy (London: Printed\nand Sold by R. Willock, 1744). This volume contains a\nwealth of detailed recipes for various afflictions, albeit\nproviding few specifics as to what was treated by using\nthem.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10354786366224289, "y": 0.8616054654121399 }, { "x": 0.1195443719625473, "y": 0.8616054654121399 }, { "x": 0.1195443719625473, "y": 0.8697375254705548 }, { "x": 0.10354786366224289, "y": 0.8697375254705548 } ], "category": "paragraph", "id": 335, "content": { "text": "34\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1443367898464203, "y": 0.8573513627052307 }, { "x": 0.4868359863758087, "y": 0.8573513627052307 }, { "x": 0.4868359863758087, "y": 0.9195577017962933 }, { "x": 0.1443367898464203, "y": 0.9195577017962933 } ], "category": "paragraph", "id": 336, "content": { "text": "Richard Walker, Memoirs of Medicine; Including a\nSketch of Medical History from the Earliest Accounts to\nthe Eighteenth Century (London: Printed for J. Johnson,\n1799).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5123732686042786, "y": 0.6126092076301575 }, { "x": 0.8971214890480042, "y": 0.6126092076301575 }, { "x": 0.8971214890480042, "y": 0.7378727793693542 }, { "x": 0.5123732686042786, "y": 0.7378727793693542 } ], "category": "paragraph", "id": 337, "content": { "text": "Peninsula to Europe, where they were customarily\nused in tinctures, purges, and other more or less\neffective elixirs. 35 Alternately, incense was used for\nits love-inducing and rejuvenating properties, as\nseen in an 1787 etching by James Gillray represent-\ning a group of five elderly women of fashion at-\ntending an altar of Love (fig. 4.5). 36\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5120858550071716, "y": 0.7599021196365356 }, { "x": 0.8975641131401062, "y": 0.7599021196365356 }, { "x": 0.8975641131401062, "y": 0.8712297827005386 }, { "x": 0.5120858550071716, "y": 0.8712297827005386 } ], "category": "paragraph", "id": 339, "content": { "text": "35\nFor the influence of the Arabian medicine on Western\nEurope, see volume 3 of John Astruc's Treatise on the\nDiseases of Women, in Which Is Attempted to Join a Just\nTheory to the Most Safe and Approved Practice... (Lon-\ndon: Printed for J. Nourse, 1767). For detailed recipes of\nmedicines containing ingredients of Arabic origin, see\nPharmacopoia Reformata cited above.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5125070810317993, "y": 0.8738232254981995 }, { "x": 0.8962226212024689, "y": 0.8738232254981995 }, { "x": 0.8962226212024689, "y": 0.9197044670581818 }, { "x": 0.5125070810317993, "y": 0.9197044670581818 } ], "category": "paragraph", "id": 340, "content": { "text": "36\nArabian incense is made by using frankincense or gum\nArabic resin mixed with sweet-smelling essential oils,\nsuch as myrrh and oud.\n", "html": "", "markdown": "" } } ] }, "01030000000119.pdf": { "elements": [ { "coordinates": [ { "x": 0.16536666452884674, "y": 0.20429952442646027 }, { "x": 0.9979804903268814, "y": 0.20429952442646027 }, { "x": 0.9979804903268814, "y": 0.4393334984779358 }, { "x": 0.16536666452884674, "y": 0.4393334984779358 } ], "category": "table", "id": 235, "content": { "text": "", "html": "
Mitosis (begins with a single cell)Meiosis (begins with a single cell)
# chromosomes in parent cells
# DNA replications
# nuclear divisions
# daughter cells produced
purpose
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JurisdictionGATS XVII Reservation (1994)Foreign Ownership PermittedRestrictions on Foreign OwnershipForeign Ownership Reporting Requirements
ArgentinaYYProhibition on ownership of property that contains or borders large and permanent bodies of water and of land in border security zones. Rural land can only be acquired upon certificate being granted (total percentage must not exceed 15% of the territory, in which shares of nationals of one country must not exceed 30%; maximum limit per foreigner; certain long-term residents exempted).
AustraliaNYApproval is needed from the Treasurer if the acquisition constitutes a \"significant action,\" including acquiring an interest in different types of land where the monetary threshold is met for that type of land. The Treasurer may prohibit a significant action that is found to be contrary to the national interest.Acquisitions of residential and agricultural land by foreign persons must be reported to the relevant government agency.
AustriaYYPrior authorization required with exceptions; authorization may be refused if the acquisition contradicts national public policy interests.
BelgiumNYNone.
BrazilYYAcquisition of rural property by an alien individual or company, including Brazilian companies controlled by foreigners, may not exceed 50 modules; foreign ownership of rural areas may not exceed a quarter of the surface of the municipalities, and ownership
", "markdown": "" } }, { "coordinates": [ { "x": 0.22931721806526184, "y": 0.047839995473623276 }, { "x": 0.769556313753128, "y": 0.047839995473623276 }, { "x": 0.769556313753128, "y": 0.06205179821699858 }, { "x": 0.22931721806526184, "y": 0.06205179821699858 } ], "category": "header", "id": 348, "content": { "text": "Restrictions on Land Ownership by Foreigners in Selected Jurisdictions\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3138399124145508, "y": 0.09549953788518906 }, { "x": 0.6855439245700836, "y": 0.09549953788518906 }, { "x": 0.6855439245700836, "y": 0.11695171892642975 }, { "x": 0.3138399124145508, "y": 0.11695171892642975 } ], "category": "heading1", "id": 349, "content": { "text": "Comparative Summary Table\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11689310520887375, "y": 0.9407148361206055 }, { "x": 0.33872105926275253, "y": 0.9407148361206055 }, { "x": 0.33872105926275253, "y": 0.9546255888417363 }, { "x": 0.11689310520887375, "y": 0.9546255888417363 } ], "category": "footer", "id": 351, "content": { "text": "The Law Library of Congress\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8651103377342224, "y": 0.9411447644233704 }, { "x": 0.8733203299343586, "y": 0.9411447644233704 }, { "x": 0.8733203299343586, "y": 0.9510265169665217 }, { "x": 0.8651103377342224, "y": 0.9510265169665217 } ], "category": "paragraph", "id": 352, "content": { "text": "5\n", "html": "", "markdown": "" } } ] }, "01030000000035.pdf": { "elements": [ { "coordinates": [ { "x": 0.14116083085536957, "y": 0.08677536249160767 }, { "x": 0.17225429601967335, "y": 0.08677536249160767 }, { "x": 0.17225429601967335, "y": 0.11257640458643436 }, { "x": 0.14116083085536957, "y": 0.11257640458643436 } ], "category": "paragraph", "id": 329, "content": { "text": "4\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14098508656024933, "y": 0.1318860650062561 }, { "x": 0.3726513832807541, "y": 0.1318860650062561 }, { "x": 0.3726513832807541, "y": 0.1516543161123991 }, { "x": 0.14098508656024933, "y": 0.1516543161123991 } ], "category": "heading1", "id": 330, "content": { "text": "Basis Fields\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1404086798429489, "y": 0.18623310327529907 }, { "x": 0.8599961251020432, "y": 0.18623310327529907 }, { "x": 0.8599961251020432, "y": 0.3388233333826065 }, { "x": 0.1404086798429489, "y": 0.3388233333826065 } ], "category": "paragraph", "id": 331, "content": { "text": "A vector field may be written as a linear combination of basis\nvector fields. If n is the dimension, then any set of n linearly\nindependent vector fields may be used as a basis. The coordinate\nbasis X is an example of a basis. 1 We will see later that not every\nbasis is a coordinate basis: in order to be a coordinate basis,\nthere must be a coordinate system such that each basis element is\nthe directional derivative operator in a corresponding coordinate\ndirection.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14049939811229706, "y": 0.3460610806941986 }, { "x": 0.8596664518117905, "y": 0.3460610806941986 }, { "x": 0.8596664518117905, "y": 0.4017692171037197 }, { "x": 0.14049939811229706, "y": 0.4017692171037197 } ], "category": "paragraph", "id": 332, "content": { "text": "Let e be a tuple of basis vector fields, such as the coordinate\nbasis X. The general vector field V applied to an arbitrary manifold\nfunction f can be expressed as a linear combination\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14090895652770996, "y": 0.4202662706375122 }, { "x": 0.8579792976379395, "y": 0.4202662706375122 }, { "x": 0.8579792976379395, "y": 0.44424245692789555 }, { "x": 0.14090895652770996, "y": 0.44424245692789555 } ], "category": "paragraph", "id": 333, "content": { "text": "v(f)(m) = e(f)(m) b(m) = (f)(m)b'(m),\n(4.1)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14020806550979614, "y": 0.4739835262298584 }, { "x": 0.8609041571617126, "y": 0.4739835262298584 }, { "x": 0.8609041571617126, "y": 0.6266784071922302 }, { "x": 0.14020806550979614, "y": 0.6266784071922302 } ], "category": "paragraph", "id": 334, "content": { "text": "where b is a tuple-valued coefficient function on the manifold.\nWhen expressed in a coordinate basis, the coefficients that specify\nthe direction of the vector are naturally expressed as functions\nbi of the coordinates of the manifold point. Here, the coefficient\nfunction b is more naturally expressed as a tuple-valued function\non the manifold. If b is the coefficient function expressed as a\nfunction of coordinates, then b = box is the coefficient function\nas a function on the manifold.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14035792648792267, "y": 0.6336891651153564 }, { "x": 0.8618476539850235, "y": 0.6336891651153564 }, { "x": 0.8618476539850235, "y": 0.8204536139965057 }, { "x": 0.14035792648792267, "y": 0.8204536139965057 } ], "category": "paragraph", "id": 335, "content": { "text": "The coordinate-basis forms have a simple definition in terms of\nthe coordinate-basis vectors and the coordinates (equation 3.40).\nWith this choice, the dual property, equation (3.41), holds without\nfurther fuss. More generally, we can define a basis of one-forms e\nthat is dual to e in that the property\ne (ej) ( = Sj\n(4.2)\nis satisfied, analogous to property (3.41). Figure 4.1 illustrates\nthe duality of basis fields.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14037884771823883, "y": 0.8490354418754578 }, { "x": 0.8600699454545975, "y": 0.8490354418754578 }, { "x": 0.8600699454545975, "y": 0.8771765269339085 }, { "x": 0.14037884771823883, "y": 0.8771765269339085 } ], "category": "footer", "id": 336, "content": { "text": "1\nWe cannot say if the basis vectors are orthogonal or normalized until we\nintroduce a metric.\n", "html": "", "markdown": "" } } ] }, "01030000000180.pdf": { "elements": [ { "coordinates": [ { "x": 0.11575496941804886, "y": 0.4834585189819336 }, { "x": 0.8838348463177681, "y": 0.4834585189819336 }, { "x": 0.8838348463177681, "y": 0.5956747233867645 }, { "x": 0.11575496941804886, "y": 0.5956747233867645 } ], "category": "table", "id": 200, "content": { "text": "", "html": "
VersionDateChangeAffected Sections
1.0April 30, 2022Original
1.0June 3, 2022Small edits for clarity on Creative Commons licensing and attribution.1. Introduction to Open Educational Resources
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PORT SHIPCALLS
ForeignDomestic
MANILA24546,125
CEBU113879,500
BATANGAS95813,196
SUBIC313136
CAGAYAN DE ORO1373,159
DAVAO75017,807
ILOILO21224,381
GENERAL SANTOS112704
ZAMBOANGA4041,27
LUCENA744,428
", "markdown": "" } }, { "coordinates": [ { "x": 0.11727799475193024, "y": 0.09388415515422821 }, { "x": 0.8815354257822037, "y": 0.09388415515422821 }, { "x": 0.8815354257822037, "y": 0.19204004853963852 }, { "x": 0.11727799475193024, "y": 0.19204004853963852 } ], "category": "paragraph", "id": 393, "content": { "text": "estuarine influenced areas. Batangas, Cebu and lloilo are located very near to protected areas\nand tourism areas. Batangas is within the center of the center of global marine biodiversity while\nCebu is in the Mactan key biodiversity area. Manila has the highest number of foreign shipcalls\nwhile Cebu has the highest domestic shipcalls and second to Manila in international shipcalls.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12649154663085938, "y": 0.2330392450094223 }, { "x": 0.16736693680286407, "y": 0.2330392450094223 }, { "x": 0.16736693680286407, "y": 0.2430008128285408 }, { "x": 0.12649154663085938, "y": 0.2430008128285408 } ], "category": "paragraph", "id": 394, "content": { "text": "PORT\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3510698974132538, "y": 0.2330266386270523 }, { "x": 0.4297296032309532, "y": 0.2330266386270523 }, { "x": 0.4297296032309532, "y": 0.2429707357659936 }, { "x": 0.3510698974132538, "y": 0.2429707357659936 } ], "category": "paragraph", "id": 395, "content": { "text": "SHIPCALLS\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11671699583530426, "y": 0.48932161927223206 }, { "x": 0.82007797062397, "y": 0.48932161927223206 }, { "x": 0.82007797062397, "y": 0.5042976113036275 }, { "x": 0.11671699583530426, "y": 0.5042976113036275 } ], "category": "paragraph", "id": 397, "content": { "text": "Table 1. Top 10 ports in the Philippines in shipcalls (2020 data from PPA, CPA and SBMA)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11673122644424438, "y": 0.5446474552154541 }, { "x": 0.8818268775939941, "y": 0.5446474552154541 }, { "x": 0.8818268775939941, "y": 0.670772597193718 }, { "x": 0.11673122644424438, "y": 0.670772597193718 } ], "category": "paragraph", "id": 398, "content": { "text": "The port of Manila has been documented to have a significant number of possible IAS. The on-\ngoing SAILS-PORTEC research program has detected IAS in Davao, Cebu and Matnog ports. These\nports are adjacent to specific oil tanker pathways/routes. In Luzon where the refineries and oil\nstorage facilities are located such as Batangas, are at higher risk. These loading ports are at high\nrisk for IAS/MNIS and these are located near to international ports.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11660698801279068, "y": 0.7113742828369141 }, { "x": 0.8823981657624245, "y": 0.7113742828369141 }, { "x": 0.8823981657624245, "y": 0.8930333852767944 }, { "x": 0.11660698801279068, "y": 0.8930333852767944 } ], "category": "paragraph", "id": 399, "content": { "text": "The shipcall statistics in Table 1 represent the year 2020, when the COVID 19 pandemic caused a\nglobal and domestic maritime transport slowdown. The average reduction in shipcalls is around\n40%. Nonetheless, Manila and Cebu are likely the main ports that need to be closely monitored\nfor potential IAS bioinvasion. In 2018, before the COVID-19 pandemic, Manila was experiencing\nport congestion with a report that ships may stay at berth for five days (Wallis, 2019). This will\nincrease the risks for biofouling. Based on the 2021 statistics from the PPA, the average berthing\ntime has been reduced to 1 day. This is a result of less shipping traffic due to the pandemic.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8632895946502686, "y": 0.9224259853363037 }, { "x": 0.8823858089745045, "y": 0.9224259853363037 }, { "x": 0.8823858089745045, "y": 0.9331061448901892 }, { "x": 0.8632895946502686, "y": 0.9331061448901892 } ], "category": "paragraph", "id": 400, "content": { "text": "10\n", "html": "", "markdown": "" } } ] }, "01030000000184.pdf": { "elements": [ { "coordinates": [ { "x": 0.0943085178732872, "y": 0.5012610554695129 }, { "x": 0.9124531373381615, "y": 0.5012610554695129 }, { "x": 0.9124531373381615, "y": 0.7570714056491852 }, { "x": 0.0943085178732872, "y": 0.7570714056491852 } ], "category": "table", "id": 217, "content": { "text": "", "html": "
1 1.8X Higher Return of InformationOptimal Attempt Reduced Information Acquisition Time2 SOTA Cutting-Edge Technology
Unlike existing search systems that only return information limited to the entered search keywords, SS Pack returns all relevant data that meet the user's search intentBy returning all semantic-based information of the search keywords, the time required for information acquisition is reduced drastically compared to that of traditional keyword-matching search systemsThe analysis of user logs saved in real-time allows us to further optimize the individual search services over time
", "markdown": "" } }, { "coordinates": [ { "x": 0.07356535643339157, "y": 0.07627663761377335 }, { "x": 0.23069613426923752, "y": 0.07627663761377335 }, { "x": 0.23069613426923752, "y": 0.09345845878124237 }, { "x": 0.07356535643339157, "y": 0.09345845878124237 } ], "category": "header", "id": 226, "content": { "text": "Semantic Search Pack: Value\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0734638199210167, "y": 0.13069425523281097 }, { "x": 0.6431535705924034, "y": 0.13069425523281097 }, { "x": 0.6431535705924034, "y": 0.16831763461232185 }, { "x": 0.0734638199210167, "y": 0.16831763461232185 } ], "category": "heading1", "id": 227, "content": { "text": "SS Pack allows businesses to access further data more rapidly\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.050336576998233795, "y": 0.3123461902141571 }, { "x": 0.6370984092354774, "y": 0.3123461902141571 }, { "x": 0.6370984092354774, "y": 0.33180490508675575 }, { "x": 0.050336576998233795, "y": 0.33180490508675575 } ], "category": "paragraph", "id": 228, "content": { "text": "The SS Pack can reduce the information acquisition time by returning all the information that matches the user's search intent.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.05027884617447853, "y": 0.3621765971183777 }, { "x": 0.7016363181173801, "y": 0.3621765971183777 }, { "x": 0.7016363181173801, "y": 0.4131843037903309 }, { "x": 0.05027884617447853, "y": 0.4131843037903309 } ], "category": "paragraph", "id": 229, "content": { "text": "The performance optimized for individual search systems is maintained by automatic updates of real-time search log records, augmented by\nUpstage's technological know-how.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09975060075521469, "y": 0.5165774822235107 }, { "x": 0.2590155526995659, "y": 0.5165774822235107 }, { "x": 0.2590155526995659, "y": 0.5934654474258423 }, { "x": 0.09975060075521469, "y": 0.5934654474258423 } ], "category": "heading1", "id": 230, "content": { "text": "1\n1.8X\nHigher Return of Information\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1477120816707611, "y": 0.5105187892913818 }, { "x": 0.16906741820275784, "y": 0.5105187892913818 }, { "x": 0.16906741820275784, "y": 0.5438571348786354 }, { "x": 0.1477120816707611, "y": 0.5438571348786354 } ], "category": "figure", "id": 231, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0987565889954567, "y": 0.6406612396240234 }, { "x": 0.3323930576443672, "y": 0.6406612396240234 }, { "x": 0.3323930576443672, "y": 0.7470699772238731 }, { "x": 0.0987565889954567, "y": 0.7470699772238731 } ], "category": "paragraph", "id": 232, "content": { "text": "Unlike existing search systems that only return\ninformation limited to the entered search keywords, SS\nPack returns all relevant data that meet the user's\nsearch intent\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.7435230612754822, "y": 0.5072636008262634 }, { "x": 0.7515690876170993, "y": 0.5072636008262634 }, { "x": 0.7515690876170993, "y": 0.5218459675088525 }, { "x": 0.7435230612754822, "y": 0.5218459675088525 } ], "category": "figure", "id": 233, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.38558539748191833, "y": 0.5266004204750061 }, { "x": 0.5353844612836838, "y": 0.5266004204750061 }, { "x": 0.5353844612836838, "y": 0.5598194226622581 }, { "x": 0.38558539748191833, "y": 0.5598194226622581 } ], "category": "heading1", "id": 234, "content": { "text": "Optimal Attempt\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.6900787353515625, "y": 0.5090557336807251 }, { "x": 0.7462726682424545, "y": 0.5090557336807251 }, { "x": 0.7462726682424545, "y": 0.5463100112974644 }, { "x": 0.6900787353515625, "y": 0.5463100112974644 } ], "category": "figure", "id": 235, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.6893965005874634, "y": 0.5086787343025208 }, { "x": 0.8268989473581314, "y": 0.5086787343025208 }, { "x": 0.8268989473581314, "y": 0.5908870249986649 }, { "x": 0.6893965005874634, "y": 0.5908870249986649 } ], "category": "heading1", "id": 236, "content": { "text": "2\nSOTA\nCutting-Edge Technology\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.38578474521636963, "y": 0.5786319375038147 }, { "x": 0.5967883616685867, "y": 0.5786319375038147 }, { "x": 0.5967883616685867, "y": 0.600202227011323 }, { "x": 0.38578474521636963, "y": 0.600202227011323 } ], "category": "heading1", "id": 237, "content": { "text": "Reduced Information Acquisition Time\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3851994276046753, "y": 0.6405428051948547 }, { "x": 0.602291539311409, "y": 0.6405428051948547 }, { "x": 0.602291539311409, "y": 0.7505591288208961 }, { "x": 0.3851994276046753, "y": 0.7505591288208961 } ], "category": "paragraph", "id": 238, "content": { "text": "By returning all semantic-based information of the\nsearch keywords, the time required for information\nacquisition is reduced drastically compared to that\nof traditional keyword-matching search systems\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.6889152526855469, "y": 0.6406831741333008 }, { "x": 0.909270778298378, "y": 0.6406831741333008 }, { "x": 0.909270778298378, "y": 0.7155135944485664 }, { "x": 0.6889152526855469, "y": 0.7155135944485664 } ], "category": "paragraph", "id": 239, "content": { "text": "The analysis of user logs saved in real-time allows us\nto further optimize the individual search services\nover time\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.05430569499731064, "y": 0.8959728479385376 }, { "x": 0.7290880307555199, "y": 0.8959728479385376 }, { "x": 0.7290880307555199, "y": 0.9398990012705326 }, { "x": 0.05430569499731064, "y": 0.9398990012705326 } ], "category": "footer", "id": 240, "content": { "text": "1 Evaluated against 100 internal test queries Comparison of the amount of information returned with at least one keyword included in the search term and the\namount of returned information against that of SS Pack\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.053722359240055084, "y": 0.9508911371231079 }, { "x": 0.060969507321715355, "y": 0.9508911371231079 }, { "x": 0.060969507321715355, "y": 0.9633974926546216 }, { "x": 0.053722359240055084, "y": 0.9633974926546216 } ], "category": "figure", "id": 241, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.05413702875375748, "y": 0.950125515460968 }, { "x": 0.3362426236271858, "y": 0.950125515460968 }, { "x": 0.3362426236271858, "y": 0.9680692758411169 }, { "x": 0.05413702875375748, "y": 0.9680692758411169 } ], "category": "footer", "id": 242, "content": { "text": "2 State-of-the-art, current highest level of results and performance\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.9661215543746948, "y": 0.9487141966819763 }, { "x": 0.9758874084800482, "y": 0.9487141966819763 }, { "x": 0.9758874084800482, "y": 0.9616766348481178 }, { "x": 0.9661215543746948, "y": 0.9616766348481178 } ], "category": "paragraph", "id": 243, "content": { "text": "22\n", "html": "", "markdown": "" } } ] }, "01030000000033.pdf": { "elements": [ { "coordinates": [ { "x": 0.14163732528686523, "y": 0.055348046123981476 }, { "x": 0.22759901732206345, "y": 0.055348046123981476 }, { "x": 0.22759901732206345, "y": 0.07026056945323944 }, { "x": 0.14163732528686523, "y": 0.07026056945323944 } ], "category": "header", "id": 375, "content": { "text": "Prologue\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8255749940872192, "y": 0.055227264761924744 }, { "x": 0.8619706444442272, "y": 0.055227264761924744 }, { "x": 0.8619706444442272, "y": 0.0671466151252389 }, { "x": 0.8255749940872192, "y": 0.0671466151252389 } ], "category": "paragraph", "id": 376, "content": { "text": "xvii\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14002631604671478, "y": 0.0898042619228363 }, { "x": 0.4543009549379349, "y": 0.0898042619228363 }, { "x": 0.4543009549379349, "y": 0.10362708196043968 }, { "x": 0.14002631604671478, "y": 0.10362708196043968 } ], "category": "heading1", "id": 377, "content": { "text": "Functional Abstraction\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14005190134048462, "y": 0.12760604918003082 }, { "x": 0.8605186343193054, "y": 0.12760604918003082 }, { "x": 0.8605186343193054, "y": 0.3842599242925644 }, { "x": 0.14005190134048462, "y": 0.3842599242925644 } ], "category": "paragraph", "id": 378, "content": { "text": "But this corrected use of Leibniz notation is ugly. We had to\nintroduce extraneous symbols (q and q) in order to indicate the ar-\ngument position specifying the partial derivative. Nothing would\nchange here if we replaced q and q by a and b. 3 We can sim-\nplify the notation by admitting that the partial derivatives of the\nLagrangian are themselves new functions, and by specifying the\nparticular partial derivative by the position of the argument that\nis varied\nd\n= 0,\ndt\nwhere IL is the function which is the partial derivative of the\nfunction L with respect to the ith argument. 4\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14027537405490875, "y": 0.3871218264102936 }, { "x": 0.8604234606027603, "y": 0.3871218264102936 }, { "x": 0.8604234606027603, "y": 0.5034141764044762 }, { "x": 0.14027537405490875, "y": 0.5034141764044762 } ], "category": "paragraph", "id": 379, "content": { "text": "Two different notions of derivative appear in this expression.\nThe functions d2L and L, constructed from the Lagrangian\nL, have the same arguments as L. The derivative d/dt is an\nexpression derivative. It applies to an expression that involves\nthe variable t and it gives the rate of change of the value of the\nexpression as the value of the variable t is varied.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1401398479938507, "y": 0.5075283646583557 }, { "x": 0.8608609139919281, "y": 0.5075283646583557 }, { "x": 0.8608609139919281, "y": 0.703543409705162 }, { "x": 0.1401398479938507, "y": 0.703543409705162 } ], "category": "paragraph", "id": 380, "content": { "text": "These are both useful interpretations of the idea of a derivative.\nBut functions give us more power. There are many equivalent\nways to write expressions that compute the same value. For\nexample 1/(1/r1 + 1/r2) = (7112)/(r1+12). These expressions\ncompute the same function of the two variables r1 and r2. The\nfirst expression fails if r1 = 0 but the second one gives the right\nvalue of the function. If we abstract the function, say as II(r1,r2),\nwe can ignore the details of how it is computed. The ideas become\nclearer because they do not depend on the detailed shape of the\nexpressions.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14053569734096527, "y": 0.7314519286155701 }, { "x": 0.8601122945547104, "y": 0.7314519286155701 }, { "x": 0.8601122945547104, "y": 0.794020913541317 }, { "x": 0.14053569734096527, "y": 0.794020913541317 } ], "category": "paragraph", "id": 381, "content": { "text": "3\nThat the symbols q and q can be replaced by other arbitrarily chosen non-\nconflicting symbols without changing the meaning of the expression tells us\nthat the partial derivative symbol is a logical quantifier, like forall and exists\n(A and 3).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14023956656455994, "y": 0.8026335835456848 }, { "x": 0.8600664436817169, "y": 0.8026335835456848 }, { "x": 0.8600664436817169, "y": 0.833816135302186 }, { "x": 0.14023956656455994, "y": 0.833816135302186 } ], "category": "footer", "id": 382, "content": { "text": "4The argument positions of the Lagrangian are indicated by indices starting\nwith zero for the time argument.\n", "html": "", "markdown": "" } } ] }, "01030000000060.pdf": { "elements": [ { "coordinates": [ { "x": 0.3002433478832245, "y": 0.103887639939785 }, { "x": 0.6514078676700592, "y": 0.103887639939785 }, { "x": 0.6514078676700592, "y": 0.11611787788569927 }, { "x": 0.3002433478832245, "y": 0.11611787788569927 } ], "category": "paragraph", "id": 264, "content": { "text": "Figure 4.8. Domestic Wood Pellets Production\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.23311792314052582, "y": 0.1305510401725769 }, { "x": 0.7277127355337143, "y": 0.1305510401725769 }, { "x": 0.7277127355337143, "y": 0.3459562808275223 }, { "x": 0.23311792314052582, "y": 0.3459562808275223 } ], "category": "figure", "id": 265, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14213362336158752, "y": 0.35899239778518677 }, { "x": 0.6574288904666901, "y": 0.35899239778518677 }, { "x": 0.6574288904666901, "y": 0.36942533031105995 }, { "x": 0.14213362336158752, "y": 0.36942533031105995 } ], "category": "paragraph", "id": 266, "content": { "text": "Source: Forestry Agency, Ministry of Agriculture, Forestry and Fishery (MAFF), 2020.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14193816483020782, "y": 0.40076717734336853 }, { "x": 0.8090188056230545, "y": 0.40076717734336853 }, { "x": 0.8090188056230545, "y": 0.4684179350733757 }, { "x": 0.14193816483020782, "y": 0.4684179350733757 } ], "category": "paragraph", "id": 267, "content": { "text": "Applications of wood pellets in Japan include power generation, boilers, stoves,\nagriculture use, and others. Although the trade statistics do not specify the usage of the\nimported wood pellets, according to the Japan Wood Pellet Association (JPA), most are\nused for power generation.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1420769989490509, "y": 0.48100563883781433 }, { "x": 0.8096527755260468, "y": 0.48100563883781433 }, { "x": 0.8096527755260468, "y": 0.5673545524477959 }, { "x": 0.1420769989490509, "y": 0.5673545524477959 } ], "category": "paragraph", "id": 268, "content": { "text": "The price of domestic wood pellets for power generation has a wide range. According to\na survey of domestic wood pellet manufacturers undertaken by JPA in 2020, the average\nprice of domestic wood pellets for power generation is around 14,000~29,000 ¥/tonne,\nwhile according to the Trade Statistics of Japan, the average cost, insurance, and freight\n(CIF) price of imported wood pellets is around 18,000 Y/tonne in 2020 (Figure 4.9).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.2054559886455536, "y": 0.5982584953308105 }, { "x": 0.7464633285999298, "y": 0.5982584953308105 }, { "x": 0.7464633285999298, "y": 0.6291547808796167 }, { "x": 0.2054559886455536, "y": 0.6291547808796167 } ], "category": "paragraph", "id": 269, "content": { "text": "Figure 4-9. Average Cost, Insurance, and Freight Prices of Wood Pellets\nand Wood Chips\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.22856374084949493, "y": 0.6419781446456909 }, { "x": 0.7300889045000076, "y": 0.6419781446456909 }, { "x": 0.7300889045000076, "y": 0.8423793166875839 }, { "x": 0.22856374084949493, "y": 0.8423793166875839 } ], "category": "figure", "id": 270, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14215949177742004, "y": 0.8595789074897766 }, { "x": 0.5087797343730927, "y": 0.8595789074897766 }, { "x": 0.5087797343730927, "y": 0.8850427195429802 }, { "x": 0.14215949177742004, "y": 0.8850427195429802 } ], "category": "paragraph", "id": 271, "content": { "text": "Average price = import value/import tonne.\nSource: Estimated by IEEJ based on Trade Statistics of Japan.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.4666992425918579, "y": 0.9455101490020752 }, { "x": 0.4851596374064684, "y": 0.9455101490020752 }, { "x": 0.4851596374064684, "y": 0.954321532510221 }, { "x": 0.4666992425918579, "y": 0.954321532510221 } ], "category": "paragraph", "id": 272, "content": { "text": "40\n", "html": "", "markdown": "" } } ] }, "01030000000165.pdf": { "elements": [ { "coordinates": [ { "x": 0.25081345438957214, "y": 0.8514317870140076 }, { "x": 0.7489090263843536, "y": 0.8514317870140076 }, { "x": 0.7489090263843536, "y": 0.8997828252613544 }, { "x": 0.25081345438957214, "y": 0.8997828252613544 } ], "category": "table", "id": 364, "content": { "text": "", "html": "
1000 soil2.5cmolc
soil
", "markdown": "" } }, { "coordinates": [ { "x": 0.0913177877664566, "y": 0.0762728601694107 }, { "x": 0.12455718591809273, "y": 0.0762728601694107 }, { "x": 0.12455718591809273, "y": 0.10107173025608063 }, { "x": 0.0913177877664566, "y": 0.10107173025608063 } ], "category": "figure", "id": 374, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1455741971731186, "y": 0.07548460364341736 }, { "x": 0.41006694734096527, "y": 0.07548460364341736 }, { "x": 0.41006694734096527, "y": 0.08741563186049461 }, { "x": 0.1455741971731186, "y": 0.08741563186049461 } ], "category": "header", "id": 375, "content": { "text": "Record your observations in Table 13.2.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09229430556297302, "y": 0.1309160739183426 }, { "x": 0.6790689527988434, "y": 0.1309160739183426 }, { "x": 0.6790689527988434, "y": 0.14958009123802185 }, { "x": 0.09229430556297302, "y": 0.14958009123802185 } ], "category": "paragraph", "id": 376, "content": { "text": "Table 13.2. Effect of cations on flocculation of a clay suspension.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09793467074632645, "y": 0.18249066174030304 }, { "x": 0.45529619604349136, "y": 0.18249066174030304 }, { "x": 0.45529619604349136, "y": 0.29356271773576736 }, { "x": 0.09793467074632645, "y": 0.29356271773576736 } ], "category": "paragraph", "id": 377, "content": { "text": "Added cation Relative Size & Settling Rates of Floccules\nK+\nNa+\nCa2+\nA13+\nCheck\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09234020113945007, "y": 0.34258750081062317 }, { "x": 0.6483135521411896, "y": 0.34258750081062317 }, { "x": 0.6483135521411896, "y": 0.3614342715591192 }, { "x": 0.09234020113945007, "y": 0.3614342715591192 } ], "category": "paragraph", "id": 378, "content": { "text": "Activity 4. Determining CEC by replacing adsorbed cations.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09204769134521484, "y": 0.3912743031978607 }, { "x": 0.9068583250045776, "y": 0.3912743031978607 }, { "x": 0.9068583250045776, "y": 0.4568665623664856 }, { "x": 0.09204769134521484, "y": 0.4568665623664856 } ], "category": "paragraph", "id": 379, "content": { "text": "In this activity, you will titrate the filtrate with a 0.01 molar solution of NaOH using phenolphthalein as an indicator.\nPhenolphthalein changes from colorless to faint pink when the quantity of OH ions added via the NaOH equals the\nquantity of H+ ions in the solution (that is, when the pH is raised to 7). For this activity, assume the soil samples have\nbeen extracted and the filtrates are now available for analysis.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0992647260427475, "y": 0.47807836532592773 }, { "x": 0.9012408703565598, "y": 0.47807836532592773 }, { "x": 0.9012408703565598, "y": 0.5054527707397938 }, { "x": 0.0992647260427475, "y": 0.5054527707397938 } ], "category": "paragraph", "id": 381, "content": { "text": "1. Place 10 ml of each filtrate into separate 125 ml flasks. This 10 ml quantity is the amount of filtrate from 1.0 gram of\nsoil.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09696071594953537, "y": 0.5135713815689087 }, { "x": 0.4372907504439354, "y": 0.5135713815689087 }, { "x": 0.4372907504439354, "y": 0.5260623535141349 }, { "x": 0.09696071594953537, "y": 0.5260623535141349 } ], "category": "paragraph", "id": 382, "content": { "text": "2. Add 10 drops of the phenolphthalein indicator.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09637511521577835, "y": 0.5311535596847534 }, { "x": 0.8903703764081001, "y": 0.5311535596847534 }, { "x": 0.8903703764081001, "y": 0.5790372528135777 }, { "x": 0.09637511521577835, "y": 0.5790372528135777 } ], "category": "paragraph", "id": 383, "content": { "text": "3. Titrate the extract with the NaOH solution to a faint pink endpoint. The titration must be done very carefully to\nobtain meaningful results. If you put too much NaOH in the flask and get a bright pink color, discard the solution\nand repeat the process. In the table below, record the milliliters of NaOH solution used to achieve the endpoint.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09176674485206604, "y": 0.6017777323722839 }, { "x": 0.12382490932941437, "y": 0.6017777323722839 }, { "x": 0.12382490932941437, "y": 0.6261236425489187 }, { "x": 0.09176674485206604, "y": 0.6261236425489187 } ], "category": "figure", "id": 384, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1455751657485962, "y": 0.6005510687828064 }, { "x": 0.5062097311019897, "y": 0.6005510687828064 }, { "x": 0.5062097311019897, "y": 0.6125340750440955 }, { "x": 0.1455751657485962, "y": 0.6125340750440955 } ], "category": "paragraph", "id": 385, "content": { "text": "Calculate the CEC and record your data in Table 13.3.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09184785932302475, "y": 0.6295035481452942 }, { "x": 0.9064060673117638, "y": 0.6295035481452942 }, { "x": 0.9064060673117638, "y": 0.6596252452582121 }, { "x": 0.09184785932302475, "y": 0.6596252452582121 } ], "category": "paragraph", "id": 386, "content": { "text": "Here is an example of how to calculate the CEC, assuming 2.5 mL of NaOH was required to achieve an end point.\nThe reaction occurring during titration is\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.36244502663612366, "y": 0.6742373108863831 }, { "x": 0.6333272457122803, "y": 0.6742373108863831 }, { "x": 0.6333272457122803, "y": 0.6920424290001392 }, { "x": 0.36244502663612366, "y": 0.6920424290001392 } ], "category": "paragraph", "id": 387, "content": { "text": "NaOH + H+\nNa+ + H2O\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09186235070228577, "y": 0.707493245601654 }, { "x": 0.9068046510219574, "y": 0.707493245601654 }, { "x": 0.9068046510219574, "y": 0.73669040389359 }, { "x": 0.09186235070228577, "y": 0.73669040389359 } ], "category": "paragraph", "id": 388, "content": { "text": "Thus, one mole of NaOH reacts with one mole of H+ Therefore, at the phenolphthalein end point, moles of NaOH added\n= moles of H+ in solution.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0918022021651268, "y": 0.7558580636978149 }, { "x": 0.8457255586981773, "y": 0.7558580636978149 }, { "x": 0.8457255586981773, "y": 0.7682705586776137 }, { "x": 0.0918022021651268, "y": 0.7682705586776137 } ], "category": "paragraph", "id": 389, "content": { "text": "The solution of 0.01 molar NaOH contains 1 cmol charge per liter (1 cmole/L). Therefore 2.5 mL NaOH contains\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0917084813117981, "y": 0.7808472514152527 }, { "x": 0.9069499373435974, "y": 0.7808472514152527 }, { "x": 0.9069499373435974, "y": 0.8931491374969482 }, { "x": 0.0917084813117981, "y": 0.8931491374969482 } ], "category": "paragraph", "id": 390, "content": { "text": "cmol of NaOH = 2.5 mL NaOH o\nNaOH\n1\nX\n= 0.0025 molc NaOH\n1\nThus, the CEC is\n1000\nsoil\n2.5cmolc\nsoil\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09209892153739929, "y": 0.9412223100662231 }, { "x": 0.2003331035375595, "y": 0.9412223100662231 }, { "x": 0.2003331035375595, "y": 0.9500587489455938 }, { "x": 0.09209892153739929, "y": 0.9500587489455938 } ], "category": "footer", "id": 391, "content": { "text": "114 Soil Colloids\n", "html": "", "markdown": "" } } ] }, "01030000000192.pdf": { "elements": [ { "coordinates": [ { "x": 0.1119680255651474, "y": 0.08729284256696701 }, { "x": 0.8883911222219467, "y": 0.08729284256696701 }, { "x": 0.8883911222219467, "y": 0.9199438616633415 }, { "x": 0.1119680255651474, "y": 0.9199438616633415 } ], "category": "table", "id": 777, "content": { "text": "", "html": "
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", "markdown": "" } }, { "coordinates": [ { "x": 0.11825219541788101, "y": 0.08829557150602341 }, { "x": 0.4876743331551552, "y": 0.08829557150602341 }, { "x": 0.4876743331551552, "y": 0.16475532948970795 }, { "x": 0.11825219541788101, "y": 0.16475532948970795 } ], "category": "paragraph", "id": 800, "content": { "text": "Edward Beeching, Clémentine Fourrier, Nathan\nHabib, Sheon Han, Nathan Lambert, Nazneen\nRajani, Omar Sanseviero, Lewis Tunstall, and\nThomas Wolf. 2023. Open Ilm leaderboard.\ntps://huggingface.co/spaces/\nHuggingFaceH4/open_llm_leaderboard.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11791670322418213, "y": 0.17597311735153198 }, { "x": 0.4857178032398224, "y": 0.17597311735153198 }, { "x": 0.4857178032398224, "y": 0.25210778415203094 }, { "x": 0.11791670322418213, "y": 0.25210778415203094 } ], "category": "paragraph", "id": 801, "content": { "text": "Tom Brown, Benjamin Mann, Nick Ryder, Melanie\nSubbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind\nNeelakantan, Pranav Shyam, Girish Sastry, Amanda\nAskell, et al. 2020. Language models are few-shot\nlearners. Advances in neural information processing\nsystems, 33:1877-1901.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1184694916009903, "y": 0.2630673944950104 }, { "x": 0.4876973181962967, "y": 0.2630673944950104 }, { "x": 0.4876973181962967, "y": 0.32681088894605637 }, { "x": 0.1184694916009903, "y": 0.32681088894605637 } ], "category": "paragraph", "id": 802, "content": { "text": "Peter Clark, Isaac Cowhey, Oren Etzioni, Tushar Khot,\nAshish Sabharwal, Carissa Schoenick, and Oyvind\nTafjord. 2018. Think you have solved question an-\nswering? try arc, the ai2 reasoning challenge. arXiv\npreprint arXiv: 1803.05457.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11885389685630798, "y": 0.3375665247440338 }, { "x": 0.4867054522037506, "y": 0.3375665247440338 }, { "x": 0.4867054522037506, "y": 0.4012782871723175 }, { "x": 0.11885389685630798, "y": 0.4012782871723175 } ], "category": "paragraph", "id": 803, "content": { "text": "Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian,\nMark Chen, Heewoo Jun, Lukasz Kaiser, Matthias\nPlappert, Jerry Tworek, Jacob Hilton, Reiichiro\nNakano, et al. 2021. Training verifiers to solve math\nword problems. arXiv preprint Xiv:2110.14168.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11861156672239304, "y": 0.4118763506412506 }, { "x": 0.48787104338407516, "y": 0.4118763506412506 }, { "x": 0.48787104338407516, "y": 0.47568149119615555 }, { "x": 0.11861156672239304, "y": 0.47568149119615555 } ], "category": "paragraph", "id": 804, "content": { "text": "Ganqu Cui, Lifan Yuan, Ning Ding, Guanming Yao,\nWei Zhu, Yuan Ni, Guotong Xie, Zhiyuan Liu, and\nMaosong Sun. 2023. Ultrafeedback: Boosting lan-\nguage models with high-quality feedback. arXiv\npreprint JarXiv:2310.01377.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11842433363199234, "y": 0.4865640699863434 }, { "x": 0.48786110430955887, "y": 0.4865640699863434 }, { "x": 0.48786110430955887, "y": 0.5370836816728115 }, { "x": 0.11842433363199234, "y": 0.5370836816728115 } ], "category": "paragraph", "id": 805, "content": { "text": "Chunyuan Deng, Yilun Zhao, Xiangru Tang, Mark Ger-\nstein, and Arman Cohan. 2023. Investigating data\ncontamination in modern benchmarks for large lan-\nguage models. arXiv preprint arXiv:2311.09783.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11862943321466446, "y": 0.5477082133293152 }, { "x": 0.48678190261125565, "y": 0.5477082133293152 }, { "x": 0.48678190261125565, "y": 0.6113487705588341 }, { "x": 0.11862943321466446, "y": 0.6113487705588341 } ], "category": "paragraph", "id": 806, "content": { "text": "Hanze Dong, Wei Xiong, Deepanshu Goyal, Rui Pan,\nShizhe Diao, Jipeng Zhang, Kashun Shum, and\nTong Zhang. 2023. Raft: Reward ranked finetuning\nfor generative foundation model alignment. arXiv\npreprint arXiv:2304.06767.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11823958158493042, "y": 0.622228741645813 }, { "x": 0.4877970516681671, "y": 0.622228741645813 }, { "x": 0.4877970516681671, "y": 0.6834704019129276 }, { "x": 0.11823958158493042, "y": 0.6834704019129276 } ], "category": "paragraph", "id": 807, "content": { "text": "Mohammad Fraiwan and Natheer Khasawneh. 2023. A\nreview of chatgpt applications in education, market-\ning, software engineering, and healthcare: Benefits,\ndrawbacks, and research directions. arXiv preprint\narXiv:2305.00237.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11790984869003296, "y": 0.6966657638549805 }, { "x": 0.4852946400642395, "y": 0.6966657638549805 }, { "x": 0.4852946400642395, "y": 0.7469882033765316 }, { "x": 0.11790984869003296, "y": 0.7469882033765316 } ], "category": "paragraph", "id": 808, "content": { "text": "Trevor Gale, Deepak Narayanan, Cliff Young, and Matei\nZaharia. 2023. Megablocks: Efficient sparse training\nwith mixture-of-experts. Proceedings of Machine\nLearning and Systems, 5.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11886084824800491, "y": 0.7580438852310181 }, { "x": 0.48766032606363297, "y": 0.7580438852310181 }, { "x": 0.48766032606363297, "y": 0.7955934964120388 }, { "x": 0.11886084824800491, "y": 0.7955934964120388 } ], "category": "paragraph", "id": 809, "content": { "text": "Andrea Gesmundo and Kaitlin Maile. 2023. Compos-\nable function-preserving expansions for transformer\narchitectures. arXiv preprint arXiv:2308.06103.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11837438493967056, "y": 0.8065880537033081 }, { "x": 0.4852970317006111, "y": 0.8065880537033081 }, { "x": 0.4852970317006111, "y": 0.8440523371100426 }, { "x": 0.11837438493967056, "y": 0.8440523371100426 } ], "category": "paragraph", "id": 810, "content": { "text": "Shahriar Golchin and Mihai Surdeanu. 2023. Time\ntravel in llms: Tracing data contamination in large\nlanguage models. arXiv preprint ModelAlpaca-GPT4OpenOrcaSynth. Math-InstructH6 (Avg.)ARCHellaSwagMMLUTruthfulQAWinograndeGSM8KSFT v1o69.1567.6686.0365.8860.1282.9552.24SFT v2Oo69.2165.3685.3965.9358.4782.7957.32SFT v3Ooo70.0365.8785.5565.3157.9381.3764.14SFT v4", "markdown": "" } }, { "coordinates": [ { "x": 0.15738673508167267, "y": 0.2189081311225891 }, { "x": 0.8405470997095108, "y": 0.2189081311225891 }, { "x": 0.8405470997095108, "y": 0.26793622225522995 }, { "x": 0.15738673508167267, "y": 0.26793622225522995 } ], "category": "table", "id": 21, "content": { "text": "", "html": "
ModelUltrafeedback CleanSynth. Math-AlignmentH6 (Avg.)ARCHellaSwagMMLUTruthfulQAWinograndeGSM8K
DPO v1o73.0671.4288.4966.1472.0481.4558.83
DPO v2oo73.4271.5088.2865.9771.7182.7960.27
DPO v1 + v2oo73.2171.3388.3665.9272.6582.7958.23
", "markdown": "" } }, { "coordinates": [ { "x": 0.21491576731204987, "y": 0.3505520522594452 }, { "x": 0.78435118496418, "y": 0.3505520522594452 }, { "x": 0.78435118496418, "y": 0.3924316056072712 }, { "x": 0.21491576731204987, "y": 0.3924316056072712 } ], "category": "table", "id": 62, "content": { "text": "", "html": "
ModelBase SFT ModelH6 (Avg.)ARCHellaSwagMMLUTruthfulQAWinograndeGSM8K
DPOSFT v373.4271.5088.2865.9771.7182.7960.27
DPOSFT v3 v473.5871.3388.0865.3972.4581.9362.32
", "markdown": "" } }, { "coordinates": [ { "x": 0.1175285205245018, "y": 0.16372981667518616 }, { "x": 0.8804224357008934, "y": 0.16372981667518616 }, { "x": 0.8804224357008934, "y": 0.20140820369124413 }, { "x": 0.1175285205245018, "y": 0.20140820369124413 } ], "category": "paragraph", "id": 93, "content": { "text": "Table 3: Ablation studies on the different datasets used for instruction tuning. 'SFT v3+v4' indicates that the model\nis merged from 'SFT v3' and 'SFT v4' by simply averaging the model weights. The best scores for H6 and the\nindividual tasks are shown in bold.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1173587292432785, "y": 0.28075191378593445 }, { "x": 0.8826843351125717, "y": 0.28075191378593445 }, { "x": 0.8826843351125717, "y": 0.3346789889037609 }, { "x": 0.1173587292432785, "y": 0.3346789889037609 } ], "category": "paragraph", "id": 95, "content": { "text": "Table 4: Ablation studies on the different datasets used during the direct preference optimization (DPO) stage.\n'SFT v3' is used as the SFT base model for DPO. We name ablated models with the 'DPO' prefix to indicate the\nalignment tuning stage. 'DPO v1+v2' indicates that the model is merged from 'DPO v1' and 'DPO v2' by simply\naveraging the model weights. The best scores for H6 and the individual tasks are shown in bold.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11769270896911621, "y": 0.4053443670272827 }, { "x": 0.8821509480476379, "y": 0.4053443670272827 }, { "x": 0.8821509480476379, "y": 0.44553712755441666 }, { "x": 0.11769270896911621, "y": 0.44553712755441666 } ], "category": "paragraph", "id": 97, "content": { "text": "Table 5: Ablation studies on the different SFT base models used during the direct preference optimization (DPO)\nstage. Ultrafeedback Clean and Synth. Math-Alignment datasets are used. We name ablated models with the 'DPO'\nprefix to indicate the alignment tuning stage. The best scores for H6 and the individual tasks are shown in bold.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11845780164003372, "y": 0.47392022609710693 }, { "x": 0.488133080303669, "y": 0.47392022609710693 }, { "x": 0.488133080303669, "y": 0.5028281901031733 }, { "x": 0.11845780164003372, "y": 0.5028281901031733 } ], "category": "paragraph", "id": 98, "content": { "text": "indicate that using OpenOrca results in a model that\nbehaves differently from using only Alpaca-GPT4.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11784086376428604, "y": 0.5211418271064758 }, { "x": 0.48786545544862747, "y": 0.5211418271064758 }, { "x": 0.48786545544862747, "y": 0.6783651560544968 }, { "x": 0.11784086376428604, "y": 0.6783651560544968 } ], "category": "paragraph", "id": 99, "content": { "text": "Second, we investigate whether Synth. Math-\nInstruct dataset is beneficial. For 'SFT v3', we\nadd the Synth. Math-Instruct dataset, which boosts\nGSM8K scores to 64.14 and achieves comparable\nscores for the other tasks. Interestingly, when we\nadd the Synth. Math-Instruct dataset to 'SFT v1'\nto train 'SFT v4', we get our highest H6 score of\n70.88 with higher scores than 'SFT v3' for all tasks.\nFrom the above, we can see that adding the Synth.\nMath-Instruct dataset is helpful.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11795572191476822, "y": 0.6970434784889221 }, { "x": 0.48819658905267715, "y": 0.6970434784889221 }, { "x": 0.48819658905267715, "y": 0.9187289923429489 }, { "x": 0.11795572191476822, "y": 0.9187289923429489 } ], "category": "paragraph", "id": 100, "content": { "text": "Lastly, we see whether merging models trained\nwith and without OpenOrca can boost performance.\nIn the first analysis, we saw that using OpenOrca re-\nsulted in a model that behaved differently from the\nmodel that was trained without OpenOrca. Build-\ning on this intuition, we merge 'SFT v3' and 'SFT\nv4' as they are the best-performing models with\nand without OpenOrca. To our surprise, the result-\ning merged model 'SFT v3+v4' retains the high\nscores for non-GSM8K tasks from 'SFT v4' but\nalso achieves a higher GSM8K score than 'SFT v3'\nor 'SFT v4'. Thus, we see that merging models\nthat specialize in different tasks is a promising way\nto obtain a model that performs well generally.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5136945843696594, "y": 0.4739108979701996 }, { "x": 0.7116974145174026, "y": 0.4739108979701996 }, { "x": 0.7116974145174026, "y": 0.4866623394191265 }, { "x": 0.5136945843696594, "y": 0.4866623394191265 } ], "category": "heading1", "id": 101, "content": { "text": "4.3.2 Alignment Tuning\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5132264494895935, "y": 0.4935572147369385 }, { "x": 0.8824682235717773, "y": 0.4935572147369385 }, { "x": 0.8824682235717773, "y": 0.6026043966412544 }, { "x": 0.5132264494895935, "y": 0.6026043966412544 } ], "category": "paragraph", "id": 102, "content": { "text": "As we utilize DPO for practical alignment tuning,\nthere are additional aspects to ablate such as the\nSFT base models used. Thus, we present ablations\nfor the different training datasets used for training,\nthe different SFT base models to initialize the DPO\nmodel, and finally, the model merging strategy to\nobtain the final alignment-tuned model.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5135300755500793, "y": 0.6162324547767639 }, { "x": 0.8826671242713928, "y": 0.6162324547767639 }, { "x": 0.8826671242713928, "y": 0.7088639438152313 }, { "x": 0.5135300755500793, "y": 0.7088639438152313 } ], "category": "paragraph", "id": 103, "content": { "text": "Ablation on the training datasets. We ablate on\nthe different alignment datasets used during DPO\nin Tab. 4. We use 'SFT v3' as the SFT base model\nfor DPO. 'DPO v1' only uses the Ultrafeedback\nClean dataset while 'DPO v2' also used the Synth.\nMath-Alignment dataset.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5132249593734741, "y": 0.7131580114364624 }, { "x": 0.8833591938018799, "y": 0.7131580114364624 }, { "x": 0.8833591938018799, "y": 0.9186529517173767 }, { "x": 0.5132249593734741, "y": 0.9186529517173767 } ], "category": "paragraph", "id": 104, "content": { "text": "First, we test how Ultrafeedback Clean and\nSynth. Math-Alignment impacts model perfor-\nmance. For 'DPO v1', it achieves 73.06 in H6,\nwhich is a substantial boost from the SFT base\nmodel score of 70.03. However, we note that while\nscores for tasks like ARC, HellaSwag, and Truth-\nfulQA all improved by good margins, the score\nfor GSM8K is 58.83, which is lower than the\nSFT base model score of 64.14. Adding Synth.\nMath-Alignment to train 'DPO v2', we see that\nthe GSM8k score improves to 60.27, which is\nlower than the SFT base model but still higher\nthan 'DPO v1'. Other task scores are also not nega-\n", "html": "", "markdown": "" } } ] }, "01030000000014.pdf": { "elements": [ { "coordinates": [ { "x": 0.1028226912021637, "y": 0.04979516938328743 }, { "x": 0.12530256994068623, "y": 0.04979516938328743 }, { "x": 0.12530256994068623, "y": 0.05827586259692907 }, { "x": 0.1028226912021637, "y": 0.05827586259692907 } ], "category": "paragraph", "id": 413, "content": { "text": "158\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.7157919406890869, "y": 0.05036139860749245 }, { "x": 0.8968182057142258, "y": 0.05036139860749245 }, { "x": 0.8968182057142258, "y": 0.05816553672775626 }, { "x": 0.7157919406890869, "y": 0.05816553672775626 } ], "category": "header", "id": 414, "content": { "text": "AL-OGAYYEL AND OSKAY\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10388131439685822, "y": 0.07451087236404419 }, { "x": 0.8946848660707474, "y": 0.07451087236404419 }, { "x": 0.8946848660707474, "y": 0.3156074583530426 }, { "x": 0.10388131439685822, "y": 0.3156074583530426 } ], "category": "figure", "id": 415, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10331390053033829, "y": 0.3280866742134094 }, { "x": 0.44608766585588455, "y": 0.3280866742134094 }, { "x": 0.44608766585588455, "y": 0.3403879450634122 }, { "x": 0.10331390053033829, "y": 0.3403879450634122 } ], "category": "paragraph", "id": 416, "content": { "text": "FIGURE 8.15\nTypical black-and-white Bedouin tent.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10311704128980637, "y": 0.37513649463653564 }, { "x": 0.48622044175863266, "y": 0.37513649463653564 }, { "x": 0.48622044175863266, "y": 0.5815739929676056 }, { "x": 0.10311704128980637, "y": 0.5815739929676056 } ], "category": "figure", "id": 417, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10335691273212433, "y": 0.592440664768219 }, { "x": 0.41502635180950165, "y": 0.592440664768219 }, { "x": 0.41502635180950165, "y": 0.6044535795226693 }, { "x": 0.10335691273212433, "y": 0.6044535795226693 } ], "category": "paragraph", "id": 418, "content": { "text": "FIGURE 8.16\nTypical three-poled Bedouin tent\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1027684435248375, "y": 0.6318629384040833 }, { "x": 0.48759638518095016, "y": 0.6318629384040833 }, { "x": 0.48759638518095016, "y": 0.7009618207812309 }, { "x": 0.1027684435248375, "y": 0.7009618207812309 } ], "category": "paragraph", "id": 419, "content": { "text": "black and white, with a little red-dyed wool for\ndecoration. This wool comes from sheep and cam-\nels, whose wool is known for its softness and, when\nleft undyed, for its beautiful natural colors. 49\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10305045545101166, "y": 0.7051630616188049 }, { "x": 0.4870549291372299, "y": 0.7051630616188049 }, { "x": 0.4870549291372299, "y": 0.8291813433170319 }, { "x": 0.10305045545101166, "y": 0.8291813433170319 } ], "category": "paragraph", "id": 420, "content": { "text": "Figure 8.16 indicates the complex nature of the\ninterior of a Bedouin tent. The inside area is divid-\ned into many parts, each of them with its specific\nuse. It is important to note that a \"well-to-do\" Bed-\nouin tent like the one shown in figure 8.16 indi-\ncates the higher status of the family living in it\nthan that of a family living in the humbler,\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5121384859085083, "y": 0.3749692738056183 }, { "x": 0.896800696849823, "y": 0.3749692738056183 }, { "x": 0.896800696849823, "y": 0.5541861802339554 }, { "x": 0.5121384859085083, "y": 0.5541861802339554 } ], "category": "paragraph", "id": 421, "content": { "text": "three-poled tent in figure 8.15. These images also\nshow that different areas are used by men and by\nwomen. 50 For example, the tent contains a space\nwhich is allocated to female weavers, like a studio\nwhere they perform their craft and practice their\nskills. 51 Thus, in the Bedouin society, the tent is a\nnot only a signifier of social relationships and fam-\nily status but also of gender roles. It is, therefore,\nan extremely important space because here wom-\nen make items that support their family or tribe.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5120289921760559, "y": 0.5580850839614868 }, { "x": 0.8964222073554993, "y": 0.5580850839614868 }, { "x": 0.8964222073554993, "y": 0.719095453619957 }, { "x": 0.5120289921760559, "y": 0.719095453619957 } ], "category": "paragraph", "id": 422, "content": { "text": "While the function of the textile is to create and\ndemarcate the Bedouin space, the way the space is\nconstructed influences the way the nomads live\nand the way the family or the tribe is perceived\nby the outside world. The textile is, therefore,\nstructuring the formation of a private and a public\nidentity by delineating the space: the outside, non-\npatterned textiles are public, while the inside,\npatterned textiles are private. 52 We can infer,\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5126762390136719, "y": 0.7586629390716553 }, { "x": 0.8963363766670227, "y": 0.7586629390716553 }, { "x": 0.8963363766670227, "y": 0.836309403181076 }, { "x": 0.5126762390136719, "y": 0.836309403181076 } ], "category": "paragraph", "id": 423, "content": { "text": "50\nSee also Dickson, The Arab of the Desert, 66-67; and\nCanavan, \"Applications of Textile Products,\" 541. Here,\nCanavan explains that dividers were parts of women's\npossessions, accompanying them into marriage, as well\nas \"testimony of a tribe's wealth and prestige.\"\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5128650665283203, "y": 0.8402041792869568 }, { "x": 0.8961882293224335, "y": 0.8402041792869568 }, { "x": 0.8961882293224335, "y": 0.8684211913496256 }, { "x": 0.5128650665283203, "y": 0.8684211913496256 } ], "category": "paragraph", "id": 424, "content": { "text": "51\nRefah Al Raheel, interviewed by Rana Al-Ogayyel, Ri-\nyadh, 2017.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5129105448722839, "y": 0.8725453019142151 }, { "x": 0.8974558711051941, "y": 0.8725453019142151 }, { "x": 0.8974558711051941, "y": 0.9013450611382723 }, { "x": 0.5129105448722839, "y": 0.9013450611382723 } ], "category": "paragraph", "id": 425, "content": { "text": "52\nWhile the outside of the traditional tents is black and\nwithout much pattern except for stripes, the inside of\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10288859158754349, "y": 0.8919503688812256 }, { "x": 0.1191101036965847, "y": 0.8919503688812256 }, { "x": 0.1191101036965847, "y": 0.9004188599064946 }, { "x": 0.10288859158754349, "y": 0.9004188599064946 } ], "category": "paragraph", "id": 426, "content": { "text": "49\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14462977647781372, "y": 0.8891799449920654 }, { "x": 0.35669414699077606, "y": 0.8891799449920654 }, { "x": 0.35669414699077606, "y": 0.9012481039389968 }, { "x": 0.14462977647781372, "y": 0.9012481039389968 } ], "category": "footer", "id": 427, "content": { "text": "For details, see Al-Sabah, Ibjad, 17.\n", "html": "", "markdown": "" } } ] }, "01030000000120.pdf": { "elements": [ { "coordinates": [ { "x": 0.07861824333667755, "y": 0.33691009879112244 }, { "x": 0.9199888855218887, "y": 0.33691009879112244 }, { "x": 0.9199888855218887, "y": 0.8267593085765839 }, { "x": 0.07861824333667755, "y": 0.8267593085765839 } ], "category": "table", "id": 274, "content": { "text": "", "html": "
Genes in DNAProteinCharacteristics
2 copies of the allele that codes for normal hemoglobin (SS)Normal hemoglobin dissolves in the cytosol of red blood cells.Disk-shaped red blood cells can squeeze through the smallest blood vessels normal health
2 copies of the allele that codes for sickle cell hemoglobin (ss)Sickle cell hemoglobin can clump in long rods in red blood cells.If sickle cell hemoglobin clumps in long rods sickle-shaped red blood cells clogged small blood vessels + fragile red blood cells pain, damage to body organs + anemia = sickle cell anemia
", "markdown": "" } }, { "coordinates": [ { "x": 0.11678540706634521, "y": 0.049501460045576096 }, { "x": 0.3928283751010895, "y": 0.049501460045576096 }, { "x": 0.3928283751010895, "y": 0.06373960990458727 }, { "x": 0.11678540706634521, "y": 0.06373960990458727 } ], "category": "header", "id": 290, "content": { "text": "MOHAVE COMMUNITY COLLEGE\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.79719477891922, "y": 0.05104098469018936 }, { "x": 0.8669274896383286, "y": 0.05104098469018936 }, { "x": 0.8669274896383286, "y": 0.0634952038526535 }, { "x": 0.79719477891922, "y": 0.0634952038526535 } ], "category": "header", "id": 291, "content": { "text": "BIO181\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11690433323383331, "y": 0.09374350309371948 }, { "x": 0.857139840722084, "y": 0.09374350309371948 }, { "x": 0.857139840722084, "y": 0.14338649809360504 }, { "x": 0.11690433323383331, "y": 0.14338649809360504 } ], "category": "paragraph", "id": 292, "content": { "text": "Sickle cell hemoglobin and normal hemoglobin differ in only a single amino acid out of more than 100\namino acids in the complete hemoglobin protein. This difference in a single amino acid results in the\ndifferent properties of sickle cell hemoglobin compared to normal hemoglobin.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11773298680782318, "y": 0.18210019171237946 }, { "x": 0.8623723238706589, "y": 0.18210019171237946 }, { "x": 0.8623723238706589, "y": 0.2133431602269411 }, { "x": 0.11773298680782318, "y": 0.2133431602269411 } ], "category": "paragraph", "id": 293, "content": { "text": "Hemoglobin is carried inside red blood cells. Normal hemoglobin dissolves in the watery cytosol of red\nblood cells. Sickle cell hemoglobin is less soluble in the cytosol because:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14750227332115173, "y": 0.22932736575603485 }, { "x": 0.6366014778614044, "y": 0.22932736575603485 }, { "x": 0.6366014778614044, "y": 0.2424543472006917 }, { "x": 0.14750227332115173, "y": 0.2424543472006917 } ], "category": "paragraph", "id": 295, "content": { "text": "Valine (Val) is much less water-soluble than glutamic acid (Glu).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14730192720890045, "y": 0.24710726737976074 }, { "x": 0.7841929942369461, "y": 0.24710726737976074 }, { "x": 0.7841929942369461, "y": 0.2605557022616267 }, { "x": 0.14730192720890045, "y": 0.2605557022616267 } ], "category": "paragraph", "id": 296, "content": { "text": "Amino acid 6 is in a crucial location on the outer surface of the hemoglobin protein.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11683160066604614, "y": 0.2642858922481537 }, { "x": 0.8256619572639465, "y": 0.2642858922481537 }, { "x": 0.8256619572639465, "y": 0.29550143145024776 }, { "x": 0.11683160066604614, "y": 0.29550143145024776 } ], "category": "paragraph", "id": 297, "content": { "text": "The chart on the next page shows how the lower solubility of sickle cell hemoglobin results in the\nsymptoms of sickle cell anemia.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11715497076511383, "y": 0.8536352515220642 }, { "x": 0.6979414969682693, "y": 0.8536352515220642 }, { "x": 0.6979414969682693, "y": 0.867188835516572 }, { "x": 0.11715497076511383, "y": 0.867188835516572 } ], "category": "paragraph", "id": 299, "content": { "text": "29a. Circle the arrows in the chart that represent transcription + translation.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.48575952649116516, "y": 0.9250786304473877 }, { "x": 0.5140905063599348, "y": 0.9250786304473877 }, { "x": 0.5140905063599348, "y": 0.9360293205827475 }, { "x": 0.48575952649116516, "y": 0.9360293205827475 } ], "category": "paragraph", "id": 300, "content": { "text": "115\n", "html": "", "markdown": "" } } ] }, "01030000000158.pdf": { "elements": [ { "coordinates": [ { "x": 0.1419757455587387, "y": 0.09683487564325333 }, { "x": 0.8567946404218674, "y": 0.09683487564325333 }, { "x": 0.8567946404218674, "y": 0.2043844386935234 }, { "x": 0.1419757455587387, "y": 0.2043844386935234 } ], "category": "paragraph", "id": 190, "content": { "text": "to expand this section to include notes, tips and feedback from\nTWP instructors. If you use these materials, please let me know\nhow it went, what worked for you, and any suggested changes or\nadditions. I'd love to hear from you at chwixson (at) plymouth (dot)\nedu or fill out as much of [this form] as you'd like.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14346790313720703, "y": 0.267521470785141 }, { "x": 0.3535100221633911, "y": 0.267521470785141 }, { "x": 0.3535100221633911, "y": 0.2886088043451309 }, { "x": 0.14346790313720703, "y": 0.2886088043451309 } ], "category": "heading1", "id": 191, "content": { "text": "Introduction\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14147049188613892, "y": 0.337766170501709 }, { "x": 0.8572104573249817, "y": 0.337766170501709 }, { "x": 0.8572104573249817, "y": 0.4681698977947235 }, { "x": 0.14147049188613892, "y": 0.4681698977947235 } ], "category": "paragraph", "id": 192, "content": { "text": "Throughout the chapters, I tried to generate Reflection &\nDiscussion Questions that could be used either as in class (whole\ngroup or think/pair/share) discussion prompts or as written\nreflections assigned out of class. If your students generate any\nwritten answers to any of the Reflection & Discussion Questions in\nthis chapter, I would be very interested to see them.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14328144490718842, "y": 0.5314655303955078 }, { "x": 0.5016235560178757, "y": 0.5314655303955078 }, { "x": 0.5016235560178757, "y": 0.5521885585039854 }, { "x": 0.14328144490718842, "y": 0.5521885585039854 } ], "category": "heading1", "id": 193, "content": { "text": "Our Mental Shortcuts\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1424029916524887, "y": 0.6014992594718933 }, { "x": 0.8561826795339584, "y": 0.6014992594718933 }, { "x": 0.8561826795339584, "y": 0.6863098368048668 }, { "x": 0.1424029916524887, "y": 0.6863098368048668 } ], "category": "paragraph", "id": 194, "content": { "text": "If you'd like to reinforce Kahneman's ideas about System 1 and\nSystem 2 thinking the video below (12 minutes) is very good, (thanks\nto Mike Davidson for this suggestion.)\n//www.youtube.com/embed/UBVV8pch1dM\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.17787522077560425, "y": 0.767021894454956 }, { "x": 0.7460991144180298, "y": 0.767021894454956 }, { "x": 0.7460991144180298, "y": 0.8022955171763897 }, { "x": 0.17787522077560425, "y": 0.8022955171763897 } ], "category": "paragraph", "id": 195, "content": { "text": "Reflection & Discussion Question 1: Taking Stock of What You\nAlready Know\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1766650229692459, "y": 0.9238962531089783 }, { "x": 0.180440979776904, "y": 0.9238962531089783 }, { "x": 0.180440979776904, "y": 0.9380583390593529 }, { "x": 0.1766650229692459, "y": 0.9380583390593529 } ], "category": "paragraph", "id": 196, "content": { "text": "I\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1429138034582138, "y": 0.924406886100769 }, { "x": 0.16520585678517818, "y": 0.924406886100769 }, { "x": 0.16520585678517818, "y": 0.9348435206338763 }, { "x": 0.1429138034582138, "y": 0.9348435206338763 } ], "category": "paragraph", "id": 197, "content": { "text": "98\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.19137907028198242, "y": 0.9243574142456055 }, { "x": 0.3892147094011307, "y": 0.9243574142456055 }, { "x": 0.3892147094011307, "y": 0.9349101576954126 }, { "x": 0.19137907028198242, "y": 0.9349101576954126 } ], "category": "footer", "id": 198, "content": { "text": "Instructor Resources\n", "html": "", "markdown": "" } } ] }, "01030000000048.pdf": { "elements": [ { "coordinates": [ { "x": 0.10291264951229095, "y": 0.05745083466172218 }, { "x": 0.11534696631133556, "y": 0.05745083466172218 }, { "x": 0.11534696631133556, "y": 0.06868347711861134 }, { "x": 0.10291264951229095, "y": 0.06868347711861134 } ], "category": "paragraph", "id": 413, "content": { "text": "8\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15709364414215088, "y": 0.0572403259575367 }, { "x": 0.40776151418685913, "y": 0.0572403259575367 }, { "x": 0.40776151418685913, "y": 0.07184526231139898 }, { "x": 0.15709364414215088, "y": 0.07184526231139898 } ], "category": "header", "id": 414, "content": { "text": "Encinas Franco and Laguna\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10458895564079285, "y": 0.11146345734596252 }, { "x": 0.5797829926013947, "y": 0.11146345734596252 }, { "x": 0.5797829926013947, "y": 0.13162158988416195 }, { "x": 0.10458895564079285, "y": 0.13162158988416195 } ], "category": "heading1", "id": 415, "content": { "text": "Filipino Women in Electoral Politics\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10290583223104477, "y": 0.15729427337646484 }, { "x": 0.8553210124373436, "y": 0.15729427337646484 }, { "x": 0.8553210124373436, "y": 0.6029425859451294 }, { "x": 0.10290583223104477, "y": 0.6029425859451294 } ], "category": "paragraph", "id": 416, "content": { "text": "The nature and extent of Filipino women's political participation\nis a product of the country's colonial history, martial law, and\ndemocratization post-1986. Historians argue that Spain's strong\nCatholic traditions ushered in patriarchal norms and practices that were\nnot present in the pre-Hispanic period. National hero, Jose Rizal, has\ndocumented this in his \"Letter to the Women of Malolos,\" praising the\nwomen for advocating their right to education. Historians also found\nproof of women's contribution to the Philippine revolution (Camagay\n1998). Decades later, the suffragist movement ushered in one of the first\nnational issues to have brought Filipino women together. It was a hard-\nfought battle; the movement had to contend with staunch opposition\nfrom antisuffragists in the Constitutional Convention that drafted the\n1935 Constitution. The reluctance was expected because only 21-year-\nold Filipino men had been allowed to vote during the time. They framed\ntheir opposition based on traditional notions of womanhood and their\nrole in the private sphere, foremost of which is motherhood. Another\nkey argument against female suffrage was the idea that politics is\nsupposed to be \"dirty\" and that this would taint families if women took\npart in politics. The assumptions catered to the age-old public-private\ndivide, strongly suggesting that only men are qualified to occupy the\nformer.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10270550847053528, "y": 0.6247014403343201 }, { "x": 0.85567507147789, "y": 0.6247014403343201 }, { "x": 0.85567507147789, "y": 0.9004480838775635 }, { "x": 0.10270550847053528, "y": 0.9004480838775635 } ], "category": "paragraph", "id": 417, "content": { "text": "Eventually, the 1935 Constitution granted women suffrage on the\ncondition that more than 300,000 women would vote affirmatively in a\nplebiscite. When signing the law paving the way for the said plebiscite,\nPresident Manuel Quezon had this to say to Filipino men: \"Are you\ngoing to deprive our women of the opportunity to say how their lives\nare going to be regulated and is it fair for us to presume that men can\nalways speak in this country for women?\" (Official Gazette 1936). In\nApril 1937, more than 400,000 women voted in favor of their right to\nvote and participate in political life. In 1946 and 1947, Filipinos elected\nthe first woman member of the House of Representatives, and senator,\nrespectively. Nonetheless, data from 1946 to 1992 indicate an uphill\nclimb. For instance, in the 1949 and 1953 elections for the House of\nRepresentatives, only one woman was elected out of the 100 positions.\n", "html": "", "markdown": "" } } ] }, "01030000000200.pdf": { "elements": [ { "coordinates": [ { "x": 0.039798468351364136, "y": 0.2213534265756607 }, { "x": 0.9595230519771576, "y": 0.2213534265756607 }, { "x": 0.9595230519771576, "y": 0.9438868910074234 }, { "x": 0.039798468351364136, "y": 0.9438868910074234 } ], "category": "table", "id": 508, "content": { "text": "", "html": "
Service StageFunction NameExplanationExpected Benefit
1. Project creationProject creation and managementSelect document type to automatically run project creation, Pipeline configuration with recommended Modelset and Endpoint deploymentThe intuitive UI environment allows the the person in charge to quickly proceed with the entire process from project creation to deployment, improving work efficiency
2. Data labeling and fine-tuningData storage managementProvides convenient functions for uploading raw data, viewer, and data management (search using image metadata, sorting, filtering, hashtags settings on image data) Image data bookmark for Qualitative EvaluationConveniently manage raw data to be used for OCR Pack and actual date from live service
Create and manage Labeling SpaceCreating a Labeling Space to manage raw data annotation, managing labeling resources (Ontology, Characters to be Recognized), data set dump, data set version management 3Labeling work can be outsourced within the pack. Labeled data is continuously supplied from which data sets can be created with ease. The Auto Labeling function increases both efficiency and convenience.
Model trainingVarious basic models for each selected document, information comparison between models, basic model training, training pause function, re-training, cancel function, and configuration support for Characters to be Recognized and Ontology that is frequently modified while developing specialized modelsProviding a foundation for customers to implement, manage, and upgrade their own OCR model specialized to the customers' needs
3. Pipeline configuration and deploymentPipeline, Endpoint Creation and managementChoose Detector, Recognizer, or Parser to create a Pipeline or an Endpoint Connect Pipelines to Endpoints, perform tasks such as deployment controllers, deployment recovery, and moreProviding a foundation for customers to implement, manage, and upgrade their own OCR model specialized to the customers' needs
4. Monitoring and evaluationProject monitoringMonitoring of deployed Pipelines and Endpoints, notifying the customer of important issues such as suspicion of model performance degradation, and Qualitative Evaluation of actual incoming customer dataMonitor important indicators for each project and quickly identify and respond to issues
Full Pack MonitoringMonitoring traffic of all deployed Endpoints, quality monitoring of all deployed models, and monitoring of resources (GPU, CPU, Storage) connected to the PackMonitoring useful information about the overall OCR Pack at a glance
Quantitative / Qualitative EvaluationQuantitative evaluation leaderboard / Qualitative EvaluationViewing the model's performance to help the customer choose the appropriate model
Guide and helpProvides context-specific guides to help you troubleshoot yourself, download terminal logs for error situations and Pack documentationThe customer can diagnose, respond to, and solve problems occurring in the Pack on their own without external help
", "markdown": "" } }, { "coordinates": [ { "x": 0.04803488776087761, "y": 0.06986458599567413 }, { "x": 0.45815716311335564, "y": 0.06986458599567413 }, { "x": 0.45815716311335564, "y": 0.16593842208385468 }, { "x": 0.04803488776087761, "y": 0.16593842208385468 } ], "category": "heading1", "id": 552, "content": { "text": "Introduction of product services and key features\nKey Functions by Main Service Flow\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.924923837184906, "y": 0.9509056210517883 }, { "x": 0.9622410610318184, "y": 0.9509056210517883 }, { "x": 0.9622410610318184, "y": 0.9679375346750021 }, { "x": 0.924923837184906, "y": 0.9679375346750021 } ], "category": "paragraph", "id": 554, "content": { "text": "ipstage-\n", "html": "", "markdown": "" } } ] }, "01030000000025.pdf": { "elements": [ { "coordinates": [ { "x": 0.680572509765625, "y": 0.08668317645788193 }, { "x": 0.8425238132476807, "y": 0.08668317645788193 }, { "x": 0.8425238132476807, "y": 0.09665372502058744 }, { "x": 0.680572509765625, "y": 0.09665372502058744 } ], "category": "header", "id": 408, "content": { "text": "2. The Lost Homeland\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1298343688249588, "y": 0.1190674677491188 }, { "x": 0.8424514085054398, "y": 0.1190674677491188 }, { "x": 0.8424514085054398, "y": 0.1762753129005432 }, { "x": 0.1298343688249588, "y": 0.1762753129005432 } ], "category": "paragraph", "id": 409, "content": { "text": "gesture in honour of local culture. Few of the artefacts were authentically\npart of this area. It told us nothing of any interest or with any authority.\nWe wondered whose culture we were looking at.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1290736049413681, "y": 0.19131863117218018 }, { "x": 0.8434682339429855, "y": 0.19131863117218018 }, { "x": 0.8434682339429855, "y": 0.2644413635134697 }, { "x": 0.1290736049413681, "y": 0.2644413635134697 } ], "category": "paragraph", "id": 410, "content": { "text": "At the central railway station, we tried to question officials, in German and\nEnglish, about the location of Steinkirche. But only Polish was spoken at\nthe information office and other counters. Nor could we locate the correct\ntrain line on the information screens.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12971585988998413, "y": 0.284071147441864 }, { "x": 0.8432009220123291, "y": 0.284071147441864 }, { "x": 0.8432009220123291, "y": 0.4800657331943512 }, { "x": 0.12971585988998413, "y": 0.4800657331943512 } ], "category": "paragraph", "id": 411, "content": { "text": "On our walk back to the centre of town, past the dilapidated theatre where\nmy mother had attended performances, John spotted another bookshop.\nSurprisingly it was trading busily on a Polish Catholic Sunday. It sold old\nmaps and books. We found old pictures of Breslau labelled in Polish and\nEnglish. We found descriptions in both Polish and English of Neumarkt\nPlatz (Novi Targ). Various maps showed clear plans of its location. They\nalso showed the Neptune fountain I had been seeking. For centuries it had\na conspicuous place in town maps as a well drawing water from the Oder,\nwhose tributaries flowed together and separated the town into different\nquarters, spanned by a multitude of bridges.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.13033975660800934, "y": 0.4956875145435333 }, { "x": 0.843234971165657, "y": 0.4956875145435333 }, { "x": 0.843234971165657, "y": 0.5526662282645702 }, { "x": 0.13033975660800934, "y": 0.5526662282645702 } ], "category": "paragraph", "id": 412, "content": { "text": "I was thrilled. Before this find, my family had begun to question whether\nthe fountain had actually existed. 'You and your fountain!' they cried.\nBut I always knew it was there, in my memory and beyond.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1297529935836792, "y": 0.5678828954696655 }, { "x": 0.8431596159934998, "y": 0.5678828954696655 }, { "x": 0.8431596159934998, "y": 0.7010708451271057 }, { "x": 0.1297529935836792, "y": 0.7010708451271057 } ], "category": "paragraph", "id": 413, "content": { "text": "When we walked to Novi Targ, we found the old houses by the square\nhad been destroyed totally by the War. So, to my disappointment, had\nthe Neptune fountain In Microcosm, his history of Wroclaw, Norman\nDavies tells how, after the War, the rubble of Breslau had been removed\nin trainloads to rebuild Warsaw in its original style. Some fine Breslau\nbuildings left standing by War were even knocked down for their\nold bricks.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.13016429543495178, "y": 0.720707356929779 }, { "x": 0.8433103263378143, "y": 0.720707356929779 }, { "x": 0.8433103263378143, "y": 0.7777450829744339 }, { "x": 0.13016429543495178, "y": 0.7777450829744339 } ], "category": "paragraph", "id": 414, "content": { "text": "I viewed this horrible information as being akin to the punishment Dante\ndished out to sinners in his Purgatory. Atonement was to be made only\nby suffering punishment that fitted the spirit of a crime.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12940341234207153, "y": 0.792762815952301 }, { "x": 0.8433189988136292, "y": 0.792762815952301 }, { "x": 0.8433189988136292, "y": 0.849788423627615 }, { "x": 0.12940341234207153, "y": 0.849788423627615 } ], "category": "paragraph", "id": 415, "content": { "text": "We then looked for the air-raid shelters in which my grandmother and\naunt Else had sheltered from the fire-bombs that rained down on the city\nin early 1945.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8893632292747498, "y": 0.9314473867416382 }, { "x": 0.9059146512299776, "y": 0.9314473867416382 }, { "x": 0.9059146512299776, "y": 0.9409008556976914 }, { "x": 0.8893632292747498, "y": 0.9409008556976914 } ], "category": "paragraph", "id": 416, "content": { "text": "11\n", "html": "", "markdown": "" } } ] }, "01030000000055.pdf": { "elements": [ { "coordinates": [ { "x": 0.14286181330680847, "y": 0.10382550209760666 }, { "x": 0.8096927106380463, "y": 0.10382550209760666 }, { "x": 0.8096927106380463, "y": 0.15264008566737175 }, { "x": 0.14286181330680847, "y": 0.15264008566737175 } ], "category": "paragraph", "id": 426, "content": { "text": "pharmaceutical products (Casson, Muliastra, and Obidzinski, 2014). The development of\nbiofuels from biomass has raised interest in expanding the palm oil plantation area.\nThis\nis because palm oil is the main raw material for biodiesel in Indonesia.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1425635814666748, "y": 0.16599668562412262 }, { "x": 0.8095229268074036, "y": 0.16599668562412262 }, { "x": 0.8095229268074036, "y": 0.2696603685617447 }, { "x": 0.1425635814666748, "y": 0.2696603685617447 } ], "category": "paragraph", "id": 427, "content": { "text": "CPO is the primary product derived from the red fruit of the oil palm, while palm kernel\noil, derived from the fruit's nut, is considered a secondary product. Oil palm biomass\nincludes EFBs, palm mesocarps fibres (PMFs), PKS, oil palm fronds, oil palm trunks, as well\nas palm oil mill effluent (POME). Oil palm fronds account for 70% of the total oil palm\nbiomass produced, while EFB accounts for 10% and oil palm trunks account for only about\n5% of the total biomass produced.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1420544981956482, "y": 0.28301864862442017 }, { "x": 0.8089630007743835, "y": 0.28301864862442017 }, { "x": 0.8089630007743835, "y": 0.36870088428258896 }, { "x": 0.1420544981956482, "y": 0.36870088428258896 } ], "category": "paragraph", "id": 428, "content": { "text": "According to Harahap et al. (2019), Indonesia housed 11 million hectares (Mha) of oil palm\nplantations and produced 31 million tonnes (Mt) of CPO in 2015. Oil extraction from palm\nfruits occurs in palm oil mills. One tonne (t) of CPO production results in nearly 5 t of solid\nbiomass waste, including EFBs, PKSs, PMFs, and POME; see Figure 3.3. This implies that,\nin 2015, Indonesia produced around 155 Mt of palm biomass residue.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3083316385746002, "y": 0.3998539447784424 }, { "x": 0.6438964605331421, "y": 0.3998539447784424 }, { "x": 0.6438964605331421, "y": 0.41153507214039564 }, { "x": 0.3083316385746002, "y": 0.41153507214039564 } ], "category": "paragraph", "id": 429, "content": { "text": "Figure 3.3. Biomass Use in Oil Palm Industry\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14358076453208923, "y": 0.4220959544181824 }, { "x": 0.8141961991786957, "y": 0.4220959544181824 }, { "x": 0.8141961991786957, "y": 0.6575399041175842 }, { "x": 0.14358076453208923, "y": 0.6575399041175842 } ], "category": "figure", "id": 430, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14248938858509064, "y": 0.6708357930183411 }, { "x": 0.3245691955089569, "y": 0.6708357930183411 }, { "x": 0.3245691955089569, "y": 0.6806613272055984 }, { "x": 0.14248938858509064, "y": 0.6806613272055984 } ], "category": "paragraph", "id": 431, "content": { "text": "Source: Harahap et al. (2019).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14220701158046722, "y": 0.7101495265960693 }, { "x": 0.8100640624761581, "y": 0.7101495265960693 }, { "x": 0.8100640624761581, "y": 0.812012068927288 }, { "x": 0.14220701158046722, "y": 0.812012068927288 } ], "category": "paragraph", "id": 432, "content": { "text": "Regarding the potential for biodiesel, the previous Table 2.10 projected the demand of\nFAME for both B30 and B40 mandates using the volume of diesel fuel needed for the road\ntransport sector. As shown, the FAME demand will reach 19.1 million kL in 2040 for the\nB30 mandate and 25.4 million kL for the B40 mandate. The current FAME production\ncapacity is 12.85 million kL, indicating a shortage of supply to meet the 2040 demand for\nboth the B30 and B40 mandates.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1424371600151062, "y": 0.8274065256118774 }, { "x": 0.8085893392562866, "y": 0.8274065256118774 }, { "x": 0.8085893392562866, "y": 0.8943668156862259 }, { "x": 0.1424371600151062, "y": 0.8943668156862259 } ], "category": "paragraph", "id": 433, "content": { "text": "Increasing the capacity for FAME production implies that the demand for domestic CPO\nwill continue to increase. The estimated CPO required to produce FAME in 2040 is also\ncalculated above (Table 2.11). The estimated CPO consumption for B30 and B40 mandate\nin 2040 will be 17.5 and 23.4 million tonnes, respectively. This was calculated based on\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.46704480051994324, "y": 0.9455405473709106 }, { "x": 0.4847941417247057, "y": 0.9455405473709106 }, { "x": 0.4847941417247057, "y": 0.9540981808677316 }, { "x": 0.46704480051994324, "y": 0.9540981808677316 } ], "category": "paragraph", "id": 434, "content": { "text": "24\n", "html": "", "markdown": "" } } ] }, "01030000000028.pdf": { "elements": [ { "coordinates": [ { "x": 0.16615349054336548, "y": 0.5563742518424988 }, { "x": 0.8309049606323242, "y": 0.5563742518424988 }, { "x": 0.8309049606323242, "y": 0.6464856043457985 }, { "x": 0.16615349054336548, "y": 0.6464856043457985 } ], "category": "table", "id": 568, "content": { "text": "", "html": "
S=kln(2)
or inverselyo=Ws,with W=e1/kB,(3)
", "markdown": "" } }, { "coordinates": [ { "x": 0.14600516855716705, "y": 0.02734057977795601 }, { "x": 0.4343631714582443, "y": 0.02734057977795601 }, { "x": 0.4343631714582443, "y": 0.04046373441815376 }, { "x": 0.14600516855716705, "y": 0.04046373441815376 } ], "category": "header", "id": 577, "content": { "text": "Probability, Combinatorics and Control\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.146397665143013, "y": 0.07425229996442795 }, { "x": 0.8501621633768082, "y": 0.07425229996442795 }, { "x": 0.8501621633768082, "y": 0.10494595393538475 }, { "x": 0.146397665143013, "y": 0.10494595393538475 } ], "category": "paragraph", "id": 578, "content": { "text": "between this and the fact that the development of the underlying wave function for\nthe whole universe is unique.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.17427688837051392, "y": 0.1074526235461235 }, { "x": 0.29100457578897476, "y": 0.1074526235461235 }, { "x": 0.29100457578897476, "y": 0.12116123456507921 }, { "x": 0.17427688837051392, "y": 0.12116123456507921 } ], "category": "paragraph", "id": 579, "content": { "text": "Summarizing:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14658135175704956, "y": 0.12273025512695312 }, { "x": 0.8386788368225098, "y": 0.12273025512695312 }, { "x": 0.8386788368225098, "y": 0.17036911100149155 }, { "x": 0.14658135175704956, "y": 0.17036911100149155 } ], "category": "paragraph", "id": 580, "content": { "text": "Definition 1. A universe U is a chain of states (one state U t for each moment of\ntime t), with the property that the transition between adjacent states is always\npossible.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14667244255542755, "y": 0.171739399433136 }, { "x": 0.8469754606485367, "y": 0.171739399433136 }, { "x": 0.8469754606485367, "y": 0.20246759615838528 }, { "x": 0.14667244255542755, "y": 0.20246759615838528 } ], "category": "paragraph", "id": 581, "content": { "text": "Definition 2. A multiverse M is the set of all possible universes U in the sense of\nDefinition 1 together with a probability measure on this set.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14662396907806396, "y": 0.2043052464723587 }, { "x": 0.8430043458938599, "y": 0.2043052464723587 }, { "x": 0.8430043458938599, "y": 0.3158164694905281 }, { "x": 0.14662396907806396, "y": 0.3158164694905281 } ], "category": "paragraph", "id": 582, "content": { "text": "It may of course be said that quantum mechanics should allow for transitions\nbetween all kinds of states, although the probability for most such transitions may be\nextremely small. In this extremely simplified treatment, I will assume that for a given\nstate at a given moment of time t, the dynamical laws will only permit transitions to a\nvery limited number of states at the previous and next moments, which will make the\nprobabilistic part of the investigation particularly simple. However, modifications are\ncalled for near the endpoints (the Big Bang and the Big Crunch); see Section 5.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1464756280183792, "y": 0.31768304109573364 }, { "x": 0.8441119939088821, "y": 0.31768304109573364 }, { "x": 0.8441119939088821, "y": 0.3809208571910858 }, { "x": 0.1464756280183792, "y": 0.3809208571910858 } ], "category": "paragraph", "id": 583, "content": { "text": "As it stands, the model presented SO far is too simple to generate any results. In\nfact, there are no observable differences at all between the states, which mean that\nthere are no measurable variables which could be related to the (so far non-\nspecified) dynamics.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14677563309669495, "y": 0.3825136721134186 }, { "x": 0.8493194282054901, "y": 0.3825136721134186 }, { "x": 0.8493194282054901, "y": 0.4458434507250786 }, { "x": 0.14677563309669495, "y": 0.4458434507250786 } ], "category": "paragraph", "id": 584, "content": { "text": "There are of course many different variables which we can choose to enrich this\nstructure, and which ones to choose must depend on what properties we want to\nexplain. For explaining the second law of thermodynamics, the obvious choice is the\nentropy.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14697271585464478, "y": 0.48381078243255615 }, { "x": 0.2511533945798874, "y": 0.48381078243255615 }, { "x": 0.2511533945798874, "y": 0.49880964402109385 }, { "x": 0.14697271585464478, "y": 0.49880964402109385 } ], "category": "heading1", "id": 585, "content": { "text": "4. Entropy\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14670711755752563, "y": 0.5167930126190186 }, { "x": 0.835945725440979, "y": 0.5167930126190186 }, { "x": 0.835945725440979, "y": 0.5475055295974016 }, { "x": 0.14670711755752563, "y": 0.5475055295974016 } ], "category": "paragraph", "id": 586, "content": { "text": "According to Boltzmann, the total entropy of a certain macro-state at a certain\ntime is given by\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1745952069759369, "y": 0.5631902813911438 }, { "x": 0.8281159698963165, "y": 0.5631902813911438 }, { "x": 0.8281159698963165, "y": 0.6407948210835457 }, { "x": 0.1745952069759369, "y": 0.6407948210835457 } ], "category": "paragraph", "id": 587, "content": { "text": "S=kln\n(2)\nor inversely\no=Ws, with W=e1/kB,\n(3)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14691896736621857, "y": 0.6583432555198669 }, { "x": 0.7569306045770645, "y": 0.6583432555198669 }, { "x": 0.7569306045770645, "y": 0.6858545485883951 }, { "x": 0.14691896736621857, "y": 0.6858545485883951 } ], "category": "paragraph", "id": 588, "content": { "text": "where S denotes the number of corresponding micro-states and kB is\nBoltzmann's constant.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14634370803833008, "y": 0.6910505294799805 }, { "x": 0.8494079113006592, "y": 0.6910505294799805 }, { "x": 0.8494079113006592, "y": 0.8350787609815598 }, { "x": 0.14634370803833008, "y": 0.8350787609815598 } ], "category": "paragraph", "id": 589, "content": { "text": "This formula was from the beginning derived for simple cases, like an ideal gas.\nNevertheless, it does represent a kind of universal truth in statistical mechanics: the\nnumber of possible micro-states corresponding to a given macro-state grows expo-\nnentially with the entropy. Although there are many complications when one tries\nto consider the entropy of the universe as a whole, I will still take it as the starting\npoint for the discussion that the entropy (at a given time t) is an exponential\nfunction of the total entropy as in (3). A more difficult question is if and how the\nconstant W may vary with time, but for the purpose of the present paper, I will\nsimply let it be constant.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1465437114238739, "y": 0.8368373513221741 }, { "x": 0.8492644727230072, "y": 0.8368373513221741 }, { "x": 0.8492644727230072, "y": 0.9324425756931305 }, { "x": 0.1465437114238739, "y": 0.9324425756931305 } ], "category": "paragraph", "id": 590, "content": { "text": "One may of course argue that this can only be true when the universe is still\nquite ordered and the entropy is very far from reaching its maximum. But this is\ncertainly what the situation is like in our universe today, and according to the\ncomputations in [10, 11], it would take an almost incredibly long time to reach such\na state of maximal entropy. Thus, it will in the following be taken for granted that\nthis time is much longer than the life-span of our universe.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14654098451137543, "y": 0.9598144888877869 }, { "x": 0.16953966952860355, "y": 0.9598144888877869 }, { "x": 0.16953966952860355, "y": 0.9680450642481446 }, { "x": 0.14654098451137543, "y": 0.9680450642481446 } ], "category": "paragraph", "id": 591, "content": { "text": "312\n", "html": "", "markdown": "" } } ] }, "01030000000092.pdf": { "elements": [ { "coordinates": [ { "x": 0.09158002585172653, "y": 0.07201752066612244 }, { "x": 0.9082934185862541, "y": 0.07201752066612244 }, { "x": 0.9082934185862541, "y": 0.3395726978778839 }, { "x": 0.09158002585172653, "y": 0.3395726978778839 } ], "category": "paragraph", "id": 666, "content": { "text": "laboratory experiments that have formed key pillars of the field, such as those experiments depicted in\nExamples 1 and 2 in the book's Introduction section. The thought experiments in Section 1 are, for the\nmost part, re-castings of the simple cognitive tests devised by psychologists and economists over the\npast three-to-four decades to illustrate the fallacies, miscalculations, and biases distinguishing Homo\nsapiens from Homo economicus. Similarly, the laboratory experiments presented in Section 2 are, for the\nmost part, re-castings of the seminal experiments conducted by Kahneman and Tversky (among many\nothers). These experiments helped motivate the revised theories of human choice behavior, such\nas\nKahneman and Tversky's (1979) Prospect Theory, which form another pillar of behavioral economics.\nAlongside these experiments, Section 2 presents the revised theories of human choice behavior with\nvarying degrees of rigor. This is where the theoretical bases of Homo economicus' rational choice\nbehavior are examined, and where key refinements to this theory are developed-theoretical\nrefinements underpinning the myriad departures from rational choice behavior we witness Homo\nsapiens make in this section's laboratory and field experiments (and which are examined further in\nSections 3 and 4).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09203049540519714, "y": 0.3447307348251343 }, { "x": 0.9071857035160065, "y": 0.3447307348251343 }, { "x": 0.9071857035160065, "y": 0.5347451418638229 }, { "x": 0.09203049540519714, "y": 0.5347451418638229 } ], "category": "paragraph", "id": 667, "content": { "text": "Section 3 submerses the student in the world of behavioral game theory. Here we explore games\nsuch as Ultimatum Bargaining presented in Example 5. We follow Camerer (2003)'s lead, first by\ncharacterizing the games analytically (i.e., identifying solution, or equilibrium, concepts that are\npredicted to result when members of Homo economicus play the games), and then by discussing\nempirical results obtained from corresponding field experiments conducted with Homo sapiens. It\nis within the context of these games and field experiments that theories of social interaction are\ntested concerning inter alia trust and trustworthiness, honesty, fairness, reciprocity, etc. As with the\nthought and laboratory experiments presented in Sections 1 and 2, the games and field experiments\npresented in Section 3 are meant to be replicated with students as subjects and the instructor as the\nexperimenter, or researcher.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09190507978200912, "y": 0.5390998721122742 }, { "x": 0.9082606062293053, "y": 0.5390998721122742 }, { "x": 0.9082606062293053, "y": 0.7106191217899323 }, { "x": 0.09190507978200912, "y": 0.7106191217899323 } ], "category": "paragraph", "id": 668, "content": { "text": "Finally, Section 4 wades into the vast sea of empirical research and choice architecture. Here the\nstudent explores studies reporting on (1) the outcomes of actual policy nudges, such as the SMarT\nretirement-savings plan presented in Example 3 of the Introduction, (2) analyses of secondary datasets\nto test for choice behavior consistent with the revised theories discussed in Section 2, such as the test\nfor loss aversion in Example 4 of the Introduction, and (3) analyses of primary datasets obtained from\nnovel field experiments to further test the revised theories. The main purpose of this section is not\nonly to introduce the student to interesting empirical studies and policy adaptations in the field of\nbehavioral economics, but also, in the process, to incubate in the student an abiding appreciation for\n3\nthe obscure settings that sometimes lend themselves to such study.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09169081598520279, "y": 0.730876088142395 }, { "x": 0.5530886128544807, "y": 0.730876088142395 }, { "x": 0.5530886128544807, "y": 0.7426741383969784 }, { "x": 0.09169081598520279, "y": 0.7426741383969784 } ], "category": "heading1", "id": 669, "content": { "text": "THE TEXTBOOK'S DIFFERENT LEVELS OF RIGOR\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09192410856485367, "y": 0.7613270878791809 }, { "x": 0.9073180928826332, "y": 0.7613270878791809 }, { "x": 0.9073180928826332, "y": 0.8745952546596527 }, { "x": 0.09192410856485367, "y": 0.8745952546596527 } ], "category": "paragraph", "id": 670, "content": { "text": "Because the mathematical and computational rigor of material presented in this textbook varies\nthroughout, particularly in Sections 2 - 4, the extent of the rigor used in the presentation of a\ngiven topic is indicated with superscripts. Topics without a superscript are considered basic and\nuniversal enough that backgrounds in economics, mathematics, or statistics are not required for the\nreader to understand the material. Topics with a single asterisk (*) indicate that higher mathematical\nreasoning skills are recommended for the reader to fully grasp the material. Topics with a double\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.07759005576372147, "y": 0.8988639116287231 }, { "x": 0.8904734328389168, "y": 0.8988639116287231 }, { "x": 0.8904734328389168, "y": 0.9443218149244785 }, { "x": 0.07759005576372147, "y": 0.9443218149244785 } ], "category": "paragraph", "id": 671, "content": { "text": "3. Our approach to studying behavioral economics is focused on the underlying laboratory experimentation and behavioral\ngames that form the bedrock of the field. As such, we eschew delving into related fields such as neuroeconomics and\nauction theory. See Cartwright (2018) and Just (2013) for introductions to the former and latter fields, respectively.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09160753339529037, "y": 0.9511936902999878 }, { "x": 0.23153576999902725, "y": 0.9511936902999878 }, { "x": 0.23153576999902725, "y": 0.958794770296663 }, { "x": 0.09160753339529037, "y": 0.958794770296663 } ], "category": "footer", "id": 672, "content": { "text": "XX ARTHUR J. CAPLAN\n", "html": "", "markdown": "" } } ] }, "01030000000179.pdf": { "elements": [ { "coordinates": [ { "x": 0.11356451362371445, "y": 0.07035472244024277 }, { "x": 0.8884877189993858, "y": 0.07035472244024277 }, { "x": 0.8884877189993858, "y": 0.5203833803534508 }, { "x": 0.11356451362371445, "y": 0.5203833803534508 } ], "category": "table", "id": 212, "content": { "text": "", "html": "
NOL
", "markdown": "" } }, { "coordinates": [ { "x": 0.11400914192199707, "y": 0.0674595981836319 }, { "x": 0.889453113079071, "y": 0.0674595981836319 }, { "x": 0.889453113079071, "y": 0.5199591368436813 }, { "x": 0.11400914192199707, "y": 0.5199591368436813 } ], "category": "figure", "id": 247, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11504713445901871, "y": 0.5237593054771423 }, { "x": 0.8635139837861061, "y": 0.5237593054771423 }, { "x": 0.8635139837861061, "y": 0.5573912411928177 }, { "x": 0.11504713445901871, "y": 0.5573912411928177 } ], "category": "paragraph", "id": 248, "content": { "text": "Figure 12.2. A set of open textbooks printed in bulk are featured in this photo. Open textbooks from the\nOpen Course Library, picture by Tom Caswell, CC BY 2.0.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11461091041564941, "y": 0.5834099650382996 }, { "x": 0.626046895980835, "y": 0.5834099650382996 }, { "x": 0.626046895980835, "y": 0.6078305002301931 }, { "x": 0.11461091041564941, "y": 0.6078305002301931 } ], "category": "heading1", "id": 249, "content": { "text": "What tool(s) do you typically use in your course?\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1149899810552597, "y": 0.6205781102180481 }, { "x": 0.8839673846960068, "y": 0.6205781102180481 }, { "x": 0.8839673846960068, "y": 0.6816740036010742 }, { "x": 0.1149899810552597, "y": 0.6816740036010742 } ], "category": "paragraph", "id": 250, "content": { "text": "Ask whether the instructor utilizes your institution's course management system (Canvas,\nBlackboard, etc.), or a separate course website to communicate and share content with students.\nThis may affect the tools and practices you recommend.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11460991948843002, "y": 0.7031024694442749 }, { "x": 0.7161675915122032, "y": 0.7031024694442749 }, { "x": 0.7161675915122032, "y": 0.7278631012886763 }, { "x": 0.11460991948843002, "y": 0.7278631012886763 } ], "category": "heading1", "id": 251, "content": { "text": "What supporting materials do you utilize for this course?\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11474405974149704, "y": 0.7407936453819275 }, { "x": 0.8839632198214531, "y": 0.7407936453819275 }, { "x": 0.8839632198214531, "y": 0.803209874778986 }, { "x": 0.11474405974149704, "y": 0.803209874778986 } ], "category": "paragraph", "id": 252, "content": { "text": "If the instructor relies on self-grading homework platforms or ancillary presentations and lecture\nnotes from publishers, you will want to discuss the various free and low-cost options available to\nreplace that content (See Chapter 15, Finding Ancillaries for OER).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11423754692077637, "y": 0.8135856986045837 }, { "x": 0.8849608898162842, "y": 0.8135856986045837 }, { "x": 0.8849608898162842, "y": 0.9160989746451378 }, { "x": 0.11423754692077637, "y": 0.9160989746451378 } ], "category": "paragraph", "id": 253, "content": { "text": "Alternatively, does the instructor already supplement their course materials with course notes or\nmaterials they have personally created? Often, when traditional materials are lacking or require\nsupplement, instructors will create notes, reading lists, or other content to \"back up\" any\ntraditional, commercial content used in their course. This instructor-created content can be\nreused with OER as well, or even adapted into a new open resource in the future.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11551933735609055, "y": 0.940889835357666 }, { "x": 0.14091640524566174, "y": 0.940889835357666 }, { "x": 0.14091640524566174, "y": 0.9509417936205864 }, { "x": 0.11551933735609055, "y": 0.9509417936205864 } ], "category": "paragraph", "id": 254, "content": { "text": "164\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16353638470172882, "y": 0.9394218325614929 }, { "x": 0.36604636907577515, "y": 0.9394218325614929 }, { "x": 0.36604636907577515, "y": 0.9523744201287627 }, { "x": 0.16353638470172882, "y": 0.9523744201287627 } ], "category": "footer", "id": 255, "content": { "text": "SUPPORTING OER ADOPTION\n", "html": "", "markdown": "" } } ] }, "01030000000089.pdf": { "elements": [ { "coordinates": [ { "x": 0.11659374833106995, "y": 0.09000900387763977 }, { "x": 0.8833527863025665, "y": 0.09000900387763977 }, { "x": 0.8833527863025665, "y": 0.9036733210086823 }, { "x": 0.11659374833106995, "y": 0.9036733210086823 } ], "category": "table", "id": 295, "content": { "text": "", "html": "
JurisdictionGATS XVII Reservation (1994)Foreign Ownership PermittedRestrictions on Foreign OwnershipForeign Ownership Reporting Requirements
by persons of same nationality must not exceed 40% of the quarter.
CanadaYYProhibition on ownership of residential property with exceptions; some provinces also restrict ownership, including of agricultural land.
ChileNYProhibition on acquisition of public lands within 10 kilometers from the border and favorable military report required for acquisition of land 5 kilometers from the coast; nationals of bordering countries and legal persons with their principal place of business in one of those countries cannot obtain rights to real estate located totally or partially in the border area.
ChinaN (2001)NNo individuals, domestic or foreign, can privately own land. The state grants land use rights to land users for a certain number of years. Foreigners can obtain such land use rights, own residential houses and apartments, or incorporate foreign-invested enterprises to invest in real estate.
EgyptYYProhibition on ownership of agriculture lands, land in Sinai Peninsula; otherwise, permitted to own up to two properties, up to 4,000 square meters, for residential purposes; no disposition for 5 years; approval required to acquire land in tourist areas; joint ownership with an Egyptian who has majority
", "markdown": "" } }, { "coordinates": [ { "x": 0.22931095957756042, "y": 0.0478389747440815 }, { "x": 0.7695094645023346, "y": 0.0478389747440815 }, { "x": 0.7695094645023346, "y": 0.06201539747416973 }, { "x": 0.22931095957756042, "y": 0.06201539747416973 } ], "category": "heading1", "id": 327, "content": { "text": "Restrictions on Land Ownership by Foreigners in Selected Jurisdictions\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11681371182203293, "y": 0.9407886862754822 }, { "x": 0.33857888728380203, "y": 0.9407886862754822 }, { "x": 0.33857888728380203, "y": 0.9545711539685726 }, { "x": 0.11681371182203293, "y": 0.9545711539685726 } ], "category": "footer", "id": 329, "content": { "text": "The Law Library of Congress\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8653510212898254, "y": 0.9411962032318115 }, { "x": 0.8735725870355964, "y": 0.9411962032318115 }, { "x": 0.8735725870355964, "y": 0.9510027095675468 }, { "x": 0.8653510212898254, "y": 0.9510027095675468 } ], "category": "paragraph", "id": 330, "content": { "text": "6\n", "html": "", "markdown": "" } } ] }, "01030000000161.pdf": { "elements": [ { "coordinates": [ { "x": 0.14886228740215302, "y": 0.11622516810894012 }, { "x": 0.8389325588941574, "y": 0.11622516810894012 }, { "x": 0.8389325588941574, "y": 0.893609032034874 }, { "x": 0.14886228740215302, "y": 0.893609032034874 } ], "category": "table", "id": 270, "content": { "text": "", "html": "
of any individual to color their decisions, even when they're acting in good faith.
Credentials: Academic credentials tend to represent a significant commitment of time towards gaining mastery of a subject, and therefore requiring a particular degree may increase the likelihood of accurate information. However, not all groups are equally represented in higher education. Degree completion is uneven across race and income factors (among others), making academia not demographically representative of our society as a whole. Some perspectives are therefore systematically underrepresented in groups with advanced degrees.
Peer Review: Peer review sometimes only results in collaborative improvements to a work. It can also prevent the publication of very obviously flawed or poorly executed or analyzed research. Very new or radical ideas may be initially rejected because they are such a departure from existing dogma. Peer review is largely a practice of academia, therefore has the same exclusionary problems mentioned in the credentials section. It is possible for individual reviewers to act in a biased or unethical way to prevent the publication of some works.
Fact Checking: Not a lot of downside here. Let me know if your students come up with anything good.
Domains: For some top level domains (mostly just gov and .edu) looking at the domain provides some assurance that the web content there is an official communication of a particular institution. There really isn't any problem with domains excluding
", "markdown": "" } }, { "coordinates": [ { "x": 0.245454341173172, "y": 0.1378730833530426 }, { "x": 0.7940286695957184, "y": 0.1378730833530426 }, { "x": 0.7940286695957184, "y": 0.17728682234883308 }, { "x": 0.245454341173172, "y": 0.17728682234883308 } ], "category": "paragraph", "id": 281, "content": { "text": "of any individual to color their decisions, even when\nthey're acting in good faith.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.21709178388118744, "y": 0.18380001187324524 }, { "x": 0.8058909028768539, "y": 0.18380001187324524 }, { "x": 0.8058909028768539, "y": 0.4515354335308075 }, { "x": 0.21709178388118744, "y": 0.4515354335308075 } ], "category": "paragraph", "id": 283, "content": { "text": "Credentials: Academic credentials tend to\nrepresent a significant commitment of time towards\ngaining mastery of a subject, and therefore requiring\na particular degree may increase the likelihood of\naccurate information. However, not all groups are\nequally represented in higher education. Degree\ncompletion is uneven across race and income factors\n(among others), making academia not\ndemographically representative of our society as a\nwhole. Some perspectives are therefore\nsystematically underrepresented in groups with\nadvanced degrees.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.2164347767829895, "y": 0.45832309126853943 }, { "x": 0.811318576335907, "y": 0.45832309126853943 }, { "x": 0.811318576335907, "y": 0.7028461545705795 }, { "x": 0.2164347767829895, "y": 0.7028461545705795 } ], "category": "paragraph", "id": 284, "content": { "text": "Peer Review: Peer review sometimes only results in\ncollaborative improvements to a work. It can also\nprevent the publication of very obviously flawed or\npoorly executed or analyzed research. Very new or\nradical ideas may be initially rejected because they\nare such a departure from existing dogma. Peer\nreview is largely a practice of academia, therefore has\nthe same exclusionary problems mentioned in the\ncredentials section. It is possible for individual\nreviewers to act in a biased or unethical way to\nprevent the publication of some works.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.21628737449645996, "y": 0.7098742127418518 }, { "x": 0.7990385293960571, "y": 0.7098742127418518 }, { "x": 0.7990385293960571, "y": 0.7486540488898754 }, { "x": 0.21628737449645996, "y": 0.7486540488898754 } ], "category": "paragraph", "id": 285, "content": { "text": "Fact Checking: Not a lot of downside here. Let me\nknow if your students come up with anything good.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.216979518532753, "y": 0.7554033398628235 }, { "x": 0.7910007983446121, "y": 0.7554033398628235 }, { "x": 0.7910007983446121, "y": 0.8633285015821457 }, { "x": 0.216979518532753, "y": 0.8633285015821457 } ], "category": "paragraph", "id": 286, "content": { "text": "Domains: For some top level domains (mostly just\ngov and .edu) looking at the domain provides some\nassurance that the web content there is an official\ncommunication of a particular institution. There\nreally isn't any problem with domains excluding\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1424829214811325, "y": 0.9241464734077454 }, { "x": 0.1737011056393385, "y": 0.9241464734077454 }, { "x": 0.1737011056393385, "y": 0.9346712687984109 }, { "x": 0.1424829214811325, "y": 0.9346712687984109 } ], "category": "paragraph", "id": 287, "content": { "text": "106\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.19968664646148682, "y": 0.9242287278175354 }, { "x": 0.39742831885814667, "y": 0.9242287278175354 }, { "x": 0.39742831885814667, "y": 0.9348464198410511 }, { "x": 0.19968664646148682, "y": 0.9348464198410511 } ], "category": "footer", "id": 288, "content": { "text": "Instructor Resources\n", "html": "", "markdown": "" } } ] }, "01030000000182.pdf": { "elements": [ { "coordinates": [ { "x": 0.028966514393687248, "y": 0.2818114161491394 }, { "x": 0.9692688267678022, "y": 0.2818114161491394 }, { "x": 0.9692688267678022, "y": 0.9444939494132996 }, { "x": 0.028966514393687248, "y": 0.9444939494132996 } ], "category": "table", "id": 256, "content": { "text": "", "html": "
OCRRecommendationProduct semantic search
PackA solution that recognizes characters in an image and extracts necessary informationA solution that recommends the best products and contentsA solution that enables semantic search, analyzes and organizes key information in unstructured text data into a standardized form (DB)
ApplicationApplicable to all fields that require text extraction from standardized documents, such as receipts, bills, credit cards, ID cards, certificates, and medical receiptsApplicable to all fields that use any form of recommendation including alternative products, products and contents that are likely to be purchased nextApplicable to all fields that deal with various types of unstructured data containing text information that require semantic search and conversion into a DB
HighlightAchieved 1st place in the OCR World Competition The team includes specialists who have presented 14 papers in the world's most renowned Al conferencesTeam with specialists and technologies that received Kaggle's Gold Medal recommendation (Education platform) Proven superior performance of more than 170% compared to other global top-tier recommendation modelsCreation of the first natural language evaluation system in Korean (KLUE) World's No.1 in Kaggle text embedding competition in E-commerce subject (Shopee)
", "markdown": "" } }, { "coordinates": [ { "x": 0.07366440445184708, "y": 0.07639086246490479 }, { "x": 0.11326251178979874, "y": 0.07639086246490479 }, { "x": 0.11326251178979874, "y": 0.09328206814825535 }, { "x": 0.07366440445184708, "y": 0.09328206814825535 } ], "category": "paragraph", "id": 274, "content": { "text": "Al Pack\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.07387454807758331, "y": 0.11093553900718689 }, { "x": 0.7606330662965775, "y": 0.11093553900718689 }, { "x": 0.7606330662965775, "y": 0.20462821424007416 }, { "x": 0.07387454807758331, "y": 0.20462821424007416 } ], "category": "paragraph", "id": 275, "content": { "text": "Upstage offers 3 Al packs that process unstructured information and data,\nmaking a tangible impact on your business\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.9663792848587036, "y": 0.9487667679786682 }, { "x": 0.9760476872324944, "y": 0.9487667679786682 }, { "x": 0.9760476872324944, "y": 0.9618439748883247 }, { "x": 0.9663792848587036, "y": 0.9618439748883247 } ], "category": "paragraph", "id": 277, "content": { "text": "11\n", "html": "", "markdown": "" } } ] }, "01030000000115.pdf": { "elements": [ { "coordinates": [ { "x": 0.12988556921482086, "y": 0.05139254778623581 }, { "x": 0.40503285825252533, "y": 0.05139254778623581 }, { "x": 0.40503285825252533, "y": 0.0658027920871973 }, { "x": 0.12988556921482086, "y": 0.0658027920871973 } ], "category": "header", "id": 294, "content": { "text": "MOHAVE COMMUNITY COLLEGE\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.811305046081543, "y": 0.05309353768825531 }, { "x": 0.8812450617551804, "y": 0.05309353768825531 }, { "x": 0.8812450617551804, "y": 0.06582551915198565 }, { "x": 0.811305046081543, "y": 0.06582551915198565 } ], "category": "header", "id": 295, "content": { "text": "BIO181\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14638414978981018, "y": 0.09327571094036102 }, { "x": 0.8394132554531097, "y": 0.09327571094036102 }, { "x": 0.8394132554531097, "y": 0.12770353257656097 }, { "x": 0.14638414978981018, "y": 0.12770353257656097 } ], "category": "paragraph", "id": 296, "content": { "text": "5. Sample problem: If the ocular has a 10x lens and the objective has a 45x lens the total\nmagnification is 10 X 45 = 450x\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11733170598745346, "y": 0.14117319881916046 }, { "x": 0.29192090779542923, "y": 0.14117319881916046 }, { "x": 0.29192090779542923, "y": 0.15643001068383455 }, { "x": 0.11733170598745346, "y": 0.15643001068383455 } ], "category": "heading1", "id": 297, "content": { "text": "Changing objectives:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14899474382400513, "y": 0.16969722509384155 }, { "x": 0.8216459155082703, "y": 0.16969722509384155 }, { "x": 0.8216459155082703, "y": 0.20578527823090553 }, { "x": 0.14899474382400513, "y": 0.20578527823090553 } ], "category": "paragraph", "id": 299, "content": { "text": "1. When changing objectives from scanning power to lower power to high power the\nfollowing changes will occur:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.20504158735275269, "y": 0.21035335958003998 }, { "x": 0.5352981686592102, "y": 0.21035335958003998 }, { "x": 0.5352981686592102, "y": 0.22228265926241875 }, { "x": 0.20504158735275269, "y": 0.22228265926241875 } ], "category": "paragraph", "id": 300, "content": { "text": "a. The size of the field of view decreases\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.2054714411497116, "y": 0.23033195734024048 }, { "x": 0.4994877129793167, "y": 0.23033195734024048 }, { "x": 0.4994877129793167, "y": 0.24218806251883507 }, { "x": 0.2054714411497116, "y": 0.24218806251883507 } ], "category": "paragraph", "id": 301, "content": { "text": "b. The field of view becomes darker\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.20568497478961945, "y": 0.25041520595550537 }, { "x": 0.47980014979839325, "y": 0.25041520595550537 }, { "x": 0.47980014979839325, "y": 0.2652433952316642 }, { "x": 0.20568497478961945, "y": 0.2652433952316642 } ], "category": "paragraph", "id": 302, "content": { "text": "C. The size of the image increases\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.20600683987140656, "y": 0.27016976475715637 }, { "x": 0.5915838032960892, "y": 0.27016976475715637 }, { "x": 0.5915838032960892, "y": 0.2852449370548129 }, { "x": 0.20600683987140656, "y": 0.2852449370548129 } ], "category": "paragraph", "id": 303, "content": { "text": "d. The resolution (ability to see detail) increases\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.2055726945400238, "y": 0.2903019189834595 }, { "x": 0.8006362020969391, "y": 0.2903019189834595 }, { "x": 0.8006362020969391, "y": 0.3056985652074218 }, { "x": 0.2055726945400238, "y": 0.3056985652074218 } ], "category": "paragraph", "id": 304, "content": { "text": "e. The working distance between the slide and the objective lens decreases\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.20611055195331573, "y": 0.31014135479927063 }, { "x": 0.7962752133607864, "y": 0.31014135479927063 }, { "x": 0.7962752133607864, "y": 0.32567592058330774 }, { "x": 0.20611055195331573, "y": 0.32567592058330774 } ], "category": "paragraph", "id": 305, "content": { "text": "f. The depth of focus (thickness of the specimen that is visible) is reduced\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14627516269683838, "y": 0.330295205116272 }, { "x": 0.8630604147911072, "y": 0.330295205116272 }, { "x": 0.8630604147911072, "y": 0.36472896486520767 }, { "x": 0.14627516269683838, "y": 0.36472896486520767 } ], "category": "paragraph", "id": 306, "content": { "text": "2. When changing from scanning to low power the field of view gets smaller. In fact, every\ntime you increase the power of the objective, the field gets smaller.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11733748763799667, "y": 0.40715843439102173 }, { "x": 0.38283421844244003, "y": 0.40715843439102173 }, { "x": 0.38283421844244003, "y": 0.42230190336704254 }, { "x": 0.11733748763799667, "y": 0.42230190336704254 } ], "category": "heading1", "id": 307, "content": { "text": "Steps for Using the Microscope:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14820590615272522, "y": 0.43568742275238037 }, { "x": 0.8731231391429901, "y": 0.43568742275238037 }, { "x": 0.8731231391429901, "y": 0.4716865010559559 }, { "x": 0.14820590615272522, "y": 0.4716865010559559 } ], "category": "paragraph", "id": 309, "content": { "text": "1. Place the slide on the stage lining it up with the rectangle and using the stage clip to hold\nit in place.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.147202268242836, "y": 0.7113455533981323 }, { "x": 0.8494864255189896, "y": 0.7113455533981323 }, { "x": 0.8494864255189896, "y": 0.7268335912376642 }, { "x": 0.147202268242836, "y": 0.7268335912376642 } ], "category": "paragraph", "id": 310, "content": { "text": "2. Click the nosepiece to the lowest (shortest) setting, the scanning objective lens or 4x.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14719977974891663, "y": 0.731610119342804 }, { "x": 0.35868264734745026, "y": 0.731610119342804 }, { "x": 0.35868264734745026, "y": 0.7465129774063826 }, { "x": 0.14719977974891663, "y": 0.7465129774063826 } ], "category": "paragraph", "id": 311, "content": { "text": "3. Look into the eyepiece.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1471947729587555, "y": 0.7513052821159363 }, { "x": 0.8788988888263702, "y": 0.7513052821159363 }, { "x": 0.8788988888263702, "y": 0.7872586399316788 }, { "x": 0.1471947729587555, "y": 0.7872586399316788 } ], "category": "paragraph", "id": 312, "content": { "text": "4.\nUse the coarse adjustment knob to bring the specimen into view. The specimen must be\nin focus before moving to the next steps.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14762437343597412, "y": 0.7917941808700562 }, { "x": 0.6166002452373505, "y": 0.7917941808700562 }, { "x": 0.6166002452373505, "y": 0.8068563742563128 }, { "x": 0.14762437343597412, "y": 0.8068563742563128 } ], "category": "paragraph", "id": 313, "content": { "text": "5. Rotate the nosepiece to the low-power objective or 10x.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14708183705806732, "y": 0.811619758605957 }, { "x": 0.5104667991399765, "y": 0.811619758605957 }, { "x": 0.5104667991399765, "y": 0.8267684485763311 }, { "x": 0.14708183705806732, "y": 0.8267684485763311 } ], "category": "paragraph", "id": 314, "content": { "text": "6. Refocus using the coarse adjustment knob.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14729541540145874, "y": 0.8315572738647461 }, { "x": 0.47325536608695984, "y": 0.8315572738647461 }, { "x": 0.47325536608695984, "y": 0.8464935263618827 }, { "x": 0.14729541540145874, "y": 0.8464935263618827 } ], "category": "paragraph", "id": 315, "content": { "text": "7. Move the slide to get a centered view.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14740090072155, "y": 0.8515586853027344 }, { "x": 0.7318129986524582, "y": 0.8515586853027344 }, { "x": 0.7318129986524582, "y": 0.8670502109453082 }, { "x": 0.14740090072155, "y": 0.8670502109453082 } ], "category": "paragraph", "id": 316, "content": { "text": "8. Now use the fine adjustment knob to get the specimen in perfect focus.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1471824049949646, "y": 0.8716254234313965 }, { "x": 0.7754199504852295, "y": 0.8716254234313965 }, { "x": 0.7754199504852295, "y": 0.88705038651824 }, { "x": 0.1471824049949646, "y": 0.88705038651824 } ], "category": "paragraph", "id": 317, "content": { "text": "9.\nYour slide MUST be focused on low power before attempting this next step.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1746433973312378, "y": 0.4711681008338928 }, { "x": 0.5071035921573639, "y": 0.4711681008338928 }, { "x": 0.5071035921573639, "y": 0.6696389615535736 }, { "x": 0.1746433973312378, "y": 0.6696389615535736 } ], "category": "figure", "id": 318, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.4896472692489624, "y": 0.92514967918396 }, { "x": 0.5091034807264805, "y": 0.92514967918396 }, { "x": 0.5091034807264805, "y": 0.9359703939408064 }, { "x": 0.4896472692489624, "y": 0.9359703939408064 } ], "category": "paragraph", "id": 319, "content": { "text": "20\n", "html": "", "markdown": "" } } ] }, "01030000000071.pdf": { "elements": [ { "coordinates": [ { "x": 0.12076114863157272, "y": 0.08732742071151733 }, { "x": 0.8795386478304863, "y": 0.08732742071151733 }, { "x": 0.8795386478304863, "y": 0.19699964672327042 }, { "x": 0.12076114863157272, "y": 0.19699964672327042 } ], "category": "paragraph", "id": 391, "content": { "text": "be used as a good opportunity to learn from each other and increase the capacity of\nhuman rights institutions in various countries. 94\nWhat works in other countries, can be learned and developed according to the\nsituation in Indonesia.\n95 Partnerships can be carried out formally through\na\nmemorandum of understanding or with a partnerships agreement for potential\nstrategic partners.\n96\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12051921337842941, "y": 0.21955861151218414 }, { "x": 0.5302613601088524, "y": 0.21955861151218414 }, { "x": 0.5302613601088524, "y": 0.23152471333742142 }, { "x": 0.12051921337842941, "y": 0.23152471333742142 } ], "category": "heading1", "id": 392, "content": { "text": "3.2.6. SDGs Dissemination in Social Media\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12010225653648376, "y": 0.25701311230659485 }, { "x": 0.8792018592357635, "y": 0.25701311230659485 }, { "x": 0.8792018592357635, "y": 0.42005881667137146 }, { "x": 0.12010225653648376, "y": 0.42005881667137146 } ], "category": "paragraph", "id": 393, "content": { "text": "Information dissemination in the digital era is closely related to the use of social\nmedia. Therefore, the dissemination of the SDGs through social media platforms\nowned by the Komnas HAM needs to be optimized as a way to increase public\nparticipation to be active as \"agents\" of the Komnas HAM in Indonesia. To be able to\nachieve this, the community needs to first receive education about the SDGs to clearly\nunderstand the focus of each goal and its derivatives. Once there is a fairly good\nunderstanding at the level of the general public, especially those who interact with the\nKomnas HAM's social media, an easier way to report SDGs related to human rights\nviolations can be formulated.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12061446160078049, "y": 0.4265764653682709 }, { "x": 0.8786477372050285, "y": 0.4265764653682709 }, { "x": 0.8786477372050285, "y": 0.5173230245709419 }, { "x": 0.12061446160078049, "y": 0.5173230245709419 } ], "category": "paragraph", "id": 394, "content": { "text": "The Komnas HAM, for example, has used social media Instagram, Twitter, and\nYouTube There has been an increase in the frequency of Instagram social media\nuploads from 2019-2020 from 111 uploads in 2019 to 198 uploads in 2020. The variety\nof content uploaded by the Komnas HAM on Instagram is also increasingly diverse\nwith the following details:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12180093675851822, "y": 0.5221339464187622 }, { "x": 0.8862808123230934, "y": 0.5221339464187622 }, { "x": 0.8862808123230934, "y": 0.7273510247468948 }, { "x": 0.12180093675851822, "y": 0.7273510247468948 } ], "category": "figure", "id": 395, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1533377319574356, "y": 0.7553743720054626 }, { "x": 0.2338498830795288, "y": 0.7553743720054626 }, { "x": 0.2338498830795288, "y": 0.7670670542865992 }, { "x": 0.1533377319574356, "y": 0.7670670542865992 } ], "category": "paragraph", "id": 396, "content": { "text": "Diagram 4\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.2763611376285553, "y": 0.7548248171806335 }, { "x": 0.7636035680770874, "y": 0.7548248171806335 }, { "x": 0.7636035680770874, "y": 0.7672847816720605 }, { "x": 0.2763611376285553, "y": 0.7672847816720605 } ], "category": "paragraph", "id": 397, "content": { "text": "Distribution of @komnas.ham Instagram Content (2019-2020)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12098298221826553, "y": 0.7918950319290161 }, { "x": 0.8792221322655678, "y": 0.7918950319290161 }, { "x": 0.8792221322655678, "y": 0.8260165862739086 }, { "x": 0.12098298221826553, "y": 0.8260165862739086 } ], "category": "paragraph", "id": 398, "content": { "text": "If observed from the Komnas HAM's Instagram account within the 2019-2020\nperiod, the SDGs have only been mentioned explicitly twice in the following contents:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12045305967330933, "y": 0.8613814115524292 }, { "x": 0.8783614635467529, "y": 0.8613814115524292 }, { "x": 0.8783614635467529, "y": 0.9131349138915539 }, { "x": 0.12045305967330933, "y": 0.9131349138915539 } ], "category": "footer", "id": 399, "content": { "text": "94 See also Komnas HAM, \"The NHRI Practice and Experience in Indonesia, Kyrgyzstan, and Palestine\nin Supporting Sustainable Development Goals Achievements\" (n. 93).\n95 Ibid.\n96 Ibid.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.49092379212379456, "y": 0.9322063326835632 }, { "x": 0.5088631082326174, "y": 0.9322063326835632 }, { "x": 0.5088631082326174, "y": 0.9415519302710891 }, { "x": 0.49092379212379456, "y": 0.9415519302710891 } ], "category": "paragraph", "id": 400, "content": { "text": "18\n", "html": "", "markdown": "" } } ] }, "01030000000170.pdf": { "elements": [ { "coordinates": [ { "x": 0.08947648108005524, "y": 0.11907658725976944 }, { "x": 0.9093162566423416, "y": 0.11907658725976944 }, { "x": 0.9093162566423416, "y": 0.3073340877890587 }, { "x": 0.08947648108005524, "y": 0.3073340877890587 } ], "category": "table", "id": 436, "content": { "text": "", "html": "
Contour FarmingContour FarmingContour Strip CroppingContour Strip CroppingContour Strip Cropping
Slope Gradient (%)Max Slope Length (ft)P ValueStrip Width (ft)P Value, RGMMP Value, RRGM
1 24000.61300.300.45
3 53000.51000.250.38
6 82000.51000.250.38
9 121200.6800.300.45
13 161000.7800.350.52
17 201000.8600.400.60
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Terrace IntervalUnderground OutletsWaterways with percent grade of:
(ft)0.1-0.30.4-0.70.8
Pt ValuesPt ValuesPt ValuesPt Values
<1100.50.60.71.0
110-1400.60.70.81.0
140-1800.70.80.91.0
180-2250.80.80.91.0
225-3000.90.91.01.0
300+1.01.01.01.0
", "markdown": "" } }, { "coordinates": [ { "x": 0.09203782677650452, "y": 0.07614535838365555 }, { "x": 0.18007591366767883, "y": 0.07614535838365555 }, { "x": 0.18007591366767883, "y": 0.09309986606240273 }, { "x": 0.09203782677650452, "y": 0.09309986606240273 } ], "category": "header", "id": 534, "content": { "text": "cropping.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09174013882875443, "y": 0.32619476318359375 }, { "x": 0.9066510871052742, "y": 0.32619476318359375 }, { "x": 0.9066510871052742, "y": 0.37438859045505524 }, { "x": 0.09174013882875443, "y": 0.37438859045505524 } ], "category": "paragraph", "id": 536, "content": { "text": "Table adapted from Jones et al. (1988) with permission. Strip cropping uses a four-year rotation of row crop followed\nby one year of a small grain and two years of meadow (forages) for RGMM, or uses two years of row crops followed by\none year of small grain and one year of meadow for RRGM. Meadow includes alfalfa, clover, grass, etc.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09166759997606277, "y": 0.3927895128726959 }, { "x": 0.12405857443809509, "y": 0.3927895128726959 }, { "x": 0.12405857443809509, "y": 0.4168182108551264 }, { "x": 0.09166759997606277, "y": 0.4168182108551264 } ], "category": "figure", "id": 537, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14963144063949585, "y": 0.3910050690174103 }, { "x": 0.7434849143028259, "y": 0.3910050690174103 }, { "x": 0.7434849143028259, "y": 0.40338143426924944 }, { "x": 0.14963144063949585, "y": 0.40338143426924944 } ], "category": "paragraph", "id": 539, "content": { "text": "How does the erosion rate under contour tillage compare to the tolerable erosion rate?\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14868147671222687, "y": 0.448697030544281 }, { "x": 0.9026969820261002, "y": 0.448697030544281 }, { "x": 0.9026969820261002, "y": 0.4616491375491023 }, { "x": 0.14868147671222687, "y": 0.4616491375491023 } ], "category": "paragraph", "id": 540, "content": { "text": "How does the erosion rate under contour tillage compare to the erosion rate under conservation tillage alone?\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09120164811611176, "y": 0.4494923949241638 }, { "x": 0.12461945414543152, "y": 0.4494923949241638 }, { "x": 0.12461945414543152, "y": 0.4751902688294649 }, { "x": 0.09120164811611176, "y": 0.4751902688294649 } ], "category": "figure", "id": 541, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09221338480710983, "y": 0.5068643093109131 }, { "x": 0.9069219753146172, "y": 0.5068643093109131 }, { "x": 0.9069219753146172, "y": 0.5899053886532784 }, { "x": 0.09221338480710983, "y": 0.5899053886532784 } ], "category": "paragraph", "id": 542, "content": { "text": "Next we will test the impact of installing terraces on the landscape. Using Table 16.5, determine the Pt factor. When\nterraces are installed, contour tillage is usually used as well. Also, note that installing a terrace results in a shorter length\nof the slope (because the terrace stops water from continuing to run down slope), SO this calculation is performed for\neach terrace individually. Also note that the net P factor is determined by multiplying the\nPc and Pt values together, or writing the RUSLE as follows:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14202287793159485, "y": 0.6071365475654602 }, { "x": 0.42207688093185425, "y": 0.6071365475654602 }, { "x": 0.42207688093185425, "y": 0.6210311846807599 }, { "x": 0.14202287793159485, "y": 0.6210311846807599 } ], "category": "paragraph", "id": 543, "content": { "text": "A4 = RxKxLS xPc X Pt\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09122029691934586, "y": 0.6641888618469238 }, { "x": 0.8726607337594032, "y": 0.6641888618469238 }, { "x": 0.8726607337594032, "y": 0.7048895470798016 }, { "x": 0.09122029691934586, "y": 0.7048895470798016 } ], "category": "paragraph", "id": 544, "content": { "text": "Table 16.5. Conservation practice (P) values for terraces with underground outlets or\nwaterways.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09216714650392532, "y": 0.9419100880622864 }, { "x": 0.11134366691112518, "y": 0.9419100880622864 }, { "x": 0.11134366691112518, "y": 0.949843286536634 }, { "x": 0.09216714650392532, "y": 0.949843286536634 } ], "category": "paragraph", "id": 546, "content": { "text": "146\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12831299006938934, "y": 0.941585123538971 }, { "x": 0.31114891171455383, "y": 0.941585123538971 }, { "x": 0.31114891171455383, "y": 0.949890504591167 }, { "x": 0.12831299006938934, "y": 0.949890504591167 } ], "category": "footer", "id": 547, "content": { "text": "Soil Erosion and Conservation\n", "html": "", "markdown": "" } } ] }, "01030000000156.pdf": { "elements": [ { "coordinates": [ { "x": 0.35849788784980774, "y": 0.09004995971918106 }, { "x": 0.3697083117440343, "y": 0.09004995971918106 }, { "x": 0.3697083117440343, "y": 0.10095431935042143 }, { "x": 0.35849788784980774, "y": 0.10095431935042143 } ], "category": "paragraph", "id": 259, "content": { "text": "2\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1441826969385147, "y": 0.09624794125556946 }, { "x": 0.35085824131965637, "y": 0.09624794125556946 }, { "x": 0.35085824131965637, "y": 0.12068407237529755 }, { "x": 0.1441826969385147, "y": 0.12068407237529755 } ], "category": "heading1", "id": 260, "content": { "text": "Fact-Checking\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.20017097890377045, "y": 0.2114243060350418 }, { "x": 0.37491850554943085, "y": 0.2114243060350418 }, { "x": 0.37491850554943085, "y": 0.7038073390722275 }, { "x": 0.20017097890377045, "y": 0.7038073390722275 } ], "category": "paragraph", "id": 261, "content": { "text": "In this\ncontext, we are\ntalking about\nfact-checking\nthat is done\nbefore a source\nis published.\nOver the last\ntwo decades\nthere has been\nan increase in\nfact checking as\nan activity that\ntakes place after\na source has\nbeen published,\na practice\ndiscussed in\nmore detail in\nthe chapter,\nSIFTing\nInformation.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.4591967463493347, "y": 0.15898972749710083 }, { "x": 0.8565429151058197, "y": 0.15898972749710083 }, { "x": 0.8565429151058197, "y": 0.3809971809387207 }, { "x": 0.4591967463493347, "y": 0.3809971809387207 } ], "category": "paragraph", "id": 262, "content": { "text": "Fact checkers verify that the names,\ndates, and facts in a work (usually an\narticle or book) are correct. For\nexample, they may contact a person\nwho is quoted in a proposed news\narticle and ask the person whether\nthis quotation is correct, or how to\nspell the person's name. Fact-\ncheckers are primarily useful in\ncatching accidental mistakes.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.4593781530857086, "y": 0.38745686411857605 }, { "x": 0.8567997813224792, "y": 0.38745686411857605 }, { "x": 0.8567997813224792, "y": 0.6983264684677124 }, { "x": 0.4593781530857086, "y": 0.6983264684677124 } ], "category": "paragraph", "id": 263, "content": { "text": "The number of people employed in\nfact-checking varies by publication.\nSome organizations have substantial\nfact-checking departments. Others\nmay hire freelancers per piece, or\nmay combine fact-checking with\nother duties. Magazines are more\nlikely to use fact checkers than\nnewspapers. Television and radio\nprograms rarely employ dedicated\nfact checkers, and instead expect\nothers, including senior staff, to\nengage in fact-checking in addition to\ntheir other duties.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11467418819665909, "y": 0.8314220309257507 }, { "x": 0.8524938002228737, "y": 0.8314220309257507 }, { "x": 0.8524938002228737, "y": 0.9044679552316666 }, { "x": 0.11467418819665909, "y": 0.9044679552316666 } ], "category": "paragraph", "id": 264, "content": { "text": "2. Content in this section is adapted from the Wikipedia\nentry \"Fact-checking\" (https://en.wikipedia.org/wiki/\nFact-checking) and is used under a CC BY-SA 3.0 license.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14215098321437836, "y": 0.9244820475578308 }, { "x": 0.16443824395537376, "y": 0.9244820475578308 }, { "x": 0.16443824395537376, "y": 0.9349068449810147 }, { "x": 0.14215098321437836, "y": 0.9349068449810147 } ], "category": "footer", "id": 265, "content": { "text": "48\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.19031581282615662, "y": 0.9238124489784241 }, { "x": 0.3507723808288574, "y": 0.9238124489784241 }, { "x": 0.3507723808288574, "y": 0.9379878360778093 }, { "x": 0.19031581282615662, "y": 0.9379878360778093 } ], "category": "footer", "id": 266, "content": { "text": "Types of Sources\n", "html": "", "markdown": "" } } ] }, "01030000000160.pdf": { "elements": [ { "coordinates": [ { "x": 0.182479128241539, "y": 0.12306512892246246 }, { "x": 0.8156568855047226, "y": 0.12306512892246246 }, { "x": 0.8156568855047226, "y": 0.34512190520763397 }, { "x": 0.182479128241539, "y": 0.34512190520763397 } ], "category": "paragraph", "id": 301, "content": { "text": "Other advice that might smooth the way for this exercise\nis to remind students right before they start that we aren't\ninterested in what these organizations' websites say about\nthemselves, but what they can learn about them from the\nrest of the internet. Encourage use of Wikipedia for this\ntype of source research. Encourage them to slow down and\nto practice \"click restraint\" once they have Googled one of\nthese orgs. What can they learn from looking at just the\nsearch results page, without clicking through to anything?\nWhat is the overall impression from a variety of results?\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.2166479229927063, "y": 0.36639997363090515 }, { "x": 0.8119146227836609, "y": 0.36639997363090515 }, { "x": 0.8119146227836609, "y": 0.520577684044838 }, { "x": 0.2166479229927063, "y": 0.520577684044838 } ], "category": "paragraph", "id": 303, "content": { "text": "Center for Consumer Freedom: Many of the Google\nsearch results (with or without including the search\nterm funding) indicate this is astroturing. A look at\nthe Wikipedia page tells us that this org was started\nby a pretty well known PR guy and the sidebar lists\ntheir focus as \"represents the interests of restaurant\nand food companies\" and their method as \"lobbying.\"\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.21673093736171722, "y": 0.5265010595321655 }, { "x": 0.7897136062383652, "y": 0.5265010595321655 }, { "x": 0.7897136062383652, "y": 0.6116166561841965 }, { "x": 0.21673093736171722, "y": 0.6116166561841965 } ], "category": "paragraph", "id": 304, "content": { "text": "National Consumers League: Students may note\nthat it has been around since 1899, has no critical\nresults on the first page of Google results, and even\nhas an entry in the Encyclopedia Britannica.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.21669639647006989, "y": 0.6179261207580566 }, { "x": 0.7983216196298599, "y": 0.6179261207580566 }, { "x": 0.7983216196298599, "y": 0.6574629843235016 }, { "x": 0.21669639647006989, "y": 0.6574629843235016 } ], "category": "paragraph", "id": 305, "content": { "text": "One Fair Wage: a legitimately grass-roots effort to\nraise the minimum wage for restaurant workers.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.21657849848270416, "y": 0.6640005707740784 }, { "x": 0.8155117779970169, "y": 0.6640005707740784 }, { "x": 0.8155117779970169, "y": 0.8139756321907043 }, { "x": 0.21657849848270416, "y": 0.8139756321907043 } ], "category": "paragraph", "id": 306, "content": { "text": "Save Our Tips: This is one case where adding the\nword funding to the search helps a bit. If we do that\nwe find sources indicating that this group is funded in\npart by the National Restaurant Association and a\nconservative strategy and consulting group. Not\nwhat you would expect for a grassroots effort lead by\nwaitstaff.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1424490511417389, "y": 0.9244097471237183 }, { "x": 0.1733726654201746, "y": 0.9244097471237183 }, { "x": 0.1733726654201746, "y": 0.9346693316474557 }, { "x": 0.1424490511417389, "y": 0.9346693316474557 } ], "category": "paragraph", "id": 307, "content": { "text": "104\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.19905023276805878, "y": 0.9243102073669434 }, { "x": 0.3968605548143387, "y": 0.9243102073669434 }, { "x": 0.3968605548143387, "y": 0.9349665325134993 }, { "x": 0.19905023276805878, "y": 0.9349665325134993 } ], "category": "footer", "id": 308, "content": { "text": "Instructor Resources\n", "html": "", "markdown": "" } } ] }, "01030000000050.pdf": { "elements": [ { "coordinates": [ { "x": 0.24136389791965485, "y": 0.056465428322553635 }, { "x": 0.8405526429414749, "y": 0.056465428322553635 }, { "x": 0.8405526429414749, "y": 0.07247982174158096 }, { "x": 0.24136389791965485, "y": 0.07247982174158096 } ], "category": "header", "id": 274, "content": { "text": "Overcoming Barriers to Filipino Women's Political Representation\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8780043721199036, "y": 0.05779295042157173 }, { "x": 0.9013340473175049, "y": 0.05779295042157173 }, { "x": 0.9013340473175049, "y": 0.0702271917834878 }, { "x": 0.8780043721199036, "y": 0.0702271917834878 } ], "category": "paragraph", "id": 275, "content": { "text": "11\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1978209763765335, "y": 0.109337218105793 }, { "x": 0.894740954041481, "y": 0.109337218105793 }, { "x": 0.894740954041481, "y": 0.14896783605217934 }, { "x": 0.1978209763765335, "y": 0.14896783605217934 } ], "category": "paragraph", "id": 277, "content": { "text": "Republic Act No. 9501: Magna Carta for Micro, Small, and\nMedium Enterprises (May 23, 2008)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1978033185005188, "y": 0.1662939041852951 }, { "x": 0.8946988582611084, "y": 0.1662939041852951 }, { "x": 0.8946988582611084, "y": 0.20599182322621346 }, { "x": 0.1978033185005188, "y": 0.20599182322621346 } ], "category": "paragraph", "id": 278, "content": { "text": "Republic Act No. 9262: Anti-Violence Against Women and\ntheir Children Act of 2004 (March 8,2004)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1977800577878952, "y": 0.22349122166633606 }, { "x": 0.8953965753316879, "y": 0.22349122166633606 }, { "x": 0.8953965753316879, "y": 0.2811446189880371 }, { "x": 0.1977800577878952, "y": 0.2811446189880371 } ], "category": "paragraph", "id": 279, "content": { "text": "Republic Act No. 9208 (May 26, 2003), as amended by\nRepublic Act No. 10364 (February 6, 2013): Anti-Trafficking in\nPersons Act of 2003\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1981782168149948, "y": 0.30255982279777527 }, { "x": 0.894879087805748, "y": 0.30255982279777527 }, { "x": 0.894879087805748, "y": 0.3417683020234108 }, { "x": 0.1981782168149948, "y": 0.3417683020234108 } ], "category": "paragraph", "id": 280, "content": { "text": "Republic Act No. 9178: Barangay Micro Business Enterprises\nAct of 2002 (November 13, 2002)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1980215311050415, "y": 0.35937023162841797 }, { "x": 0.89503014087677, "y": 0.35937023162841797 }, { "x": 0.89503014087677, "y": 0.39900263026356697 }, { "x": 0.1980215311050415, "y": 0.39900263026356697 } ], "category": "paragraph", "id": 281, "content": { "text": "Republic Act No. 8972: Solo Parent's Welfare Act (November\n7, 2000)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1980038434267044, "y": 0.41662245988845825 }, { "x": 0.895004466176033, "y": 0.41662245988845825 }, { "x": 0.895004466176033, "y": 0.45619339123368263 }, { "x": 0.1980038434267044, "y": 0.45619339123368263 } ], "category": "paragraph", "id": 282, "content": { "text": "Republic Act No. 8505: Rape Victim Assistance and Protection\nAct (February 13, 1998)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.19770826399326324, "y": 0.4736984372138977 }, { "x": 0.8946563154459, "y": 0.4736984372138977 }, { "x": 0.8946563154459, "y": 0.5130691714584827 }, { "x": 0.19770826399326324, "y": 0.5130691714584827 } ], "category": "paragraph", "id": 283, "content": { "text": "Republic Act No. 8504: Philippine AIDS Prevention and\nControl Act of 1998 (February 13, 1998)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.19769056141376495, "y": 0.5308960676193237 }, { "x": 0.8934062272310257, "y": 0.5308960676193237 }, { "x": 0.8934062272310257, "y": 0.5702853910624981 }, { "x": 0.19769056141376495, "y": 0.5702853910624981 } ], "category": "paragraph", "id": 284, "content": { "text": "Republic Act No. 8353: Anti-Rape Law of 1997 (September 30,\n1997)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.19739483296871185, "y": 0.5876564383506775 }, { "x": 0.8939670771360397, "y": 0.5876564383506775 }, { "x": 0.8939670771360397, "y": 0.627593170851469 }, { "x": 0.19739483296871185, "y": 0.627593170851469 } ], "category": "paragraph", "id": 285, "content": { "text": "Republic Act No. 7877: Anti-Sexual Harassment Act of 1995\n(February 14, 1995)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1451512575149536, "y": 0.644899308681488 }, { "x": 0.8961239457130432, "y": 0.644899308681488 }, { "x": 0.8961239457130432, "y": 0.7492902129888535 }, { "x": 0.1451512575149536, "y": 0.7492902129888535 } ], "category": "paragraph", "id": 286, "content": { "text": "During the first Aquino administration (1986-1992), three women\nsectoral representatives were appointed in Congress. Yet feminist\nactivists such as Teresita Quintos-Deles and Jurgette Honculada's\nappointments were blocked by the House Committee on Appointments\n(Abao and Yang 2001, 19).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14481429755687714, "y": 0.766897439956665 }, { "x": 0.895554706454277, "y": 0.766897439956665 }, { "x": 0.895554706454277, "y": 0.9143969416618347 }, { "x": 0.14481429755687714, "y": 0.9143969416618347 } ], "category": "paragraph", "id": 287, "content": { "text": "While reliable electoral data during the Marcos regime is\nunavailable, it is safe to argue that the repressive regime hampered\nthe participation of women in formal politics given the widespread\nmilitarization and electoral fraud characterizing the dictatorship. And\neven with the legal framework guaranteed by the transition, women\nfound it difficult to enter formal politics, despite women's consistently\nhigh voter turnout during elections (Table 1).\n", "html": "", "markdown": "" } } ] }, "01030000000109.pdf": { "elements": [ { "coordinates": [ { "x": 0.08716103434562683, "y": 0.20451566576957703 }, { "x": 0.9097802340984344, "y": 0.20451566576957703 }, { "x": 0.9097802340984344, "y": 0.45936119556427 }, { "x": 0.08716103434562683, "y": 0.45936119556427 } ], "category": "table", "id": 208, "content": { "text": "", "html": "
y=19t2
Rearranging Equation (8) gives:
t=(2))0.5(9)
Substitution of t and V from Equations 9 and 2 into Equation 7 results in:
x = CuV2gh(2)). (10)
Equations (10) can be rearranged to find Cv:
(11)
", "markdown": "" } }, { "coordinates": [ { "x": 0.09216378629207611, "y": 0.07213141769170761 }, { "x": 0.9067274779081345, "y": 0.07213141769170761 }, { "x": 0.9067274779081345, "y": 0.10812623053789139 }, { "x": 0.09216378629207611, "y": 0.10812623053789139 } ], "category": "paragraph", "id": 230, "content": { "text": "the jet velocity can be assumed to remain constant. Therefore, the horizontal distance traveled by jet\n(x) in time (t) is equal to:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09203896671533585, "y": 0.12353786826133728 }, { "x": 0.22766820341348648, "y": 0.12353786826133728 }, { "x": 0.22766820341348648, "y": 0.14088701456785202 }, { "x": 0.09203896671533585, "y": 0.14088701456785202 } ], "category": "paragraph", "id": 232, "content": { "text": "x=v.t\n(7)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09184414893388748, "y": 0.15818841755390167 }, { "x": 0.9062231853604317, "y": 0.15818841755390167 }, { "x": 0.9062231853604317, "y": 0.19422665610909462 }, { "x": 0.09184414893388748, "y": 0.19422665610909462 } ], "category": "paragraph", "id": 233, "content": { "text": "The vertical component of the trajectory of the jet will have a constant acceleration downward due to\nthe force of gravity. Therefore, at any time, t, the y-position of the jet may be calculated as:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09237581491470337, "y": 0.21004371345043182 }, { "x": 0.24748660624027252, "y": 0.21004371345043182 }, { "x": 0.24748660624027252, "y": 0.2312865499407053 }, { "x": 0.09237581491470337, "y": 0.2312865499407053 } ], "category": "paragraph", "id": 234, "content": { "text": "y=19t2\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09270298480987549, "y": 0.24684061110019684 }, { "x": 0.3453822731971741, "y": 0.24684061110019684 }, { "x": 0.3453822731971741, "y": 0.26221482921391726 }, { "x": 0.09270298480987549, "y": 0.26221482921391726 } ], "category": "paragraph", "id": 235, "content": { "text": "Rearranging Equation (8) gives:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09274347126483917, "y": 0.27724507451057434 }, { "x": 0.2603515088558197, "y": 0.27724507451057434 }, { "x": 0.2603515088558197, "y": 0.30305010452866554 }, { "x": 0.09274347126483917, "y": 0.30305010452866554 } ], "category": "paragraph", "id": 236, "content": { "text": "t=(2))0.5\n(9)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09183100610971451, "y": 0.31704726815223694 }, { "x": 0.6792446151375771, "y": 0.31704726815223694 }, { "x": 0.6792446151375771, "y": 0.3328353054821491 }, { "x": 0.09183100610971451, "y": 0.3328353054821491 } ], "category": "paragraph", "id": 237, "content": { "text": "Substitution of t and V from Equations 9 and 2 into Equation 7 results in:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09214042872190475, "y": 0.3480169475078583 }, { "x": 0.352582685649395, "y": 0.3480169475078583 }, { "x": 0.352582685649395, "y": 0.37405794858932495 }, { "x": 0.09214042872190475, "y": 0.37405794858932495 } ], "category": "paragraph", "id": 238, "content": { "text": "x = CuV2gh(2)).\n(10)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09219963103532791, "y": 0.38791897892951965 }, { "x": 0.445759154856205, "y": 0.38791897892951965 }, { "x": 0.445759154856205, "y": 0.40374545753002167 }, { "x": 0.09219963103532791, "y": 0.40374545753002167 } ], "category": "paragraph", "id": 239, "content": { "text": "Equations (10) can be rearranged to find Cv:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09252035617828369, "y": 0.42081475257873535 }, { "x": 0.27205875515937805, "y": 0.42081475257873535 }, { "x": 0.27205875515937805, "y": 0.43830803595483303 }, { "x": 0.09252035617828369, "y": 0.43830803595483303 } ], "category": "paragraph", "id": 240, "content": { "text": "(11)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09153283387422562, "y": 0.4579799771308899 }, { "x": 0.9066162183880806, "y": 0.4579799771308899 }, { "x": 0.9066162183880806, "y": 0.5137802064418793 }, { "x": 0.09153283387422562, "y": 0.5137802064418793 } ], "category": "paragraph", "id": 241, "content": { "text": "Therefore, for steady flow conditions (i.e., constant h in the head tank), the value of Cv can be\ndetermined from the X, y coordinates of the jet trajectory. A graph of x plotted against Vyh will have\na slope of 2Cv.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09234225004911423, "y": 0.5335264801979065 }, { "x": 0.6693365499377251, "y": 0.5335264801979065 }, { "x": 0.6693365499377251, "y": 0.5456004859879613 }, { "x": 0.09234225004911423, "y": 0.5456004859879613 } ], "category": "heading1", "id": 242, "content": { "text": "7.2. DETERMINATION OF THE COEFFICIENT OF DISCHARGE\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09224128723144531, "y": 0.5607017278671265 }, { "x": 0.9063143134117126, "y": 0.5607017278671265 }, { "x": 0.9063143134117126, "y": 0.6021324843168259 }, { "x": 0.09224128723144531, "y": 0.6021324843168259 } ], "category": "paragraph", "id": 243, "content": { "text": "If Cd is assumed to be constant, then a graph of Q plotted against Vh (Equation 6) will be linear, and\nthe slope of this graph will be:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09308639168739319, "y": 0.6177443861961365 }, { "x": 0.3006940931081772, "y": 0.6177443861961365 }, { "x": 0.3006940931081772, "y": 0.6348046511411667 }, { "x": 0.09308639168739319, "y": 0.6348046511411667 } ], "category": "paragraph", "id": 244, "content": { "text": "S = CdAov2g\n(12)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.59942626953125, "y": 0.941662073135376 }, { "x": 0.9059107601642609, "y": 0.941662073135376 }, { "x": 0.9059107601642609, "y": 0.9497146671637893 }, { "x": 0.59942626953125, "y": 0.9497146671637893 } ], "category": "footer", "id": 245, "content": { "text": "EXPERIMENT #6: ORIFICE AND FREE JET FLOW 53\n", "html": "", "markdown": "" } } ] }, "01030000000145.pdf": { "elements": [ { "coordinates": [ { "x": 0.15167886018753052, "y": 0.20345160365104675 }, { "x": 0.3037359416484833, "y": 0.20345160365104675 }, { "x": 0.3037359416484833, "y": 0.2280922643840313 }, { "x": 0.15167886018753052, "y": 0.2280922643840313 } ], "category": "paragraph", "id": 296, "content": { "text": "Chapter 4\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15157468616962433, "y": 0.2592187523841858 }, { "x": 0.5410945266485214, "y": 0.2592187523841858 }, { "x": 0.5410945266485214, "y": 0.2883995249867439 }, { "x": 0.15157468616962433, "y": 0.2883995249867439 } ], "category": "heading1", "id": 297, "content": { "text": "Nonlinear equations\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15042589604854584, "y": 0.33692723512649536 }, { "x": 0.3443648964166641, "y": 0.33692723512649536 }, { "x": 0.3443648964166641, "y": 0.3498117569833994 }, { "x": 0.15042589604854584, "y": 0.3498117569833994 } ], "category": "heading1", "id": 298, "content": { "text": "4.1 Introduction\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.150164395570755, "y": 0.36718234419822693 }, { "x": 0.8613612949848175, "y": 0.36718234419822693 }, { "x": 0.8613612949848175, "y": 0.39424635656178 }, { "x": 0.150164395570755, "y": 0.39424635656178 } ], "category": "paragraph", "id": 299, "content": { "text": "The pressure drop in a fluid in motion is examined. For a flow in a pipe with a circular cross\nsection of diameter D (meter), the Reynolds number, Re, is given by\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.470042884349823, "y": 0.4039001166820526 }, { "x": 0.545296385884285, "y": 0.4039001166820526 }, { "x": 0.545296385884285, "y": 0.42984469421207905 }, { "x": 0.470042884349823, "y": 0.42984469421207905 } ], "category": "paragraph", "id": 300, "content": { "text": "Re = Do ,\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15060734748840332, "y": 0.438906192779541 }, { "x": 0.8614143133163452, "y": 0.438906192779541 }, { "x": 0.8614143133163452, "y": 0.4788407124578953 }, { "x": 0.15060734748840332, "y": 0.4788407124578953 } ], "category": "paragraph", "id": 301, "content": { "text": "in which V (m/s) is the average flow velocity and V (m2/s) is the viscosity of the fluid. The flow is\ncalled laminar if Re < 2100 (low flow velocity) and turbulent if Re > 3000. For 2100 < Re < 3000,\nthe flow is neither laminar nor turbulent.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15065909922122955, "y": 0.48897498846054077 }, { "x": 0.7304976731538773, "y": 0.48897498846054077 }, { "x": 0.7304976731538773, "y": 0.5020936587825418 }, { "x": 0.15065909922122955, "y": 0.5020936587825418 } ], "category": "paragraph", "id": 302, "content": { "text": "For turbulent flows, the pressure drop between inflow and outflow is given by\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15068648755550385, "y": 0.5522183179855347 }, { "x": 0.8618259280920029, "y": 0.5522183179855347 }, { "x": 0.8618259280920029, "y": 0.5953130349516869 }, { "x": 0.15068648755550385, "y": 0.5953130349516869 } ], "category": "paragraph", "id": 303, "content": { "text": "in which w is a friction coefficient, p g/m3 is the fluid density, L (m) is the length and g (m/s2)\nis the acceleration of gravity. If the fluid contains particles (sand, paper fibers), then the friction\ncoefficient W satisfies the equation\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1506815254688263, "y": 0.6467920541763306 }, { "x": 0.5316709876060486, "y": 0.6467920541763306 }, { "x": 0.5316709876060486, "y": 0.6591318231076002 }, { "x": 0.1506815254688263, "y": 0.6591318231076002 } ], "category": "paragraph", "id": 304, "content": { "text": "in which k is a parameter known from experiments.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1506684422492981, "y": 0.6668089032173157 }, { "x": 0.8611376881599426, "y": 0.6668089032173157 }, { "x": 0.8611376881599426, "y": 0.6910041458904743 }, { "x": 0.1506684422492981, "y": 0.6910041458904743 } ], "category": "paragraph", "id": 305, "content": { "text": "In this chapter, numerical methods will be discussed that can be used to determine W if the values\nof Re and k are known.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1504596471786499, "y": 0.7179387211799622 }, { "x": 0.3295123130083084, "y": 0.7179387211799622 }, { "x": 0.3295123130083084, "y": 0.7309589367359877 }, { "x": 0.1504596471786499, "y": 0.7309589367359877 } ], "category": "heading1", "id": 306, "content": { "text": "4.2 Definitions\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15055222809314728, "y": 0.748091995716095 }, { "x": 0.861526682972908, "y": 0.748091995716095 }, { "x": 0.861526682972908, "y": 0.7896326705813408 }, { "x": 0.15055222809314728, "y": 0.7896326705813408 } ], "category": "paragraph", "id": 307, "content": { "text": "In this chapter, various iterative methods will be considered to solve nonlinear equations of the\nform f(p) = 0. The point p is called a zero of the function f, or a root of the equation f(x) = 0.\nFirst, some useful definitions and concepts are introduced.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15120480954647064, "y": 0.7975093722343445 }, { "x": 0.24992821365594864, "y": 0.7975093722343445 }, { "x": 0.24992821365594864, "y": 0.8094393219798803 }, { "x": 0.15120480954647064, "y": 0.8094393219798803 } ], "category": "heading1", "id": 308, "content": { "text": "Convergence\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1504937708377838, "y": 0.8104657530784607 }, { "x": 0.8616810142993927, "y": 0.8104657530784607 }, { "x": 0.8616810142993927, "y": 0.8525247797369957 }, { "x": 0.1504937708377838, "y": 0.8525247797369957 } ], "category": "paragraph", "id": 309, "content": { "text": "Each numerical method generates a sequence {pn} = P0,P1,P2, which should converge to p:\nlimn->00 Pn = p. Assume that the sequence indeed converges, with Pn # p for all n. If there exist\npositive constants l and a satisfying\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.4335089325904846, "y": 0.8709803819656372 }, { "x": 0.5620080679655075, "y": 0.8709803819656372 }, { "x": 0.5620080679655075, "y": 0.880106552504003 }, { "x": 0.4335089325904846, "y": 0.880106552504003 } ], "category": "paragraph", "id": 310, "content": { "text": "lim =\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8296472430229187, "y": 0.8705659508705139 }, { "x": 0.8613904081285, "y": 0.8705659508705139 }, { "x": 0.8613904081285, "y": 0.8825829504057765 }, { "x": 0.8296472430229187, "y": 0.8825829504057765 } ], "category": "paragraph", "id": 311, "content": { "text": "(4.1)\n", "html": "", "markdown": "" } } ] }, "01030000000123.pdf": { "elements": [ { "coordinates": [ { "x": 0.1417372077703476, "y": 0.10242512077093124 }, { "x": 0.6767517179250717, "y": 0.10242512077093124 }, { "x": 0.6767517179250717, "y": 0.14023644104599953 }, { "x": 0.1417372077703476, "y": 0.14023644104599953 } ], "category": "heading1", "id": 203, "content": { "text": "The Data Journey\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14176447689533234, "y": 0.1777866929769516 }, { "x": 0.8549892455339432, "y": 0.1777866929769516 }, { "x": 0.8549892455339432, "y": 0.21952448785305023 }, { "x": 0.14176447689533234, "y": 0.21952448785305023 } ], "category": "paragraph", "id": 204, "content": { "text": "1\nTo get started, let's consider the data visualization in Figure 1.1\nbelow.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16144885122776031, "y": 0.23916229605674744 }, { "x": 0.7004759460687637, "y": 0.23916229605674744 }, { "x": 0.7004759460687637, "y": 0.43506087362766266 }, { "x": 0.16144885122776031, "y": 0.43506087362766266 } ], "category": "figure", "id": 205, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.7325695157051086, "y": 0.23522546887397766 }, { "x": 0.8528700917959213, "y": 0.23522546887397766 }, { "x": 0.8528700917959213, "y": 0.40258288383483887 }, { "x": 0.7325695157051086, "y": 0.40258288383483887 } ], "category": "paragraph", "id": 206, "content": { "text": "Figure 7.7.\nProduction\nof apples,\nblueberries,\ncranberries,\ngraphs,\nand\nstrawberrie\nS in British\nColumbia,\n2016-2020.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14185966551303864, "y": 0.5210451483726501 }, { "x": 0.8558943420648575, "y": 0.5210451483726501 }, { "x": 0.8558943420648575, "y": 0.5791791491210461 }, { "x": 0.14185966551303864, "y": 0.5791791491210461 } ], "category": "paragraph", "id": 207, "content": { "text": "The underlying raw data went through many stages before it\nwas presented to you in this data visualization. The information\nhad to be:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1629725843667984, "y": 0.6110047698020935 }, { "x": 0.42326296865940094, "y": 0.6110047698020935 }, { "x": 0.42326296865940094, "y": 0.6255259467288852 }, { "x": 0.1629725843667984, "y": 0.6255259467288852 } ], "category": "paragraph", "id": 209, "content": { "text": "Collected via surveys\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16206331551074982, "y": 0.633647620677948 }, { "x": 0.46761782467365265, "y": 0.633647620677948 }, { "x": 0.46761782467365265, "y": 0.6481448216363788 }, { "x": 0.16206331551074982, "y": 0.6481448216363788 } ], "category": "paragraph", "id": 210, "content": { "text": "Inputted into a database\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16221541166305542, "y": 0.6566228866577148 }, { "x": 0.46602678298950195, "y": 0.6566228866577148 }, { "x": 0.46602678298950195, "y": 0.6684623127803206 }, { "x": 0.16221541166305542, "y": 0.6684623127803206 } ], "category": "paragraph", "id": 211, "content": { "text": "Stored on secure servers\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16191263496875763, "y": 0.6796256303787231 }, { "x": 0.6160215884447098, "y": 0.6796256303787231 }, { "x": 0.6160215884447098, "y": 0.6942001059651375 }, { "x": 0.16191263496875763, "y": 0.6942001059651375 } ], "category": "paragraph", "id": 212, "content": { "text": "Cleaned for accuracy and consistency\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16191309690475464, "y": 0.7023710608482361 }, { "x": 0.5837548077106476, "y": 0.7023710608482361 }, { "x": 0.5837548077106476, "y": 0.7168515175580978 }, { "x": 0.16191309690475464, "y": 0.7168515175580978 } ], "category": "paragraph", "id": 213, "content": { "text": "Analyzed to understand the trends\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16191355884075165, "y": 0.7251403331756592 }, { "x": 0.47117961943149567, "y": 0.7251403331756592 }, { "x": 0.47117961943149567, "y": 0.7397546116262674 }, { "x": 0.16191355884075165, "y": 0.7397546116262674 } ], "category": "paragraph", "id": 214, "content": { "text": "Presented as a bar graph\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12546022236347198, "y": 0.8096774816513062 }, { "x": 0.8460726886987686, "y": 0.8096774816513062 }, { "x": 0.8460726886987686, "y": 0.9045628234744072 }, { "x": 0.12546022236347198, "y": 0.9045628234744072 } ], "category": "paragraph", "id": 215, "content": { "text": "1. Statistics Canada. Table 32-10-0364-01 Area, production and farm gate\nvalue of marketed fruits. Data is reproduced and distributed on an \"as\nis\" basis with the permission of Statistics Canada. Retrieved January\n9th, 2022. DOI: https://doi.org/10.25318/3210036401-eng. Statistics\nCanada Open Licence: https://www.statcan.gc.ca/en/reference/licence\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16771502792835236, "y": 0.9350911378860474 }, { "x": 0.1711032255552709, "y": 0.9350911378860474 }, { "x": 0.1711032255552709, "y": 0.94795629568398 }, { "x": 0.16771502792835236, "y": 0.94795629568398 } ], "category": "paragraph", "id": 216, "content": { "text": "I\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14344991743564606, "y": 0.935444176197052 }, { "x": 0.15527575742453337, "y": 0.935444176197052 }, { "x": 0.15527575742453337, "y": 0.946107130497694 }, { "x": 0.14344991743564606, "y": 0.946107130497694 } ], "category": "paragraph", "id": 217, "content": { "text": "4\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.18261772394180298, "y": 0.9352940320968628 }, { "x": 0.36144810914993286, "y": 0.9352940320968628 }, { "x": 0.36144810914993286, "y": 0.9479340799152851 }, { "x": 0.18261772394180298, "y": 0.9479340799152851 } ], "category": "footer", "id": 218, "content": { "text": "The Data Journey\n", "html": "", "markdown": "" } } ] }, "01030000000019.pdf": { "elements": [ { "coordinates": [ { "x": 0.25474581122398376, "y": 0.20860475301742554 }, { "x": 0.7172481417655945, "y": 0.20860475301742554 }, { "x": 0.7172481417655945, "y": 0.2759232521057129 }, { "x": 0.25474581122398376, "y": 0.2759232521057129 } ], "category": "heading1", "id": 349, "content": { "text": "Author's Note to the\n2021 Edition\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12931962311267853, "y": 0.34533214569091797 }, { "x": 0.8449672609567642, "y": 0.34533214569091797 }, { "x": 0.8449672609567642, "y": 0.44352737069129944 }, { "x": 0.12931962311267853, "y": 0.44352737069129944 } ], "category": "paragraph", "id": 350, "content": { "text": "This book is a minimally amended, reprinted version of Sing me that\nlovely song again (Pandanus Press, 2006). The title was chosen by Ian\nTempleman, the publisher, because he was more interested in its literary\nmerits than in academic history. For that reason, many of my dates were\nremoved from the original manuscript during editing.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1294945329427719, "y": 0.45768308639526367 }, { "x": 0.8436871021986008, "y": 0.45768308639526367 }, { "x": 0.8436871021986008, "y": 0.6552750170230865 }, { "x": 0.1294945329427719, "y": 0.6552750170230865 } ], "category": "paragraph", "id": 351, "content": { "text": "My original intention was to get my parents and the elder of my two\nbrothers to write their own memories of how they experienced their\ninternment in Persia and five years behind barbed wire in Australia\nduring World War II, focusing on individual memory by gender and age.\nIt seemed a remarkable opportunity to make this anecdotal and analytical\ncontribution to social science: they had each lived in the same space with\nthe same people for the same period. It was to be an experiment made in\nheaven, that is, within an impeccable laboratory. But my parents had been\ntoo distressed by their loss of freedom and the congested and pressured\natmosphere of life in camp to collaborate.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12933699786663055, "y": 0.6698418259620667 }, { "x": 0.8433480709791183, "y": 0.6698418259620667 }, { "x": 0.8433480709791183, "y": 0.7479867786169052 }, { "x": 0.12933699786663055, "y": 0.7479867786169052 } ], "category": "paragraph", "id": 352, "content": { "text": "Because I wanted to keep the focus on my own memories, and the tone\nof voice my own, I wrote my own book with only minimal research in\nvarious archives in Australia and abroad. I did some research as a check on\nsome important facts.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1284179985523224, "y": 0.761812150478363 }, { "x": 0.8439657986164093, "y": 0.761812150478363 }, { "x": 0.8439657986164093, "y": 0.9196237027645111 }, { "x": 0.1284179985523224, "y": 0.9196237027645111 } ], "category": "paragraph", "id": 353, "content": { "text": "Asked to speak about my book at an academic conference at the\nUniversity of Queensland in 2006, I did some further research to validate\nmy contribution. My speech was then published in National Socialism in\nOceania (edited by Emily Turner-Graham and Christine Winter, Peter\nLang, 2010) with the title I had originally suggested to Pandanus Press,\n'At Home in Exile: Ambiguities of wartime patriotism'. When in 2015\nI was asked by Japanese scholars to speak at Cowra, NSW, at a conference\non internment, I suggested that my younger brother, Peter, also be invited\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8936327695846558, "y": 0.9317705631256104 }, { "x": 0.9088592976331711, "y": 0.9317705631256104 }, { "x": 0.9088592976331711, "y": 0.9410003051161766 }, { "x": 0.8936327695846558, "y": 0.9410003051161766 } ], "category": "paragraph", "id": 354, "content": { "text": "ix\n", "html": "", "markdown": "" } } ] }, "01030000000058.pdf": { "elements": [ { "coordinates": [ { "x": 0.14258383214473724, "y": 0.10452862083911896 }, { "x": 0.8084170073270798, "y": 0.10452862083911896 }, { "x": 0.8084170073270798, "y": 0.14035490527749062 }, { "x": 0.14258383214473724, "y": 0.14035490527749062 } ], "category": "heading1", "id": 204, "content": { "text": "3.\nPerspective of supply and demand balance of wood pellets and cost\nstructure in Japan\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14218087494373322, "y": 0.1539301872253418 }, { "x": 0.8095263987779617, "y": 0.1539301872253418 }, { "x": 0.8095263987779617, "y": 0.2218090072274208 }, { "x": 0.14218087494373322, "y": 0.2218090072274208 } ], "category": "paragraph", "id": 205, "content": { "text": "According to a survey taken by the Japan Woody Bioenergy Association in FY2018 (from\nApril 2018 to March 2019) with 55 biomass power generators, more than half of fuel for\nbiomass power generation is domestically produced wood biomass at present in Japan in\nterms of weight (Figure 4.5).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.22224552929401398, "y": 0.25329071283340454 }, { "x": 0.7291961461305618, "y": 0.25329071283340454 }, { "x": 0.7291961461305618, "y": 0.2653397433459759 }, { "x": 0.22224552929401398, "y": 0.2653397433459759 } ], "category": "paragraph", "id": 206, "content": { "text": "Figure 4.5. Breakdown of Biomass Power Generation Fuel in Japan\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.2923533320426941, "y": 0.2793682813644409 }, { "x": 0.6173864006996155, "y": 0.2793682813644409 }, { "x": 0.6173864006996155, "y": 0.4679771661758423 }, { "x": 0.2923533320426941, "y": 0.4679771661758423 } ], "category": "figure", "id": 207, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14296618103981018, "y": 0.486232727766037 }, { "x": 0.2863171845674515, "y": 0.486232727766037 }, { "x": 0.2863171845674515, "y": 0.49599441699683666 }, { "x": 0.14296618103981018, "y": 0.49599441699683666 } ], "category": "paragraph", "id": 208, "content": { "text": "PKS = palm kernel shell.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14300280809402466, "y": 0.5009733438491821 }, { "x": 0.8081734776496887, "y": 0.5009733438491821 }, { "x": 0.8081734776496887, "y": 0.526006082072854 }, { "x": 0.14300280809402466, "y": 0.526006082072854 } ], "category": "paragraph", "id": 209, "content": { "text": "Note: The share of fuel calculated in terms of biomass fuel weight ('Wood pellets', 'Construction wood waste',\n'Waste materials', 'Others': tonne; others: dry tonne).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14253149926662445, "y": 0.5310282111167908 }, { "x": 0.6635712236166, "y": 0.5310282111167908 }, { "x": 0.6635712236166, "y": 0.5414231223985553 }, { "x": 0.14253149926662445, "y": 0.5414231223985553 } ], "category": "paragraph", "id": 210, "content": { "text": "Source: Depicted by IEEJ based on Japan Woody Bioenergy Association (JWBA), 2020.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14212638139724731, "y": 0.5720968246459961 }, { "x": 0.8089883327484131, "y": 0.5720968246459961 }, { "x": 0.8089883327484131, "y": 0.6391339972615242 }, { "x": 0.14212638139724731, "y": 0.6391339972615242 } ], "category": "paragraph", "id": 211, "content": { "text": "When translating the survey result into energy form, it is estimated that, within biomass\npower generation using wood biomass ('Unutilised wood', 'General wood', and\n'Construction wood waste'), around 30% of input fuel is met by import biomass fuel\n(Figure 4.6).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.4671511650085449, "y": 0.945438802242279 }, { "x": 0.48497262597084045, "y": 0.945438802242279 }, { "x": 0.48497262597084045, "y": 0.9544584285467863 }, { "x": 0.4671511650085449, "y": 0.9544584285467863 } ], "category": "paragraph", "id": 212, "content": { "text": "38\n", "html": "", "markdown": "" } } ] }, "01030000000059.pdf": { "elements": [ { "coordinates": [ { "x": 0.19122709333896637, "y": 0.1037682443857193 }, { "x": 0.7598523646593094, "y": 0.1037682443857193 }, { "x": 0.7598523646593094, "y": 0.11605748441070318 }, { "x": 0.19122709333896637, "y": 0.11605748441070318 } ], "category": "paragraph", "id": 283, "content": { "text": "Figure 4.6. Input Biomass Fuel for Each Type of Biomass Power Generation\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.21825966238975525, "y": 0.13397949934005737 }, { "x": 0.7352944910526276, "y": 0.13397949934005737 }, { "x": 0.7352944910526276, "y": 0.35275299847126007 }, { "x": 0.21825966238975525, "y": 0.35275299847126007 } ], "category": "figure", "id": 284, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14282526075839996, "y": 0.37186580896377563 }, { "x": 0.8085225969552994, "y": 0.37186580896377563 }, { "x": 0.8085225969552994, "y": 0.42133285477757454 }, { "x": 0.14282526075839996, "y": 0.42133285477757454 } ], "category": "paragraph", "id": 285, "content": { "text": "PKS = palm kernel shell.\nHeat value used: Domestic logs and wood chips: 19.4 MJ/kg; Domestic wood pellets, Import pellets, chips:\n15.5 MJ/kg; PKS: 18 MJ/kg; Construction wood waste, Other waste, and Others: assuming the same with wood\npellets.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14216935634613037, "y": 0.42389538884162903 }, { "x": 0.6156061589717865, "y": 0.42389538884162903 }, { "x": 0.6156061589717865, "y": 0.43440731056034565 }, { "x": 0.14216935634613037, "y": 0.43440731056034565 } ], "category": "paragraph", "id": 286, "content": { "text": "Source: Depicted by IEEJ based on Japan Woody Bioenergy Association, 2020.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.142148956656456, "y": 0.46344122290611267 }, { "x": 0.8086261600255966, "y": 0.46344122290611267 }, { "x": 0.8086261600255966, "y": 0.530876487493515 }, { "x": 0.142148956656456, "y": 0.530876487493515 } ], "category": "paragraph", "id": 287, "content": { "text": "According to Japan's trade statistics, its import of wood pellets has increased around 16\ntimes from 2014 to 2019. Viet Nam and Canada are the largest suppliers of Japan's wood\npellet imports (Figure 4.7). On the other hand, domestic wood pellet production stayed\nalmost the same over the same period (Figure 4.8).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.35464632511138916, "y": 0.5644920468330383 }, { "x": 0.5975852310657501, "y": 0.5644920468330383 }, { "x": 0.5975852310657501, "y": 0.5762882903218269 }, { "x": 0.35464632511138916, "y": 0.5762882903218269 } ], "category": "paragraph", "id": 288, "content": { "text": "Figure 4.7. Wood Pellets Import\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.228536456823349, "y": 0.5914080739021301 }, { "x": 0.72644904255867, "y": 0.5914080739021301 }, { "x": 0.72644904255867, "y": 0.8097453266382217 }, { "x": 0.228536456823349, "y": 0.8097453266382217 } ], "category": "figure", "id": 289, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1424364447593689, "y": 0.8308454155921936 }, { "x": 0.3627897948026657, "y": 0.8308454155921936 }, { "x": 0.3627897948026657, "y": 0.8417055504396558 }, { "x": 0.1424364447593689, "y": 0.8417055504396558 } ], "category": "paragraph", "id": 290, "content": { "text": "Source: Trade Statistics of Japan.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.4670197069644928, "y": 0.945572555065155 }, { "x": 0.48449155129492283, "y": 0.945572555065155 }, { "x": 0.48449155129492283, "y": 0.9543042536824942 }, { "x": 0.4670197069644928, "y": 0.9543042536824942 } ], "category": "paragraph", "id": 291, "content": { "text": "39\n", "html": "", "markdown": "" } } ] }, "01030000000027.pdf": { "elements": [ { "coordinates": [ { "x": 0.14630013704299927, "y": 0.027570359408855438 }, { "x": 0.4344865381717682, "y": 0.027570359408855438 }, { "x": 0.4344865381717682, "y": 0.040379407815635204 }, { "x": 0.14630013704299927, "y": 0.040379407815635204 } ], "category": "heading1", "id": 157, "content": { "text": "Probability, Combinatorics and Control\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.21830424666404724, "y": 0.07434530556201935 }, { "x": 0.7792395651340485, "y": 0.07434530556201935 }, { "x": 0.7792395651340485, "y": 0.2995251566171646 }, { "x": 0.21830424666404724, "y": 0.2995251566171646 } ], "category": "figure", "id": 158, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14625488221645355, "y": 0.3135368525981903 }, { "x": 0.46491043269634247, "y": 0.3135368525981903 }, { "x": 0.46491043269634247, "y": 0.3369944207370281 }, { "x": 0.14625488221645355, "y": 0.3369944207370281 } ], "category": "paragraph", "id": 159, "content": { "text": "Figure 7.\nEstimated cumulative damage for impeller blades.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.22010688483715057, "y": 0.36293068528175354 }, { "x": 0.7785124033689499, "y": 0.36293068528175354 }, { "x": 0.7785124033689499, "y": 0.5888183265924454 }, { "x": 0.22010688483715057, "y": 0.5888183265924454 } ], "category": "figure", "id": 160, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14596562087535858, "y": 0.6027746796607971 }, { "x": 0.5834269970655441, "y": 0.6027746796607971 }, { "x": 0.5834269970655441, "y": 0.6264714151620865 }, { "x": 0.14596562087535858, "y": 0.6264714151620865 } ], "category": "paragraph", "id": 161, "content": { "text": "Figure 8.\nEstimated residual life of impeller blades by the criterion of cracking.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.21984457969665527, "y": 0.667532205581665 }, { "x": 0.7787368893623352, "y": 0.667532205581665 }, { "x": 0.7787368893623352, "y": 0.8947990089654922 }, { "x": 0.21984457969665527, "y": 0.8947990089654922 } ], "category": "figure", "id": 162, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14622537791728973, "y": 0.908208966255188 }, { "x": 0.6218921095132828, "y": 0.908208966255188 }, { "x": 0.6218921095132828, "y": 0.9319045636802912 }, { "x": 0.14622537791728973, "y": 0.9319045636802912 } ], "category": "paragraph", "id": 163, "content": { "text": "Figure 9.\nEstimated residual life of impeller blades at the stage of crack development.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14683808386325836, "y": 0.9596037864685059 }, { "x": 0.16460748575627804, "y": 0.9596037864685059 }, { "x": 0.16460748575627804, "y": 0.9681005412712693 }, { "x": 0.14683808386325836, "y": 0.9681005412712693 } ], "category": "paragraph", "id": 164, "content": { "text": "48\n", "html": "", "markdown": "" } } ] }, "01030000000132.pdf": { "elements": [ { "coordinates": [ { "x": 0.09749109297990799, "y": 0.07783018797636032 }, { "x": 0.39641327410936356, "y": 0.07783018797636032 }, { "x": 0.39641327410936356, "y": 0.19342542439699173 }, { "x": 0.09749109297990799, "y": 0.19342542439699173 } ], "category": "table", "id": 371, "content": { "text": "", "html": "
Fish species on IUCN Red List
Potosi PupfishCyprinodon alvarezi
La Palma PupfishCyprinodon longidorsalis
Butterfly SplitfinAmeca splendens
Golden SkiffiaSkiffia francesae
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Actions to prevent the\nextinction of the Barrens Topminnow\ninclude monitoring populations and\npropagating and stocking juveniles into\nexisting or newly created spring habitats.\nThe Tennessee Aquarium assisted with\npropagations and developed a program\ncalled \"Keeper Kids,\" where students on\nspring break help feed the Barrens\nTopminnows in a behind-the-scenes\nexperience.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.4189651906490326, "y": 0.2693372964859009 }, { "x": 0.901515394449234, "y": 0.2693372964859009 }, { "x": 0.901515394449234, "y": 0.488492488861084 }, { "x": 0.4189651906490326, "y": 0.488492488861084 } ], "category": "figure", "id": 387, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.419064462184906, "y": 0.494026780128479 }, { "x": 0.8593358397483826, "y": 0.494026780128479 }, { "x": 0.8593358397483826, "y": 0.5199923142790794 }, { "x": 0.419064462184906, "y": 0.5199923142790794 } ], "category": "paragraph", "id": 388, "content": { "text": "Figure 6.3: Photo of the critically endangered Butterfly Splitfin (Ameca\nspendens).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09723158925771713, "y": 0.5438057780265808 }, { "x": 0.9011493548750877, "y": 0.5438057780265808 }, { "x": 0.9011493548750877, "y": 0.6946623474359512 }, { "x": 0.09723158925771713, "y": 0.6946623474359512 } ], "category": "paragraph", "id": 389, "content": { "text": "The breeding colonies of the Butterfly Splitfin (Figure 6.3) at the London Zoo and elsewhere serve as ark\npopulations essential to the survival of this species. Butterfly Splitfins are endemic to the Río Ameca in\nwestern Mexico and almost extinct in the wild. Actions such as nonnative fish removal, stream restoration, and\nsanctuary designation may take decades before eventual introduction and survival in the wild. The Tennessee\nAquarium is part of a large partnership to guide hatchery augmentation and recovery of the rarest darter in\nNorth America (U.S. Fish and Wildlife Service 2019). The Conasauga Logperch (Percina jenkinsi), a federally\nendangered darter (Percidae), is found only in a 30-mile (48 km) stretch of the Conasauga River in Georgia and\nTennessee (Moyer et al. 2015).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10134942084550858, "y": 0.7016493678092957 }, { "x": 0.5671331658959389, "y": 0.7016493678092957 }, { "x": 0.5671331658959389, "y": 0.8357208669185638 }, { "x": 0.10134942084550858, "y": 0.8357208669185638 } ], "category": "figure", "id": 390, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09796935319900513, "y": 0.8415198922157288 }, { "x": 0.40102851390838623, "y": 0.8415198922157288 }, { "x": 0.40102851390838623, "y": 0.8538833986967802 }, { "x": 0.09796935319900513, "y": 0.8538833986967802 } ], "category": "paragraph", "id": 391, "content": { "text": "Figure 6.4: Lake Sturgeon (Acipenser fulvescens).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.581671953201294, "y": 0.7129989266395569 }, { "x": 0.9009459912776947, "y": 0.7129989266395569 }, { "x": 0.9009459912776947, "y": 0.8826242387294769 }, { "x": 0.581671953201294, "y": 0.8826242387294769 } ], "category": "paragraph", "id": 392, "content": { "text": "The Banggai Cardinalfish (Pterapogon\nkauderni), a small, endangered tropical\ncardinalfish in the family Apogonidae, is\nnow bred and displayed in numerous public\naquariums after overharvest in the wild\ndrove wild populations to near extinction.\nConsequently, most Banggai Cardinalfish\nsold to hobbyists in the United States and\nEuropean Union today are captive bred.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09776974469423294, "y": 0.9361052513122559 }, { "x": 0.11793724820017815, "y": 0.9361052513122559 }, { "x": 0.11793724820017815, "y": 0.9448620676994324 }, { "x": 0.09776974469423294, "y": 0.9448620676994324 } ], "category": "paragraph", "id": 393, "content": { "text": "132\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12596344947814941, "y": 0.9347376823425293 }, { "x": 0.6088413894176483, "y": 0.9347376823425293 }, { "x": 0.6088413894176483, "y": 0.9485620502382517 }, { "x": 0.12596344947814941, "y": 0.9485620502382517 } ], "category": "footer", "id": 394, "content": { "text": "I Public Aquariums and Their Role in Education, Science, and Conservation\n", "html": "", "markdown": "" } } ] }, "01030000000174.pdf": { "elements": [ { "coordinates": [ { "x": 0.5269607305526733, "y": 0.5225322246551514 }, { "x": 0.8562803864479065, "y": 0.5225322246551514 }, { "x": 0.8562803864479065, "y": 0.7824628949165344 }, { "x": 0.5269607305526733, "y": 0.7824628949165344 } ], "category": "table", "id": 201, "content": { "text": "", "html": "
LOANNIS KEPPLERI Mathematici Carfarei hand Imaginem ARCENTORATINS MATTHIAS BERNEGGERVS MOCKEVEL
", "markdown": "" } }, { "coordinates": [ { "x": 0.14274226129055023, "y": 0.09608231484889984 }, { "x": 0.529118075966835, "y": 0.09608231484889984 }, { "x": 0.529118075966835, "y": 0.12069602683186531 }, { "x": 0.14274226129055023, "y": 0.12069602683186531 } ], "category": "heading1", "id": 205, "content": { "text": "Tycho Brahe's Observatory\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14155712723731995, "y": 0.1586550623178482 }, { "x": 0.8584131300449371, "y": 0.1586550623178482 }, { "x": 0.8584131300449371, "y": 0.3810655325651169 }, { "x": 0.14155712723731995, "y": 0.3810655325651169 } ], "category": "paragraph", "id": 206, "content": { "text": "Three years after the publication of Copernicus' De Revolutionibus,\nTycho Brahe was born to a family of Danish nobility. He developed\nan early interest in astronomy and, as a young man, made significant\nastronomical observations. Among these was a careful study of what\nwe now know was an exploding star that flared up to great brilliance\nin the night sky. His growing reputation gained him the patronage of\nthe Danish King Frederick II, and at the age of 30, Brahe was able to\nestablish a fine astronomical observatory on the North Sea island of\nHven (Figure 1). Brahe was the last and greatest of the pre-telescopic\nobservers in Europe.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1778244525194168, "y": 0.43763992190361023 }, { "x": 0.820918396115303, "y": 0.43763992190361023 }, { "x": 0.820918396115303, "y": 0.4910399429500103 }, { "x": 0.1778244525194168, "y": 0.4910399429500103 } ], "category": "paragraph", "id": 207, "content": { "text": "Tycho Brahe (1546-1601) and Johannes Kepler\n(1571-1630).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14290761947631836, "y": 0.5232678055763245 }, { "x": 0.8576629161834717, "y": 0.5232678055763245 }, { "x": 0.8576629161834717, "y": 0.8002308309078217 }, { "x": 0.14290761947631836, "y": 0.8002308309078217 } ], "category": "figure", "id": 208, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3041781485080719, "y": 0.8080310821533203 }, { "x": 0.32084483839571476, "y": 0.8080310821533203 }, { "x": 0.32084483839571476, "y": 0.8178676776587963 }, { "x": 0.3041781485080719, "y": 0.8178676776587963 } ], "category": "paragraph", "id": 209, "content": { "text": "(a)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.68141770362854, "y": 0.8081198334693909 }, { "x": 0.6986339632421732, "y": 0.8081198334693909 }, { "x": 0.6986339632421732, "y": 0.81794822961092 }, { "x": 0.68141770362854, "y": 0.81794822961092 } ], "category": "paragraph", "id": 210, "content": { "text": "(b)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15376399457454681, "y": 0.8289955854415894 }, { "x": 0.8443947285413742, "y": 0.8289955854415894 }, { "x": 0.8443947285413742, "y": 0.891200341284275 }, { "x": 0.15376399457454681, "y": 0.891200341284275 } ], "category": "paragraph", "id": 211, "content": { "text": "Figure 1. (a) A stylized engraving shows Tycho Brahe using his\ninstruments to measure the altitude of celestial objects above the\nhorizon. The large curved instrument in the foreground allowed\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.2625370919704437, "y": 0.9157862663269043 }, { "x": 0.8564305603504181, "y": 0.9157862663269043 }, { "x": 0.8564305603504181, "y": 0.9302647039294243 }, { "x": 0.2625370919704437, "y": 0.9302647039294243 } ], "category": "footer", "id": 212, "content": { "text": "Chapter 3 Orbits and Gravity Section 3.1: The Laws of Planetary\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.7390730381011963, "y": 0.9321434497833252 }, { "x": 0.8069536909461021, "y": 0.9321434497833252 }, { "x": 0.8069536909461021, "y": 0.9428323907777667 }, { "x": 0.7390730381011963, "y": 0.9428323907777667 } ], "category": "footer", "id": 213, "content": { "text": "Motion\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8330168724060059, "y": 0.9323349595069885 }, { "x": 0.855875650420785, "y": 0.9323349595069885 }, { "x": 0.855875650420785, "y": 0.9428288359194994 }, { "x": 0.8330168724060059, "y": 0.9428288359194994 } ], "category": "paragraph", "id": 214, "content": { "text": "99\n", "html": "", "markdown": "" } } ] }, "01030000000084.pdf": { "elements": [ { "coordinates": [ { "x": 0.16599689424037933, "y": 0.17147834599018097 }, { "x": 0.8331124633550644, "y": 0.17147834599018097 }, { "x": 0.8331124633550644, "y": 0.28348833322525024 }, { "x": 0.16599689424037933, "y": 0.28348833322525024 } ], "category": "table", "id": 155, "content": { "text": "", "html": "
SmallMediumLarge
Total applicable compliances7841,1881,693
Compliances with imprisonment154362622
Percentage of imprisonment clauses20%30%37%
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RangeSmallMidLarge
Less than 3 months104282
3 months to less than 1 year67203373
1 year to less than 3 years505868
3 years to less than 5 years84080
5 years to 10 years191919
", "markdown": "" } }, { "coordinates": [ { "x": 0.1657121777534485, "y": 0.04228290542960167 }, { "x": 0.38537372648715973, "y": 0.04228290542960167 }, { "x": 0.38537372648715973, "y": 0.05472327955067158 }, { "x": 0.1657121777534485, "y": 0.05472327955067158 } ], "category": "header", "id": 201, "content": { "text": "Jailed for Doing Business\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16561584174633026, "y": 0.11668158322572708 }, { "x": 0.6511344760656357, "y": 0.11668158322572708 }, { "x": 0.6511344760656357, "y": 0.14812592417001724 }, { "x": 0.16561584174633026, "y": 0.14812592417001724 } ], "category": "heading1", "id": 202, "content": { "text": "TABLE 38: THREE CASE STUDIES ON NBFC\nCOMPLIANCES*\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16603966057300568, "y": 0.2876405119895935 }, { "x": 0.48629264533519745, "y": 0.2876405119895935 }, { "x": 0.48629264533519745, "y": 0.2982580717653036 }, { "x": 0.16603966057300568, "y": 0.2982580717653036 } ], "category": "paragraph", "id": 204, "content": { "text": "* These are real data from three NBFCs\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16545620560646057, "y": 0.3615044951438904 }, { "x": 0.8148646652698517, "y": 0.3615044951438904 }, { "x": 0.8148646652698517, "y": 0.3936374559998512 }, { "x": 0.16545620560646057, "y": 0.3936374559998512 } ], "category": "heading1", "id": 205, "content": { "text": "TABLE 39: BREAKDOWN OF IMPRISONMENT CLAUSES IN\nNBFC CASE STUDIES*\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1659497320652008, "y": 0.5681865811347961 }, { "x": 0.2657443732023239, "y": 0.5681865811347961 }, { "x": 0.2657443732023239, "y": 0.5787425106391311 }, { "x": 0.1659497320652008, "y": 0.5787425106391311 } ], "category": "paragraph", "id": 207, "content": { "text": "* In table 38\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.48529115319252014, "y": 0.9506086111068726 }, { "x": 0.5142196472734213, "y": 0.9506086111068726 }, { "x": 0.5142196472734213, "y": 0.9651767332106829 }, { "x": 0.48529115319252014, "y": 0.9651767332106829 } ], "category": "paragraph", "id": 208, "content": { "text": "86\n", "html": "", "markdown": "" } } ] }, "01030000000169.pdf": { "elements": [ { "coordinates": [ { "x": 0.12169571220874786, "y": 0.07523152232170105 }, { "x": 0.3450526297092438, "y": 0.07523152232170105 }, { "x": 0.3450526297092438, "y": 0.08758361544460058 }, { "x": 0.12169571220874786, "y": 0.08758361544460058 } ], "category": "paragraph", "id": 417, "content": { "text": "Lime is recommended if pH < 5.8\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0923226922750473, "y": 0.10705944150686264 }, { "x": 0.2767602652311325, "y": 0.10705944150686264 }, { "x": 0.2767602652311325, "y": 0.12384648993611336 }, { "x": 0.0923226922750473, "y": 0.12384648993611336 } ], "category": "heading1", "id": 418, "content": { "text": "Target pH of 5.5 :\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09607571363449097, "y": 0.13750210404396057 }, { "x": 0.7846810221672058, "y": 0.13750210404396057 }, { "x": 0.7846810221672058, "y": 0.156565610319376 }, { "x": 0.09607571363449097, "y": 0.156565610319376 } ], "category": "paragraph", "id": 419, "content": { "text": "[6, 405 - (1,590 buffer pH) + (98 buffer pH buffer pH)] depth\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10279867053031921, "y": 0.17805930972099304 }, { "x": 0.2437286674976349, "y": 0.17805930972099304 }, { "x": 0.2437286674976349, "y": 0.1901518553495407 }, { "x": 0.10279867053031921, "y": 0.1901518553495407 } ], "category": "paragraph", "id": 421, "content": { "text": "Depth is in inches\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1032450944185257, "y": 0.19508345425128937 }, { "x": 0.7641870528459549, "y": 0.19508345425128937 }, { "x": 0.7641870528459549, "y": 0.20814617536962032 }, { "x": 0.1032450944185257, "y": 0.20814617536962032 } ], "category": "paragraph", "id": 422, "content": { "text": "Used if cash flow is limited or in lime availability problem areas in Central and Western Kansas\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10272001475095749, "y": 0.2133428007364273 }, { "x": 0.3448110297322273, "y": 0.2133428007364273 }, { "x": 0.3448110297322273, "y": 0.22571103367954493 }, { "x": 0.10272001475095749, "y": 0.22571103367954493 } ], "category": "paragraph", "id": 423, "content": { "text": "Lime is recommended if pH < 5.5\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09166868031024933, "y": 0.24668771028518677 }, { "x": 0.9070050865411758, "y": 0.24668771028518677 }, { "x": 0.9070050865411758, "y": 0.3130367547273636 }, { "x": 0.09166868031024933, "y": 0.3130367547273636 } ], "category": "paragraph", "id": 424, "content": { "text": "This buffer contains chromium (Cr), a toxic heavy metal. Therefore, your lab instructor will perform the SMP buffer\nanalysis. As a class, determine which soil-water mixtures from Activity 1 need lime (pH 6.4). To those solutions, add\n10 ml of the SMP buffer solution, and stir with a glass rod. Allow the mixtures to stand for 30 minutes, which should be\nenough time for the acid cations to be displaced from the CEC and forced into solution. Read the pH on meter.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09120815247297287, "y": 0.3310365080833435 }, { "x": 0.12476072087883949, "y": 0.3310365080833435 }, { "x": 0.12476072087883949, "y": 0.35558855161070824 }, { "x": 0.09120815247297287, "y": 0.35558855161070824 } ], "category": "figure", "id": 425, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.13751459121704102, "y": 0.32865533232688904 }, { "x": 0.9070989489555359, "y": 0.32865533232688904 }, { "x": 0.9070989489555359, "y": 0.359415365383029 }, { "x": 0.13751459121704102, "y": 0.359415365383029 } ], "category": "paragraph", "id": 426, "content": { "text": "Assuming the desired pH is 6.0 (i.e. use the middle equation), calculate the lime requirement, show your work\nbelow, and record your results in Table 14.1.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09215559810400009, "y": 0.4317191243171692 }, { "x": 0.4556440934538841, "y": 0.4317191243171692 }, { "x": 0.4556440934538841, "y": 0.4507754873484373 }, { "x": 0.09215559810400009, "y": 0.4507754873484373 } ], "category": "heading1", "id": 427, "content": { "text": "Activity 5: Evaluating Liming Materials\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09171303361654282, "y": 0.480135440826416 }, { "x": 0.9071882590651512, "y": 0.480135440826416 }, { "x": 0.9071882590651512, "y": 0.5465196669101715 }, { "x": 0.09171303361654282, "y": 0.5465196669101715 } ], "category": "paragraph", "id": 428, "content": { "text": "The type of liming material and the size or fineness of the material determine how efficiently liming materials raise soil\npH. This experiment was actually initiated earlier in the semester to allow time for the liming agents to react. Amending\nthe soil with several different liming agents allows us assess the effects of particle size and liming material based on the\nrelative changes in soil. The treatments included the following:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10301373153924942, "y": 0.5675697326660156 }, { "x": 0.26905176788568497, "y": 0.5675697326660156 }, { "x": 0.26905176788568497, "y": 0.5796625791117549 }, { "x": 0.10301373153924942, "y": 0.5796625791117549 } ], "category": "paragraph", "id": 430, "content": { "text": "Reagent grade CaCO3\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10319055616855621, "y": 0.5854473114013672 }, { "x": 0.2523003965616226, "y": 0.5854473114013672 }, { "x": 0.2523003965616226, "y": 0.5977289397269487 }, { "x": 0.10319055616855621, "y": 0.5977289397269487 } ], "category": "paragraph", "id": 431, "content": { "text": "Reagent grade CaO\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10320500284433365, "y": 0.6028600931167603 }, { "x": 0.2672239765524864, "y": 0.6028600931167603 }, { "x": 0.2672239765524864, "y": 0.6152869984507561 }, { "x": 0.10320500284433365, "y": 0.6152869984507561 } ], "category": "paragraph", "id": 432, "content": { "text": "Reagent grade CaSO4\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10311166197061539, "y": 0.6204450726509094 }, { "x": 0.3780478909611702, "y": 0.6204450726509094 }, { "x": 0.3780478909611702, "y": 0.6327673979103565 }, { "x": 0.10311166197061539, "y": 0.6327673979103565 } ], "category": "paragraph", "id": 433, "content": { "text": "Coarse dolomitic limestone (35 mesh)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1031264066696167, "y": 0.6382319927215576 }, { "x": 0.36598438024520874, "y": 0.6382319927215576 }, { "x": 0.36598438024520874, "y": 0.65059370175004 }, { "x": 0.1031264066696167, "y": 0.65059370175004 } ], "category": "paragraph", "id": 434, "content": { "text": "Fine dolomitic limestone (120 mesh)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10292486846446991, "y": 0.6557457447052002 }, { "x": 0.29589182138442993, "y": 0.6557457447052002 }, { "x": 0.29589182138442993, "y": 0.6680972399190068 }, { "x": 0.10292486846446991, "y": 0.6680972399190068 } ], "category": "paragraph", "id": 435, "content": { "text": "Control (no amendments)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09199565649032593, "y": 0.6892983913421631 }, { "x": 0.9074456691741943, "y": 0.6892983913421631 }, { "x": 0.9074456691741943, "y": 0.7374107800424099 }, { "x": 0.09199565649032593, "y": 0.7374107800424099 } ], "category": "paragraph", "id": 436, "content": { "text": "When this experiment was initiated, each lab section was divided into six groups, with each group responsible for one\nof the six treatments. Your laboratory instructor assigned a treatment to your group, and you completed the following\nsteps:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09901425242424011, "y": 0.7591120600700378 }, { "x": 0.2744366228580475, "y": 0.7591120600700378 }, { "x": 0.2744366228580475, "y": 0.7717569600790739 }, { "x": 0.09901425242424011, "y": 0.7717569600790739 } ], "category": "paragraph", "id": 438, "content": { "text": "1. Label four plastic bags\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0973546952009201, "y": 0.7765981554985046 }, { "x": 0.4418047219514847, "y": 0.7765981554985046 }, { "x": 0.4418047219514847, "y": 0.7892560288310051 }, { "x": 0.0973546952009201, "y": 0.7892560288310051 } ], "category": "paragraph", "id": 439, "content": { "text": "2. Weigh 20 g of air-dry soil into each plastic bag.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09688311070203781, "y": 0.7939628958702087 }, { "x": 0.5756885930895805, "y": 0.7939628958702087 }, { "x": 0.5756885930895805, "y": 0.8070780523121357 }, { "x": 0.09688311070203781, "y": 0.8070780523121357 } ], "category": "paragraph", "id": 440, "content": { "text": "3.\nWeigh 0.1 gram of designated liming material onto weighing paper.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09668196737766266, "y": 0.8118506073951721 }, { "x": 0.7015605121850967, "y": 0.8118506073951721 }, { "x": 0.7015605121850967, "y": 0.824859382584691 }, { "x": 0.09668196737766266, "y": 0.824859382584691 } ], "category": "paragraph", "id": 441, "content": { "text": "4. Add the liming material to the soil and mix thoroughly to distribute evenly in the soil.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0969124510884285, "y": 0.8295563459396362 }, { "x": 0.4174368157982826, "y": 0.8295563459396362 }, { "x": 0.4174368157982826, "y": 0.8423916073516011 }, { "x": 0.0969124510884285, "y": 0.8423916073516011 } ], "category": "paragraph", "id": 442, "content": { "text": "5. Add a few mL of water to each bag and mix.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09708916395902634, "y": 0.8473665118217468 }, { "x": 0.35460468381643295, "y": 0.8473665118217468 }, { "x": 0.35460468381643295, "y": 0.8596630552783608 }, { "x": 0.09708916395902634, "y": 0.8596630552783608 } ], "category": "paragraph", "id": 443, "content": { "text": "6. Close the bags to start incubation.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09217508137226105, "y": 0.8810499310493469 }, { "x": 0.6224702149629593, "y": 0.8810499310493469 }, { "x": 0.6224702149629593, "y": 0.8938934886828065 }, { "x": 0.09217508137226105, "y": 0.8938934886828065 } ], "category": "paragraph", "id": 444, "content": { "text": "Now that the liming agents have had time to react, you will collect the results.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09202315658330917, "y": 0.9417726397514343 }, { "x": 0.11186443082988262, "y": 0.9417726397514343 }, { "x": 0.11186443082988262, "y": 0.9497289406135678 }, { "x": 0.09202315658330917, "y": 0.9497289406135678 } ], "category": "paragraph", "id": 445, "content": { "text": "130\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12912842631340027, "y": 0.941011905670166 }, { "x": 0.3297852426767349, "y": 0.941011905670166 }, { "x": 0.3297852426767349, "y": 0.9526832327246666 }, { "x": 0.12912842631340027, "y": 0.9526832327246666 } ], "category": "footer", "id": 446, "content": { "text": "Soil Acidity and Adjusting Soil pH\n", "html": "", "markdown": "" } } ] }, "01030000000032.pdf": { "elements": [ { "coordinates": [ { "x": 0.1402384340763092, "y": 0.08710197359323502 }, { "x": 0.31456324458122253, "y": 0.08710197359323502 }, { "x": 0.31456324458122253, "y": 0.11205206997692585 }, { "x": 0.1402384340763092, "y": 0.11205206997692585 } ], "category": "heading1", "id": 347, "content": { "text": "Prologue\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1399451643228531, "y": 0.1417609304189682 }, { "x": 0.5972738415002823, "y": 0.1417609304189682 }, { "x": 0.5972738415002823, "y": 0.15939538925886154 }, { "x": 0.1399451643228531, "y": 0.15939538925886154 } ], "category": "heading1", "id": 348, "content": { "text": "Programming and Understanding\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14025656878948212, "y": 0.18023154139518738 }, { "x": 0.8605581372976303, "y": 0.18023154139518738 }, { "x": 0.8605581372976303, "y": 0.376224160194397 }, { "x": 0.14025656878948212, "y": 0.376224160194397 } ], "category": "paragraph", "id": 349, "content": { "text": "One way to become aware of the precision required to unam-\nbiguously communicate a mathematical idea is to program it for\na computer. Rather than using canned programs purely as an\naid to visualization or numerical computation, we use computer\nprogramming in a functional style to encourage clear thinking.\nProgramming forces us to be precise and unambiguous, without\nforcing us to be excessively rigorous. The computer does not toler-\nate vague descriptions or incomplete constructions. Thus the act\nof programming makes us keenly aware of our errors of reasoning\nor unsupported conclusions.1\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.13983605802059174, "y": 0.37993037700653076 }, { "x": 0.8609059303998947, "y": 0.37993037700653076 }, { "x": 0.8609059303998947, "y": 0.49608172476291656 }, { "x": 0.13983605802059174, "y": 0.49608172476291656 } ], "category": "paragraph", "id": 350, "content": { "text": "Although this book is about differential geometry, we can show\nhow thinking about programming can help in understanding in a\nmore elementary context. The traditional use of Leibniz's notation\nand Newton's notation is convenient in simple situations, but in\nmore complicated situations it can be a serious handicap to clear\nreasoning.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14016370475292206, "y": 0.4995552897453308 }, { "x": 0.8614338487386703, "y": 0.4995552897453308 }, { "x": 0.8614338487386703, "y": 0.6126848608255386 }, { "x": 0.14016370475292206, "y": 0.6126848608255386 } ], "category": "paragraph", "id": 351, "content": { "text": "A mechanical system is described by a Lagrangian function of\nthe system state (time, coordinates, and velocities). A motion of\nthe system is described by a path that gives the coordinates for\neach moment of time. A path is allowed if and only if it satisfies\nthe Lagrange equations. Traditionally, the Lagrange equations are\nwritten\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14325347542762756, "y": 0.6274218559265137 }, { "x": 0.27049247920513153, "y": 0.6274218559265137 }, { "x": 0.27049247920513153, "y": 0.6672855280339718 }, { "x": 0.14325347542762756, "y": 0.6672855280339718 } ], "category": "paragraph", "id": 352, "content": { "text": "d OL\nOL\ndt dq dq\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14034171402454376, "y": 0.682586669921875 }, { "x": 0.6153666228055954, "y": 0.682586669921875 }, { "x": 0.6153666228055954, "y": 0.699090164154768 }, { "x": 0.14034171402454376, "y": 0.699090164154768 } ], "category": "paragraph", "id": 353, "content": { "text": "What could this expression possibly mean?\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14030969142913818, "y": 0.7028843760490417 }, { "x": 0.8602010607719421, "y": 0.7028843760490417 }, { "x": 0.8602010607719421, "y": 0.7989846840500832 }, { "x": 0.14030969142913818, "y": 0.7989846840500832 } ], "category": "paragraph", "id": 354, "content": { "text": "Let's try to write a program that implements Lagrange equa-\ntions. What are Lagrange equations for? Our program must take\na proposed path and give a result that allows us to decide if the\npath is allowed. This is already a problem; the equation shown\nabove does not have a slot for a path to be tested.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1399839073419571, "y": 0.8272173404693604 }, { "x": 0.860082820057869, "y": 0.8272173404693604 }, { "x": 0.860082820057869, "y": 0.8741414360702038 }, { "x": 0.1399839073419571, "y": 0.8741414360702038 } ], "category": "footer", "id": 355, "content": { "text": "1\nThe idea of using computer programming to develop skills of clear thinking\nwas originally advocated by Seymour Papert. An extensive discussion of this\nidea, applied to the education of young children, can be found in Papert [13].\n", "html": "", "markdown": "" } } ] }, "01030000000057.pdf": { "elements": [ { "coordinates": [ { "x": 0.2756325900554657, "y": 0.10400613397359848 }, { "x": 0.6764777302742004, "y": 0.10400613397359848 }, { "x": 0.6764777302742004, "y": 0.11603602953255177 }, { "x": 0.2756325900554657, "y": 0.11603602953255177 } ], "category": "paragraph", "id": 333, "content": { "text": "Figure 4.2. Operating Capacity under the FIT Scheme\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15249650180339813, "y": 0.12488223612308502 }, { "x": 0.8046780079603195, "y": 0.12488223612308502 }, { "x": 0.8046780079603195, "y": 0.30909252166748047 }, { "x": 0.15249650180339813, "y": 0.30909252166748047 } ], "category": "figure", "id": 334, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.142574742436409, "y": 0.32033807039260864 }, { "x": 0.27681849896907806, "y": 0.32033807039260864 }, { "x": 0.27681849896907806, "y": 0.34488071873784065 }, { "x": 0.142574742436409, "y": 0.34488071873784065 } ], "category": "paragraph", "id": 335, "content": { "text": "FIT = feed-in-tariff.\nSource: METI (2021a).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14227408170700073, "y": 0.3781127333641052 }, { "x": 0.809145450592041, "y": 0.3781127333641052 }, { "x": 0.809145450592041, "y": 0.481932133436203 }, { "x": 0.14227408170700073, "y": 0.481932133436203 } ], "category": "paragraph", "id": 336, "content": { "text": "The newly approved capacity has stagnated lately because some strict measures reduced\nthe accumulated idle capacity in the revised FIT Act of 2017. For instance, developers are\nrequired to have entered into the grid connection agreement with a utility company for\nan FIT approval and to submit a business plan for assessment of feasibility and\nsustainability. As a result, the approved biomass power capacity is about 160MW on\naverage in FY2018 and FY2019.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14220111072063446, "y": 0.49528223276138306 }, { "x": 0.8100233525037766, "y": 0.49528223276138306 }, { "x": 0.8100233525037766, "y": 0.6884259283542633 }, { "x": 0.14220111072063446, "y": 0.6884259283542633 } ], "category": "paragraph", "id": 337, "content": { "text": "A recent change in the FIT scheme is that new projects of biomass co-firing with coal in\nthe category of unutilised wood, general wood, and construction wood waste are no\nlonger eligible for the FIT scheme from FY2019.4 4 The data collected after implementation\nof the FIT scheme revealed that the generation costs of these biomass co-firing with coal\nare lower than the estimated costs of conventional biomass power plants in terms of\ncapital expenditures, operation and maintenance, and fuels. Hence, biomass co-firing\nwith coal does not have a rationale to receive support through the FIT scheme since it\ncould make profits without it. For reference, Figure 4.3 illustrates a biomass co-firing ratio\nof the major power utilities' coal-fired power plants. Nearly half of the coal-fired power\nplants co-combusted biomass in FY2019 and most of them are less than 1% ratio of\nbiomass.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14222806692123413, "y": 0.8862397074699402 }, { "x": 0.7806748151779175, "y": 0.8862397074699402 }, { "x": 0.7806748151779175, "y": 0.8981806868687272 }, { "x": 0.14222806692123413, "y": 0.8981806868687272 } ], "category": "footer", "id": 338, "content": { "text": "4\nBiomass of waste materials co-firing with coal is not eligible for the FIT scheme from FY2021.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.4673059284687042, "y": 0.9455455541610718 }, { "x": 0.4842603038996458, "y": 0.9455455541610718 }, { "x": 0.4842603038996458, "y": 0.9542567040771246 }, { "x": 0.4673059284687042, "y": 0.9542567040771246 } ], "category": "paragraph", "id": 339, "content": { "text": "31\n", "html": "", "markdown": "" } } ] }, "01030000000004.pdf": { "elements": [ { "coordinates": [ { "x": 0.14154188334941864, "y": 0.055270466953516006 }, { "x": 0.17177448607981205, "y": 0.055270466953516006 }, { "x": 0.17177448607981205, "y": 0.06398843694478273 }, { "x": 0.14154188334941864, "y": 0.06398843694478273 } ], "category": "paragraph", "id": 427, "content": { "text": "322\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8063771724700928, "y": 0.05595291778445244 }, { "x": 0.8837717473506927, "y": 0.05595291778445244 }, { "x": 0.8837717473506927, "y": 0.06404515169560909 }, { "x": 0.8063771724700928, "y": 0.06404515169560909 } ], "category": "header", "id": 428, "content": { "text": "YARROW\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14126412570476532, "y": 0.09209368377923965 }, { "x": 0.8841261714696884, "y": 0.09209368377923965 }, { "x": 0.8841261714696884, "y": 0.14853253960609436 }, { "x": 0.14126412570476532, "y": 0.14853253960609436 } ], "category": "paragraph", "id": 429, "content": { "text": "observer model with three parameters captures PSS, sensory noise and an in-\nterval bias (i.e., a tendency to select one interval in preference to the other\nunder uncertainty).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14060235023498535, "y": 0.15291115641593933 }, { "x": 0.8848627209663391, "y": 0.15291115641593933 }, { "x": 0.8848627209663391, "y": 0.45212268829345703 }, { "x": 0.14060235023498535, "y": 0.45212268829345703 } ], "category": "paragraph", "id": 430, "content": { "text": "The 2xSJ task provides estimates that correlate fairly well with equivalent\nparameters estimated using TOJS, SJS, and ternary tasks. However, each trial\ntakes longer than in those single-presentation tasks, which makes experi-\nments more onerous. There are a few reasons why the roving-standard 2xSJ is\nstill worth considering. Firstly, it asks about synchrony explicitly (unlike the\nTOJ) and by requiring relative judgements it reveals a point of maximal syn-\nchrony perception (whereas the SJ and ternary tasks often reveal a range of\nSOA values that are classified as synchronous). Secondly, it can be added in\nto a single-presentation task (as a follow-up question every two trials), which\nsomewhat mitigates the burden of additional experimental time. Finally, a case\ncan be made that it will be more resistant to some forms of decision-level bias\n(Morgan, Grant, Melmoth, & Solomon, 2015; Morgan, Melmoth, & Solomon,\n2013). As with the other tasks I have described, code to fit data from the 2xSJ\naccompanies this chapter.23 For further information, read the comments there\nand consult Yarrow et al. (2016).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14152118563652039, "y": 0.49684008955955505 }, { "x": 0.3315759599208832, "y": 0.49684008955955505 }, { "x": 0.3315759599208832, "y": 0.5088436165824533 }, { "x": 0.14152118563652039, "y": 0.5088436165824533 } ], "category": "heading1", "id": 431, "content": { "text": "12\nConclusion\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14082364737987518, "y": 0.5366120338439941 }, { "x": 0.8838519304990768, "y": 0.5366120338439941 }, { "x": 0.8838519304990768, "y": 0.8364602029323578 }, { "x": 0.14082364737987518, "y": 0.8364602029323578 } ], "category": "paragraph", "id": 432, "content": { "text": "In this chapter, I have outlined the benefits of fitting formal observer models\nto judgements about simultaneity, and described how this can be achieved us-\ning Matlab code (see book's GitHub repository). In doing so, I have presented\none particular observer model in some detail, and highlighted the fundamen-\ntally subjective nature of the SJ task, which requires us to think carefully about\nhow both the strategic decisions and perceptual sensitivity of a participant\ncan affect their psychometric function. I have gone on to supply a brief over-\nview of appropriate models for several closely related timing tasks. I hope I\nhave also provided enough of a tutorial regarding bespoke model fitting and\nevaluation to allow the interested reader to go forward and explore their own\nmodels of perceived simultaneity. Modelling may seem intimidating, but in\nfact, a good understanding of just a few basic concepts (which is best gained\nthrough practical exploration) will take you a long way, providing tools to\nengage more fully with the timing literature. This is an endeavour I would very\nmuch encourage!\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14175602793693542, "y": 0.8658228516578674 }, { "x": 0.1608324944972992, "y": 0.8658228516578674 }, { "x": 0.1608324944972992, "y": 0.8750128857791424 }, { "x": 0.14175602793693542, "y": 0.8750128857791424 } ], "category": "paragraph", "id": 433, "content": { "text": "23\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1882190704345703, "y": 0.8627514839172363 }, { "x": 0.5942055583000183, "y": 0.8627514839172363 }, { "x": 0.5942055583000183, "y": 0.8758830837905407 }, { "x": 0.1882190704345703, "y": 0.8758830837905407 } ], "category": "footer", "id": 434, "content": { "text": ".\n", "html": "", "markdown": "" } } ] }, "01030000000082.pdf": { "elements": [ { "coordinates": [ { "x": 0.16651929914951324, "y": 0.17130745947360992 }, { "x": 0.8328845053911209, "y": 0.17130745947360992 }, { "x": 0.8328845053911209, "y": 0.351718932390213 }, { "x": 0.16651929914951324, "y": 0.351718932390213 } ], "category": "table", "id": 208, "content": { "text": "", "html": "
Imprisonment termsNumber of clausesPercentage of all statesPercentage of total
Less than 3 months4,44821.3%17.0%
3 months to less than 1 year4,80623.0%18.4%
1 year to less than 3 years9,76646.7%37.4%
3 years to less than 5 years8344.0%3.2%
5 years to less than 10 years1,0214.9%3.9%
More than 10 years200.1%0.1%
", "markdown": "" } }, { "coordinates": [ { "x": 0.16579174995422363, "y": 0.48482242226600647 }, { "x": 0.8328758478164673, "y": 0.48482242226600647 }, { "x": 0.8328758478164673, "y": 0.6550114005804062 }, { "x": 0.16579174995422363, "y": 0.6550114005804062 } ], "category": "table", "id": 237, "content": { "text": "", "html": "
StateNumber of clausesGSDP (In Rs lakh crore)GSDP (In $ billion)
Gujarat146915.6200.4
Punjab12735.370.2
Maharashtra121026.3351.0
Karnataka117515.4205.9
Tamil Nadu104316.3217.4
", "markdown": "" } }, { "coordinates": [ { "x": 0.7330852746963501, "y": 0.042327042669057846 }, { "x": 0.8332361057400703, "y": 0.042327042669057846 }, { "x": 0.8332361057400703, "y": 0.054639482870697975 }, { "x": 0.7330852746963501, "y": 0.054639482870697975 } ], "category": "header", "id": 267, "content": { "text": "Appendices\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16561579704284668, "y": 0.11662320047616959 }, { "x": 0.8154374361038208, "y": 0.11662320047616959 }, { "x": 0.8154374361038208, "y": 0.14824719727039337 }, { "x": 0.16561579704284668, "y": 0.14824719727039337 } ], "category": "heading1", "id": 268, "content": { "text": "TABLE 28: BREAKDOWN OF IMPRISONMENT CLAUSES IN\nSTATE LAWS\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16657237708568573, "y": 0.3572816550731659 }, { "x": 0.3536013811826706, "y": 0.3572816550731659 }, { "x": 0.3536013811826706, "y": 0.3685207422822714 }, { "x": 0.16657237708568573, "y": 0.3685207422822714 } ], "category": "paragraph", "id": 270, "content": { "text": "Source: TeamLease Regtech\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1657448559999466, "y": 0.43038734793663025 }, { "x": 0.6482793241739273, "y": 0.43038734793663025 }, { "x": 0.6482793241739273, "y": 0.4617845490574837 }, { "x": 0.1657448559999466, "y": 0.4617845490574837 } ], "category": "heading1", "id": 271, "content": { "text": "TABLE 29: STATES WITH MORE THAN 1,000\nIMPRISONMENT CLAUSES\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16567550599575043, "y": 0.6609818339347839 }, { "x": 0.6263650208711624, "y": 0.6609818339347839 }, { "x": 0.6263650208711624, "y": 0.6909490674734116 }, { "x": 0.16567550599575043, "y": 0.6909490674734116 } ], "category": "paragraph", "id": 273, "content": { "text": "Sources: TeamLease Regtech, and Reserve Bank of India for GSDPs\nExchange rate: Rs 75 to USD\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.4857174754142761, "y": 0.9507289528846741 }, { "x": 0.5136116612702608, "y": 0.9507289528846741 }, { "x": 0.5136116612702608, "y": 0.9650034215301275 }, { "x": 0.4857174754142761, "y": 0.9650034215301275 } ], "category": "paragraph", "id": 274, "content": { "text": "81\n", "html": "", "markdown": "" } } ] }, "01030000000040.pdf": { "elements": [ { "coordinates": [ { "x": 0.1175946295261383, "y": 0.08593908697366714 }, { "x": 0.4621533155441284, "y": 0.08593908697366714 }, { "x": 0.4621533155441284, "y": 0.22294341772794724 }, { "x": 0.1175946295261383, "y": 0.22294341772794724 } ], "category": "paragraph", "id": 471, "content": { "text": "Thailand, Philippines and Indonesia in\nparticular, identifying known experts at\nthe national, subnational and community\nlevel. The survey and interviews with\nkey informants asked key questions to\nregional experts on violent extremism to\nascertain if hostile sentiments espoused\nare exacerbating insecurities for women.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11784353107213974, "y": 0.25229504704475403 }, { "x": 0.462588332593441, "y": 0.25229504704475403 }, { "x": 0.462588332593441, "y": 0.4783068150281906 }, { "x": 0.11784353107213974, "y": 0.4783068150281906 } ], "category": "paragraph", "id": 472, "content": { "text": "The survey was made available in\nEnglish, Bahasa, Thai and Tagalog. We\nused the Qualtrics platform to facilitate\nthe lease of dissemination and response\nfrom home computers, iPads or mobile\nphone survey options. Qualtrics, one of\nthe most widely used research platforms,\nsupports the implementation of both\nlarge-scale survey and experimental\nstudy designs. It is administered online\nwith responses gathered into a central\nand privacy protected database that only\nthe approved researchers have access to.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1179041638970375, "y": 0.5074421167373657 }, { "x": 0.4620747044682503, "y": 0.5074421167373657 }, { "x": 0.4620747044682503, "y": 0.6623960882425308 }, { "x": 0.1179041638970375, "y": 0.6623960882425308 } ], "category": "paragraph", "id": 473, "content": { "text": "The platform allows for the easy\nmigration of data into various statistical\npackages, including STATA, the main\nstatistical analysis package that we will\nuse to analyse the data. A limitation\nof this study is that we were unable\nto translate the survey in all ASEAN\nlanguages, and there is a selection bias in\nthat we are focussing the survey in areas\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.528387188911438, "y": 0.08717107027769089 }, { "x": 0.8765886425971985, "y": 0.08717107027769089 }, { "x": 0.8765886425971985, "y": 0.1688365936279297 }, { "x": 0.528387188911438, "y": 0.1688365936279297 } ], "category": "paragraph", "id": 474, "content": { "text": "of the region that most experience violent\nextremism and terrorism. However,\nthrough our networks, where possible,\nwe disseminated the survey throughout\nall ASEAN countries.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5279846787452698, "y": 0.20013682544231415 }, { "x": 0.8775826990604401, "y": 0.20013682544231415 }, { "x": 0.8775826990604401, "y": 0.40845686197280884 }, { "x": 0.5279846787452698, "y": 0.40845686197280884 } ], "category": "paragraph", "id": 475, "content": { "text": "It is important to note the limitations\nof this six-month study. Although the\nsurvey was disseminated among all\nmember states, the majority of expert\nrespondents came from Indonesia, the\nPhilippines and Thailand. While this can\nbe regarded as highly selective rather\nthan representative, it is important to\nnote that Indonesia, the Philippines and\nThailand are the countries that continue\nto face the most pressing threat of\nongoing violent extremism and conflict.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5282807946205139, "y": 0.43759986758232117 }, { "x": 0.8772114217281342, "y": 0.43759986758232117 }, { "x": 0.8772114217281342, "y": 0.6637648046016693 }, { "x": 0.5282807946205139, "y": 0.6637648046016693 } ], "category": "paragraph", "id": 476, "content": { "text": "This is with the exception of Myanmar.\nGiven the current political circumstances\nand challenges posed by COVID-19, on\ntop of the short project time span, it was\nunfeasible to include Myanmar within the\nscope of this study. It is also important\nto note that the data derived from the\nsurveys and interviews were based on the\nperceptions of experts and key informants,\nwho are involved in peacebuilding, and\non P/CVE strategies throughout the\nregion. As a result, it is important to note\nthe subjectivity of responses.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3280533254146576, "y": 0.7012555599212646 }, { "x": 0.6720615327358246, "y": 0.7012555599212646 }, { "x": 0.6720615327358246, "y": 0.7135603204369545 }, { "x": 0.3280533254146576, "y": 0.7135603204369545 } ], "category": "paragraph", "id": 477, "content": { "text": "Figure 1: Age by gender of respondents\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11118833720684052, "y": 0.7247406244277954 }, { "x": 0.8884141892194748, "y": 0.7247406244277954 }, { "x": 0.8884141892194748, "y": 0.9333638846874237 }, { "x": 0.11118833720684052, "y": 0.9333638846874237 } ], "category": "figure", "id": 478, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.03296156972646713, "y": 0.9753262996673584 }, { "x": 0.7164840921759605, "y": 0.9753262996673584 }, { "x": 0.7164840921759605, "y": 0.9856872633099556 }, { "x": 0.03296156972646713, "y": 0.9856872633099556 } ], "category": "footer", "id": 479, "content": { "text": "Gender Analysis of Violent Extremism and the Impact of COVID-19 on Peace and Security in ASEAN\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.9273097515106201, "y": 0.9761351346969604 }, { "x": 0.9445667192339897, "y": 0.9761351346969604 }, { "x": 0.9445667192339897, "y": 0.9836487197317183 }, { "x": 0.9273097515106201, "y": 0.9836487197317183 } ], "category": "paragraph", "id": 480, "content": { "text": "26\n", "html": "", "markdown": "" } } ] }, "01030000000080.pdf": { "elements": [ { "coordinates": [ { "x": 0.16434450447559357, "y": 0.16890741884708405 }, { "x": 0.4504636079072952, "y": 0.16890741884708405 }, { "x": 0.4504636079072952, "y": 0.25098466873168945 }, { "x": 0.16434450447559357, "y": 0.25098466873168945 } ], "category": "heading1", "id": 256, "content": { "text": "Regulatory\ncholesterol\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5119515061378479, "y": 0.11763040721416473 }, { "x": 0.8359028995037079, "y": 0.11763040721416473 }, { "x": 0.8359028995037079, "y": 0.6054092198610306 }, { "x": 0.5119515061378479, "y": 0.6054092198610306 } ], "category": "paragraph", "id": 257, "content": { "text": "T\nhis\nreport\ndefines\n'regulatory\ncholesterol'\nas the policy actions of\nthe three arms of the State, i.e. the\nexecutive, the legislature, and the\njudiciary, using the instruments of\nlegislations, rules, regulations\nor\norders, to create or raise barriers to\na smooth flow of ideas, organisation,\nmoney and most importantly, the flow\nof the entrepreneurial spirit. In India,\na wrong political choice in the early\ndecades of Independence has created a\npolicy fraternity that shuns data and\ncausalities and leans on rhetoric and\nideologies to frame economic policies.\nInflation in the 1970s, for instance, was\nnot caused by hoarders and speculators;\nit was a matter of supply and demand.\n\"Excoriating, coercing, or imprisoning\nthe hoarders and speculators changes\nnothing in terms of creating new\nsupply,\" write Vijay Kelkar and Ajay\nShah.28 \"The economic theory of people\nhostile to economic forces is wrong.\"\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5136491656303406, "y": 0.6300442218780518 }, { "x": 0.8350683450698853, "y": 0.6300442218780518 }, { "x": 0.8350683450698853, "y": 0.8717624694108963 }, { "x": 0.5136491656303406, "y": 0.8717624694108963 } ], "category": "paragraph", "id": 258, "content": { "text": "By taking one policy tool -\nimprisonment - this report highlights\nthe excesses of overregulation and\nthe resultant regulatory cholesterol\nwhile doing business in India.\nAlthough the biggest constituency\nat the receiving end of these laws\nis that of entrepreneurs running for-\nprofit firms and corporations, this\nregulatory overreach also impacts\nnot-for-profits such as schools and\nhospitals-both necessary institutions\nfor India with a huge demand. Step\n", "html": "", "markdown": "" } } ] }, "01030000000105.pdf": { "elements": [ { "coordinates": [ { "x": 0.08680994063615799, "y": 0.08664650470018387 }, { "x": 0.5335281565785408, "y": 0.08664650470018387 }, { "x": 0.5335281565785408, "y": 0.10926525853574276 }, { "x": 0.08680994063615799, "y": 0.10926525853574276 } ], "category": "heading1", "id": 189, "content": { "text": "The Scholarly Publishing Cycle\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08787153661251068, "y": 0.1468266397714615 }, { "x": 0.9109362810850143, "y": 0.1468266397714615 }, { "x": 0.9109362810850143, "y": 0.18432708084583282 }, { "x": 0.08787153661251068, "y": 0.18432708084583282 } ], "category": "paragraph", "id": 190, "content": { "text": "Having explored the scholarly publishing ecosystem and its primary relationships, we\ncan update the cycle as follows:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.20690490305423737, "y": 0.21163977682590485 }, { "x": 0.7867276817560196, "y": 0.21163977682590485 }, { "x": 0.7867276817560196, "y": 0.5413403660058975 }, { "x": 0.20690490305423737, "y": 0.5413403660058975 } ], "category": "figure", "id": 191, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.087866872549057, "y": 0.6259969472885132 }, { "x": 0.9109969437122345, "y": 0.6259969472885132 }, { "x": 0.9109969437122345, "y": 0.6630158610641956 }, { "x": 0.087866872549057, "y": 0.6630158610641956 } ], "category": "paragraph", "id": 192, "content": { "text": "Our project set out to explore and address the shortfall in serving the scholarly reader\nidentified in this section. This shortfall is made clear in two connected points:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10744445770978928, "y": 0.6902067065238953 }, { "x": 0.8614060208201408, "y": 0.6902067065238953 }, { "x": 0.8614060208201408, "y": 0.7251029126346111 }, { "x": 0.10744445770978928, "y": 0.7251029126346111 } ], "category": "paragraph", "id": 194, "content": { "text": "Scholarly readers are not just content consumers; scholarly reading is an act of\ncreation as well.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10793060809373856, "y": 0.7339032292366028 }, { "x": 0.8796084597706795, "y": 0.7339032292366028 }, { "x": 0.8796084597706795, "y": 0.7714538350701332 }, { "x": 0.10793060809373856, "y": 0.7714538350701332 } ], "category": "paragraph", "id": 195, "content": { "text": "Publishers and aggregators are not incentivized to create better tools to support\nscholarly reading.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08714255690574646, "y": 0.7979447245597839 }, { "x": 0.9112875759601593, "y": 0.7979447245597839 }, { "x": 0.9112875759601593, "y": 0.8985975310206413 }, { "x": 0.08714255690574646, "y": 0.8985975310206413 } ], "category": "paragraph", "id": 196, "content": { "text": "From here, this report will consider the experiences of publishers, librarians and readers\nthrough a synthesis of interviews conducted with several members of each group, as\nwell as a short online survey aimed at readers. We will then share some of our own\nphilosophy on the future of scholarly reading, then detail the path forward we see for our\nown work in the area.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08728533238172531, "y": 0.937059760093689 }, { "x": 0.3534754440188408, "y": 0.937059760093689 }, { "x": 0.3534754440188408, "y": 0.9481020383536816 }, { "x": 0.08728533238172531, "y": 0.9481020383536816 } ], "category": "footer", "id": 197, "content": { "text": "10 I The Scholarly Publishing Ecosystem\n", "html": "", "markdown": "" } } ] }, "01030000000051.pdf": { "elements": [ { "coordinates": [ { "x": 0.10376754403114319, "y": 0.17960231006145477 }, { "x": 0.8543790280818939, "y": 0.17960231006145477 }, { "x": 0.8543790280818939, "y": 0.5128806978464127 }, { "x": 0.10376754403114319, "y": 0.5128806978464127 } ], "category": "table", "id": 267, "content": { "text": "", "html": "
Government PositionNo. of SeatsAquino Administration (1986-1992)Ramos Administration (1992-1998)
Senate248.316.7
House of Representatives2029.410.4
Cabinet2015.05.0
Governor735.45.4
Provincial Board Member6269.910.9
City/Municipal Mayor1,5787.411.2
City/Municipal Vice Mayor1,5786.514.9
City Municipal Councilor12,40610.5N/A
", "markdown": "" } }, { "coordinates": [ { "x": 0.10284699499607086, "y": 0.057322464883327484 }, { "x": 0.12516068667173386, "y": 0.057322464883327484 }, { "x": 0.12516068667173386, "y": 0.06844235304743052 }, { "x": 0.10284699499607086, "y": 0.06844235304743052 } ], "category": "paragraph", "id": 306, "content": { "text": "12\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1569276750087738, "y": 0.05714718997478485 }, { "x": 0.40801113843917847, "y": 0.05714718997478485 }, { "x": 0.40801113843917847, "y": 0.0717556681483984 }, { "x": 0.1569276750087738, "y": 0.0717556681483984 } ], "category": "header", "id": 307, "content": { "text": "Encinas Franco and Laguna\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10376836359500885, "y": 0.11112925410270691 }, { "x": 0.8530991226434708, "y": 0.11112925410270691 }, { "x": 0.8530991226434708, "y": 0.14440594613552094 }, { "x": 0.10376836359500885, "y": 0.14440594613552094 } ], "category": "heading1", "id": 308, "content": { "text": "Table 1: Percentage of Government Positions Held by Women During the\nPresidencies of Corazon Aquino and Fidel Ramos\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10382720082998276, "y": 0.5280372500419617 }, { "x": 0.5498444363474846, "y": 0.5280372500419617 }, { "x": 0.5498444363474846, "y": 0.5431136693805456 }, { "x": 0.10382720082998276, "y": 0.5431136693805456 } ], "category": "paragraph", "id": 310, "content": { "text": "Source: Tancangco 1991 as cited in Valte (1992).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10433200001716614, "y": 0.5943158864974976 }, { "x": 0.5068256556987762, "y": 0.5943158864974976 }, { "x": 0.5068256556987762, "y": 0.6104989740997553 }, { "x": 0.10433200001716614, "y": 0.6104989740997553 } ], "category": "heading1", "id": 311, "content": { "text": "Current Situation: 2001-2019\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1032426729798317, "y": 0.6393076181411743 }, { "x": 0.8538930788636208, "y": 0.6393076181411743 }, { "x": 0.8538930788636208, "y": 0.8077792674303055 }, { "x": 0.1032426729798317, "y": 0.8077792674303055 } ], "category": "paragraph", "id": 312, "content": { "text": "Filipino women are still very much a minority in the formal\npolitical sphere. It can also be observed that in executive positions such\nas the cabinet, few women are appointed, especially during President\nFidel Ramos's time, compared to Cory Aquino's administration\n(Table 1). As mentioned above, the Philippines has made significant\nstrides in legislating for women's rights. However, 35 years after re-\ndemocratization and 84 years after the grant of suffrage, participation\nof women in politics is still a work in progress, as in most countries.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10327883064746857, "y": 0.8263256549835205 }, { "x": 0.8535223752260208, "y": 0.8263256549835205 }, { "x": 0.8535223752260208, "y": 0.8861296139657497 }, { "x": 0.10327883064746857, "y": 0.8861296139657497 } ], "category": "paragraph", "id": 313, "content": { "text": "In 2019, the overall percentage of women in all elective posts in\nthe country was only about 20 percent (PCW 2021), barely reaching\nthe 30 percent international requirement for women's political\n", "html": "", "markdown": "" } } ] }, "01030000000097.pdf": { "elements": [ { "coordinates": [ { "x": 0.21297359466552734, "y": 0.06704967468976974 }, { "x": 0.7854239344596863, "y": 0.06704967468976974 }, { "x": 0.7854239344596863, "y": 0.44666873663663864 }, { "x": 0.21297359466552734, "y": 0.44666873663663864 } ], "category": "figure", "id": 397, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11007651686668396, "y": 0.4472469389438629 }, { "x": 0.6131803691387177, "y": 0.4472469389438629 }, { "x": 0.6131803691387177, "y": 0.467848464846611 }, { "x": 0.11007651686668396, "y": 0.467848464846611 } ], "category": "heading1", "id": 398, "content": { "text": "Now, how do we solve for the game's analytical equilibrium?12\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.13673672080039978, "y": 0.4709787368774414 }, { "x": 0.9118724763393402, "y": 0.4709787368774414 }, { "x": 0.9118724763393402, "y": 0.6621244102716446 }, { "x": 0.13673672080039978, "y": 0.6621244102716446 } ], "category": "paragraph", "id": 399, "content": { "text": "Here, Player 2 applies backward induction to find what's known as a Perfect Bayesian Equilibrium\n(PBE). As we already know, if Player 2 is the weak type and Player 1 has chosen to invade, then Player\n2 should concede. If he is the strong type, then Player 2 should fight. We also know that Player 1\nrecognizes that she gets a payoff of $0 if she concedes in the first round, regardless of Player 2's type.\nIf she instead chooses to invade in the first round, then Player 1's expected payoff from invading is\np - 0.2(1 - p) = 1.2p - 0.2. This is merely the weighted average of Player 1's expected payoff\nwhen Player 2 is weak and her expected payoff when Player 2 is strong. Thus, invade is a better strategy\nthan concede for Player 1 when 1.2p - 0.2 > 0 P > 1/6. In other words, if the probability that\nPlayer 1 assigns to Player 2 being weak is greater than one-sixth, Player 1 should choose to invade in the\nfirst round. Otherwise, Player 1 should concede and be done with it.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09223752468824387, "y": 0.6661632061004639 }, { "x": 0.906768374145031, "y": 0.6661632061004639 }, { "x": 0.906768374145031, "y": 0.6975458972156048 }, { "x": 0.09223752468824387, "y": 0.6975458972156048 } ], "category": "paragraph", "id": 400, "content": { "text": "What's the outcome when you and your classmates play this more complicated version of the\nEscalation Game?\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09257278591394424, "y": 0.7222433090209961 }, { "x": 0.33788030594587326, "y": 0.7222433090209961 }, { "x": 0.33788030594587326, "y": 0.7331642434000969 }, { "x": 0.09257278591394424, "y": 0.7331642434000969 } ], "category": "heading1", "id": 401, "content": { "text": "BURNING BRIDGES GAME\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09004687517881393, "y": 0.751689076423645 }, { "x": 0.9075324460864067, "y": 0.751689076423645 }, { "x": 0.9075324460864067, "y": 0.8074741400778294 }, { "x": 0.09004687517881393, "y": 0.8074741400778294 } ], "category": "paragraph", "id": 402, "content": { "text": "This game shares starkly similar features with the Escalation Game, but there is no uncertainty\n(thus, the analytical equilibrium is an SPE rather than a PBE). The SPE has much to say about the\nrelationship between two tenacious competitors. Spaniel (2011) portrays the game as follows:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.06791803240776062, "y": 0.8664152026176453 }, { "x": 0.8928686678409576, "y": 0.8664152026176453 }, { "x": 0.8928686678409576, "y": 0.9441551715135574 }, { "x": 0.06791803240776062, "y": 0.9441551715135574 } ], "category": "paragraph", "id": 403, "content": { "text": "12. This equilibrium is known as a Perfect Bayesian Equilibrium (PBE) rather than an SPE because of the uncertainty that at\nleast one of the players is forced to contend with. Similar to Nash, Thomas Bayes is considered a towering figure. He was\nan 18th-century English statistician, philosopher, and Presbyterian minister who is known for formulating a specific case\nof the theorem that bears his name: Bayes Theorem. Bayes never published his theory himself-his notes were edited and\npublished posthumously.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09283743053674698, "y": 0.9508423209190369 }, { "x": 0.2372368946671486, "y": 0.9508423209190369 }, { "x": 0.2372368946671486, "y": 0.9589855708181858 }, { "x": 0.09283743053674698, "y": 0.9589855708181858 } ], "category": "footer", "id": 404, "content": { "text": "132 ARTHUR J. CAPLAN\n", "html": "", "markdown": "" } } ] }, "01030000000031.pdf": { "elements": [ { "coordinates": [ { "x": 0.14643791317939758, "y": 0.027195187285542488 }, { "x": 0.4343035817146301, "y": 0.027195187285542488 }, { "x": 0.4343035817146301, "y": 0.04126351699233055 }, { "x": 0.14643791317939758, "y": 0.04126351699233055 } ], "category": "header", "id": 531, "content": { "text": "Probability, Combinatorics and Control\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.36688029766082764, "y": 0.08313822746276855 }, { "x": 0.8287975788116455, "y": 0.08313822746276855 }, { "x": 0.8287975788116455, "y": 0.1059661041945219 }, { "x": 0.36688029766082764, "y": 0.1059661041945219 } ], "category": "paragraph", "id": 532, "content": { "text": "and\nlim\n(13)\nPLH + PHL\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1473306268453598, "y": 0.12203793972730637 }, { "x": 0.83561871945858, "y": 0.12203793972730637 }, { "x": 0.83561871945858, "y": 0.15353436768054962 }, { "x": 0.1473306268453598, "y": 0.15353436768054962 } ], "category": "paragraph", "id": 533, "content": { "text": "equal zero when certain parameters tend to infinity in some well-defined way.\nHowever, it is worthwhile at this stage to note their implications for cosmology.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14630037546157837, "y": 0.1547001600265503 }, { "x": 0.8502842783927917, "y": 0.1547001600265503 }, { "x": 0.8502842783927917, "y": 0.34818558394908905 }, { "x": 0.14630037546157837, "y": 0.34818558394908905 } ], "category": "paragraph", "id": 534, "content": { "text": "The strong broken symmetry in Definition 5 actually means that a monotonic\nbehavior of the entropy is far more probable than a non-monotonic one. In the case\nof a weak broken symmetry, this is not necessarily so; it could very well be that the\nmost probable scenario would be high entropy at both ends. Thus, this is definitely a\nweaker statement, but it can nevertheless be argued that it can be used to explain\nthe time asymmetry that we observe, referring to a kind of anthropic principle: it is\nan obvious observational fact that we live in a universe with low entropy at at least\none end. If the statement in Definition 4 is fulfilled, then clearly among such\nscenarios, the monotonic ones (LH and HL) are the by far most probable ones.\nThus, since universes with high entropy at both ends would seem to be quite\nuninhabitable, one can argue that given the existence of an observer, then with\nalmost certainty he must live in a universe with monotonic entropy.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14671862125396729, "y": 0.34923234581947327 }, { "x": 0.8490155339241028, "y": 0.34923234581947327 }, { "x": 0.8490155339241028, "y": 0.3969750590622425 }, { "x": 0.14671862125396729, "y": 0.3969750590622425 } ], "category": "paragraph", "id": 535, "content": { "text": "Summing up, both limits above can be used to argue in favor of time asymmetry.\nNevertheless, at least to the mind of the author, the strong broken symmetry is the\npreferable one. This alternative will be further studied in Section 9.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14688484370708466, "y": 0.4299117922782898 }, { "x": 0.7296769469976425, "y": 0.4299117922782898 }, { "x": 0.7296769469976425, "y": 0.4462500475347042 }, { "x": 0.14688484370708466, "y": 0.4462500475347042 } ], "category": "heading1", "id": 536, "content": { "text": "8. Numerical computations in the combinatorial multiverse\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14669585227966309, "y": 0.46309757232666016 }, { "x": 0.8500277996063232, "y": 0.46309757232666016 }, { "x": 0.8500277996063232, "y": 0.5430413484573364 }, { "x": 0.14669585227966309, "y": 0.5430413484573364 } ], "category": "paragraph", "id": 537, "content": { "text": "With the setup in Sections 6 and 7, we can now use Mathematica or MATLAB to\ngenerate instances of the combinatorial multiverse for small values of m and W and\nthen compute the corresponding probability weights PLL, PLH, PHL and . It is\nimportant to note that the matrices here can be treated as sparse, rather than as full\nmatrices, which make the computations considerably faster.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14676058292388916, "y": 0.5438425540924072 }, { "x": 0.814618706703186, "y": 0.5438425540924072 }, { "x": 0.814618706703186, "y": 0.6082137897610664 }, { "x": 0.14676058292388916, "y": 0.6082137897610664 } ], "category": "paragraph", "id": 538, "content": { "text": "In particular, in the case m = 2 in Section 6 and with a randomly generated\ndynamics which is manifested by an adjacency matrix A, we can compute the\npower A4 and read of the first row, which contains all the information we need\nabout the paths from the state at t = -2 with S = 0. So what do we find?\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1468561738729477, "y": 0.6089180111885071 }, { "x": 0.8501767963171005, "y": 0.6089180111885071 }, { "x": 0.8501767963171005, "y": 0.6729093790054321 }, { "x": 0.1468561738729477, "y": 0.6729093790054321 } ], "category": "paragraph", "id": 539, "content": { "text": "In Figure 3, I have plotted the ratio NLL (NLH + NHL) for the cases m = 2 (light\ngray) and m = 3 (dark gray) for values of W ranging from 3 to 30. What is actually\ndisplayed are the mean values of 1000 randomly generated matrices as above for\neach value of W. Although the picture clearly supports the claim that\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.2727801501750946, "y": 0.7041665315628052 }, { "x": 0.7205512225627899, "y": 0.7041665315628052 }, { "x": 0.7205512225627899, "y": 0.8928920775651932 }, { "x": 0.2727801501750946, "y": 0.8928920775651932 } ], "category": "figure", "id": 540, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1466311514377594, "y": 0.9083433747291565 }, { "x": 0.8417285978794098, "y": 0.9083433747291565 }, { "x": 0.8417285978794098, "y": 0.9322780705988407 }, { "x": 0.1466311514377594, "y": 0.9322780705988407 } ], "category": "paragraph", "id": 541, "content": { "text": "Figure 3.\nThe ratio NLL/NLH + NHL) as a function of W for the cases m = 2 (light gray) and 1=3 (dark gray) [4].\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14663316309452057, "y": 0.9598013758659363 }, { "x": 0.1699171606451273, "y": 0.9598013758659363 }, { "x": 0.1699171606451273, "y": 0.9682214772328734 }, { "x": 0.14663316309452057, "y": 0.9682214772328734 } ], "category": "paragraph", "id": 542, "content": { "text": "318\n", "html": "", "markdown": "" } } ] }, "01030000000124.pdf": { "elements": [ { "coordinates": [ { "x": 0.2781965136528015, "y": 0.09202573448419571 }, { "x": 0.8576926589012146, "y": 0.09202573448419571 }, { "x": 0.8576926589012146, "y": 0.3725619986653328 }, { "x": 0.2781965136528015, "y": 0.3725619986653328 } ], "category": "table", "id": 253, "content": { "text": "", "html": "
Figure 2.9.
Ontario Television Viewing in 2004A pie chart
displaying
34.12
5% 22%categories of television
viewing in
29% 3%Ontario in
3%2004
14provides
7%too much
114 746 14%visual
information
, making it
News and public effairs Documentaryhard to
Acedemic Instruction Social and/or recreational. Instructionread.
Religion Sports
Veriety and games Music and dance
Cornectly Creme
Videonassella recorder (VCR) Other télevision programmes
", "markdown": "" } }, { "coordinates": [ { "x": 0.3174566924571991, "y": 0.11750289052724838 }, { "x": 0.5143939256668091, "y": 0.11750289052724838 }, { "x": 0.5143939256668091, "y": 0.1259697824716568 }, { "x": 0.3174566924571991, "y": 0.1259697824716568 } ], "category": "paragraph", "id": 292, "content": { "text": "Ontario Television Viewing in 2004\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.2751687467098236, "y": 0.13315190374851227 }, { "x": 0.6391031444072723, "y": 0.13315190374851227 }, { "x": 0.6391031444072723, "y": 0.3734406381845474 }, { "x": 0.2751687467098236, "y": 0.3734406381845474 } ], "category": "figure", "id": 293, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.7322311401367188, "y": 0.09462030977010727 }, { "x": 0.8553388491272926, "y": 0.09462030977010727 }, { "x": 0.8553388491272926, "y": 0.3407488241791725 }, { "x": 0.7322311401367188, "y": 0.3407488241791725 } ], "category": "paragraph", "id": 294, "content": { "text": "Figure 2.9.\nA pie chart\ndisplaying\n12\ncategories\nof television\nviewing in\nOntario in\n2004\nprovides\ntoo much\nvisual\ninformation\n, making it\nhard to\nread.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14468644559383392, "y": 0.49243468046188354 }, { "x": 0.4366253465414047, "y": 0.49243468046188354 }, { "x": 0.4366253465414047, "y": 0.5123201496899128 }, { "x": 0.14468644559383392, "y": 0.5123201496899128 } ], "category": "heading1", "id": 295, "content": { "text": "False Causation\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14273007214069366, "y": 0.5563905835151672 }, { "x": 0.8565083891153336, "y": 0.5563905835151672 }, { "x": 0.8565083891153336, "y": 0.7095105350017548 }, { "x": 0.14273007214069366, "y": 0.7095105350017548 } ], "category": "paragraph", "id": 296, "content": { "text": "Correlation does not imply causation.\nIf you've ever taken a statistics or data analysis course, you\nhave almost certainly come across this common phrase. It\nmeans that, just because two trends seem to fluctuate\nalongside each other, it doesn't prove that one causes the other\nor that they are related in a meaningful way.\nReview Figure 2.10 below, which shows a line graph of the\n23\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12126710265874863, "y": 0.7689143419265747 }, { "x": 0.8377494439482689, "y": 0.7689143419265747 }, { "x": 0.8377494439482689, "y": 0.8847527056932449 }, { "x": 0.12126710265874863, "y": 0.8847527056932449 } ], "category": "paragraph", "id": 297, "content": { "text": "2. Statistics Canada. Table 37-10-0079-01 Registered apprenticeship\ntraining, registrations by major trade groups and sex. Data is\nreproduced and distributed on an \"as is\" basis with the permission of\nStatistics Canada. Retrieved February 2nd, 2022. DOI: https://doi.org/\n10.25318/3710007901-eng. Statistics Canada Open Licence:\nhtps://www.statcan.gc.ca/en/reference/licence\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12127359211444855, "y": 0.8907127380371094 }, { "x": 0.8460918813943863, "y": 0.8907127380371094 }, { "x": 0.8460918813943863, "y": 0.9047428341582417 }, { "x": 0.12127359211444855, "y": 0.9047428341582417 } ], "category": "paragraph", "id": 298, "content": { "text": "3. Statistics Canada. Table 32-10-0364-01 Area, production and farm gate\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14297907054424286, "y": 0.9354629516601562 }, { "x": 0.16841423884034157, "y": 0.9354629516601562 }, { "x": 0.16841423884034157, "y": 0.9456513812765479 }, { "x": 0.14297907054424286, "y": 0.9456513812765479 } ], "category": "paragraph", "id": 299, "content": { "text": "46\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.19643403589725494, "y": 0.9347686767578125 }, { "x": 0.5031758099794388, "y": 0.9347686767578125 }, { "x": 0.5031758099794388, "y": 0.9483853308483958 }, { "x": 0.19643403589725494, "y": 0.9483853308483958 } ], "category": "footer", "id": 300, "content": { "text": "Misleading Data Visualizations\n", "html": "", "markdown": "" } } ] }, "01030000000162.pdf": { "elements": [ { "coordinates": [ { "x": 0.21073086559772491, "y": 0.13807542622089386 }, { "x": 0.43886297941207886, "y": 0.13807542622089386 }, { "x": 0.43886297941207886, "y": 0.15362924057990313 }, { "x": 0.21073086559772491, "y": 0.15362924057990313 } ], "category": "paragraph", "id": 262, "content": { "text": "1.\nEdward Bernays\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.2079491764307022, "y": 0.1609017550945282 }, { "x": 0.5526863187551498, "y": 0.1609017550945282 }, { "x": 0.5526863187551498, "y": 0.17699844017624855 }, { "x": 0.2079491764307022, "y": 0.17699844017624855 } ], "category": "paragraph", "id": 263, "content": { "text": "2.\nWikipedia. Public Relations\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.2075973004102707, "y": 0.1836179792881012 }, { "x": 0.6222601681947708, "y": 0.1836179792881012 }, { "x": 0.6222601681947708, "y": 0.1980872182175517 }, { "x": 0.2075973004102707, "y": 0.1980872182175517 } ], "category": "paragraph", "id": 264, "content": { "text": "3.\nPinterest. Retrieved June 10, 2021.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.20769214630126953, "y": 0.20599456131458282 }, { "x": 0.7493143081665039, "y": 0.20599456131458282 }, { "x": 0.7493143081665039, "y": 0.22264480963349342 }, { "x": 0.20769214630126953, "y": 0.22264480963349342 } ], "category": "paragraph", "id": 265, "content": { "text": "4.\nBernays, Edward. Crystalizing Public Opinion.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.20779010653495789, "y": 0.22918638586997986 }, { "x": 0.5679445266723633, "y": 0.22918638586997986 }, { "x": 0.5679445266723633, "y": 0.24554680846631527 }, { "x": 0.20779010653495789, "y": 0.24554680846631527 } ], "category": "paragraph", "id": 266, "content": { "text": "5.\nEncyclopedia of Propaganda\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.2061900794506073, "y": 0.26290571689605713 }, { "x": 0.6033385097980499, "y": 0.26290571689605713 }, { "x": 0.6033385097980499, "y": 0.27623224817216396 }, { "x": 0.2061900794506073, "y": 0.27623224817216396 } ], "category": "paragraph", "id": 267, "content": { "text": "Possible directions for the discussion:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.2167050540447235, "y": 0.3006424605846405 }, { "x": 0.7974104583263397, "y": 0.3006424605846405 }, { "x": 0.7974104583263397, "y": 0.4538975805044174 }, { "x": 0.2167050540447235, "y": 0.4538975805044174 } ], "category": "paragraph", "id": 269, "content": { "text": "What the sources suggest about the level of\nresearch. Do sources like Wikipedia and Pinterest\nindicate a deep engagement with the topic? What\nabout the Encyclopedia of Propaganda? Call back to\nthe chapter, Identifying a Topic, encyclopedias are\ngood preliminary sources, but if research stops with\nan overview source, how valuable is it?\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.217134028673172, "y": 0.4615831971168518 }, { "x": 0.8154039084911346, "y": 0.4615831971168518 }, { "x": 0.8154039084911346, "y": 0.6617711931467056 }, { "x": 0.217134028673172, "y": 0.6617711931467056 } ], "category": "paragraph", "id": 270, "content": { "text": "Ways in which the citations are ambiguous. Is\nenough information provided that readers can find\nthe original information? Is number 1 about that\nperson or written by that person? Is number 4 a book\nor an article? It has implications for how we would\nlook for it. For number 5, there is more than one\nbook with the title Encyclopedia of Propaganda, and\nalso it's unlikely they meant to refer to the whole\nencyclopedia.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.21716390550136566, "y": 0.6679015159606934 }, { "x": 0.8148472756147385, "y": 0.6679015159606934 }, { "x": 0.8148472756147385, "y": 0.8456161469221115 }, { "x": 0.21716390550136566, "y": 0.8456161469221115 } ], "category": "paragraph", "id": 271, "content": { "text": "The difference between discovering a source on a\nsocial media platform and citing the content. Is\nenough information given to find the Pinterest\nsource? Revisit the creator concept from the chapter,\nTypes of Sources. Social media companies distribute\nbut do not create content, SO they are not the ones\nthat should be cited. Opportunity to talk about\nspecific sources students have found on social media\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14244508743286133, "y": 0.9244493246078491 }, { "x": 0.16828523017466068, "y": 0.9244493246078491 }, { "x": 0.16828523017466068, "y": 0.9347447175532579 }, { "x": 0.14244508743286133, "y": 0.9347447175532579 } ], "category": "paragraph", "id": 272, "content": { "text": "114\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1941022276878357, "y": 0.9242103099822998 }, { "x": 0.39149588346481323, "y": 0.9242103099822998 }, { "x": 0.39149588346481323, "y": 0.9352054866030812 }, { "x": 0.1941022276878357, "y": 0.9352054866030812 } ], "category": "footer", "id": 273, "content": { "text": "Instructor Resources\n", "html": "", "markdown": "" } } ] }, "01030000000136.pdf": { "elements": [ { "coordinates": [ { "x": 0.10043392330408096, "y": 0.09176869690418243 }, { "x": 0.8830563798546791, "y": 0.09176869690418243 }, { "x": 0.8830563798546791, "y": 0.38499732315540314 }, { "x": 0.10043392330408096, "y": 0.38499732315540314 } ], "category": "table", "id": 275, "content": { "text": "", "html": "
Getting away from the usual demands 34%
Being close to nature 33%
Enjoying the sounds and smells of nature 32%
Catching fish 31%
Spending time with family or friends 29%
The scenic beauty 16%
Experiencing solitude 14%
Experiencing excitement/adventure 14%
Reliving my childhood memories of going fishing12%
Catching my own food12%
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Long description.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09779561311006546, "y": 0.4843731224536896 }, { "x": 0.9009569361805916, "y": 0.4843731224536896 }, { "x": 0.9009569361805916, "y": 0.5372031405568123 }, { "x": 0.09779561311006546, "y": 0.5372031405568123 } ], "category": "paragraph", "id": 366, "content": { "text": "Over time, an angler's motivation may change from a catch orientation to emphasize noncatch motivations,\nsuch as being outdoors or passing on their passion for fishing (McKenna 2013). The progression often follows\nthese stages:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10896755754947662, "y": 0.5609097480773926 }, { "x": 0.3716884106397629, "y": 0.5609097480773926 }, { "x": 0.3716884106397629, "y": 0.5743412086740136 }, { "x": 0.10896755754947662, "y": 0.5743412086740136 } ], "category": "paragraph", "id": 368, "content": { "text": "Stage 1: I just want to catch a fish!\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10918929427862167, "y": 0.5805586576461792 }, { "x": 0.3866155669093132, "y": 0.5805586576461792 }, { "x": 0.3866155669093132, "y": 0.5939418682828546 }, { "x": 0.10918929427862167, "y": 0.5939418682828546 } ], "category": "paragraph", "id": 369, "content": { "text": "Stage 2: I want to catch a lot of fish!\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10909771919250488, "y": 0.5998666882514954 }, { "x": 0.35843731462955475, "y": 0.5998666882514954 }, { "x": 0.35843731462955475, "y": 0.6138438396155834 }, { "x": 0.10909771919250488, "y": 0.6138438396155834 } ], "category": "paragraph", "id": 370, "content": { "text": "Stage 3: I want to catch big fish.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10931915044784546, "y": 0.6190043687820435 }, { "x": 0.41587206721305847, "y": 0.6190043687820435 }, { "x": 0.41587206721305847, "y": 0.6331732785329223 }, { "x": 0.10931915044784546, "y": 0.6331732785329223 } ], "category": "paragraph", "id": 371, "content": { "text": "Stage 4: I'm just happy to be out fishing.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10922770947217941, "y": 0.6382899880409241 }, { "x": 0.5930907055735588, "y": 0.6382899880409241 }, { "x": 0.5930907055735588, "y": 0.6528769787400961 }, { "x": 0.10922770947217941, "y": 0.6528769787400961 } ], "category": "paragraph", "id": 372, "content": { "text": "Stage 5: I want to pass on my knowledge and passion for fishing.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09800316393375397, "y": 0.6754807829856873 }, { "x": 0.9012369066476822, "y": 0.6754807829856873 }, { "x": 0.9012369066476822, "y": 0.7487020418047905 }, { "x": 0.09800316393375397, "y": 0.7487020418047905 } ], "category": "paragraph", "id": 373, "content": { "text": "Studies of angler characteristics confirm that there is no such thing as an \"average\" angler. Rather, anglers are\na heterogeneous and changing group. Therefore, we can segment anglers in distinct categories for analysis\n(Bryan 1977; Kyle et al. 2007; Beardmore et al. 2013; TenHarmsel et al. 2019). For example, Magee (2018)\ncategorized recreational anglers into five distinct fisher classes with differing motivations (Table 10.1).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0979103296995163, "y": 0.9362067580223083 }, { "x": 0.11810602620244026, "y": 0.9362067580223083 }, { "x": 0.11810602620244026, "y": 0.944761149585247 }, { "x": 0.0979103296995163, "y": 0.944761149585247 } ], "category": "paragraph", "id": 374, "content": { "text": "216\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.13641981780529022, "y": 0.9356834888458252 }, { "x": 0.3903924375772476, "y": 0.9356834888458252 }, { "x": 0.3903924375772476, "y": 0.9478503251448274 }, { "x": 0.13641981780529022, "y": 0.9478503251448274 } ], "category": "footer", "id": 375, "content": { "text": "Recreational Fishing and Keep Fish Wet\n", "html": "", "markdown": "" } } ] }, "01030000000096.pdf": { "elements": [ { "coordinates": [ { "x": 0.1552896499633789, "y": 0.07648468017578125 }, { "x": 0.6633549928665161, "y": 0.07648468017578125 }, { "x": 0.6633549928665161, "y": 0.3203612118959427 }, { "x": 0.1552896499633789, "y": 0.3203612118959427 } ], "category": "figure", "id": 258, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.118596151471138, "y": 0.3539857268333435 }, { "x": 0.9046577960252762, "y": 0.3539857268333435 }, { "x": 0.9046577960252762, "y": 0.44729260355234146 }, { "x": 0.118596151471138, "y": 0.44729260355234146 } ], "category": "paragraph", "id": 260, "content": { "text": "8. Suppose Evelyn the Environmental Economist is presenting her case in a public meeting for\nwhy raising the price of municipal water in the face of persistent drought conditions would be\na good thing for the community, when someone in the audience yells out, \"That's unfair for\nseniors and others living on fixed incomes.\" How might Evelyn frame her response in a way\nthat dispels the audience's concerns about the fairness of a price increase?\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11815284937620163, "y": 0.4733201265335083 }, { "x": 0.896496407687664, "y": 0.4733201265335083 }, { "x": 0.896496407687664, "y": 0.5082503370940685 }, { "x": 0.11815284937620163, "y": 0.5082503370940685 } ], "category": "paragraph", "id": 261, "content": { "text": "9. How would the indifference curve in Figure 6.1 change when drawn for a person who suffers\nfrom guilt but not envy? Draw the curve.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1110185906291008, "y": 0.5343079566955566 }, { "x": 0.902142159640789, "y": 0.5343079566955566 }, { "x": 0.902142159640789, "y": 0.5691823735833168 }, { "x": 0.1110185906291008, "y": 0.5691823735833168 } ], "category": "paragraph", "id": 262, "content": { "text": "10. Can you recall an example from your own life where you exhibited an Endowment Effect that\nultimately led to regret?\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1100316271185875, "y": 0.5951906442642212 }, { "x": 0.8939981684088707, "y": 0.5951906442642212 }, { "x": 0.8939981684088707, "y": 0.6499177850782871 }, { "x": 0.1100316271185875, "y": 0.6499177850782871 } ], "category": "paragraph", "id": 263, "content": { "text": "11. The Gender Gap experiment discussed in this chapter measured gender differences in terms\nof how males and females deal with competitive situations. Think of another situation where\na gender gap may exist and design an experiment to test for it.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1097424179315567, "y": 0.6759655475616455 }, { "x": 0.8944791704416275, "y": 0.6759655475616455 }, { "x": 0.8944791704416275, "y": 0.7496603205800056 }, { "x": 0.1097424179315567, "y": 0.7496603205800056 } ], "category": "paragraph", "id": 264, "content": { "text": "12. It was shown in this chapter that a Homo economicus who exhibits convex-shaped indifference\ncurves exhibits an Endowment Effect. Does this result still hold if Homo economicus exhibits\nlinearly shaped indifference curves, as depicted in the figure below? Show your result using\nthis graph.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.6404423117637634, "y": 0.9512497186660767 }, { "x": 0.9062101244926453, "y": 0.9512497186660767 }, { "x": 0.9062101244926453, "y": 0.9586885944008827 }, { "x": 0.6404423117637634, "y": 0.9586885944008827 } ], "category": "footer", "id": 265, "content": { "text": "BEHAVIORAL ECONOMICS PRACTICUM 117\n", "html": "", "markdown": "" } } ] }, "01030000000181.pdf": { "elements": [ { "coordinates": [ { "x": 0.06736593693494797, "y": 0.420369416475296 }, { "x": 0.905521921813488, "y": 0.420369416475296 }, { "x": 0.905521921813488, "y": 0.7766015529632568 }, { "x": 0.06736593693494797, "y": 0.7766015529632568 } ], "category": "table", "id": 83, "content": { "text": "", "html": "
Our PurposeOur MissionWhat We Do
Making Al BeneficialEasy-to-apply Al,Providing the world's best and easy-to-use
EverywhereAl solutions for everyone
Plug-and-play to cross/multi-cloud system
Ensuring performance tailored to customer data via retraining
Providing a platform that allows easy distribution and management of
Al solutions
Al consulting service to help AI transformation
", "markdown": "" } }, { "coordinates": [ { "x": 0.0741947665810585, "y": 0.09945128113031387 }, { "x": 0.5386633351445198, "y": 0.09945128113031387 }, { "x": 0.5386633351445198, "y": 0.19319023936986923 }, { "x": 0.0741947665810585, "y": 0.19319023936986923 } ], "category": "paragraph", "id": 109, "content": { "text": "Upstage aims to enrich your business by providing\nEasy-to-Apply Al solutions\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.07225682586431503, "y": 0.4287453889846802 }, { "x": 0.14063365757465363, "y": 0.4287453889846802 }, { "x": 0.14063365757465363, "y": 0.4493774585425854 }, { "x": 0.07225682586431503, "y": 0.4493774585425854 } ], "category": "paragraph", "id": 110, "content": { "text": "Our Purpose\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.07299324125051498, "y": 0.49437880516052246 }, { "x": 0.2255895510315895, "y": 0.49437880516052246 }, { "x": 0.2255895510315895, "y": 0.523653507232666 }, { "x": 0.07299324125051498, "y": 0.523653507232666 } ], "category": "paragraph", "id": 111, "content": { "text": "Making Al Beneficial\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3258993327617645, "y": 0.4285494387149811 }, { "x": 0.3918423354625702, "y": 0.4285494387149811 }, { "x": 0.3918423354625702, "y": 0.4456896297633648 }, { "x": 0.3258993327617645, "y": 0.4456896297633648 } ], "category": "paragraph", "id": 112, "content": { "text": "Our Mission\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3267506957054138, "y": 0.49482524394989014 }, { "x": 0.4523908644914627, "y": 0.49482524394989014 }, { "x": 0.4523908644914627, "y": 0.5725312978029251 }, { "x": 0.3267506957054138, "y": 0.5725312978029251 } ], "category": "paragraph", "id": 113, "content": { "text": "Easy-to-apply Al,\nEverywhere\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5672298073768616, "y": 0.42850372195243835 }, { "x": 0.6374335065484047, "y": 0.42850372195243835 }, { "x": 0.6374335065484047, "y": 0.44548418186604977 }, { "x": 0.5672298073768616, "y": 0.44548418186604977 } ], "category": "heading1", "id": 114, "content": { "text": "What We Do\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5672170519828796, "y": 0.49425044655799866 }, { "x": 0.8907471895217896, "y": 0.49425044655799866 }, { "x": 0.8907471895217896, "y": 0.5723733678460121 }, { "x": 0.5672170519828796, "y": 0.5723733678460121 } ], "category": "paragraph", "id": 115, "content": { "text": "Providing the world's best and easy-to-use\nAl solutions for everyone\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5677141547203064, "y": 0.6292000412940979 }, { "x": 0.7721219807863235, "y": 0.6292000412940979 }, { "x": 0.7721219807863235, "y": 0.6485330667346716 }, { "x": 0.5677141547203064, "y": 0.6485330667346716 } ], "category": "paragraph", "id": 117, "content": { "text": "Plug-and-play to cross/multi-cloud system\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5673990845680237, "y": 0.660669207572937 }, { "x": 0.8661255836486816, "y": 0.660669207572937 }, { "x": 0.8661255836486816, "y": 0.6798656340688467 }, { "x": 0.5673990845680237, "y": 0.6798656340688467 } ], "category": "paragraph", "id": 118, "content": { "text": "Ensuring performance tailored to customer data via retraining\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5674163103103638, "y": 0.6899629235267639 }, { "x": 0.9030963480472565, "y": 0.6899629235267639 }, { "x": 0.9030963480472565, "y": 0.7369045428931713 }, { "x": 0.5674163103103638, "y": 0.7369045428931713 } ], "category": "paragraph", "id": 119, "content": { "text": "Providing a platform that allows easy distribution and management of\nAl solutions\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5677862763404846, "y": 0.7516880035400391 }, { "x": 0.7926234751939774, "y": 0.7516880035400391 }, { "x": 0.7926234751939774, "y": 0.7701525390148163 }, { "x": 0.5677862763404846, "y": 0.7701525390148163 } ], "category": "paragraph", "id": 120, "content": { "text": "Al consulting service to help AI transformation\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.9716198444366455, "y": 0.948341965675354 }, { "x": 0.9760964326560497, "y": 0.948341965675354 }, { "x": 0.9760964326560497, "y": 0.9614607580006123 }, { "x": 0.9716198444366455, "y": 0.9614607580006123 } ], "category": "paragraph", "id": 121, "content": { "text": "3\n", "html": "", "markdown": "" } } ] }, "01030000000069.pdf": { "elements": [ { "coordinates": [ { "x": 0.11762320250272751, "y": 0.09064889699220657 }, { "x": 0.179819505661726, "y": 0.09064889699220657 }, { "x": 0.179819505661726, "y": 0.10364966467022896 }, { "x": 0.11762320250272751, "y": 0.10364966467022896 } ], "category": "heading1", "id": 412, "content": { "text": "Replace\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11870035529136658, "y": 0.11037024110555649 }, { "x": 0.8215321600437164, "y": 0.11037024110555649 }, { "x": 0.8215321600437164, "y": 0.32717414945364 }, { "x": 0.11870035529136658, "y": 0.32717414945364 } ], "category": "paragraph", "id": 414, "content": { "text": "I.\nReplace Plastics with Recyclable Materials. Plastics can be replaced by material\nmade from polypropylene, a material type that is 100% recyclable. However, recyclable\nmaterials should have a forward linkage - link to a recycler who is willing to take on\nthe recyclables. Paper-based wrappers are another alternative for bagels and sandwich\npapers. Containers and packaging can use plastics with a certain percentage of recycled\ncontent and designed to be recyclable or reusable. Highly recyclable packaging is of\nlittle benefit if it is not disposed of correctly. The success of a recyclable package is an\nequal demand from recycling companies through improved recyclability of packaging\nand investments in efficient recycling facilities and systems. This requires investment and\ninnovation since quality and availability are still often a stumbling block for companies\nto use recycled plastic. The recyclability of plastic packaging can often be improved by:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16161493957042694, "y": 0.33276718854904175 }, { "x": 0.6403099745512009, "y": 0.33276718854904175 }, { "x": 0.6403099745512009, "y": 0.3468451611697674 }, { "x": 0.16161493957042694, "y": 0.3468451611697674 } ], "category": "paragraph", "id": 415, "content": { "text": "choosing a common type of plastic (such as PE, PP or PET);\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1617375761270523, "y": 0.3530902862548828 }, { "x": 0.6021395772695541, "y": 0.3530902862548828 }, { "x": 0.6021395772695541, "y": 0.3671900639310479 }, { "x": 0.1617375761270523, "y": 0.3671900639310479 } ], "category": "paragraph", "id": 416, "content": { "text": "choosing a common color (white or transparent); and\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16186022758483887, "y": 0.3732259273529053 }, { "x": 0.8025733828544617, "y": 0.3732259273529053 }, { "x": 0.8025733828544617, "y": 0.4276983514428139 }, { "x": 0.16186022758483887, "y": 0.4276983514428139 } ], "category": "paragraph", "id": 417, "content": { "text": "avoiding combinations of materials, such as plastic windows in cardboard\npackaging. Watermarking technology is also being developed so that packaging\ncan be more easily recognized by sorters.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11692040413618088, "y": 0.4544162452220917 }, { "x": 0.15984395146369934, "y": 0.4544162452220917 }, { "x": 0.15984395146369934, "y": 0.46488533541560173 }, { "x": 0.11692040413618088, "y": 0.46488533541560173 } ], "category": "heading1", "id": 418, "content": { "text": "Trash\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11766285449266434, "y": 0.4743345379829407 }, { "x": 0.8215327337384224, "y": 0.4743345379829407 }, { "x": 0.8215327337384224, "y": 0.6271235793828964 }, { "x": 0.11766285449266434, "y": 0.6271235793828964 } ], "category": "paragraph", "id": 420, "content": { "text": "m.\nWaste Segregation and Segregated Bins. Shakey's Philippines implementation of\nwaste segregation and 3R (Reduce, Reuse, Recycle) in its corporate office is one good\ntestament of compliance to RA 9003. The country's premier pizza restaurant has installed\n\"Stop Before You Drop\" trash bins for the implementation of company-wide proper\nwaste management. The bins are labeled to indicate the different types of waste to aid in\nproper disposal and culture development of its employees. Waste collected are weighed\non a daily basis to aid in monitoring wastages and to map out more waste management\ninitiatives.56\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11746779829263687, "y": 0.6564396619796753 }, { "x": 0.44353795796632767, "y": 0.6564396619796753 }, { "x": 0.44353795796632767, "y": 0.6701976740732789 }, { "x": 0.11746779829263687, "y": 0.6701976740732789 } ], "category": "paragraph", "id": 421, "content": { "text": "n.\nIn-store Sorting and Recycling Bins.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1605672538280487, "y": 0.6763064861297607 }, { "x": 0.5007394850254059, "y": 0.6763064861297607 }, { "x": 0.5007394850254059, "y": 0.831512987613678 }, { "x": 0.1605672538280487, "y": 0.831512987613678 } ], "category": "paragraph", "id": 422, "content": { "text": "McDonalds has installed sorting and\nrecycling points in select restaurants in\nits markets. It also improved its recycling\nbin signage to make the recycling process\neasier to understand. McDonald's Germany,\nAustria, Czech Republic and Slovakia on the\nother hand, collect customer waste to sort for\nrecycling. initiatives.57\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5406672358512878, "y": 0.7796949148178101 }, { "x": 0.8099983036518097, "y": 0.7796949148178101 }, { "x": 0.8099983036518097, "y": 0.8039605747908354 }, { "x": 0.5406672358512878, "y": 0.8039605747908354 } ], "category": "paragraph", "id": 423, "content": { "text": "Figure 32. In-store Sorting and Recycling Bins,\nMcDonalds\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5379706025123596, "y": 0.6546523571014404 }, { "x": 0.8128267228603363, "y": 0.6546523571014404 }, { "x": 0.8128267228603363, "y": 0.7763850316405296 }, { "x": 0.5379706025123596, "y": 0.7763850316405296 } ], "category": "figure", "id": 424, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11718051880598068, "y": 0.872081458568573 }, { "x": 0.6887313053011894, "y": 0.872081458568573 }, { "x": 0.6887313053011894, "y": 0.899853901937604 }, { "x": 0.11718051880598068, "y": 0.899853901937604 } ], "category": "paragraph", "id": 425, "content": { "text": "56\nhttps://www.shakeyspizza.ph/images/asm-2021/PIZZA_ASM_2020_Report.pdf\n57\nhhttps://corporate.mcdonalds.com/corpmcd/our-purpose-and-impact/our-planet/packaging-and-waste.htm\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.03140324726700783, "y": 0.945307195186615 }, { "x": 0.05421474762260914, "y": 0.945307195186615 }, { "x": 0.05421474762260914, "y": 0.9590844307094812 }, { "x": 0.03140324726700783, "y": 0.9590844307094812 } ], "category": "paragraph", "id": 426, "content": { "text": "76\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08473781496286392, "y": 0.9476549625396729 }, { "x": 0.5653369501233101, "y": 0.9476549625396729 }, { "x": 0.5653369501233101, "y": 0.9605712462216616 }, { "x": 0.08473781496286392, "y": 0.9605712462216616 } ], "category": "footer", "id": 427, "content": { "text": "Study on Plastics Use and Waste Management in the Food Service Industry\n", "html": "", "markdown": "" } } ] }, "01030000000157.pdf": { "elements": [ { "coordinates": [ { "x": 0.14420011639595032, "y": 0.0987279936671257 }, { "x": 0.21804751455783844, "y": 0.0987279936671257 }, { "x": 0.21804751455783844, "y": 0.12402292154729366 }, { "x": 0.14420011639595032, "y": 0.12402292154729366 } ], "category": "heading1", "id": 281, "content": { "text": "Stop\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14177173376083374, "y": 0.16662244498729706 }, { "x": 0.540476381778717, "y": 0.16662244498729706 }, { "x": 0.540476381778717, "y": 0.591293528676033 }, { "x": 0.14177173376083374, "y": 0.591293528676033 } ], "category": "paragraph", "id": 282, "content": { "text": "Check your emotions. If a claim\ncauses strong emotion - anger, glee,\npride, vindication - STOP. You must\nfact-check this claim. Remember\nfrom the chapter, Our Mental\nShortcuts, that we more readily\naccept information that confirms our\nbeliefs (confirmation bias) and we\ntend to think less critically about that\nkind of information than we do about\ninformation that challenges our\nbeliefs (motivated reasoning.) A\nstrong emotional reaction is a sign\nthat these cognitive biases are at\nwork. Remember, these mental\nshortcuts don't make us bad people,\nwe all have them. But we do need to\naccount for them if we want to move\ntoward better information.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14176341891288757, "y": 0.6011942028999329 }, { "x": 0.6045429706573486, "y": 0.6011942028999329 }, { "x": 0.6045429706573486, "y": 0.7973736822605133 }, { "x": 0.14176341891288757, "y": 0.7973736822605133 } ], "category": "paragraph", "id": 283, "content": { "text": "In addition, if you get lost while\nworking on the other moves, or hit\ndead ends, or find yourself going\ndown an increasingly confusing\nrabbit hole during your investigation,\nSTOP. Back up and start over knowing\nwhat you know now. You're likely to\ntake a more informed path with\ndifferent search terms and better decisions.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.6188990473747253, "y": 0.14941944181919098 }, { "x": 0.794226884841919, "y": 0.14941944181919098 }, { "x": 0.794226884841919, "y": 0.7141047269105911 }, { "x": 0.6188990473747253, "y": 0.7141047269105911 } ], "category": "paragraph", "id": 284, "content": { "text": "In these\nchapters we're\nfocusing on\nresearching a\nwicked problem,\nbut the SIFT\nmethod is a\ngreat thing to\nuse before you\nshare\ninformation on\nsocial media.\nOften we feel\ncompelled to\nshare the things\nthat evoke the\nstrongest\nfeelings, but\nthose strong\nfeelings are a\ngood sign that\nthose things\nneed to be\nchecked before\nthey are shared.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.6186667084693909, "y": 0.9237281680107117 }, { "x": 0.8066245317459106, "y": 0.9237281680107117 }, { "x": 0.8066245317459106, "y": 0.9381884625181556 }, { "x": 0.6186667084693909, "y": 0.9381884625181556 } ], "category": "footer", "id": 285, "content": { "text": "SIFTing Information\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8335385322570801, "y": 0.9245883822441101 }, { "x": 0.8557334244251251, "y": 0.9245883822441101 }, { "x": 0.8557334244251251, "y": 0.9348358754068613 }, { "x": 0.8335385322570801, "y": 0.9348358754068613 } ], "category": "paragraph", "id": 286, "content": { "text": "69\n", "html": "", "markdown": "" } } ] }, "01030000000108.pdf": { "elements": [ { "coordinates": [ { "x": 0.0856705978512764, "y": 0.24552227556705475 }, { "x": 0.91435457020998, "y": 0.24552227556705475 }, { "x": 0.91435457020998, "y": 0.7689218670129776 }, { "x": 0.0856705978512764, "y": 0.7689218670129776 } ], "category": "table", "id": 121, "content": { "text": "", "html": "
About the Publishervii
About This Projectix
Acknowledgmentsxi
LAB MANUAL
Experiment #1: Hydrostatic Pressure3
Experiment #2: Bernoulli's Theorem Demonstration13
Experiment #3: Energy Loss in Pipe Fittings24
Experiment #4: Energy Loss in Pipes33
Experiment #5: Impact of a Jet43
Experiment #6: Orifice and Free Jet Flow50
Experiment #7: Osborne Reynolds' Demonstration59
Experiment #8: Free and Forced Vortices66
Experiment #9: Flow Over Weirs76
Experiment #10: Pumps84
References101
Links by Chapter102
Image Credits104
", "markdown": "" } }, { "coordinates": [ { "x": 0.13834425806999207, "y": 0.1473473459482193 }, { "x": 0.2514207288622856, "y": 0.1473473459482193 }, { "x": 0.2514207288622856, "y": 0.159984583966434 }, { "x": 0.13834425806999207, "y": 0.159984583966434 } ], "category": "heading1", "id": 158, "content": { "text": "CONTENTS\n", "html": "", "markdown": "" } } ] }, "01030000000101.pdf": { "elements": [ { "coordinates": [ { "x": 0.14105218648910522, "y": 0.07145487517118454 }, { "x": 0.9067111015319824, "y": 0.07145487517118454 }, { "x": 0.9067111015319824, "y": 0.127361498773098 }, { "x": 0.14105218648910522, "y": 0.127361498773098 } ], "category": "paragraph", "id": 673, "content": { "text": "[markets] build loyalty and-more important-make people want to extend themselves to the\ndegree that corporations need today: to be flexible, concerned, and willing to pitch in. That's\nwhat a social relationship delivers.\" (page 90)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09210063517093658, "y": 0.13015598058700562 }, { "x": 0.9067307859659195, "y": 0.13015598058700562 }, { "x": 0.9067307859659195, "y": 0.16649044305086136 }, { "x": 0.09210063517093658, "y": 0.16649044305086136 } ], "category": "paragraph", "id": 674, "content": { "text": "Hence, in the less-predictable world of Homo sapiens, businesses must decide the extent to which\nthey participate with their employees and customers in monetary and/or social markets.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09178538620471954, "y": 0.16892112791538239 }, { "x": 0.9066693335771561, "y": 0.16892112791538239 }, { "x": 0.9066693335771561, "y": 0.28274083137512207 }, { "x": 0.09178538620471954, "y": 0.28274083137512207 } ], "category": "paragraph", "id": 675, "content": { "text": "As a follow-on to Heyman and Ariely's (2004) experiments exploring the payment-effort trade-off,\nVohs et al. (2006) sought to understand the behavioral psychology underscoring the trade-off. In its\nmost general terms, the authors' hypothesis is that money makes Homo sapiens feel self-sufficient and\nbehave accordingly. When reminded of money, people desire to be free from dependency upon others\nand prefer that others not depend upon them. Vohs et al. designed several experiments to test this\nhypothesis from a variety of angles.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0917128175497055, "y": 0.2858044505119324 }, { "x": 0.9070485085248947, "y": 0.2858044505119324 }, { "x": 0.9070485085248947, "y": 0.5745935142040253 }, { "x": 0.0917128175497055, "y": 0.5745935142040253 } ], "category": "paragraph", "id": 676, "content": { "text": "In one experiment, the authors found that participants (a sample of University of Minnesota\nstudents) who were reminded about money-both Monopoly money and real money-in the context\nof a series of word descrambling tasks worked longer at the tasks than participants in a non-money-\n25\nprimed control group before requesting help from the experimenter. In subsequent experiments\nwith different groups of students, Vohs et al. found that (1) participants in a high-money treatment\nworked significantly longer than participants in a low-money treatment before asking for help from\nanother available participant, (2) participants in a money-primed treatment volunteered to help code\nfewer data sheets than did participants in the non-money-primed control condition, (3) participants\nin a high-money treatment volunteered to gather fewer pencils that had spilled onto the floor than\ndid participants in a low-money treatment, and (4) participants in a money-primed treatment donated\nsignificantly less money to a university student fund than participants in the non-money primed\ncontrol. Three final experiments tested the effects of money on social intimacy, desire to engage in\nleisure activities alone, and preference to work alone. As expected, participants who were primed with\nmoney ahead of time were subsequently less socially intimate and exhibited a stronger preference for\nengaging in leisure activities and working alone.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09200689941644669, "y": 0.577328085899353 }, { "x": 0.9065965786576271, "y": 0.577328085899353 }, { "x": 0.9065965786576271, "y": 0.613062497228384 }, { "x": 0.09200689941644669, "y": 0.613062497228384 } ], "category": "paragraph", "id": 677, "content": { "text": "So yes, Vohs et al.'s experiments suggest that money makes Homo sapiens feel self-sufficient and\nbehave accordingly.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09268733859062195, "y": 0.6339303851127625 }, { "x": 0.4194355010986328, "y": 0.6339303851127625 }, { "x": 0.4194355010986328, "y": 0.6455592447891831 }, { "x": 0.09268733859062195, "y": 0.6455592447891831 } ], "category": "heading1", "id": 678, "content": { "text": "PRICE AND THE PLACEBO EFFECT\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09178168326616287, "y": 0.6633979678153992 }, { "x": 0.9069062545895576, "y": 0.6633979678153992 }, { "x": 0.9069062545895576, "y": 0.8359524011611938 }, { "x": 0.09178168326616287, "y": 0.8359524011611938 } ], "category": "paragraph", "id": 679, "content": { "text": "Is it possible that the magnitudes of placebo effects experienced by Homo sapiens (e.g., through medical\ntherapies or medications) are somehow influenced by the prices we pay for them? To investigate\nthis possibility, Waber et al. (2008) studied the effect of price on a group of Homo sapiens' analgesic\nresponses to placebo pills. Over 80 healthy volunteers in Boston, MA were recruited via an online\nadvertisement to participate in a field experiment where each participant was informed by a brochure\nabout a purported new opioid analgesic recently approved by the Food and Drug Administration. The\nopioid was described as similar to codeine but with a faster onset time. In reality, and not disclosed\nto the participants, the pill was a placebo. After randomization, half of the participants were informed\nthat the drug had a regular price of $2.50 per pill (\"regular price\"), and half of the participants that\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.06858919560909271, "y": 0.8509045243263245 }, { "x": 0.9059935659170151, "y": 0.8509045243263245 }, { "x": 0.9059935659170151, "y": 0.943938210606575 }, { "x": 0.06858919560909271, "y": 0.943938210606575 } ], "category": "paragraph", "id": 680, "content": { "text": "25. The descrambling task consisted of 30 sets of five jumbled words. Participants created sensible phrases using four of the\nfive words. In the control and play-money treatment, the phrases primed neutral concepts (e.g., \"cold it desk outside is\"\nbecame \"it is cold outside\"). In the real-money treatment, 15 of the phrases primed the concept of money (e.g., \"high a salary\ndesk paying\" became \"a high-paying salary\"), whereas the remaining 15 were neutral phrases. Participants in the play-\nmoney treatment were primed with money by a stack of Monopoly money in their visual periphery while completing the\nneutral descrambling task.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09218135476112366, "y": 0.9509927034378052 }, { "x": 0.2371557205915451, "y": 0.9509927034378052 }, { "x": 0.2371557205915451, "y": 0.9590161377564073 }, { "x": 0.09218135476112366, "y": 0.9590161377564073 } ], "category": "footer", "id": 681, "content": { "text": "220 ARTHUR J. CAPLAN\n", "html": "", "markdown": "" } } ] }, "01030000000114.pdf": { "elements": [ { "coordinates": [ { "x": 0.07785580307245255, "y": 0.02968454919755459 }, { "x": 0.35354749113321304, "y": 0.02968454919755459 }, { "x": 0.35354749113321304, "y": 0.044002143666148186 }, { "x": 0.07785580307245255, "y": 0.044002143666148186 } ], "category": "header", "id": 88, "content": { "text": "MOHAVE COMMUNITY COLLEGE\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8735904693603516, "y": 0.03132213279604912 }, { "x": 0.9435478374361992, "y": 0.03132213279604912 }, { "x": 0.9435478374361992, "y": 0.04358902666717768 }, { "x": 0.8735904693603516, "y": 0.04358902666717768 } ], "category": "header", "id": 89, "content": { "text": "BIO181\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.07370134443044662, "y": 0.08083740621805191 }, { "x": 0.4041828140616417, "y": 0.08083740621805191 }, { "x": 0.4041828140616417, "y": 0.0938725434243679 }, { "x": 0.07370134443044662, "y": 0.0938725434243679 } ], "category": "paragraph", "id": 90, "content": { "text": "Genetics Lab - Blood Disorders\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.9175069332122803, "y": 0.0812685415148735 }, { "x": 0.9430775102227926, "y": 0.0812685415148735 }, { "x": 0.9430775102227926, "y": 0.09317067917436361 }, { "x": 0.9175069332122803, "y": 0.09317067917436361 } ], "category": "paragraph", "id": 91, "content": { "text": "94\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.07384560257196426, "y": 0.11008922010660172 }, { "x": 0.5810880437493324, "y": 0.11008922010660172 }, { "x": 0.5810880437493324, "y": 0.1262448951601982 }, { "x": 0.07384560257196426, "y": 0.1262448951601982 } ], "category": "paragraph", "id": 92, "content": { "text": "Human Traits Governed by Mendelian Genetics\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.07385071367025375, "y": 0.1980569064617157 }, { "x": 0.35833098739385605, "y": 0.1980569064617157 }, { "x": 0.35833098739385605, "y": 0.2113287691026926 }, { "x": 0.07385071367025375, "y": 0.2113287691026926 } ], "category": "paragraph", "id": 93, "content": { "text": "Human Genetics Problems\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.9171791076660156, "y": 0.11075866222381592 }, { "x": 0.9430467672646046, "y": 0.11075866222381592 }, { "x": 0.9430467672646046, "y": 0.1226541893556714 }, { "x": 0.9171791076660156, "y": 0.1226541893556714 } ], "category": "paragraph", "id": 94, "content": { "text": "97\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.07385557144880295, "y": 0.13860802352428436 }, { "x": 0.9431024715304375, "y": 0.13860802352428436 }, { "x": 0.9431024715304375, "y": 0.18498031795024872 }, { "x": 0.07385557144880295, "y": 0.18498031795024872 } ], "category": "paragraph", "id": 95, "content": { "text": "1.\nRecord your phenotype and genotype for the following Mendelian traits: 97\nHuman Traits not Governed by Mendelian Genetics\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.9175678491592407, "y": 0.16953420639038086 }, { "x": 0.9426979143172503, "y": 0.16953420639038086 }, { "x": 0.9426979143172503, "y": 0.18144917767494917 }, { "x": 0.9175678491592407, "y": 0.18144917767494917 } ], "category": "paragraph", "id": 96, "content": { "text": "98\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.9052862524986267, "y": 0.19882600009441376 }, { "x": 0.9429623037576675, "y": 0.19882600009441376 }, { "x": 0.9429623037576675, "y": 0.21080325078219175 }, { "x": 0.9052862524986267, "y": 0.21080325078219175 } ], "category": "paragraph", "id": 97, "content": { "text": "100\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.07383615523576736, "y": 0.22807584702968597 }, { "x": 0.265553779900074, "y": 0.22807584702968597 }, { "x": 0.265553779900074, "y": 0.24357360880821943 }, { "x": 0.07383615523576736, "y": 0.24357360880821943 } ], "category": "paragraph", "id": 98, "content": { "text": "Pedigree Analysis\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.905099093914032, "y": 0.22802074253559113 }, { "x": 0.9429429322481155, "y": 0.22802074253559113 }, { "x": 0.9429429322481155, "y": 0.2401541704311967 }, { "x": 0.905099093914032, "y": 0.2401541704311967 } ], "category": "paragraph", "id": 99, "content": { "text": "102\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.07359662652015686, "y": 0.2575768828392029 }, { "x": 0.26994870603084564, "y": 0.2575768828392029 }, { "x": 0.26994870603084564, "y": 0.2703125989064574 }, { "x": 0.07359662652015686, "y": 0.2703125989064574 } ], "category": "paragraph", "id": 100, "content": { "text": "Practice Problems\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.9052780270576477, "y": 0.25744494795799255 }, { "x": 0.942909449338913, "y": 0.25744494795799255 }, { "x": 0.942909449338913, "y": 0.26949287950992584 }, { "x": 0.9052780270576477, "y": 0.26949287950992584 } ], "category": "paragraph", "id": 101, "content": { "text": "102\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.07344464212656021, "y": 0.2866247296333313 }, { "x": 0.21899517625570297, "y": 0.2866247296333313 }, { "x": 0.21899517625570297, "y": 0.2991233002394438 }, { "x": 0.07344464212656021, "y": 0.2991233002394438 } ], "category": "paragraph", "id": 102, "content": { "text": "Lab Materials\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.9053496718406677, "y": 0.2868879437446594 }, { "x": 0.9433582164347172, "y": 0.2868879437446594 }, { "x": 0.9433582164347172, "y": 0.29892114270478487 }, { "x": 0.9053496718406677, "y": 0.29892114270478487 } ], "category": "paragraph", "id": 103, "content": { "text": "104\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.07342761009931564, "y": 0.3159877359867096 }, { "x": 0.3884712681174278, "y": 0.3159877359867096 }, { "x": 0.3884712681174278, "y": 0.32886337768286467 }, { "x": 0.07342761009931564, "y": 0.32886337768286467 } ], "category": "paragraph", "id": 104, "content": { "text": "Contributors and Attributions\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.9054070115089417, "y": 0.3163449466228485 }, { "x": 0.9434403218328953, "y": 0.3163449466228485 }, { "x": 0.9434403218328953, "y": 0.3283860730007291 }, { "x": 0.9054070115089417, "y": 0.3283860730007291 } ], "category": "paragraph", "id": 105, "content": { "text": "104\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.07379040122032166, "y": 0.345105916261673 }, { "x": 0.6641726791858673, "y": 0.345105916261673 }, { "x": 0.6641726791858673, "y": 0.3613739851862192 }, { "x": 0.07379040122032166, "y": 0.3613739851862192 } ], "category": "paragraph", "id": 106, "content": { "text": "From Gene to Protein via Transcription and Translation\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.9054883718490601, "y": 0.34537824988365173 }, { "x": 0.943001925945282, "y": 0.34537824988365173 }, { "x": 0.943001925945282, "y": 0.35769419372081757 }, { "x": 0.9054883718490601, "y": 0.35769419372081757 } ], "category": "paragraph", "id": 107, "content": { "text": "105\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.4944674074649811, "y": 0.9683732986450195 }, { "x": 0.5043644504621625, "y": 0.9683732986450195 }, { "x": 0.5043644504621625, "y": 0.9793314198032022 }, { "x": 0.4944674074649811, "y": 0.9793314198032022 } ], "category": "paragraph", "id": 108, "content": { "text": "2\n", "html": "", "markdown": "" } } ] }, "01030000000137.pdf": { "elements": [ { "coordinates": [ { "x": 0.10111922770738602, "y": 0.07665503770112991 }, { "x": 0.9021291211247444, "y": 0.07665503770112991 }, { "x": 0.9021291211247444, "y": 0.36741507798433304 }, { "x": 0.10111922770738602, "y": 0.36741507798433304 } ], "category": "figure", "id": 446, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.44429638981819153, "y": 0.39714473485946655 }, { "x": 0.5872828960418701, "y": 0.39714473485946655 }, { "x": 0.5872828960418701, "y": 0.41534388437867165 }, { "x": 0.44429638981819153, "y": 0.41534388437867165 } ], "category": "paragraph", "id": 447, "content": { "text": "Catch Per Day\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09569783508777618, "y": 0.43337562680244446 }, { "x": 0.8852718621492386, "y": 0.43337562680244446 }, { "x": 0.8852718621492386, "y": 0.45906314440071583 }, { "x": 0.09569783508777618, "y": 0.45906314440071583 } ], "category": "paragraph", "id": 448, "content": { "text": "Figure 10.5: Frequency distribution displays the number of angler days resulting in differing catch per day for a hypothetical 8\nfish per day creel limit and estimated change if creel limit is reduced to 4 fish per day. Long description.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09780054539442062, "y": 0.5236511826515198 }, { "x": 0.9012949392199516, "y": 0.5236511826515198 }, { "x": 0.9012949392199516, "y": 0.6733384877443314 }, { "x": 0.09780054539442062, "y": 0.6733384877443314 } ], "category": "paragraph", "id": 449, "content": { "text": "Creel limits are one of many elements that may be used by anglers to define fishing success. When more\nfish are harvested per trip, anglers rate fishing higher. High creel limits may cause anglers to have unrealistic\nexpectations about the potential supply of fish compared to the demand (Cook et al. 2001). Creel limit\nreductions may be unsuccessful in reducing angler harvest or affecting fish populations. The hypothetical\nangler success graph (Figure 10.5) demonstrates that a reduction in creel from 8 to 4 would affect only a few\ntrips and result in a small harvest reduction. Furthermore, creel limits are applied on a per-angler basis, SO they\ncannot control total harvest if total fishing effort increases or if noncompliance is high. Finally, since anglers\nhave a variety of motivations, they likely respond differently to regulation changes (Beard et al. 2011).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09771743416786194, "y": 0.6918067932128906 }, { "x": 0.9010585248470306, "y": 0.6918067932128906 }, { "x": 0.9010585248470306, "y": 0.8027789816260338 }, { "x": 0.09771743416786194, "y": 0.8027789816260338 } ], "category": "paragraph", "id": 450, "content": { "text": "The ethic of fairness is involved in setting creel limit regulations because many anglers do not harvest a single\nfish during an angling trip. In Wisconsin lakes, Walleye harvest was not equally distributed. Only 7.4% of Walleye\nangler trips were successful in harvesting at least one Walleye, and <1% harvested a limit during a fishing trip\n(Staggs 1989). In Minnesota, anglers were slightly more successful, where 27.2% of angler trips ended with a\nharvest of at least one Walleye and about 1% harvesting a limit. The ideal creel limit would distribute the catch\namong more anglers and prevent overuse by a few individuals.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09768207371234894, "y": 0.8209468722343445 }, { "x": 0.9013444930315018, "y": 0.8209468722343445 }, { "x": 0.9013444930315018, "y": 0.9123579114675522 }, { "x": 0.09768207371234894, "y": 0.9123579114675522 } ], "category": "paragraph", "id": 451, "content": { "text": "Long-term trends in panfish populations (i.e., Bluegill, Yellow Perch, Black Crappie, Pumpkinseed, and Rock\nBass) in Wisconsin lakes showed significant declines due to overfishing (Rypel et al. 2016). The daily limit for\npanfish was 50 aggregate per day from 1967 through 1998, which was reduced to 25 in 1998. Further reduction\nin daily limits for panfish (10) to improve undesirable small sizes of Bluegill populations increased both mean\nlength and mean maximum length relative to sizes in control lakes (Jacobson 2005; Rypel et al. 2015).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09789931029081345, "y": 0.9360834360122681 }, { "x": 0.12059779092669487, "y": 0.9360834360122681 }, { "x": 0.12059779092669487, "y": 0.9447328355163336 }, { "x": 0.09789931029081345, "y": 0.9447328355163336 } ], "category": "paragraph", "id": 452, "content": { "text": "226\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1391076147556305, "y": 0.9357467889785767 }, { "x": 0.3926316499710083, "y": 0.9357467889785767 }, { "x": 0.3926316499710083, "y": 0.947722758166492 }, { "x": 0.1391076147556305, "y": 0.947722758166492 } ], "category": "footer", "id": 453, "content": { "text": "Recreational Fishing and Keep Fish Wet\n", "html": "", "markdown": "" } } ] }, "01030000000191.pdf": { "elements": [ { "coordinates": [ { "x": 0.11806667596101761, "y": 0.08684390038251877 }, { "x": 0.2853042408823967, "y": 0.08684390038251877 }, { "x": 0.2853042408823967, "y": 0.10053209587931633 }, { "x": 0.11806667596101761, "y": 0.10053209587931633 } ], "category": "heading1", "id": 770, "content": { "text": "Acknowledgements\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11755894124507904, "y": 0.11234629899263382 }, { "x": 0.48801811039447784, "y": 0.11234629899263382 }, { "x": 0.48801811039447784, "y": 0.33172667771577835 }, { "x": 0.11755894124507904, "y": 0.33172667771577835 } ], "category": "paragraph", "id": 771, "content": { "text": "We would like to extend our gratitude to the teams\nat Hugging Face, particularly Clémentine Four-\nrier, Lewis Tunstall, Omar Sanseviero, and Philipp\nSchmid. Our appreciation also extends to the teams\nat AWS, notably Ritesh Vajaria, Gal Oshri, Jay\nKwon, Brandon Lee, Effie Bae, and Rahul Sharma.\nWe are grateful to the teams at Korea Telecom\n(KT), especially Jin Hyoung Lee, Jungsuk Park,\nSungjoon Park, Hong-rae Wang, Kyeongsoo Jung,\nand Sunyoong Yoon, whose significant support has\nbeen instrumental in ensuring the broad compati-\nbility of our model. Additionally, we would like to\nextend our thanks to the open community for their\ninvaluable contributions and feedback.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1183682233095169, "y": 0.3494296669960022 }, { "x": 0.21803149580955505, "y": 0.3494296669960022 }, { "x": 0.21803149580955505, "y": 0.36008497700095177 }, { "x": 0.1183682233095169, "y": 0.36008497700095177 } ], "category": "heading1", "id": 772, "content": { "text": "Limitations\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11798927187919617, "y": 0.3752027750015259 }, { "x": 0.4882771074771881, "y": 0.3752027750015259 }, { "x": 0.4882771074771881, "y": 0.5803447365760803 }, { "x": 0.11798927187919617, "y": 0.5803447365760803 } ], "category": "paragraph", "id": 773, "content": { "text": "Our study on the Depth Up-Scaling (DUS) has im-\nportant limitations and considerations. One key\nlimitation is the need for more thorough explo-\nrations of hyperparameters used in the DUS ap-\nproach. Namely, we removed m = 8 layers from\nboth ends of our base model, primarily due to hard-\nware limitations. However, we have not yet deter-\nmined if this value is optimal for enhancing perfor-\nmance. The extended time and cost of continued\npretraining made it challenging to conduct more\ncomprehensive experiments, which we aim to ad-\ndress in future work through various comparative\nanalyses.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11780139058828354, "y": 0.5843342542648315 }, { "x": 0.48808231204748154, "y": 0.5843342542648315 }, { "x": 0.48808231204748154, "y": 0.7736690193414688 }, { "x": 0.11780139058828354, "y": 0.7736690193414688 } ], "category": "paragraph", "id": 774, "content": { "text": "In terms of the model's broader implications,\nthere are several points to note. The model's sig-\nnificant computational demands for training and\ninference might limit its use, especially for those\nwith restricted computational resources. Addition-\nally, like all machine learning models, it is vulnera-\nble to biases in its training data, which could lead\nto skewed outcomes in certain situations. Further-\nmore, the substantial energy consumption required\nfor training and operating the model raises environ-\nmental concerns, which are critical in the pursuit\nof sustainable AI development.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11732878535985947, "y": 0.7773396968841553 }, { "x": 0.48819225281476974, "y": 0.7773396968841553 }, { "x": 0.48819225281476974, "y": 0.9187170267105103 }, { "x": 0.11732878535985947, "y": 0.9187170267105103 } ], "category": "paragraph", "id": 775, "content": { "text": "Lastly, while the fine-tuned variant of the model\nshows improved performance in following instruc-\ntions, it still requires task-specific fine-tuning for\noptimal performance in specialized applications.\nThis fine-tuning process can be resource-intensive\nand not always effective. Recognizing and address-\ning these limitations is essential for a comprehen-\nsive understanding of the proposed Large Language\nModel's capabilities and for guiding future research\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5137650370597839, "y": 0.0874687135219574 }, { "x": 0.796187162399292, "y": 0.0874687135219574 }, { "x": 0.796187162399292, "y": 0.10016322880983353 }, { "x": 0.5137650370597839, "y": 0.10016322880983353 } ], "category": "paragraph", "id": 776, "content": { "text": "and development in the field of LLMs.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5134338736534119, "y": 0.11600376665592194 }, { "x": 0.6595980674028397, "y": 0.11600376665592194 }, { "x": 0.6595980674028397, "y": 0.12699997890740633 }, { "x": 0.5134338736534119, "y": 0.12699997890740633 } ], "category": "heading1", "id": 777, "content": { "text": "Ethics Statement\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.51278156042099, "y": 0.14261116087436676 }, { "x": 0.8832795321941376, "y": 0.14261116087436676 }, { "x": 0.8832795321941376, "y": 0.281644731760025 }, { "x": 0.51278156042099, "y": 0.281644731760025 } ], "category": "paragraph", "id": 778, "content": { "text": "We conscientiously address and emphasize the\ncommitment of SOLAR 10.7B in maintaining the\nhighest ethical standards. First, we highlight that\nSOLAR 10.7B-Instruct has shown low levels of\ndata contamination in our evaluations, a testament\nto our rigorous data handling and processing pro-\ntocols. This aspect is crucial, as it underpins the\nreliability and integrity of the results obtained from\nSOLAR.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5134115219116211, "y": 0.2879856526851654 }, { "x": 0.8830994963645935, "y": 0.2879856526851654 }, { "x": 0.8830994963645935, "y": 0.3969929665327072 }, { "x": 0.5134115219116211, "y": 0.3969929665327072 } ], "category": "paragraph", "id": 779, "content": { "text": "Furthermore, during the course of our experi-\nments, we ensured that all setups and methodolo-\ngies employed steer clear of any potential ethical\npitfalls. This preemptive consideration and avoid-\nance of ethically questionable practices underscore\nour dedication to conducting research that is not\nonly innovative but also responsible.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.513175368309021, "y": 0.40097787976264954 }, { "x": 0.8837361037731171, "y": 0.40097787976264954 }, { "x": 0.8837361037731171, "y": 0.5261854231357574 }, { "x": 0.513175368309021, "y": 0.5261854231357574 } ], "category": "paragraph", "id": 780, "content": { "text": "Additionally, we ensure that SOLAR complies\nwith general ethical considerations in all aspects\nof its operation. This includes adherence to pri-\nvacy norms, respect for intellectual property, and\nensuring the absence of bias in our algorithms. Our\ncommitment to these ethical principles is unwaver-\ning, and we believe it significantly contributes to\nthe credibility and societal acceptance of SOLAR.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5132119655609131, "y": 0.5301249623298645 }, { "x": 0.8835501670837402, "y": 0.5301249623298645 }, { "x": 0.8835501670837402, "y": 0.6068195328116417 }, { "x": 0.5132119655609131, "y": 0.6068195328116417 } ], "category": "paragraph", "id": 781, "content": { "text": "In conclusion, the ethical framework within\nwhich SOLAR operates is robust and comprehen-\nsive, ensuring that our advancements in this field\nare not only scientifically sound but also ethically\nresponsible.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5139118432998657, "y": 0.6378481984138489 }, { "x": 0.6073541343212128, "y": 0.6378481984138489 }, { "x": 0.6073541343212128, "y": 0.6486023310571909 }, { "x": 0.5139118432998657, "y": 0.6486023310571909 } ], "category": "heading1", "id": 782, "content": { "text": "References\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5135079026222229, "y": 0.6615214943885803 }, { "x": 0.8815047740936279, "y": 0.6615214943885803 }, { "x": 0.8815047740936279, "y": 0.7379458099603653 }, { "x": 0.5135079026222229, "y": 0.7379458099603653 } ], "category": "paragraph", "id": 783, "content": { "text": "Ian L Alberts, Lorenzo Mercolli, Thomas Pyka, George\nPrenosil, Kuangyu Shi, Axel Rominger, and Ali\nAfshar-Oromieh. 2023. Large language models\n(llm) and chatgpt: what will the impact on nuclear\nmedicine be? European journal of nuclear medicine\nand molecular imaging, 50(6):1549-1552.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5136474967002869, "y": 0.7516634464263916 }, { "x": 0.8831546604633331, "y": 0.7516634464263916 }, { "x": 0.8831546604633331, "y": 0.8153291344642639 }, { "x": 0.5136474967002869, "y": 0.8153291344642639 } ], "category": "paragraph", "id": 784, "content": { "text": "Rohan Anil, Andrew M Dai, Orhan Firat, Melvin John-\nson, Dmitry Lepikhin, Alexandre Passos, Siamak\nShakeri, Emanuel Taropa, Paige Bailey, Zhifeng\nChen, et al. 2023. Palm 2 technical report. arXiv\npreprint MarXiv:2305.10403.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5138049721717834, "y": 0.8284851312637329 }, { "x": 0.8832516968250275, "y": 0.8284851312637329 }, { "x": 0.8832516968250275, "y": 0.91611547768116 }, { "x": 0.5138049721717834, "y": 0.91611547768116 } ], "category": "paragraph", "id": 785, "content": { "text": "Aram Bahrini, Mohammadsadra Khamoshifar, Hos-\nsein Abbasimehr, Robert J Riggs, Maryam Esmaeili,\nRastin Mastali Majdabadkohne, and Morteza Pase-\nhvar. 2023. Chatgpt: Applications, opportunities,\nand threats. In 2023 Systems and Information Engi-\nneering Design Symposium (SIEDS), pages 274-279.\nIEEE.\n", "html": "", "markdown": "" } } ] }, "01030000000144.pdf": { "elements": [ { "coordinates": [ { "x": 0.15074007213115692, "y": 0.08618641644716263 }, { "x": 0.4022378474473953, "y": 0.08618641644716263 }, { "x": 0.4022378474473953, "y": 0.09868568368256092 }, { "x": 0.15074007213115692, "y": 0.09868568368256092 } ], "category": "header", "id": 358, "content": { "text": "Chapter 3. Numerical differentiation\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8448402881622314, "y": 0.08653674274682999 }, { "x": 0.8615587055683136, "y": 0.08653674274682999 }, { "x": 0.8615587055683136, "y": 0.09577921032905579 }, { "x": 0.8448402881622314, "y": 0.09577921032905579 } ], "category": "paragraph", "id": 359, "content": { "text": "35\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15056176483631134, "y": 0.12382902950048447 }, { "x": 0.38268521428108215, "y": 0.12382902950048447 }, { "x": 0.38268521428108215, "y": 0.1366345575079322 }, { "x": 0.15056176483631134, "y": 0.1366345575079322 } ], "category": "paragraph", "id": 360, "content": { "text": "Note that the exact error equals\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.354326069355011, "y": 0.14997471868991852 }, { "x": 0.6305768489837646, "y": 0.14997471868991852 }, { "x": 0.6305768489837646, "y": 0.16215698048472404 }, { "x": 0.354326069355011, "y": 0.16215698048472404 } ], "category": "paragraph", "id": 361, "content": { "text": "M Q(h) = -2.7525... -0.0342\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1502998322248459, "y": 0.17586515843868256 }, { "x": 0.799411877989769, "y": 0.17586515843868256 }, { "x": 0.799411877989769, "y": 0.21033328771591187 }, { "x": 0.1502998322248459, "y": 0.21033328771591187 } ], "category": "paragraph", "id": 362, "content": { "text": "In this example the error estimate is very reliable.\nTo receive a better approximation the error estimate can be added to the approximation:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.33326393365859985, "y": 0.22279994189739227 }, { "x": 0.6725326180458069, "y": 0.22279994189739227 }, { "x": 0.6725326180458069, "y": 0.23614887986332178 }, { "x": 0.33326393365859985, "y": 0.23614887986332178 } ], "category": "paragraph", "id": 363, "content": { "text": "(h)+cph==2.7525... - 0.0348\n= 2.7177.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15045776963233948, "y": 0.2564871311187744 }, { "x": 0.8623377978801727, "y": 0.2564871311187744 }, { "x": 0.8623377978801727, "y": 0.3118032477796078 }, { "x": 0.15045776963233948, "y": 0.3118032477796078 } ], "category": "paragraph", "id": 364, "content": { "text": "In the above example, the value of p was computed using Richardson's extrapolation. However,\nusing Theorem 3.2.1, it is clear that p = 1, and this value could have been used immediately in\nequation (3.13b) in order to determine Cphp. In practice, more complex situations are found, and\nthe following complications may occur:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.17911189794540405, "y": 0.3250553607940674 }, { "x": 0.7528787851333618, "y": 0.3250553607940674 }, { "x": 0.7528787851333618, "y": 0.33803840819746256 }, { "x": 0.17911189794540405, "y": 0.33803840819746256 } ], "category": "paragraph", "id": 366, "content": { "text": "- It is not known whether higher-order derivatives exist and/or are bounded.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.17889492213726044, "y": 0.34867140650749207 }, { "x": 0.8615458458662033, "y": 0.34867140650749207 }, { "x": 0.8615458458662033, "y": 0.3759862333536148 }, { "x": 0.17889492213726044, "y": 0.3759862333536148 } ], "category": "paragraph", "id": 367, "content": { "text": "- The final result is a combination of various approximation methods. The influence of these\napproximations on p is not always clear.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1791616529226303, "y": 0.3868425488471985 }, { "x": 0.8271981328725815, "y": 0.3868425488471985 }, { "x": 0.8271981328725815, "y": 0.3999189669266343 }, { "x": 0.1791616529226303, "y": 0.3999189669266343 } ], "category": "paragraph", "id": 368, "content": { "text": "- During implementation of the algorithm in a computer program, errors may be made.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15032777190208435, "y": 0.41294336318969727 }, { "x": 0.8614880740642548, "y": 0.41294336318969727 }, { "x": 0.8614880740642548, "y": 0.4400771502405405 }, { "x": 0.15032777190208435, "y": 0.4400771502405405 } ], "category": "paragraph", "id": 369, "content": { "text": "To reveal any of these complications it is good practice to verify whether the calculated p is close\nto the p that follows from theory.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15053999423980713, "y": 0.4606427252292633 }, { "x": 0.7831409573554993, "y": 0.4606427252292633 }, { "x": 0.7831409573554993, "y": 0.4755250960588455 }, { "x": 0.15053999423980713, "y": 0.4755250960588455 } ], "category": "heading1", "id": 370, "content": { "text": "3.7.3 Formulae of higher accuracy from Richardson's extrapolation *\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15062540769577026, "y": 0.4844839870929718 }, { "x": 0.8615355491638184, "y": 0.4844839870929718 }, { "x": 0.8615355491638184, "y": 0.5118246544152498 }, { "x": 0.15062540769577026, "y": 0.5118246544152498 } ], "category": "paragraph", "id": 371, "content": { "text": "In several applications the value of p in (3.10) is known. In that case Richardson's extrapolation\ncan be used to determine formulae of higher accuracy.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15022288262844086, "y": 0.5202494859695435 }, { "x": 0.7983559221029282, "y": 0.5202494859695435 }, { "x": 0.7983559221029282, "y": 0.533212348818779 }, { "x": 0.15022288262844086, "y": 0.533212348818779 } ], "category": "paragraph", "id": 372, "content": { "text": "This is done by making use of the fact that the error estimates for Q(h) and Q(2h) equal\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3797989785671234, "y": 0.5455997586250305 }, { "x": 0.8616071343421936, "y": 0.5455997586250305 }, { "x": 0.8616071343421936, "y": 0.5810511261224747 }, { "x": 0.3797989785671234, "y": 0.5810511261224747 } ], "category": "paragraph", "id": 373, "content": { "text": "M - Q(h) =cphP+O(hP+1) =\n(3.15a)\nM Q(2h)=cp(2h)p+O(hp+1)\n(3.15b)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1504586935043335, "y": 0.5939779281616211 }, { "x": 0.7687777280807495, "y": 0.5939779281616211 }, { "x": 0.7687777280807495, "y": 0.6070591965690255 }, { "x": 0.1504586935043335, "y": 0.6070591965690255 } ], "category": "paragraph", "id": 374, "content": { "text": "Multiplying equation (3.15a) by 2P and subtracting equation (3.15b) from this yields\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15018098056316376, "y": 0.6210854053497314 }, { "x": 0.8613149374723434, "y": 0.6210854053497314 }, { "x": 0.8613149374723434, "y": 0.7139642387628555 }, { "x": 0.15018098056316376, "y": 0.7139642387628555 } ], "category": "paragraph", "id": 375, "content": { "text": "2P =\nsuch that\n(2P -1)M-2PQ(h)+Q(2h)=O(hp+1). =\nThis means that\n(3.16)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1502581089735031, "y": 0.7283007502555847 }, { "x": 0.8615368455648422, "y": 0.7283007502555847 }, { "x": 0.8615368455648422, "y": 0.7556830830872059 }, { "x": 0.1502581089735031, "y": 0.7556830830872059 } ], "category": "paragraph", "id": 376, "content": { "text": "The value (2PQ(h) - Q(2h))/(2P - 1) is a new approximation formula for M with an accuracy\nthat is one order higher than the order of Q(h).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1508415937423706, "y": 0.7740947604179382 }, { "x": 0.5587624609470367, "y": 0.7740947604179382 }, { "x": 0.5587624609470367, "y": 0.7865880345925689 }, { "x": 0.1508415937423706, "y": 0.7865880345925689 } ], "category": "heading1", "id": 377, "content": { "text": "Example 3.7.2 (Forward difference of higher accuracy)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15072883665561676, "y": 0.7975350618362427 }, { "x": 0.8626365810632706, "y": 0.7975350618362427 }, { "x": 0.8626365810632706, "y": 0.8244309928268194 }, { "x": 0.15072883665561676, "y": 0.8244309928268194 } ], "category": "paragraph", "id": 378, "content": { "text": "As an example, the forward-difference method is considered. The error in the forward-difference\nformula may be written as\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15058453381061554, "y": 0.8256134986877441 }, { "x": 0.8613037616014481, "y": 0.8256134986877441 }, { "x": 0.8613037616014481, "y": 0.8615596480667591 }, { "x": 0.15058453381061554, "y": 0.8615596480667591 } ], "category": "paragraph", "id": 379, "content": { "text": "f(x)-Q/(h)=qh+0(if)\n(3.17)\nand the difference for 2h equals\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3876124620437622, "y": 0.8747643828392029 }, { "x": 0.8614301383495331, "y": 0.8747643828392029 }, { "x": 0.8614301383495331, "y": 0.8902175519615412 }, { "x": 0.3876124620437622, "y": 0.8902175519615412 } ], "category": "paragraph", "id": 380, "content": { "text": "f'(x)-Qf(2h)=c12h+(h2) -\n(3.18)\n", "html": "", "markdown": "" } } ] }, "01030000000171.pdf": { "elements": [ { "coordinates": [ { "x": 0.1375240981578827, "y": 0.17266342043876648 }, { "x": 0.9118511974811554, "y": 0.17266342043876648 }, { "x": 0.9118511974811554, "y": 0.2777694910764694 }, { "x": 0.1375240981578827, "y": 0.2777694910764694 } ], "category": "table", "id": 244, "content": { "text": "", "html": "
Acknowledgment of CountryV
Accessibility Informationvi
Acknowledgmentsvii
About the Authorsviii
Introduction1
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Section 1.1: Data and Types of Statistical Variables3
Section 1.2: Descriptive Statistics5
Section 1.3: Missing Data6
Section 1.4: Checking Values7
Section 1.5: Normality8
Section 1.6: Outliers9
Section 1.7: Chapter One Self-Test10
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Part II. Chapter Two - Test Statistics, p Values, Confidence Intervals and Effect Sizes
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Section 2.1: p Values12
Section 2.2: Significance13
Section 2.3: Confidence Intervals14
Section 2.4: Effect Sizes16
Section 2.5: Statistical Power17
Section 2.6: Chapter Two Self-Test18
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Section 3.1: Looking at Group Differences20
Section 3.2: Between Versus Within Groups Analysis21
Section 3.3: Independent T-test Assumptions, Interpretation, and Write Up22
Section 3.4: Paired T-test Assumptions, Interpretation, and Write Up25
Section 3.5: Chapter Three Self-Test27
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Section 4.1: Examining Relationships29
Section 4.2: Correlation Assumptions, Interpretation, and Write Up31
Section 4.3: Chapter Four Self-Test33
", "markdown": "" } }, { "coordinates": [ { "x": 0.0966125950217247, "y": 0.0742521658539772 }, { "x": 0.237882561981678, "y": 0.0742521658539772 }, { "x": 0.237882561981678, "y": 0.09365394897758961 }, { "x": 0.0966125950217247, "y": 0.09365394897758961 } ], "category": "paragraph", "id": 308, "content": { "text": "Contents\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14242494106292725, "y": 0.3004381060600281 }, { "x": 0.447101354598999, "y": 0.3004381060600281 }, { "x": 0.447101354598999, "y": 0.313270696438849 }, { "x": 0.14242494106292725, "y": 0.313270696438849 } ], "category": "paragraph", "id": 310, "content": { "text": "Part I. Chapter One - Exploring Your Data\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14276878535747528, "y": 0.49011752009391785 }, { "x": 0.7447379678487778, "y": 0.49011752009391785 }, { "x": 0.7447379678487778, "y": 0.5036764610558748 }, { "x": 0.14276878535747528, "y": 0.5036764610558748 } ], "category": "paragraph", "id": 312, "content": { "text": "Part II. Chapter Two - Test Statistics, p Values, Confidence Intervals and Effect Sizes\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14257775247097015, "y": 0.5263625979423523 }, { "x": 0.28281891345977783, "y": 0.5263625979423523 }, { "x": 0.28281891345977783, "y": 0.5376508366316557 }, { "x": 0.14257775247097015, "y": 0.5376508366316557 } ], "category": "paragraph", "id": 313, "content": { "text": "Section 2.1: p Values\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8906108140945435, "y": 0.526718258857727 }, { "x": 0.9041641335934401, "y": 0.526718258857727 }, { "x": 0.9041641335934401, "y": 0.5349656203761697 }, { "x": 0.8906108140945435, "y": 0.5349656203761697 } ], "category": "paragraph", "id": 314, "content": { "text": "12\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1426454782485962, "y": 0.5458505749702454 }, { "x": 0.31173060834407806, "y": 0.5458505749702454 }, { "x": 0.31173060834407806, "y": 0.5574475154280663 }, { "x": 0.1426454782485962, "y": 0.5574475154280663 } ], "category": "paragraph", "id": 315, "content": { "text": "Section 2.2: Significance\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8901009559631348, "y": 0.5464439392089844 }, { "x": 0.9037388302385807, "y": 0.5464439392089844 }, { "x": 0.9037388302385807, "y": 0.5546802217140794 }, { "x": 0.8901009559631348, "y": 0.5546802217140794 } ], "category": "paragraph", "id": 316, "content": { "text": "13\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14265400171279907, "y": 0.5654875636100769 }, { "x": 0.37273356318473816, "y": 0.5654875636100769 }, { "x": 0.37273356318473816, "y": 0.5745479315519333 }, { "x": 0.14265400171279907, "y": 0.5745479315519333 } ], "category": "paragraph", "id": 317, "content": { "text": "Section 2.3: Confidence Intervals\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.890353262424469, "y": 0.5662019848823547 }, { "x": 0.9041766254231334, "y": 0.5662019848823547 }, { "x": 0.9041766254231334, "y": 0.574320082552731 }, { "x": 0.890353262424469, "y": 0.574320082552731 } ], "category": "paragraph", "id": 318, "content": { "text": "14\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14257752895355225, "y": 0.5856298208236694 }, { "x": 0.30783621966838837, "y": 0.5856298208236694 }, { "x": 0.30783621966838837, "y": 0.5944648971781135 }, { "x": 0.14257752895355225, "y": 0.5944648971781135 } ], "category": "paragraph", "id": 319, "content": { "text": "Section 2.4: Effect Sizes\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14261743426322937, "y": 0.6053110361099243 }, { "x": 0.34464891254901886, "y": 0.6053110361099243 }, { "x": 0.34464891254901886, "y": 0.6142307687550783 }, { "x": 0.14261743426322937, "y": 0.6142307687550783 } ], "category": "paragraph", "id": 320, "content": { "text": "Section 2.5: Statistical Power\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8899105787277222, "y": 0.5860850811004639 }, { "x": 0.9039262533187866, "y": 0.5860850811004639 }, { "x": 0.9039262533187866, "y": 0.5943492660298944 }, { "x": 0.8899105787277222, "y": 0.5943492660298944 } ], "category": "paragraph", "id": 321, "content": { "text": "16\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.142577663064003, "y": 0.6248943209648132 }, { "x": 0.3860122263431549, "y": 0.6248943209648132 }, { "x": 0.3860122263431549, "y": 0.6363814156502485 }, { "x": 0.142577663064003, "y": 0.6363814156502485 } ], "category": "paragraph", "id": 322, "content": { "text": "Section 2.6: Chapter Two Self-Test\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.891619086265564, "y": 0.6058955788612366 }, { "x": 0.9044966837391257, "y": 0.6058955788612366 }, { "x": 0.9044966837391257, "y": 0.6139329643920064 }, { "x": 0.891619086265564, "y": 0.6139329643920064 } ], "category": "paragraph", "id": 323, "content": { "text": "17\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.142731711268425, "y": 0.6616736650466919 }, { "x": 0.5400971621274948, "y": 0.6616736650466919 }, { "x": 0.5400971621274948, "y": 0.6743425577878952 }, { "x": 0.142731711268425, "y": 0.6743425577878952 } ], "category": "paragraph", "id": 324, "content": { "text": "Part III. Chapter Three - Comparing Two Group Means\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8903208374977112, "y": 0.625525176525116 }, { "x": 0.9037658451125026, "y": 0.625525176525116 }, { "x": 0.9037658451125026, "y": 0.6337820142507553 }, { "x": 0.8903208374977112, "y": 0.6337820142507553 } ], "category": "paragraph", "id": 325, "content": { "text": "18\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1425701528787613, "y": 0.6965510249137878 }, { "x": 0.43194662034511566, "y": 0.6965510249137878 }, { "x": 0.43194662034511566, "y": 0.7083726171404123 }, { "x": 0.1425701528787613, "y": 0.7083726171404123 } ], "category": "paragraph", "id": 326, "content": { "text": "Section 3.1: Looking at Group Differences\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8865026831626892, "y": 0.6970618367195129 }, { "x": 0.9036511983722448, "y": 0.6970618367195129 }, { "x": 0.9036511983722448, "y": 0.7055633431300521 }, { "x": 0.8865026831626892, "y": 0.7055633431300521 } ], "category": "paragraph", "id": 327, "content": { "text": "20\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1427076756954193, "y": 0.7163721919059753 }, { "x": 0.5071283280849457, "y": 0.7163721919059753 }, { "x": 0.5071283280849457, "y": 0.7278513591736555 }, { "x": 0.1427076756954193, "y": 0.7278513591736555 } ], "category": "paragraph", "id": 328, "content": { "text": "Section 3.2: Between Versus Within Groups Analysis\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8904212713241577, "y": 0.7168083190917969 }, { "x": 0.9040802819654346, "y": 0.7168083190917969 }, { "x": 0.9040802819654346, "y": 0.7251442857086658 }, { "x": 0.8904212713241577, "y": 0.7251442857086658 } ], "category": "paragraph", "id": 329, "content": { "text": "21\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14265979826450348, "y": 0.7361627221107483 }, { "x": 0.6677998453378677, "y": 0.7361627221107483 }, { "x": 0.6677998453378677, "y": 0.7480149175971746 }, { "x": 0.14265979826450348, "y": 0.7480149175971746 } ], "category": "paragraph", "id": 330, "content": { "text": "Section 3.3: Independent T-test Assumptions, Interpretation, and Write Up\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.887749433517456, "y": 0.7367931604385376 }, { "x": 0.9041351173073053, "y": 0.7367931604385376 }, { "x": 0.9041351173073053, "y": 0.7450878387317061 }, { "x": 0.887749433517456, "y": 0.7450878387317061 } ], "category": "paragraph", "id": 331, "content": { "text": "22\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14257565140724182, "y": 0.7558371424674988 }, { "x": 0.6225294470787048, "y": 0.7558371424674988 }, { "x": 0.6225294470787048, "y": 0.7676641382277012 }, { "x": 0.14257565140724182, "y": 0.7676641382277012 } ], "category": "paragraph", "id": 332, "content": { "text": "Section 3.4: Paired T-test Assumptions, Interpretation, and Write Up\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14250893890857697, "y": 0.7757766842842102 }, { "x": 0.39723680913448334, "y": 0.7757766842842102 }, { "x": 0.39723680913448334, "y": 0.7871986068785191 }, { "x": 0.14250893890857697, "y": 0.7871986068785191 } ], "category": "paragraph", "id": 333, "content": { "text": "Section 3.5: Chapter Three Self-Test\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8875730037689209, "y": 0.7562849521636963 }, { "x": 0.9040699899196625, "y": 0.7562849521636963 }, { "x": 0.9040699899196625, "y": 0.764871989376843 }, { "x": 0.8875730037689209, "y": 0.764871989376843 } ], "category": "paragraph", "id": 334, "content": { "text": "25\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14259374141693115, "y": 0.8117532730102539 }, { "x": 0.6564947366714478, "y": 0.8117532730102539 }, { "x": 0.6564947366714478, "y": 0.8252149494364858 }, { "x": 0.14259374141693115, "y": 0.8252149494364858 } ], "category": "paragraph", "id": 335, "content": { "text": "Part IV. Chapter Four - Comparing Associations Between Two Variables\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1424114853143692, "y": 0.847580075263977 }, { "x": 0.39560355246067047, "y": 0.847580075263977 }, { "x": 0.39560355246067047, "y": 0.8591874847188592 }, { "x": 0.1424114853143692, "y": 0.8591874847188592 } ], "category": "paragraph", "id": 336, "content": { "text": "Section 4.1: Examining Relationships\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8890397548675537, "y": 0.776170015335083 }, { "x": 0.9044638620689511, "y": 0.776170015335083 }, { "x": 0.9044638620689511, "y": 0.7844214774668217 }, { "x": 0.8890397548675537, "y": 0.7844214774668217 } ], "category": "paragraph", "id": 337, "content": { "text": "27\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8869667649269104, "y": 0.8480122685432434 }, { "x": 0.9039882943034172, "y": 0.8480122685432434 }, { "x": 0.9039882943034172, "y": 0.8565781088545918 }, { "x": 0.8869667649269104, "y": 0.8565781088545918 } ], "category": "paragraph", "id": 338, "content": { "text": "29\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1425440013408661, "y": 0.8670015335083008 }, { "x": 0.6105567216873169, "y": 0.8670015335083008 }, { "x": 0.6105567216873169, "y": 0.8789838282391429 }, { "x": 0.1425440013408661, "y": 0.8789838282391429 } ], "category": "paragraph", "id": 339, "content": { "text": "Section 4.2: Correlation Assumptions, Interpretation, and Write Up\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14251863956451416, "y": 0.8870152831077576 }, { "x": 0.9037268757820129, "y": 0.8870152831077576 }, { "x": 0.9037268757820129, "y": 0.8991214772686362 }, { "x": 0.14251863956451416, "y": 0.8991214772686362 } ], "category": "paragraph", "id": 340, "content": { "text": "Section 4.3: Chapter Four Self-Test\n33\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8903418779373169, "y": 0.867617130279541 }, { "x": 0.9041917510330677, "y": 0.867617130279541 }, { "x": 0.9041917510330677, "y": 0.8762093363329768 }, { "x": 0.8903418779373169, "y": 0.8762093363329768 } ], "category": "paragraph", "id": 341, "content": { "text": "31\n", "html": "", "markdown": "" } } ] }, "01030000000183.pdf": { "elements": [ { "coordinates": [ { "x": 0.07423170655965805, "y": 0.07585133612155914 }, { "x": 0.2782024219632149, "y": 0.07585133612155914 }, { "x": 0.2782024219632149, "y": 0.09335741028189659 }, { "x": 0.07423170655965805, "y": 0.09335741028189659 } ], "category": "header", "id": 185, "content": { "text": "Recommendation Pack: Track Record\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.07380368560552597, "y": 0.12975731492042542 }, { "x": 0.8172289356589317, "y": 0.12975731492042542 }, { "x": 0.8172289356589317, "y": 0.22555992752313614 }, { "x": 0.07380368560552597, "y": 0.22555992752313614 } ], "category": "heading1", "id": 186, "content": { "text": "Recommendation pack shows outstanding performance of 1.7~2.6 times that of\ncompeting models even when using commercial service data\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.06614839285612106, "y": 0.2803330719470978 }, { "x": 0.26077818125486374, "y": 0.2803330719470978 }, { "x": 0.26077818125486374, "y": 0.3577984720468521 }, { "x": 0.06614839285612106, "y": 0.3577984720468521 } ], "category": "paragraph", "id": 187, "content": { "text": "Comparison with Beauty Commerce\nRecommendation Models\nRecommendation model Hit Ratio comparison\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.07247208803892136, "y": 0.4407727122306824 }, { "x": 0.28308146446943283, "y": 0.4407727122306824 }, { "x": 0.28308146446943283, "y": 0.913190484046936 }, { "x": 0.07247208803892136, "y": 0.913190484046936 } ], "category": "figure", "id": 188, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3680463433265686, "y": 0.27970337867736816 }, { "x": 0.5849985331296921, "y": 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"text": "Education Content Platform PoC Case\nComparison of prediction rates of correct/incorrect\nanswers based on personalized questions\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.6980741620063782, "y": 0.5279005169868469 }, { "x": 0.9250346422195435, "y": 0.5279005169868469 }, { "x": 0.9250346422195435, "y": 0.8477827906608582 }, { "x": 0.6980741620063782, "y": 0.8477827906608582 } ], "category": "figure", "id": 192, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.9661781191825867, "y": 0.9481317400932312 }, { "x": 0.9763915240764618, "y": 0.9481317400932312 }, { "x": 0.9763915240764618, "y": 0.9613270545378327 }, { "x": 0.9661781191825867, "y": 0.9613270545378327 } ], "category": "paragraph", "id": 193, "content": { "text": "20\n", "html": "", "markdown": "" } } ] }, "01030000000177.pdf": { "elements": [ { "coordinates": [ { "x": 0.4123590290546417, "y": 0.0749872475862503 }, { "x": 0.5826843678951263, "y": 0.0749872475862503 }, { "x": 0.5826843678951263, "y": 0.2000226229429245 }, { "x": 0.4123590290546417, "y": 0.2000226229429245 } ], "category": "figure", "id": 388, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.32349711656570435, "y": 0.21763460338115692 }, { "x": 0.6470275521278381, "y": 0.21763460338115692 }, { "x": 0.6470275521278381, "y": 0.2720276117324829 }, { "x": 0.32349711656570435, "y": 0.2720276117324829 } ], "category": "paragraph", "id": 389, "content": { "text": "Figure 7.3. You can read more about KSU's\nmarketing approach in Marking Open and\nAffordable Courses (Hare, Kirschner, and Reed\n2020).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11588460206985474, "y": 0.29748979210853577 }, { "x": 0.883339524269104, "y": 0.29748979210853577 }, { "x": 0.883339524269104, "y": 0.390646293759346 }, { "x": 0.11588460206985474, "y": 0.390646293759346 } ], "category": "paragraph", "id": 390, "content": { "text": "For an even simpler graphic, we can look to Kansas State University. KSU's Open/Alternative\nTextbook Initiative developed their OER icon, a book with an \"O\" on the cover, to be recognizable\neven at a small scale. This was done because it would be used as a marking denoting the use of\nopen materials in their course schedule. This graphic is clear, easy to read, and emblematic of the\ninitiative itself, by representing open textbooks with a book icon.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11512382328510284, "y": 0.41840213537216187 }, { "x": 0.3938496559858322, "y": 0.41840213537216187 }, { "x": 0.3938496559858322, "y": 0.43684019334614277 }, { "x": 0.11512382328510284, "y": 0.43684019334614277 } ], "category": "heading1", "id": 391, "content": { "text": "Aligning with Your Identity\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11586440354585648, "y": 0.45778971910476685 }, { "x": 0.8833366110920906, "y": 0.45778971910476685 }, { "x": 0.8833366110920906, "y": 0.5306273773312569 }, { "x": 0.11586440354585648, "y": 0.5306273773312569 } ], "category": "paragraph", "id": 392, "content": { "text": "Like KSU did with their OER icon, your branding should be reflective of your initiative's work\nin some way. Think about your audience and what you want them to feel when they see your\nprogram's marketing on campus. Does your program have a unique name or tagline that\ninfluences the way you present it (e.g., playful, bold, colorful, or innovative)?\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11720891296863556, "y": 0.5487713813781738 }, { "x": 0.3520333170890808, "y": 0.5487713813781738 }, { "x": 0.3520333170890808, "y": 0.7875784039497375 }, { "x": 0.11720891296863556, "y": 0.7875784039497375 } ], "category": "figure", "id": 393, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11427468806505203, "y": 0.7994418740272522 }, { "x": 0.3338775411248207, "y": 0.7994418740272522 }, { "x": 0.3338775411248207, "y": 0.8682132139801979 }, { "x": 0.11427468806505203, "y": 0.8682132139801979 } ], "category": "paragraph", "id": 394, "content": { "text": "Figure 7.4. You can read more\nabout CVCC's marketing\napproach in Marking Open and\nAffordable Courses (Hare,\nKirschner, and Reed 2020).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.37015557289123535, "y": 0.5506425499916077 }, { "x": 0.8829149603843689, "y": 0.5506425499916077 }, { "x": 0.8829149603843689, "y": 0.6630205735564232 }, { "x": 0.37015557289123535, "y": 0.6630205735564232 } ], "category": "paragraph", "id": 395, "content": { "text": "A great example of a program whose name and messaging align\nclearly with their work is Central Virginia Community College\n(CVCC). CVCC uses the tagline \"OpenEd CVCC: Innovation and\nAffordability\" as their program's name and their icon features this\ntheme of innovation through graphics of light bulbs, gears, and\nrepresentations of various disciplines.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.37028685212135315, "y": 0.6834306120872498 }, { "x": 0.8832694590091705, "y": 0.6834306120872498 }, { "x": 0.8832694590091705, "y": 0.855468675494194 }, { "x": 0.37028685212135315, "y": 0.855468675494194 } ], "category": "paragraph", "id": 396, "content": { "text": "CVCC's logo is more complex than the ones we shared in our\n\"simple\" section. However, this isn't a problem in their case. Keep\nin mind that the simplicity of any graphic will depend on where\nand how it's used. CVCC's logo might have more going on than\nKSU's icon, but it is meant to be used at a larger scale, so it can\naccommodate this complexity. If your logo will be used in print\nmaterials or as a smaller icon, that's when you'll want to focus on\nsimpler designs. For graphics that will be displayed more\nprominently, though, a larger graphic works fine.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11560807377099991, "y": 0.941657304763794 }, { "x": 0.13168173842132092, "y": 0.941657304763794 }, { "x": 0.13168173842132092, "y": 0.9504494117572904 }, { "x": 0.11560807377099991, "y": 0.9504494117572904 } ], "category": "paragraph", "id": 397, "content": { "text": "90\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1562475860118866, "y": 0.9416370391845703 }, { "x": 0.33334261178970337, "y": 0.9416370391845703 }, { "x": 0.33334261178970337, "y": 0.9503417629748583 }, { "x": 0.1562475860118866, "y": 0.9503417629748583 } ], "category": "footer", "id": 398, "content": { "text": "PROGRAM MANAGEMENT\n", "html": "", "markdown": "" } } ] }, "01030000000197.pdf": { "elements": [ { "coordinates": [ { "x": 0.11882376670837402, "y": 0.46336331963539124 }, { "x": 0.4834234118461609, "y": 0.46336331963539124 }, { "x": 0.4834234118461609, "y": 0.49574102088809013 }, { "x": 0.11882376670837402, "y": 0.49574102088809013 } ], "category": "table", "id": 262, "content": { "text": "", "html": "
ARCHellaSwagMMLUTruthfulQAWinograndeGSM8K
0.06N/A0.150.28N/A0.70
", "markdown": "" } }, { "coordinates": [ { "x": 0.11911618709564209, "y": 0.0863911584019661 }, { "x": 0.3539939373731613, "y": 0.0863911584019661 }, { "x": 0.3539939373731613, "y": 0.09790120180696249 }, { "x": 0.11911618709564209, "y": 0.09790120180696249 } ], "category": "heading1", "id": 276, "content": { "text": "C Additional Information\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11767514795064926, "y": 0.1120196208357811 }, { "x": 0.4868036136031151, "y": 0.1120196208357811 }, { "x": 0.4868036136031151, "y": 0.1412830390036106 }, { "x": 0.11767514795064926, "y": 0.1412830390036106 } ], "category": "paragraph", "id": 277, "content": { "text": "We present additional information for the sake of\nspace in the main paper.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11814684420824051, "y": 0.15286995470523834 }, { "x": 0.4851704016327858, "y": 0.15286995470523834 }, { "x": 0.4851704016327858, "y": 0.19784808158874512 }, { "x": 0.11814684420824051, "y": 0.19784808158874512 } ], "category": "paragraph", "id": 278, "content": { "text": "Filtered task names. We present task names\nwe use to filter FLAN dervied datasets such as\nOpenOrca in Table 8.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.13241088390350342, "y": 0.2181880623102188 }, { "x": 0.2702052444219589, "y": 0.2181880623102188 }, { "x": 0.2702052444219589, "y": 0.22789691481739283 }, { "x": 0.13241088390350342, "y": 0.22789691481739283 } ], "category": "paragraph", "id": 279, "content": { "text": "Filtered Task Name\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12530842423439026, "y": 0.24007773399353027 }, { "x": 0.39873042702674866, "y": 0.24007773399353027 }, { "x": 0.39873042702674866, "y": 0.3906584233045578 }, { "x": 0.12530842423439026, "y": 0.3906584233045578 } ], "category": "paragraph", "id": 280, "content": { "text": "task228_arc_answer_generation_easy\nai2_arcARCChallenge:1.0.0\nai2_arcARCEasy:1.0.0\ntask229_arc_answer_generation_hard\nhellaswag:1.1.0\ntask1389_hellaswag_completion\ncot_gsm8k\ncot_gsm8k_ii\ndrop:2.0.0\nwinogrande:1.1.0\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11758025735616684, "y": 0.4081496298313141 }, { "x": 0.4852310046553612, "y": 0.4081496298313141 }, { "x": 0.4852310046553612, "y": 0.4341414552181959 }, { "x": 0.11758025735616684, "y": 0.4341414552181959 } ], "category": "paragraph", "id": 281, "content": { "text": "Table 8: Task names that we use to filter data for FLAN\nderived datasets such as OpenOrca.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11741138249635696, "y": 0.5086327791213989 }, { "x": 0.4879551902413368, "y": 0.5086327791213989 }, { "x": 0.4879551902413368, "y": 0.603509210050106 }, { "x": 0.11741138249635696, "y": 0.603509210050106 } ], "category": "paragraph", "id": 283, "content": { "text": "Table 9: Data contamination test results for SOLAR\n10.7B-Instruct. We show 'result < 0.1, %' values where\na value higher than 0.9 indicates high probability of data\ncontamination. HellaSwag and Winogrande datasets are\nnot currently supported. We set SOLAR 10.7B as our\nreference model when performing the data contamina-\ntion tests.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11782839894294739, "y": 0.6333669424057007 }, { "x": 0.4883232116699219, "y": 0.6333669424057007 }, { "x": 0.4883232116699219, "y": 0.8072183728218079 }, { "x": 0.11782839894294739, "y": 0.8072183728218079 } ], "category": "paragraph", "id": 284, "content": { "text": "Results on data contamination. To show the in-\ntegrity of SOLAR 10.7B-Instruct, we also report\nthe data contamination test (Shi et al., 2023) results\nin Table. 9. All four tested benchmark datasets\nyield results well below the contamination thresh-\nold, affirming the absence of data contamination\nin our model. One interesting point is that the\nvalue for GSM8K is noticeably higher than for\nother datasets, even without contamination. One\npotential reason for this is the stronger data similar-\nity in math-related instruction datasets.\n", "html": "", "markdown": "" } } ] }, "01030000000083.pdf": { "elements": [ { "coordinates": [ { "x": 0.16521655023097992, "y": 0.17123080790042877 }, { "x": 0.8331207484006882, "y": 0.17123080790042877 }, { "x": 0.8331207484006882, "y": 0.41010162234306335 }, { "x": 0.16521655023097992, "y": 0.41010162234306335 } ], "category": "table", "id": 274, "content": { "text": "", "html": "
CategoryNumber of clauses in Union lawsIn percentNumber of clauses in State lawsIn percent
Commercial52910.1%8173.9%
Environment, Health and Safety83415.9%3451.7%
Finance & Taxation410.8%8884.2%
General751.4%3601.7%
Industry Specific297956.9%12005.7%
Labour53410.2%1728582.7%
Secretarial2474.7%00.0%
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SmallMediumLarge
Total Applicable Compliances6693,1095,796
Compliances with imprisonment4612,1724,085
Percentage of imprisonment clauses69%70%70%
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SmallMediumLarge
Less than 3 months2582185
3 months to less than 1 year1876991,220
1 year to less than 3 years1781,0701,964
3 years to less than 5 years59245505
5 years to 10 years1276211
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Introduction\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1155875101685524, "y": 0.24805103242397308 }, { "x": 0.882078506052494, "y": 0.24805103242397308 }, { "x": 0.882078506052494, "y": 0.31494706124067307 }, { "x": 0.1155875101685524, "y": 0.31494706124067307 } ], "category": "paragraph", "id": 443, "content": { "text": "This report, prepared by the research staff of the Law Library of Congress, surveys 39\njurisdictions regarding whether, and if SO how, they restrict ownership of land by foreigners.1\nThe jurisdictions surveyed were among those with the highest gross domestic product according\nto 2021 World Bank data, selected to ensure broadly representative coverage.2\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11714499443769455, "y": 0.334619402885437 }, { "x": 0.8820008561015129, "y": 0.334619402885437 }, { "x": 0.8820008561015129, "y": 0.38361330330371857 }, { "x": 0.11714499443769455, "y": 0.38361330330371857 } ], "category": "paragraph", "id": 444, "content": { "text": "We identified 10 countries that do not restrict land ownership by foreigners: Belgium, France,\nGermany, Ireland, Japan, the Netherlands, Norway, Portugal, Sweden, and the\nUnited Kingdom.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1169506162405014, "y": 0.40341657400131226 }, { "x": 0.8823191970586777, "y": 0.40341657400131226 }, { "x": 0.8823191970586777, "y": 0.45284320414066315 }, { "x": 0.1169506162405014, "y": 0.45284320414066315 } ], "category": "paragraph", "id": 445, "content": { "text": "We found that the following countries do not permit foreign ownership of land, although\nexceptions may apply in some cases or other rights to land may be acquired: China, Indonesia,\nNigeria, Philippines, and Thailand.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1170651987195015, "y": 0.4727959930896759 }, { "x": 0.8826596215367317, "y": 0.4727959930896759 }, { "x": 0.8826596215367317, "y": 0.5567877814173698 }, { "x": 0.1170651987195015, "y": 0.5567877814173698 } ], "category": "paragraph", "id": 446, "content": { "text": "Among the other jurisdictions surveyed, some have restrictions that apply to different types of\nland, including agricultural, residential, and commercial land. Other types of restriction are based\non the location of the land, such as near the border or military establishments. Some jurisdictions\nrestrict particular categories of foreigners from land ownership. Some require special permission\nor approval for foreigners before they can acquire land.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11575541645288467, "y": 0.576055645942688 }, { "x": 0.8818413391709328, "y": 0.576055645942688 }, { "x": 0.8818413391709328, "y": 0.6597779169678688 }, { "x": 0.11575541645288467, "y": 0.6597779169678688 } ], "category": "paragraph", "id": 447, "content": { "text": "Ownership of agricultural land by foreigners is restricted by some provinces of Canada, and by\nEgypt, India (restricted for diplomatic personnel, nonresidents of Indian origin and nonresident\ncitizens without registration), Iran, Poland (permit required), and Russia. Argentina, Brazil, and\nTurkey restrict ownership of rural or local land to a percentage of the total land of the local\njurisdiction.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11712809652090073, "y": 0.6797512769699097 }, { "x": 0.8819042667746544, "y": 0.6797512769699097 }, { "x": 0.8819042667746544, "y": 0.7288647852838039 }, { "x": 0.11712809652090073, "y": 0.7288647852838039 } ], "category": "paragraph", "id": 448, "content": { "text": "Article XVII of the General Agreement on Trade in Services (GATS) obligates members to provide\nnational treatment to other members, i.e., \"treatment no less favourable than that it accords to its\nown.\"3 If land ownership restrictions result in less favorable treatment of foreigners, GATS\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11678950488567352, "y": 0.7541813254356384 }, { "x": 0.8721656054258347, "y": 0.7541813254356384 }, { "x": 0.8721656054258347, "y": 0.826521746814251 }, { "x": 0.11678950488567352, "y": 0.826521746814251 } ], "category": "paragraph", "id": 449, "content": { "text": "1\nThe surveyed jurisdictions are Argentina, Australia, Austria, Belgium, Brazil, Canada, Chile, China, Egypt,\nFinland, Germany, Greece, India, Indonesia, Iran, Ireland, Israel, Italy, Japan, Mexico, the Netherlands,\nNew Zealand, Nigeria, Norway, Philippines, Poland, Portugal, Russia, Saudi Arabia, South Africa, South\nKorea, Spain, Sweden, Switzerland, Taiwan, Thailand, Turkey, United Arab Emirates, and the United\nKingdom.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1166691854596138, "y": 0.8360605835914612 }, { "x": 0.795839436352253, "y": 0.8360605835914612 }, { "x": 0.795839436352253, "y": 0.8491602363064885 }, { "x": 0.1166691854596138, "y": 0.8491602363064885 } ], "category": "footer", "id": 450, "content": { "text": "2 World Bank Databank, Gross Domestic Product 2021 (Jan. 15, 2023), https://perma.cc/GP7Y-Z8K8.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11481144279241562, "y": 0.8586622476577759 }, { "x": 0.8806759342551231, "y": 0.8586622476577759 }, { "x": 0.8806759342551231, "y": 0.8991063423454762 }, { "x": 0.11481144279241562, "y": 0.8991063423454762 } ], "category": "paragraph", "id": 451, "content": { "text": "3 General Agreement on Trade in Services (GATS), Apr. 15, 1994, Marrakesh Agreement Establishing the World\nTrade Organization, Annex 1B, art. XVII, 1869 U.N.T.S. 183, 33 I.L.M. 1167 (1994), https://perma.cc/Z89Y-\nSEVS.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11686422675848007, "y": 0.94076007604599 }, { "x": 0.3390442058444023, "y": 0.94076007604599 }, { "x": 0.3390442058444023, "y": 0.9544305512681603 }, { "x": 0.11686422675848007, "y": 0.9544305512681603 } ], "category": "footer", "id": 452, "content": { "text": "The Law Library of Congress\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8655149936676025, "y": 0.9413285255432129 }, { "x": 0.8732451242394745, "y": 0.9413285255432129 }, { "x": 0.8732451242394745, "y": 0.9512153957039118 }, { "x": 0.8655149936676025, "y": 0.9512153957039118 } ], "category": "paragraph", "id": 453, "content": { "text": "1\n", "html": "", "markdown": "" } } ] }, "01030000000141.pdf": { "elements": [ { "coordinates": [ { "x": 0.5202288627624512, "y": 0.3045933246612549 }, { "x": 0.9417901933193207, "y": 0.3045933246612549 }, { "x": 0.9417901933193207, "y": 0.9367848634719849 }, { "x": 0.5202288627624512, "y": 0.9367848634719849 } ], "category": "table", "id": 439, "content": { "text": "", "html": "
6 Copyright gives a lot of protection, but it also limitations. Not everything gets copyright Facts and ideas are not protected by copyright, are US Government documents, like NASA reports by federal agencies. has protection. neither photos and
7 Another limitation of copyright is \"fair use,\" which allows us to copy and re-use copyrighted work without the artist's permission in certain, limited ways that are still fair to the creator.
When you re-use portions of someone else's for a school project-like using images or songs a presentation in class-that's a fair use situation. You don't need the author's permission. work for
9 Copyright protection doesn't last forever. Eventually it expires, and the creative work falls into the \"public domain.\" Works in the public :- domain are free to re-use and share however you want.
10 Some creators are happy to share their creative work. They use a licensing system cc for sharing called Creative Commons. You can find millions of CC work that are free to share or re-use.
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1We're all both consumers and creators of creative work. As consumers, we watch movies, listen music, read books, and more! As creators, we take photos, write songs, make videos, etc.to
2Copyright protects creative work, so people generally copy or share or perform other people's work without permission.can't
3Copyright comes from the Constitution. Its to promote more creativity. The idea is that each of us decide what happens to our own will encourage us to keep creating. purpose is letting creations
4All creative work is protected by copyright as it's written down or recorded or saved-and not work by professional artists or big studios. protects all of us-our photos on Instagram and everything we write or create. soon as just Copyright
5If you copy or share other people's creative works without permission, that's called copyright infringement. Examples: Downloading music, movies, ebooks, or from illegal sources that operate without permission. Uploading your collection of music, movies, ebooks, or games for your friends to copy. Copyright infringement is illegal and carries serious penalties. games artists'
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0.9716865457594395 } ], "category": "footer", "id": 520, "content": { "text": "CopyrightandCreativity.org\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8740963339805603, "y": 0.9195823669433594 }, { "x": 0.9683796539902687, "y": 0.9195823669433594 }, { "x": 0.9683796539902687, "y": 0.9811471663415432 }, { "x": 0.8740963339805603, "y": 0.9811471663415432 } ], "category": "figure", "id": 521, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5304672122001648, "y": 0.27089083194732666 }, { "x": 0.9422069787979126, "y": 0.27089083194732666 }, { "x": 0.9422069787979126, "y": 0.8994840979576111 }, { "x": 0.5304672122001648, "y": 0.8994840979576111 } ], "category": "figure", "id": 522, "content": { "text": "", "html": "", "markdown": "" } } ] }, "01030000000116.pdf": { "elements": [ { "coordinates": [ { "x": 0.11819107085466385, "y": 0.6836516857147217 }, { "x": 0.843207485973835, "y": 0.6836516857147217 }, { "x": 0.843207485973835, "y": 0.7890600711107254 }, { "x": 0.11819107085466385, "y": 0.7890600711107254 } ], "category": "table", "id": 171, "content": { "text": "", "html": "
SaccharometerDI WaterGlucose SolutionYeast Suspension
1* *8 ml*6 ml0 ml
2*12 ml0 ml*2 ml
3*6 ml* 6 ml*2 ml
4*2 ml*6 ml*6 ml
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"content": { "text": "Transfer pipettes\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14674870669841766, "y": 0.11134736984968185 }, { "x": 0.28683456778526306, "y": 0.11134736984968185 }, { "x": 0.28683456778526306, "y": 0.1225217031314969 }, { "x": 0.14674870669841766, "y": 0.1225217031314969 } ], "category": "paragraph", "id": 198, "content": { "text": "Test tube rack\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14707399904727936, "y": 0.12840792536735535 }, { "x": 0.7365061789751053, "y": 0.12840792536735535 }, { "x": 0.7365061789751053, "y": 0.14328087121248245 }, { "x": 0.14707399904727936, "y": 0.14328087121248245 } ], "category": "paragraph", "id": 199, "content": { "text": "4 large (20 ml) test tubes or small Erlenmeyer flasks for larger volumes\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14696796238422394, "y": 0.14604125916957855 }, { "x": 0.31328238546848297, "y": 0.14604125916957855 }, { "x": 0.31328238546848297, "y": 0.16073195170611143 }, { "x": 0.14696796238422394, "y": 0.16073195170611143 } ], "category": "paragraph", "id": 200, "content": { "text": "Large plastic tray\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1469697654247284, "y": 0.16350576281547546 }, { "x": 0.3696106970310211, "y": 0.16350576281547546 }, { "x": 0.3696106970310211, "y": 0.17830715514719486 }, { "x": 0.1469697654247284, "y": 0.17830715514719486 } ], "category": "paragraph", "id": 201, "content": { "text": "Masking tape or lab tape\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14686369895935059, "y": 0.18087910115718842 }, { "x": 0.39169199764728546, "y": 0.18087910115718842 }, { "x": 0.39169199764728546, "y": 0.19553384836763144 }, { "x": 0.14686369895935059, "y": 0.19553384836763144 } ], "category": "paragraph", "id": 202, "content": { "text": "Large weigh boat (4/group)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.147081196308136, "y": 0.19835126399993896 }, { "x": 0.27019549161195755, "y": 0.19835126399993896 }, { "x": 0.27019549161195755, "y": 0.20959347113966942 }, { "x": 0.147081196308136, "y": 0.20959347113966942 } ], "category": "paragraph", "id": 203, "content": { "text": "Metric ruler\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14708298444747925, "y": 0.21565614640712738 }, { "x": 0.3211396634578705, "y": 0.21565614640712738 }, { "x": 0.3211396634578705, "y": 0.22703602258116007 }, { "x": 0.14708298444747925, "y": 0.22703602258116007 } ], "category": "paragraph", "id": 204, "content": { "text": "Electronic balance\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14719264209270477, "y": 0.2333126813173294 }, { "x": 0.2348977029323578, "y": 0.2333126813173294 }, { "x": 0.2348977029323578, "y": 0.24796593748033047 }, { "x": 0.14719264209270477, "y": 0.24796593748033047 } ], "category": "paragraph", "id": 205, "content": { "text": "Spatula\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14751799404621124, "y": 0.25066715478897095 }, { "x": 0.27728162705898285, "y": 0.25066715478897095 }, { "x": 0.27728162705898285, "y": 0.2654348909854889 }, { "x": 0.14751799404621124, "y": 0.2654348909854889 } ], "category": "paragraph", "id": 206, "content": { "text": "Weigh paper\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14784333109855652, "y": 0.26790985465049744 }, { "x": 0.40017828345298767, "y": 0.26790985465049744 }, { "x": 0.40017828345298767, "y": 0.282655986957252 }, { "x": 0.14784333109855652, "y": 0.282655986957252 } ], "category": "paragraph", "id": 207, "content": { "text": "Red food coloring (optional)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11667706817388535, "y": 0.30076897144317627 }, { "x": 0.39782797545194626, "y": 0.30076897144317627 }, { "x": 0.39782797545194626, "y": 0.5883913338184357 }, { "x": 0.11667706817388535, "y": 0.5883913338184357 } ], "category": "figure", "id": 208, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3966677188873291, "y": 0.5766726136207581 }, { "x": 0.5890304297208786, "y": 0.5766726136207581 }, { "x": 0.5890304297208786, "y": 0.5915215536952019 }, { "x": 0.3966677188873291, "y": 0.5915215536952019 } ], "category": "paragraph", "id": 209, "content": { "text": "Figure 3. Saccharometer\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1763107031583786, "y": 0.6499447822570801 }, { "x": 0.8229445070028305, "y": 0.6499447822570801 }, { "x": 0.8229445070028305, "y": 0.6786456890404224 }, { "x": 0.1763107031583786, "y": 0.6786456890404224 } ], "category": "paragraph", "id": 210, "content": { "text": "Table 2. Contents of Saccharometers when testing fermentation with various yeast\nconcentrations.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11743327230215073, "y": 0.8114764094352722 }, { "x": 0.8610574826598167, "y": 0.8114764094352722 }, { "x": 0.8610574826598167, "y": 0.8402383346110582 }, { "x": 0.11743327230215073, "y": 0.8402383346110582 } ], "category": "paragraph", "id": 212, "content": { "text": "*Double these amounts if using saccharometers that have a 15-cm vertical tube. See table\nbelow\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1204327642917633, "y": 0.8666552901268005 }, { "x": 0.628404825925827, "y": 0.8666552901268005 }, { "x": 0.628404825925827, "y": 0.8814512751996517 }, { "x": 0.1204327642917633, "y": 0.8814512751996517 } ], "category": "paragraph", "id": 213, "content": { "text": "Saccharometer DI Water Glucose Solution Yeast Suspension\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12282701581716537, "y": 0.8879609107971191 }, { "x": 0.12850948004052043, "y": 0.8879609107971191 }, { "x": 0.12850948004052043, "y": 0.8989076381549239 }, { "x": 0.12282701581716537, "y": 0.8989076381549239 } ], "category": "paragraph", "id": 214, "content": { "text": "1\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.25386908650398254, "y": 0.8879226446151733 }, { "x": 0.29703573510050774, "y": 0.8879226446151733 }, { "x": 0.29703573510050774, "y": 0.8991281324997544 }, { "x": 0.25386908650398254, "y": 0.8991281324997544 } ], "category": "paragraph", "id": 215, "content": { "text": "16 ml\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.33844250440597534, "y": 0.8878241181373596 }, { "x": 0.3820497654378414, "y": 0.8878241181373596 }, { "x": 0.3820497654378414, "y": 0.8990607755258679 }, { "x": 0.33844250440597534, "y": 0.8990607755258679 } ], "category": "paragraph", "id": 216, "content": { "text": "12 ml\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.48318952322006226, "y": 0.8878475427627563 }, { "x": 0.5183926671743393, "y": 0.8878475427627563 }, { "x": 0.5183926671743393, "y": 0.8991042925044894 }, { "x": 0.48318952322006226, "y": 0.8991042925044894 } ], "category": "paragraph", "id": 217, "content": { "text": "0 ml\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.4961221218109131, "y": 0.9732478260993958 }, { "x": 0.5104274563491344, "y": 0.9732478260993958 }, { "x": 0.5104274563491344, "y": 0.9845490828156471 }, { "x": 0.4961221218109131, "y": 0.9845490828156471 } ], "category": "paragraph", "id": 218, "content": { "text": "58\n", "html": "", "markdown": "" } } ] }, "01030000000127.pdf": { "elements": [ { "coordinates": [ { "x": 0.08460714668035507, "y": 0.06674564629793167 }, { "x": 0.9120332226157188, "y": 0.06674564629793167 }, { "x": 0.9120332226157188, "y": 0.27054326981306076 }, { "x": 0.08460714668035507, "y": 0.27054326981306076 } ], "category": "table", "id": 428, "content": { "text": "", "html": "
Year3-Year5-Year7-Year
133.0%20.00%14.29%
244.45%32.00%24.49%
314.81%19.20%17.49%
47.41%11.52%12.49%
511.52%8.93%
65.76%8.93%
78.93%
84.46%
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YearRecovery RateUnadjusted BasisDepreciation ExpenseAccumulated Depreciation
1.1667$100,000$16,670$16,670
2.3333$100,000$33,330$50,000
3.3333$100,000$33,330$88,330
4.1667$100,000$16,670$100,000
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YearRecovery RateUnadjusted BasisDepreciation ExpenseAccumulated Depreciation
1.3333$100,000$33,333$33,333
2.4445$100,000$44,450$77,780
3.1481$100,000$14,810$92,950
4.741$100,000$7,410$100,000
", "markdown": "" } }, { "coordinates": [ { "x": 0.08731399476528168, "y": 0.2927457094192505 }, { "x": 0.9113842695951462, "y": 0.2927457094192505 }, { "x": 0.9113842695951462, "y": 0.34415704384446144 }, { "x": 0.08731399476528168, "y": 0.34415704384446144 } ], "category": "paragraph", "id": 521, "content": { "text": "Suppose your business just purchased a $100,000 asset that has a 3-year useful life, and falls into\n3-year class of assets. Using the SL method, the depreciation expense each year for the next 3 years\nwould be:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08750629425048828, "y": 0.5001240968704224 }, { "x": 0.9114437699317932, "y": 0.5001240968704224 }, { "x": 0.9114437699317932, "y": 0.5531261004507542 }, { "x": 0.08750629425048828, "y": 0.5531261004507542 } ], "category": "paragraph", "id": 523, "content": { "text": "Note that the book value or basis of the asset (acquisition cost - accumulated depreciation) would\nbe $0 after it has been fully depreciated at the end of 4 years. Because of the half-year convention, it\ntakes 4 years to depreciate the asset, even though it falls into the 3-year classification.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0887431800365448, "y": 0.5716612339019775 }, { "x": 0.8326385915279388, "y": 0.5716612339019775 }, { "x": 0.8326385915279388, "y": 0.5853908862918615 }, { "x": 0.0887431800365448, "y": 0.5853908862918615 } ], "category": "paragraph", "id": 524, "content": { "text": "Depreciation expense for the same asset using the MACRS method would be calculated as:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0868089571595192, "y": 0.738755464553833 }, { "x": 0.9112683907151222, "y": 0.738755464553833 }, { "x": 0.9112683907151222, "y": 0.7922307625412941 }, { "x": 0.0868089571595192, "y": 0.7922307625412941 } ], "category": "paragraph", "id": 526, "content": { "text": "Note again that the depreciation expense using MACRS is higher in the early years and lower in later\nyears than with the SL method and that the book value after 4 years is again zero. Businesses often\nuse MACRS for tax purposes and SL for profit reporting. Can you think of any reasons why?\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08717962354421616, "y": 0.8095973134040833 }, { "x": 0.9124298319220543, "y": 0.8095973134040833 }, { "x": 0.9124298319220543, "y": 0.9028567001223564 }, { "x": 0.08717962354421616, "y": 0.9028567001223564 } ], "category": "paragraph", "id": 527, "content": { "text": "Some businesses that invest small amounts in capital assets are allowed to deduct up to $1,000,000\nof the cost of acquired depreciable property as a current expenditure instead of a capital expenditure.\nThis is known as direct expensing, and is available only to businesses that don't make large capital\npurchases each year. The allowable expensing amount is reduced by one dollar for each dollar of\ncapital investment expenditure over $2,500,000 during the year. Other restrictions also apply.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11117663234472275, "y": 0.9512039422988892 }, { "x": 0.1139394985511899, "y": 0.9512039422988892 }, { "x": 0.1139394985511899, "y": 0.9611711166799068 }, { "x": 0.11117663234472275, "y": 0.9611711166799068 } ], "category": "paragraph", "id": 528, "content": { "text": "I\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08778180927038193, "y": 0.9514509439468384 }, { "x": 0.10403854213654995, "y": 0.9514509439468384 }, { "x": 0.10403854213654995, "y": 0.9595064045861363 }, { "x": 0.08778180927038193, "y": 0.9595064045861363 } ], "category": "paragraph", "id": 529, "content": { "text": "42\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12145835906267166, "y": 0.9510723948478699 }, { "x": 0.31226230412721634, "y": 0.9510723948478699 }, { "x": 0.31226230412721634, "y": 0.9613638082519174 }, { "x": 0.12145835906267166, "y": 0.9613638082519174 } ], "category": "footer", "id": 530, "content": { "text": "Ch. 3. The Federal Tax System\n", "html": "", "markdown": "" } } ] }, "01030000000054.pdf": { "elements": [ { "coordinates": [ { "x": 0.1427210420370102, "y": 0.10306989401578903 }, { "x": 0.29596269130706787, "y": 0.10306989401578903 }, { "x": 0.29596269130706787, "y": 0.1252161767333746 }, { "x": 0.1427210420370102, "y": 0.1252161767333746 } ], "category": "paragraph", "id": 368, "content": { "text": "EFB = empty fruit bunch.\nSource: Murdiyatmo (2021).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14262352883815765, "y": 0.13010677695274353 }, { "x": 0.8102494329214096, "y": 0.13010677695274353 }, { "x": 0.8102494329214096, "y": 0.25332964211702347 }, { "x": 0.14262352883815765, "y": 0.25332964211702347 } ], "category": "paragraph", "id": 369, "content": { "text": "However, the main obstacle with producing second-generation bioethanol is the cost of\nenzymes. Murdiyatmo (2021) stated that, at the pilot scale, the cost of enzymes is very\nhigh, i.e. Rp18,000 per litre of ethanol produced. Some studies provided the cost of\nenzymes in the US. NREL (2011), for instance, estimated that the cost of enzymes to\nproduce second-generation bioethanol in the US was equivalent to around $0.34 per\ngallon or Rp1,5292 per litre of ethanol produced, i.e. less than one-tenth of the cost of\nenzymes in Indonesia.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1423335075378418, "y": 0.26576268672943115 }, { "x": 0.8099372982978821, "y": 0.26576268672943115 }, { "x": 0.8099372982978821, "y": 0.40480567514896393 }, { "x": 0.1423335075378418, "y": 0.40480567514896393 } ], "category": "paragraph", "id": 370, "content": { "text": "In the next sub-sections, we analyse biodiesel and bioethanol introduction in Indonesia.\nIn each sub-section, we first discuss the current supply and demand of the biofuels and\nthe related conventional transport fuel. Second, we estimate the conventional transport\nfuel, i.e. gasoline and diesel fuel demand in road transportation during the period of\n2020-50. Third, we estimate the volume of pure biofuel (fatty acid methyl ester\n[FAME]/biodiesel and bioethanol) needs in scenarios, and in the amount of feedstock, i.e.\nCPO in biodiesel and molasses in bioethanol needed to meet the demand required in each\nscenario.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14283373951911926, "y": 0.4201303720474243 }, { "x": 0.37393468618392944, "y": 0.4201303720474243 }, { "x": 0.37393468618392944, "y": 0.42988848593086004 }, { "x": 0.14283373951911926, "y": 0.42988848593086004 } ], "category": "heading1", "id": 371, "content": { "text": "2.1.\nDiesel and biodiesel use\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14203330874443054, "y": 0.44481161236763 }, { "x": 0.8094562590122223, "y": 0.44481161236763 }, { "x": 0.8094562590122223, "y": 0.6046851724386215 }, { "x": 0.14203330874443054, "y": 0.6046851724386215 } ], "category": "paragraph", "id": 372, "content": { "text": "The consumption of diesel fuel in Indonesia, used primarily for road freight transport,\nfluctuated between 2010 and 2019 as it correlated with the economic condition (Table\n2.8). Diesel consumption in the industry sector decreased significantly, around 10% per\nyear between 2010 and 2019, resulting from the shift to another energy type. During the\nsame period, with some fluctuations, diesel production increased at 3.6% annual growth\nrate, while imports were cut by half from nearly 13 billion litres in 2010 to nearly 6.5 billion\nlitres in 2018. The biodiesel blending rate increased from only 1% in 2010 to nearly 20%\nin 2019, representing a growing level of mandatory biodiesel programmes. Apparently,\ndiesel imports dropped with the increase of the biodiesel (B100) blending rate.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14242596924304962, "y": 0.8716145157814026 }, { "x": 0.7767458707094193, "y": 0.8716145157814026 }, { "x": 0.7767458707094193, "y": 0.8985945284366608 }, { "x": 0.14242596924304962, "y": 0.8985945284366608 } ], "category": "footer", "id": 373, "content": { "text": "2 Assuming average inflation rate of 2% between 2011 and 2021 and an exchange rate of $1 =\nRp14,131.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.46790531277656555, "y": 0.9456213116645813 }, { "x": 0.48422905802726746, "y": 0.9456213116645813 }, { "x": 0.48422905802726746, "y": 0.9541947161778808 }, { "x": 0.46790531277656555, "y": 0.9541947161778808 } ], "category": "paragraph", "id": 374, "content": { "text": "11\n", "html": "", "markdown": "" } } ] }, "01030000000045.pdf": { "elements": [ { "coordinates": [ { "x": 0.12431038171052933, "y": 0.2571081519126892 }, { "x": 0.8920455053448677, "y": 0.2571081519126892 }, { "x": 0.8920455053448677, "y": 0.6041413843631744 }, { "x": 0.12431038171052933, "y": 0.6041413843631744 } ], "category": "table", "id": 142, "content": { "text": "", "html": "
No.Name of organizationNumber of accredited observers
1Union of Youth Federations of Cambodia (UYFC)17,266
2Cambodian Women for Peace and Development9,835
3Association of Democratic Students of Cambodia711
4Association of Intellectual and Youth Volunteer46
5Our Friends Association27
6COMFREL26
7Traditional and Modern Mental Health Organization15
Total27,926
", "markdown": "" } }, { "coordinates": [ { "x": 0.6706203818321228, "y": 0.05926426500082016 }, { "x": 0.8886256366968155, "y": 0.05926426500082016 }, { "x": 0.8886256366968155, "y": 0.07343620341271162 }, { "x": 0.6706203818321228, "y": 0.07343620341271162 } ], "category": "header", "id": 171, "content": { "text": "Civil Society Engagement\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12819315493106842, "y": 0.09519661217927933 }, { "x": 0.8881026655435562, "y": 0.09519661217927933 }, { "x": 0.8881026655435562, "y": 0.15707193687558174 }, { "x": 0.12819315493106842, "y": 0.15707193687558174 } ], "category": "paragraph", "id": 172, "content": { "text": "election integrity. The registration of local election observers runs until\n25 May, and the NEC is still reviewing the application of nearly 5,000\nobservers.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1275509148836136, "y": 0.19398696720600128 }, { "x": 0.8339229971170425, "y": 0.19398696720600128 }, { "x": 0.8339229971170425, "y": 0.2311299964785576 }, { "x": 0.1275509148836136, "y": 0.2311299964785576 } ], "category": "paragraph", "id": 173, "content": { "text": "Table: The number of accredited observers as of 28 April\n2022 15\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12902352213859558, "y": 0.9010134339332581 }, { "x": 0.44274893403053284, "y": 0.9010134339332581 }, { "x": 0.44274893403053284, "y": 0.9115627594292164 }, { "x": 0.12902352213859558, "y": 0.9115627594292164 } ], "category": "footer", "id": 175, "content": { "text": "15 https://www.nec.gov.kh/khmer/content/5524\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.86763596534729, "y": 0.9287630915641785 }, { "x": 0.8876783773303032, "y": 0.9287630915641785 }, { "x": 0.8876783773303032, "y": 0.9398262789472938 }, { "x": 0.86763596534729, "y": 0.9398262789472938 } ], "category": "paragraph", "id": 176, "content": { "text": "17\n", "html": "", "markdown": "" } } ] }, "01030000000081.pdf": { "elements": [ { "coordinates": [ { "x": 0.16657209396362305, "y": 0.17201346158981323 }, { "x": 0.8342849612236023, "y": 0.17201346158981323 }, { "x": 0.8342849612236023, "y": 0.31368255615234375 }, { "x": 0.16657209396362305, "y": 0.31368255615234375 } ], "category": "table", "id": 206, "content": { "text": "", "html": "
LawUnion/State ruleImprisonment clauses
Arms Act, 1959 and Arms Rules 2016Union152
Food Safety & Standards Act, 2006 & Food Safety and Standards (Licensing and Registration of Food Businesses) Regulations, 2011Union123
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Imprisonment termNumber of clausesNumber of laws
Less than 3 months15035
3 months to less than 1 year19914
1 year to less than 3 years32616
3 years to less than 5 years35722
5 years to less than 10 years14727
More than 10 years00
", "markdown": "" } }, { "coordinates": [ { "x": 0.16530044376850128, "y": 0.042279526591300964 }, { "x": 0.3854035288095474, "y": 0.042279526591300964 }, { "x": 0.3854035288095474, "y": 0.054599395021796227 }, { "x": 0.16530044376850128, "y": 0.054599395021796227 } ], "category": "header", "id": 243, "content": { "text": "Jailed for Doing Business\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16538971662521362, "y": 0.11673302948474884 }, { "x": 0.7748420238494873, "y": 0.11673302948474884 }, { "x": 0.7748420238494873, "y": 0.14819207042455673 }, { "x": 0.16538971662521362, "y": 0.14819207042455673 } ], "category": "heading1", "id": 244, "content": { "text": "TABLE 22: COMMERCIAL LAWS WITH MORE THAN 100\nIMPRISONMENT CLAUSES\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1663530468940735, "y": 0.3195558190345764 }, { "x": 0.35379575192928314, "y": 0.3195558190345764 }, { "x": 0.35379575192928314, "y": 0.33062833826988935 }, { "x": 0.1663530468940735, "y": 0.33062833826988935 } ], "category": "paragraph", "id": 246, "content": { "text": "Source: TeamLease Regtech\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1654866337776184, "y": 0.3924657106399536 }, { "x": 0.806799054145813, "y": 0.3924657106399536 }, { "x": 0.806799054145813, "y": 0.4236179534345865 }, { "x": 0.1654866337776184, "y": 0.4236179534345865 } ], "category": "heading1", "id": 247, "content": { "text": "TABLE 23: IMPRISONMENT CLAUSES IN ENVIRONMENT,\nHEALTH AND SAFETY LAWS\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16696345806121826, "y": 0.6246473789215088 }, { "x": 0.3535902500152588, "y": 0.6246473789215088 }, { "x": 0.3535902500152588, "y": 0.6357740107923746 }, { "x": 0.16696345806121826, "y": 0.6357740107923746 } ], "category": "paragraph", "id": 249, "content": { "text": "Source: TeamLease Regtech\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16597473621368408, "y": 0.6611728072166443 }, { "x": 0.8331997990608215, "y": 0.6611728072166443 }, { "x": 0.8331997990608215, "y": 0.7117902413010597 }, { "x": 0.16597473621368408, "y": 0.7117902413010597 } ], "category": "paragraph", "id": 250, "content": { "text": "NOTE: The inconsistency in number of laws is because a single law could have\nmultiple clauses on criminality; it could have a few clauses of less than\nthree months and few of between three and five years.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.48551374673843384, "y": 0.9508510828018188 }, { "x": 0.5146264731884003, "y": 0.9508510828018188 }, { "x": 0.5146264731884003, "y": 0.964984635822475 }, { "x": 0.48551374673843384, "y": 0.964984635822475 } ], "category": "paragraph", "id": 251, "content": { "text": "78\n", "html": "", "markdown": "" } } ] }, "01030000000006.pdf": { "elements": [ { "coordinates": [ { "x": 0.42847901582717896, "y": 0.06264942139387131 }, { "x": 0.5440423488616943, "y": 0.06264942139387131 }, { "x": 0.5440423488616943, "y": 0.07882210426032543 }, { "x": 0.42847901582717896, "y": 0.07882210426032543 } ], "category": "header", "id": 40, "content": { "text": "Chuj Country\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.829463541507721, "y": 0.06717387586832047 }, { "x": 0.8457102049142122, "y": 0.06717387586832047 }, { "x": 0.8457102049142122, "y": 0.07693842239677906 }, { "x": 0.829463541507721, "y": 0.07693842239677906 } ], "category": "paragraph", "id": 41, "content": { "text": "19\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.13285787403583527, "y": 0.09986250847578049 }, { "x": 0.8375452905893326, "y": 0.09986250847578049 }, { "x": 0.8375452905893326, "y": 0.8328967019915581 }, { "x": 0.13285787403583527, "y": 0.8328967019915581 } ], "category": "figure", "id": 42, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.2369835376739502, "y": 0.8402698636054993 }, { "x": 0.7331749200820923, "y": 0.8402698636054993 }, { "x": 0.7331749200820923, "y": 0.8940581269562244 }, { "x": 0.2369835376739502, "y": 0.8940581269562244 } ], "category": "paragraph", "id": 43, "content": { "text": "FIGURE 1.15. On the trail in the Yolcultac (yol k'ultak,\n\"center of the brushland\") forest, municipio of Nentón.\nMay 1965, at the end of the dry season. Photo by the author.\n", "html": "", "markdown": "" } } ] }, "01030000000198.pdf": { "elements": [ { "coordinates": [ { "x": 0.06775893270969391, "y": 0.33433592319488525 }, { "x": 0.861700251698494, "y": 0.33433592319488525 }, { "x": 0.861700251698494, "y": 0.72676882147789 }, { "x": 0.06775893270969391, "y": 0.72676882147789 } ], "category": "table", "id": 33, "content": { "text": "", "html": "
1. Overview of OCR Pack
2. Introduction of Product Services and Key Features
3. Product - Detail Specification
4. Integration Policy
5. FAQ
", "markdown": "" } }, { "coordinates": [ { "x": 0.06184201315045357, "y": 0.12746460735797882 }, { "x": 0.21928885951638222, "y": 0.12746460735797882 }, { "x": 0.21928885951638222, "y": 0.1806231252849102 }, { "x": 0.06184201315045357, "y": 0.1806231252849102 } ], "category": "paragraph", "id": 44, "content": { "text": "Contents\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.33435168862342834, "y": 0.35388800501823425 }, { "x": 0.8222631216049194, "y": 0.35388800501823425 }, { "x": 0.8222631216049194, "y": 0.7156367599964142 }, { "x": 0.33435168862342834, "y": 0.7156367599964142 } ], "category": "paragraph", "id": 45, "content": { "text": "1. Overview of OCR Pack\n2. Introduction of Product Services and Key Features\n3. Product - Detail Specification\n4. Integration Policy\n5. FAQ\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.9665642380714417, "y": 0.9488860964775085 }, { "x": 0.9722311217337847, "y": 0.9488860964775085 }, { "x": 0.9722311217337847, "y": 0.9704352486878633 }, { "x": 0.9665642380714417, "y": 0.9704352486878633 } ], "category": "paragraph", "id": 46, "content": { "text": "I\n", "html": "", "markdown": "" } } ] }, "01030000000140.pdf": { "elements": [ { "coordinates": [ { "x": 0.09741220623254776, "y": 0.08262842893600464 }, { "x": 0.5455531254410744, "y": 0.08262842893600464 }, { "x": 0.5455531254410744, "y": 0.38826894760131836 }, { "x": 0.09741220623254776, "y": 0.38826894760131836 } ], "category": "paragraph", "id": 534, "content": { "text": "There is no question that fishing is the major factor driving\ngrouper stocks on the downward spiral, but those that have\nlarge spawning aggregations are most vulnerable to declines\n(Coleman et al. 1996; Asch and Erisman 2018; Sadovy de\nMitcheson et al. 2020). Because it takes a long time for\nscientists to obtain needed life history information, fisheries-\nindependent survey data, and catch history, grouper\npopulations may be overfished long before data are even\navailable for a stock assessment. Without formal stock\nassessments, general indicators of population status are\nbased on catch trends. Very few grouper stocks that have\nspawning aggregations are managed sustainably. In a recent\nglobal analysis of the status of populations that form\nspawning aggregations, 45% were unknown, 33% were\ndecreasing, and 5% were already gone (Figure 13.5). Only 12%\nhad stable populations, and 5% were increasing.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5855053663253784, "y": 0.09285001456737518 }, { "x": 0.8802473247051239, "y": 0.09285001456737518 }, { "x": 0.8802473247051239, "y": 0.2832539826631546 }, { "x": 0.5855053663253784, "y": 0.2832539826631546 } ], "category": "figure", "id": 535, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5581924915313721, "y": 0.3184901773929596 }, { "x": 0.8997835516929626, "y": 0.3184901773929596 }, { "x": 0.8997835516929626, "y": 0.37099749222397804 }, { "x": 0.5581924915313721, "y": 0.37099749222397804 } ], "category": "paragraph", "id": 536, "content": { "text": "Figure 13.5: Current known status reflecting changes\nof exploited grouper aggregations globally, as noted by\nfisher interviews, monitoring, or underwater surveys\n(N = 509). Long description.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09754329919815063, "y": 0.4058763384819031 }, { "x": 0.901374876499176, "y": 0.4058763384819031 }, { "x": 0.901374876499176, "y": 0.5142795294523239 }, { "x": 0.09754329919815063, "y": 0.5142795294523239 } ], "category": "paragraph", "id": 537, "content": { "text": "Of the 167 species of grouper, 9.6% are vulnerable, 4.8% are near threatened, 1.2% are endangered, and 0.6%\nare critically endangered (Figure 13.6). The majority of species (68.9%) are classified as least concern and 15%\nare data deficient, with insufficient data for classification. The larger (>50 cm total length) and long-lived (>20\nyears) species of grouper that also had smaller geographic ranges were most likely to be endangered or critically\nendangered (Luiz et al. 2016). Market prices for grouper are escalating, and other lower-valued fish are often\nmislabeled or substituted.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12195653468370438, "y": 0.5297801494598389 }, { "x": 0.44956187158823013, "y": 0.5297801494598389 }, { "x": 0.44956187158823013, "y": 0.8300547003746033 }, { "x": 0.12195653468370438, "y": 0.8300547003746033 } ], "category": "figure", "id": 538, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09738846868276596, "y": 0.8464831709861755 }, { "x": 0.45145799964666367, "y": 0.8464831709861755 }, { "x": 0.45145799964666367, "y": 0.8855589628219604 }, { "x": 0.09738846868276596, "y": 0.8855589628219604 } ], "category": "paragraph", "id": 539, "content": { "text": "Figure 13.6: Categories of all grouper species (N = 167)\naccording to the IUCN Red List (IUCN Red List\nAssessments, updated November 2018). Long description.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.48683130741119385, "y": 0.5354241728782654 }, { "x": 0.9018232226371765, "y": 0.5354241728782654 }, { "x": 0.9018232226371765, "y": 0.8991148471832275 }, { "x": 0.48683130741119385, "y": 0.8991148471832275 } ], "category": "paragraph", "id": 540, "content": { "text": "To protect grouper from overfishing, many measures are\nbeing implemented, such as minimum and slot-size\nlimits, recreational bag limits, commercial fishing quotas,\ngear and seasonal controls, marine protected areas, and\nlimited entry (Rocklin et al. 2022). The effectiveness will\ndepend on traits of the species and the local context.\nRegulations to prevent marketing of undersize fish will\nmitigate growth overfishing. Allowing smaller fish to\nreach maturity at least once before harvest will mitigate\nrecruitment overfishing. Size-limit regulations focused\non protecting spawning-size fish may be ineffective for\ndeepwater recreational fishing. Grouper have a\nphysoclistous (i.e., closed) swim bladder, making them\nparticularly susceptible to ruptured swim bladders,\nbloating, stomach distention, and protruding eyes caused\nby rapid decompression when hauled to the surface\n(Brulé et al. 2015). The proportion of grouper with\ndistended stomachs was 70% in one study of commercial\nhook-and-line fishing and as high as 95% for Red\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09809540957212448, "y": 0.9361710548400879 }, { "x": 0.11777504533529282, "y": 0.9361710548400879 }, { "x": 0.11777504533529282, "y": 0.9445587946102023 }, { "x": 0.09809540957212448, "y": 0.9445587946102023 } ], "category": "paragraph", "id": 541, "content": { "text": "312\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.13565538823604584, "y": 0.9357007145881653 }, { "x": 0.37270863354206085, "y": 0.9357007145881653 }, { "x": 0.37270863354206085, "y": 0.9478613650426269 }, { "x": 0.13565538823604584, "y": 0.9478613650426269 } ], "category": "footer", "id": 542, "content": { "text": "Grouper and Spawning Aggregations\n", "html": "", "markdown": "" } } ] }, "01030000000112.pdf": { "elements": [ { "coordinates": [ { "x": 0.12623675167560577, "y": 0.07266097515821457 }, { "x": 0.6430348306894302, "y": 0.07266097515821457 }, { "x": 0.6430348306894302, "y": 0.08833710290491581 }, { "x": 0.12623675167560577, "y": 0.08833710290491581 } ], "category": "paragraph", "id": 293, "content": { "text": "Adjust the point gauge to read 10 mm greater than the datum.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12681443989276886, "y": 0.09916718304157257 }, { "x": 0.33859890699386597, "y": 0.09916718304157257 }, { "x": 0.33859890699386597, "y": 0.11449585668742657 }, { "x": 0.12681443989276886, "y": 0.11449585668742657 } ], "category": "paragraph", "id": 294, "content": { "text": "Record the reading as h.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12663322687149048, "y": 0.12530970573425293 }, { "x": 0.8845712542533875, "y": 0.12530970573425293 }, { "x": 0.8845712542533875, "y": 0.16053232178092003 }, { "x": 0.12663322687149048, "y": 0.16053232178092003 } ], "category": "paragraph", "id": 295, "content": { "text": "Turn on the pump, and slightly adjust the flow until the water level coincides with the point\ngauge. Check that the level has stabilized before taking readings.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12626072764396667, "y": 0.1710652858018875 }, { "x": 0.5384472012519836, "y": 0.1710652858018875 }, { "x": 0.5384472012519836, "y": 0.1867938470095396 }, { "x": 0.12626072764396667, "y": 0.1867938470095396 } ], "category": "paragraph", "id": 296, "content": { "text": "Measure the flow rate using the volumetric tank.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12651292979717255, "y": 0.1972518414258957 }, { "x": 0.5815979093313217, "y": 0.1972518414258957 }, { "x": 0.5815979093313217, "y": 0.21326305717229843 }, { "x": 0.12651292979717255, "y": 0.21326305717229843 } ], "category": "paragraph", "id": 297, "content": { "text": "Observe the shape of the nappe and take pictures of it.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09195961058139801, "y": 0.2305014431476593 }, { "x": 0.9067505747079849, "y": 0.2305014431476593 }, { "x": 0.9067505747079849, "y": 0.3015877828001976 }, { "x": 0.09195961058139801, "y": 0.3015877828001976 } ], "category": "paragraph", "id": 298, "content": { "text": "Note: The surface of the water will fall as it approaches the weir. This is particularly noticeable at high\nflow rates by high heads. To obtain an accurate measurement of the undisturbed water level above the\ncrest of the weir, it is necessary to place the measuring gauge at a distance of at least three times the\nhead above the weir.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1460801362991333, "y": 0.322014182806015 }, { "x": 0.9032542705535889, "y": 0.322014182806015 }, { "x": 0.9032542705535889, "y": 0.39641399681568146 }, { "x": 0.1460801362991333, "y": 0.39641399681568146 } ], "category": "paragraph", "id": 299, "content": { "text": "Increase the flow by opening the bench regulating valve to set the heads above the datum level\nin 10 mm increments until the regulating valve is fully open. Take care not to allow spillage to\noccur over the plate top that is adjacent to the notch. At each condition, measure the flow rate\nand observe the shape of the nappe.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09199346601963043, "y": 0.4133484959602356 }, { "x": 0.90681292116642, "y": 0.4133484959602356 }, { "x": 0.90681292116642, "y": 0.44576993957161903 }, { "x": 0.09199346601963043, "y": 0.44576993957161903 } ], "category": "paragraph", "id": 300, "content": { "text": "Note: To obtain a sufficiently accurate result, collect around 25 liters of water each time, or collect the\nwater for at least 120 seconds.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12611673772335052, "y": 0.46623557806015015 }, { "x": 0.8379275649785995, "y": 0.46623557806015015 }, { "x": 0.8379275649785995, "y": 0.48326391726732254 }, { "x": 0.12611673772335052, "y": 0.48326391726732254 } ], "category": "paragraph", "id": 302, "content": { "text": "Close the regulating valve, stop the pump, and then replace the weir with the V-notch.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12615245580673218, "y": 0.4927109181880951 }, { "x": 0.8505328893661499, "y": 0.4927109181880951 }, { "x": 0.8505328893661499, "y": 0.5252567753195763 }, { "x": 0.12615245580673218, "y": 0.5252567753195763 } ], "category": "paragraph", "id": 303, "content": { "text": "Repeat the experiment with the V-notch weir plate, but with 5 mm increments in water\nsurface elevation.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12588880956172943, "y": 0.5388319492340088 }, { "x": 0.6003266721963882, "y": 0.5388319492340088 }, { "x": 0.6003266721963882, "y": 0.5552777461707592 }, { "x": 0.12588880956172943, "y": 0.5552777461707592 } ], "category": "paragraph", "id": 304, "content": { "text": "Collect seven head and discharge readings for each weir.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3654753267765045, "y": 0.5705698728561401 }, { "x": 0.6329886615276337, "y": 0.5705698728561401 }, { "x": 0.6329886615276337, "y": 0.8459382355213165 }, { "x": 0.3654753267765045, "y": 0.8459382355213165 } ], "category": "figure", "id": 305, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.18574631214141846, "y": 0.8582563400268555 }, { "x": 0.6196337938308716, "y": 0.8582563400268555 }, { "x": 0.6196337938308716, "y": 0.8713413765653968 }, { "x": 0.18574631214141846, "y": 0.8713413765653968 } ], "category": "paragraph", "id": 306, "content": { "text": "Figure 9.3: Position of the notch and Vernier height gauge to set the datum.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0921197161078453, "y": 0.9413735270500183 }, { "x": 0.36963560432195663, "y": 0.9413735270500183 }, { "x": 0.36963560432195663, "y": 0.9503024769946933 }, { "x": 0.0921197161078453, "y": 0.9503024769946933 } ], "category": "footer", "id": 307, "content": { "text": "80 APPLIED FLUID MECHANICS LAB MANUAL\n", "html": "", "markdown": "" } } ] }, "01030000000149.pdf": { "elements": [ { "coordinates": [ { "x": 0.04040919989347458, "y": 0.030146809294819832 }, { "x": 0.12738680839538574, "y": 0.030146809294819832 }, { "x": 0.12738680839538574, "y": 0.06914100237190723 }, { "x": 0.04040919989347458, "y": 0.06914100237190723 } ], "category": "figure", "id": 129, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08370492607355118, "y": 0.061296701431274414 }, { "x": 0.12655900791287422, "y": 0.061296701431274414 }, { "x": 0.12655900791287422, "y": 0.0709359934553504 }, { "x": 0.08370492607355118, "y": 0.0709359934553504 } ], "category": "header", "id": 130, "content": { "text": "Circle\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.6850802302360535, "y": 0.027926655486226082 }, { "x": 0.7555420473217964, "y": 0.027926655486226082 }, { "x": 0.7555420473217964, "y": 0.06015549786388874 }, { "x": 0.6850802302360535, "y": 0.06015549786388874 } ], "category": "figure", "id": 131, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.762539803981781, "y": 0.031571947038173676 }, { "x": 0.9119955897331238, "y": 0.031571947038173676 }, { "x": 0.9119955897331238, "y": 0.056066589429974556 }, { "x": 0.762539803981781, "y": 0.056066589429974556 } ], "category": "header", "id": 132, "content": { "text": "Co-funded by\nthe European Union\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1423676311969757, "y": 0.20963478088378906 }, { "x": 0.8283509314060211, "y": 0.20963478088378906 }, { "x": 0.8283509314060211, "y": 0.24135373905301094 }, { "x": 0.1423676311969757, "y": 0.24135373905301094 } ], "category": "paragraph", "id": 133, "content": { "text": "With this in mind, here we have the 7 key competence areas selected to form a part of Eco-\nCircle's Competence Framework:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.24954228103160858, "y": 0.2616339921951294 }, { "x": 0.5046038180589676, "y": 0.2616339921951294 }, { "x": 0.5046038180589676, "y": 0.27354996651411057 }, { "x": 0.24954228103160858, "y": 0.27354996651411057 } ], "category": "heading1", "id": 134, "content": { "text": "Eco-Circle Competence Framework\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.24837327003479004, "y": 0.29018115997314453 }, { "x": 0.5041813254356384, "y": 0.29018115997314453 }, { "x": 0.5041813254356384, "y": 0.3019872633740306 }, { "x": 0.24837327003479004, "y": 0.3019872633740306 } ], "category": "paragraph", "id": 135, "content": { "text": "#1: The 3 Rs: Recycle-Reuse-Reduce\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.24831897020339966, "y": 0.3181970417499542 }, { "x": 0.4843028783798218, "y": 0.3181970417499542 }, { "x": 0.4843028783798218, "y": 0.33018588181585073 }, { "x": 0.24831897020339966, "y": 0.33018588181585073 } ], "category": "paragraph", "id": 136, "content": { "text": "#2: Lifecycle of Circular Economy\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.24828724563121796, "y": 0.34614697098731995 }, { "x": 0.6065589636564255, "y": 0.34614697098731995 }, { "x": 0.6065589636564255, "y": 0.3585841925814748 }, { "x": 0.24828724563121796, "y": 0.3585841925814748 } ], "category": "paragraph", "id": 137, "content": { "text": "#3: Social Entrepreneurship and Circular Economy\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.2482440322637558, "y": 0.37485888600349426 }, { "x": 0.5570139437913895, "y": 0.37485888600349426 }, { "x": 0.5570139437913895, "y": 0.3870956329628825 }, { "x": 0.2482440322637558, "y": 0.3870956329628825 } ], "category": "paragraph", "id": 138, "content": { "text": "#4: Corporate Environmental Sustainability\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.24840162694454193, "y": 0.40311816334724426 }, { "x": 0.493130698800087, "y": 0.40311816334724426 }, { "x": 0.493130698800087, "y": 0.4152526315301657 }, { "x": 0.24840162694454193, "y": 0.4152526315301657 } ], "category": "paragraph", "id": 139, "content": { "text": "#5: Embodying Sustainable Values\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.2483457326889038, "y": 0.4318113327026367 }, { "x": 0.47410258650779724, "y": 0.4318113327026367 }, { "x": 0.47410258650779724, "y": 0.44305518083274364 }, { "x": 0.2483457326889038, "y": 0.44305518083274364 } ], "category": "paragraph", "id": 140, "content": { "text": "#6: Environmental Engagement\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.24828411638736725, "y": 0.4595412611961365 }, { "x": 0.6327332705259323, "y": 0.4595412611961365 }, { "x": 0.6327332705259323, "y": 0.47192675434052944 }, { "x": 0.24828411638736725, "y": 0.47192675434052944 } ], "category": "paragraph", "id": 141, "content": { "text": "#7: Supporting Local Eco-friendly and Green Activities\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15212632715702057, "y": 0.9035323262214661 }, { "x": 0.8590406328439713, "y": 0.9035323262214661 }, { "x": 0.8590406328439713, "y": 0.927137104794383 }, { "x": 0.15212632715702057, "y": 0.927137104794383 } ], "category": "footer", "id": 142, "content": { "text": "This\nproject has been funded with the support of the European Commission. This publication reflects the views only of the author\nand the Commission cannot be held responsible for any use which may be made of the information contained therein.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3677663803100586, "y": 0.9395521283149719 }, { "x": 0.6441012322902679, "y": 0.9395521283149719 }, { "x": 0.6441012322902679, "y": 0.9490204434841871 }, { "x": 0.3677663803100586, "y": 0.9490204434841871 } ], "category": "footer", "id": 143, "content": { "text": "Project No: : 2021-2-FR02-KA220-YOU-000048126\n", "html": "", "markdown": "" } } ] }, "01030000000186.pdf": { "elements": [ { "coordinates": [ { "x": 0.20409706234931946, "y": 0.08796180039644241 }, { "x": 0.797231525182724, "y": 0.08796180039644241 }, { "x": 0.797231525182724, "y": 0.2341085448861122 }, { "x": 0.20409706234931946, "y": 0.2341085448861122 } ], "category": "table", "id": 737, "content": { "text": "", "html": "
Step 1-1Step 1-2OutputOutputOutput
OutputOutputOutputLayers24 Layers 3 Layers
Merge Layers
32Copy 328 LayersContinued
LayersLayers24 LayersInput24 4 LayersPretraining
InputInputInputInputInput
Step 1. Depthwise Scaling Step 2. Continued Pretraining
", "markdown": "" } }, { "coordinates": [ { "x": 0.20398715138435364, "y": 0.08440828323364258 }, { "x": 0.8037618696689606, "y": 0.08440828323364258 }, { "x": 0.8037618696689606, "y": 0.23967939615249634 }, { "x": 0.20398715138435364, "y": 0.23967939615249634 } ], "category": "figure", "id": 792, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11832509934902191, "y": 0.2532294988632202 }, { "x": 0.8805540055036545, "y": 0.2532294988632202 }, { "x": 0.8805540055036545, "y": 0.27912712283432484 }, { "x": 0.11832509934902191, "y": 0.27912712283432484 } ], "category": "paragraph", "id": 793, "content": { "text": "Figure 1: Depth up-scaling for the case with n = 32, S = 48, and m = 8. Depth up-scaling is achieved through a\ndual-stage process of depthwise scaling followed by continued pretraining.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11835247278213501, "y": 0.30771109461784363 }, { "x": 0.4846966862678528, "y": 0.30771109461784363 }, { "x": 0.4846966862678528, "y": 0.33643085323274136 }, { "x": 0.11835247278213501, "y": 0.33643085323274136 } ], "category": "paragraph", "id": 794, "content": { "text": "for wider access and application of these models\nby researchers and developers globally.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11848196387290955, "y": 0.35064759850502014 }, { "x": 0.3011168986558914, "y": 0.35064759850502014 }, { "x": 0.3011168986558914, "y": 0.3639353597536683 }, { "x": 0.11848196387290955, "y": 0.3639353597536683 } ], "category": "heading1", "id": 795, "content": { "text": "2 Depth Up-Scaling\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1178872287273407, "y": 0.3754076063632965 }, { "x": 0.48765066266059875, "y": 0.3754076063632965 }, { "x": 0.48765066266059875, "y": 0.5325201004743576 }, { "x": 0.1178872287273407, "y": 0.5325201004743576 } ], "category": "paragraph", "id": 796, "content": { "text": "To efficiently scale-up LLMs, we aim to utilize pre-\ntrained weights of base models to scale up to larger\nLLMs (Komatsuzaki et al., 2022). While exist-\ning methods such as Komatsuzaki et al. (2022) use\nMoE (Shazeer et al., 2017) to scale-up the model ar-\nchitecture, we opt for a different depthwise scaling\nstrategy inspired by Tan and Le (2019). We then\ncontinually pretrain the scaled model as just scaling\nthe model without further pretraining degrades the\nperformance.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11813770234584808, "y": 0.5440011024475098 }, { "x": 0.4877653867006302, "y": 0.5440011024475098 }, { "x": 0.4877653867006302, "y": 0.7014251202344894 }, { "x": 0.11813770234584808, "y": 0.7014251202344894 } ], "category": "paragraph", "id": 797, "content": { "text": "Base model. Any n-layer transformer architec-\nture can be used but we select the 32-layer Llama\n2 architecture as our base model. We initialize the\nLlama 2 architecture with pretrained weights from\nMistral 7B, as it is one of the top performers com-\npatible with the Llama 2 architecture. By adopting\nthe Llama 2 architecture for our base model, we\naim to leverage the vast pool of community re-\nsources while introducing novel modifications to\nfurther enhance its capabilities.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11819421499967575, "y": 0.7128930687904358 }, { "x": 0.4848050996661186, "y": 0.7128930687904358 }, { "x": 0.4848050996661186, "y": 0.771254375576973 }, { "x": 0.11819421499967575, "y": 0.771254375576973 } ], "category": "paragraph", "id": 798, "content": { "text": "Depthwise scaling. From the base model with n\nlayers, we set the target layer count S for the scaled\nmodel, which is largely dictated by the available\nhardware.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11777874827384949, "y": 0.7774916291236877 }, { "x": 0.48710501194000244, "y": 0.7774916291236877 }, { "x": 0.48710501194000244, "y": 0.9187832921743393 }, { "x": 0.11777874827384949, "y": 0.9187832921743393 } ], "category": "paragraph", "id": 799, "content": { "text": "With the above, the depthwise scaling process\nis as follows. The base model with n layers is\nduplicated for subsequent modification. Then, we\nremove the final m layers from the original model\nand the initial m layers from its duplicate, thus\nforming two distinct models with n - m layers.\nThese two models are concatenated to form a scaled\nmodel with S = 2.(n-m) layers. Note that n = 32\nfrom our base model and we set S = 48 considering\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5135110020637512, "y": 0.30781254172325134 }, { "x": 0.8817608654499054, "y": 0.30781254172325134 }, { "x": 0.8817608654499054, "y": 0.4005233123898506 }, { "x": 0.5135110020637512, "y": 0.4005233123898506 } ], "category": "paragraph", "id": 800, "content": { "text": "our hardware constraints and the efficiency of the\nscaled model, i.e., fitting between 7 and 13 billion\nparameters. Naturally, this leads to the removal of\nm = 8 layers. The depthwise scaling process with\nn = 32, S = 48, and m = 8 is depicted in 'Step 1:\nDepthwise Scaling' of Fig. 1.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5134608149528503, "y": 0.40525487065315247 }, { "x": 0.8812694549560547, "y": 0.40525487065315247 }, { "x": 0.8812694549560547, "y": 0.4658917933702469 }, { "x": 0.5134608149528503, "y": 0.4658917933702469 } ], "category": "paragraph", "id": 801, "content": { "text": "We note that a method in the community that also\nscale the model in the same manner 2 as 'Step 1:\nDepthwise Scaling' of Fig. 1 has been concurrently\ndeveloped.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5133315324783325, "y": 0.4807628393173218 }, { "x": 0.8825181722640991, "y": 0.4807628393173218 }, { "x": 0.8825181722640991, "y": 0.6703736037015915 }, { "x": 0.5133315324783325, "y": 0.6703736037015915 } ], "category": "paragraph", "id": 802, "content": { "text": "Continued pretraining. The performance of the\ndepthwise scaled model initially drops below that\nof the base LLM. Thus, we additionally apply\nthe continued pretraining step as shown in 'Step\n2: Continued Pretraining' of Fig. 1. Experimen-\ntally, we observe rapid performance recovery of\nthe scaled model during continued pretraining, a\nphenomenon also observed in Komatsuzaki et al.\n(2022). We consider that the particular way of\ndepthwise scaling has isolated the heterogeneity\nin the scaled model which allowed for this fast\nperformance recovery.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5135602951049805, "y": 0.6748671531677246 }, { "x": 0.8818125128746033, "y": 0.6748671531677246 }, { "x": 0.8818125128746033, "y": 0.7824803069233894 }, { "x": 0.5135602951049805, "y": 0.7824803069233894 } ], "category": "paragraph", "id": 803, "content": { "text": "Delving deeper into the heterogeneity of the\nscaled model, a simpler alternative to depthwise\nscaling could be to just repeat its layers once more,\ni.e., from n to 2n layers. Then, the 'layer distance',\nor the difference in the layer indices in the base\nmodel, is only bigger than 1 where layers n and\nn + 1 are connected, i.e., at the seam.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5133111476898193, "y": 0.7883995771408081 }, { "x": 0.8824480473995209, "y": 0.7883995771408081 }, { "x": 0.8824480473995209, "y": 0.8810365200042725 }, { "x": 0.5133111476898193, "y": 0.8810365200042725 } ], "category": "paragraph", "id": 804, "content": { "text": "However, this results in maximum layer distance\nat the seam, which may be too significant of a\ndiscrepancy for continued pretraining to quickly\nresolve. Instead, depthwise scaling sacrifices the\n2m middle layers, thereby reducing the discrep-\nancy at the seam and making it easier for continued\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5135708451271057, "y": 0.8942437767982483 }, { "x": 0.8051449656486511, "y": 0.8942437767982483 }, { "x": 0.8051449656486511, "y": 0.9162202272564173 }, { "x": 0.5135708451271057, "y": 0.9162202272564173 } ], "category": "footer", "id": 805, "content": { "text": "Phttps://huggingface.co/Undi95\nMistral-11B-v0.1\n", "html": "", "markdown": "" } } ] }, "01030000000073.pdf": { "elements": [ { "coordinates": [ { "x": 0.569725513458252, "y": 0.46424204111099243 }, { "x": 0.8791851699352264, "y": 0.46424204111099243 }, { "x": 0.8791851699352264, "y": 0.5198988243937492 }, { "x": 0.569725513458252, "y": 0.5198988243937492 } ], "category": "table", "id": 225, "content": { "text": "", "html": "
Figure 6DPN Argentina Content: World Health Day Celebration (7 April 2021).98
", "markdown": "" } }, { "coordinates": [ { "x": 0.11971025913953781, "y": 0.08685290813446045 }, { "x": 0.8792360350489616, "y": 0.08685290813446045 }, { "x": 0.8792360350489616, "y": 0.2717906981706619 }, { "x": 0.11971025913953781, "y": 0.2717906981706619 } ], "category": "paragraph", "id": 228, "content": { "text": "In this content, DPN Argentina provides a brief explanation of the SDGs and\nthe 2030 Agenda action plans, and most importantly, their role in advancing the 2030\nAgenda through the SDGs Monitoring and Evaluation Program with a focus on certain\nthematic areas. These focuses allow DPN Argentina to investigate through monitoring\nand preparing reports on the development of public policies and actions of\norganizations responsible for compliance with the SDGs, as well as proposals, and\nrecommendations to strengthen related processes.\nFurthermore, DPN Argentina also regularly uploads commemorations of\ndays related to the SDGs by also including the SDGs logo in each of these uploads.\nExamples of such greetings are as follows:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12384170293807983, "y": 0.291660338640213 }, { "x": 0.5263629853725433, "y": 0.291660338640213 }, { "x": 0.5263629853725433, "y": 0.6006693840026855 }, { "x": 0.12384170293807983, "y": 0.6006693840026855 } ], "category": "figure", "id": 229, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.578713595867157, "y": 0.4859486520290375 }, { "x": 0.6426124647259712, "y": 0.4859486520290375 }, { "x": 0.6426124647259712, "y": 0.497646925970912 }, { "x": 0.578713595867157, "y": 0.497646925970912 } ], "category": "paragraph", "id": 230, "content": { "text": "Figure 6\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.6851711273193359, "y": 0.4657060503959656 }, { "x": 0.8611012548208237, "y": 0.4657060503959656 }, { "x": 0.8611012548208237, "y": 0.5193246714770794 }, { "x": 0.6851711273193359, "y": 0.5193246714770794 } ], "category": "paragraph", "id": 231, "content": { "text": "DPN Argentina\nContent: World Health\nDay Celebration\n(7 April 2021).98\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12030287832021713, "y": 0.8880196809768677 }, { "x": 0.876625083386898, "y": 0.8880196809768677 }, { "x": 0.876625083386898, "y": 0.9153709448873997 }, { "x": 0.12030287832021713, "y": 0.9153709448873997 } ], "category": "footer", "id": 232, "content": { "text": "98\nDPN Argentina, \"Día Mundial de la #Salud\", accessed on 5 December 2021, \"https://twitter.com/D\nPNArgentina/status/1379765916259483648\n", "html": "", "markdown": "" } } ] }, "01030000000135.pdf": { "elements": [ { "coordinates": [ { "x": 0.09765836596488953, "y": 0.08247452974319458 }, { "x": 0.9021031558513641, "y": 0.08247452974319458 }, { "x": 0.9021031558513641, "y": 0.2322710156440735 }, { "x": 0.09765836596488953, "y": 0.2322710156440735 } ], "category": "paragraph", "id": 583, "content": { "text": "Fly fishers targeting trout had an important influence in developing and sustaining conservation programs,\nalthough they were sometimes criticized for exclusive or single-interest advocacy. Here I review the history\nof trout fishing and fly-fishing with special focus on the Rocky Mountain West, where fly fishers first exerted\ntheir influence on conservation ethics and sportfishing policy. Although many individuals and organizations\nplayed roles, I concentrate on only two: Fly Fishers International (FFI) and Trout Unlimited (TU). These two\norganizations had similar interests in conservation, but important differences prevented them from working\ntogether on a unified goal of conservation. The legacy of fly-fishing demonstrates the importance of passion,\npersistence, and partnerships in fish conservation.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09746619313955307, "y": 0.25069135427474976 }, { "x": 0.9013281092047691, "y": 0.25069135427474976 }, { "x": 0.9013281092047691, "y": 0.42000100016593933 }, { "x": 0.09746619313955307, "y": 0.42000100016593933 } ], "category": "paragraph", "id": 584, "content": { "text": "Trout and salmon are the only sport fish native to the Western states, and fly-fishing here became more than\na leisure activity. Norman Maclean's novel, A River Runs through It (1976), begins, \"In our family there was no\n1\nclear line between religion and fly fishing.\" Later Maclean writes that \"Something within fishermen tries to\nmake fishing into a world perfect and apart.\" The iconography of Western fly-fishing that Maclean and others\nwrote about was created by anglers, fisheries managers, tourists, guides, businesses, and region promoters. The\nhistory of Rocky Mountain fly-fishing parallels the history of the expansion of our Western frontier as well as\nfisheries management (Brown 2015). Although Henry David Thoreau (1862) maintained that \"In wildness is the\npreservation of the world,\" humans are part of the trout fishing system and helped create, destroy, maintain,\nand restore the trout fishing we have today.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09742255508899689, "y": 0.43818917870521545 }, { "x": 0.902082160115242, "y": 0.43818917870521545 }, { "x": 0.902082160115242, "y": 0.5685443729162216 }, { "x": 0.09742255508899689, "y": 0.5685443729162216 } ], "category": "paragraph", "id": 585, "content": { "text": "The first trout fishers were Native Americans. Native Americans used a variety of fishing methods, including\nweirs, spears, nets, traps, baskets, hook-and-line methods, and baits. They also caught fish by hand via tickling.\nTickling for trout involves rubbing the underbelly of a trout with fingers to get the trout to go into a trance, after\nwhich they can then easily be thrown onto the bank (Martindale 1901). Native Americans were more patient\nthan others. This method is different from noodling for catfish, where the noodler uses fingers as bait and grabs\nthe catfish by its mouth. Native Americans also caught fish by fly-fishing with deer-hair flies, according to the\nwritings of early American naturalist William Bartram (1739-1823) (Monahan, no date).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09744910150766373, "y": 0.586951494216919 }, { "x": 0.9015999212861061, "y": 0.586951494216919 }, { "x": 0.9015999212861061, "y": 0.7753805816173553 }, { "x": 0.09744910150766373, "y": 0.7753805816173553 } ], "category": "paragraph", "id": 586, "content": { "text": "The story of Rocky Mountain trout fishing begins with displacement of Native Americans from their historical\nfishing and hunting grounds. Uninhabited wilderness had to be created through the dispossession of Native\npeople before it could be preserved (Spence 1999). Explorers, trappers, pioneers, soldiers, and homesteaders\nbrought fishing gear to frontier outposts. The Lewis and Clark Expedition (1804-1806) included a designated\nangler named Silas Goodrich. The expedition first described several new species of fish, including the\nYellowstone Cutthroat Trout and Westslope Cutthroat Trout, caught by Goodrich. Later military expeditions\nspent time trout fishing in addition to fighting Native Americans. Custer's Last Stand at Little Bighorn might\nhave been avoided if he'd joined a column of reinforcements under General George Crook. Crook's soldiers\nwere comfortably camped close by on Goose Creek near the Tongue River-fishing, not fighting (Monnett 1993;\nOwens 2002a; Lessner 2010).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08400346338748932, "y": 0.8865483403205872 }, { "x": 0.8404013067483902, "y": 0.8865483403205872 }, { "x": 0.8404013067483902, "y": 0.9195674993097782 }, { "x": 0.08400346338748932, "y": 0.9195674993097782 } ], "category": "paragraph", "id": 587, "content": { "text": "1. Although Maclean and other writers use the term fishermen, women are active anglers and contribute\nsignificantly to the sport.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.6247899532318115, "y": 0.9356311559677124 }, { "x": 0.865753635764122, "y": 0.9356311559677124 }, { "x": 0.865753635764122, "y": 0.9478011596947908 }, { "x": 0.6247899532318115, "y": 0.9478011596947908 } ], "category": "footer", "id": 588, "content": { "text": "Fly-Fishing's Legacy for Conservation\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8834616541862488, "y": 0.9362221956253052 }, { "x": 0.9012256748974323, "y": 0.9362221956253052 }, { "x": 0.9012256748974323, "y": 0.9446666473522782 }, { "x": 0.8834616541862488, "y": 0.9446666473522782 } ], "category": "paragraph", "id": 589, "content": { "text": "191\n", "html": "", "markdown": "" } } ] }, "01030000000159.pdf": { "elements": [ { "coordinates": [ { "x": 0.14214785397052765, "y": 0.096687451004982 }, { "x": 0.8556875139474869, "y": 0.096687451004982 }, { "x": 0.8556875139474869, "y": 0.18173202127218246 }, { "x": 0.14214785397052765, "y": 0.18173202127218246 } ], "category": "paragraph", "id": 301, "content": { "text": "be a starting point for asking questions too, but I would recommend\nagainst brainstorming as the only strategy towards topic and\nquestion identification since it does not enable students to get to\ntopics they didn't know existed.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1418151706457138, "y": 0.18836364150047302 }, { "x": 0.8566716760396957, "y": 0.18836364150047302 }, { "x": 0.8566716760396957, "y": 0.36458374559879303 }, { "x": 0.1418151706457138, "y": 0.36458374559879303 } ], "category": "paragraph", "id": 302, "content": { "text": "I struggle with getting students to actually read the sources we\nfind together in our research consultations. They seem to want\nto do all the searching first and all the reading later. No matter\nhow I tell them it's iterative and you need to go back and forth\nbetween reading and searching many many times, the messages\nwasn't landing. This chapter is my next iteration in how to talk\nabout the research process, but I really don't now what the secret\nrecipe is yet. Let me know if you think this one lands.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14348673820495605, "y": 0.4276012182235718 }, { "x": 0.41138264536857605, "y": 0.4276012182235718 }, { "x": 0.41138264536857605, "y": 0.4556679502129555 }, { "x": 0.14348673820495605, "y": 0.4556679502129555 } ], "category": "heading1", "id": 303, "content": { "text": "Types of Sources\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14139679074287415, "y": 0.49805644154548645 }, { "x": 0.8579325973987579, "y": 0.49805644154548645 }, { "x": 0.8579325973987579, "y": 0.6739377975463867 }, { "x": 0.14139679074287415, "y": 0.6739377975463867 } ], "category": "paragraph", "id": 304, "content": { "text": "I am a big fan of Mike Caulfield's information literacy work (see\nthe next chapter, SIFTing Information.) Sometimes I have found\nmy attempts to use his strategies in the classroom were hard for\nstudents. For example, when I've tried the exercise about the\nAmerican Academy of Pediatrics and the American College of\nPediatricians (Reflection & Discussion Question 1) without first\ntalking about professional organizations, students rarely got how\nthey were different, and it did not build their confidence.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14188586175441742, "y": 0.6809481978416443 }, { "x": 0.8561907261610031, "y": 0.6809481978416443 }, { "x": 0.8561907261610031, "y": 0.7886091768741608 }, { "x": 0.14188586175441742, "y": 0.7886091768741608 } ], "category": "paragraph", "id": 305, "content": { "text": "It's hard to identify a legitimate professional association if you've\nnever heard of the concept of professional associations. This\nchapter may be long, but I felt it was important to enumerate at\nleast some of the dimensions of the sources they may find, SO that\nwhen we get to Caulfield's SIFT method they are set up for success.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1425996869802475, "y": 0.9242022037506104 }, { "x": 0.17347673699259758, "y": 0.9242022037506104 }, { "x": 0.17347673699259758, "y": 0.9349957341328263 }, { "x": 0.1425996869802475, "y": 0.9349957341328263 } ], "category": "paragraph", "id": 306, "content": { "text": "102\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.19869175553321838, "y": 0.924358606338501 }, { "x": 0.3964291363954544, "y": 0.924358606338501 }, { "x": 0.3964291363954544, "y": 0.9348275354132056 }, { "x": 0.19869175553321838, "y": 0.9348275354132056 } ], "category": "footer", "id": 307, "content": { "text": "Instructor Resources\n", "html": "", "markdown": "" } } ] }, "01030000000150.pdf": { "elements": [ { "coordinates": [ { "x": 0.11871100217103958, "y": 0.21982209384441376 }, { "x": 0.8755227401852608, "y": 0.21982209384441376 }, { "x": 0.8755227401852608, "y": 0.7176831215620041 }, { "x": 0.11871100217103958, "y": 0.7176831215620041 } ], "category": "table", "id": 215, "content": { "text": "", "html": "
Competence Area#1 THE 3 Rs: RECYCLE-REUSE-REDUCE
Competence StatementTo know the basics of the 3 Rs and their importance and implementation into daily life in relation to green entrepreneurship and circular economy.
Learning Outcomes
KnowledgeTo understand the meaning of reducing, reusing and recycling and how they connect To understand the importance of the 3 Rs as waste management To be familiar with the expansion of the 3 Rs - the 7 Rs
SkillsTo implement different ways of waste management into daily life To properly implement recycling in day-to-day activities To promote reducing and reusing before recycling
Attitudes and ValuesTo acquire a proactive approach to implementing the 3 Rs into daily personal life To educate others on the importance of sustainable waste management
", "markdown": "" } }, { "coordinates": [ { "x": 0.03990175202488899, "y": 0.030832989141345024 }, { "x": 0.12764647230505943, "y": 0.030832989141345024 }, { "x": 0.12764647230505943, "y": 0.07108290307223797 }, { "x": 0.03990175202488899, "y": 0.07108290307223797 } ], "category": "figure", "id": 231, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.6849205493927002, "y": 0.027972519397735596 }, { "x": 0.7553095817565918, "y": 0.027972519397735596 }, { "x": 0.7553095817565918, "y": 0.06030676141381264 }, { "x": 0.6849205493927002, "y": 0.06030676141381264 } ], "category": "figure", "id": 232, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.7627584338188171, "y": 0.03131020814180374 }, { "x": 0.9124770164489746, "y": 0.03131020814180374 }, { "x": 0.9124770164489746, "y": 0.056015755981206894 }, { "x": 0.7627584338188171, "y": 0.056015755981206894 } ], "category": "header", "id": 233, "content": { "text": "Co-funded by\nthe European Union\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14360204339027405, "y": 0.15581771731376648 }, { "x": 0.6915955245494843, "y": 0.15581771731376648 }, { "x": 0.6915955245494843, "y": 0.17195253632962704 }, { "x": 0.14360204339027405, "y": 0.17195253632962704 } ], "category": "heading1", "id": 234, "content": { "text": "6.\nECO CIRCLE COMPETENCE FRAMEWORK\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1521652191877365, "y": 0.904519259929657 }, { "x": 0.8596652001142502, "y": 0.904519259929657 }, { "x": 0.8596652001142502, "y": 0.926546148955822 }, { "x": 0.1521652191877365, "y": 0.926546148955822 } ], "category": "footer", "id": 236, "content": { "text": "This project has been funded with the support of the European Commission. This publication reflects the views only of the author\nand the Commission cannot be held responsible for any use which may be made of the information contained therein.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3678869903087616, "y": 0.9397825002670288 }, { "x": 0.6442329585552216, "y": 0.9397825002670288 }, { "x": 0.6442329585552216, "y": 0.9485743409022689 }, { "x": 0.3678869903087616, "y": 0.9485743409022689 } ], "category": "footer", "id": 237, "content": { "text": "Project No: : 2021-2-FR02-KA220-YOU-000048126\n", "html": "", "markdown": "" } } ] }, "01030000000036.pdf": { "elements": [ { "coordinates": [ { "x": 0.26902520656585693, "y": 0.08657541126012802 }, { "x": 0.8386737704277039, "y": 0.08657541126012802 }, { "x": 0.8386737704277039, "y": 0.11370310373604298 }, { "x": 0.26902520656585693, "y": 0.11370310373604298 } ], "category": "heading1", "id": 533, "content": { "text": "2. General Profile of MSMEs\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.06745069473981857, "y": 0.14786088466644287 }, { "x": 0.4468049928545952, "y": 0.14786088466644287 }, { "x": 0.4468049928545952, "y": 0.2870059609413147 }, { "x": 0.06745069473981857, "y": 0.2870059609413147 } ], "category": "paragraph", "id": 534, "content": { "text": "In July 2020, the survey established a general profile\nof the MSMEs interviewed. The respondents updated\nthe interviewers on the status of their business in each\nsubsequent phase. Respondents whose business\nhad permanently closed were only asked the reasons\nfor closing (Section 2.4) and about government\nassistance programs (Section 7). The demographics\nof respondents and business characteristics (i.e., the\nproportions) remained roughly the same across all\nthree survey phases.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.461188942193985, "y": 0.14809206128120422 }, { "x": 0.8417754471302032, "y": 0.14809206128120422 }, { "x": 0.8417754471302032, "y": 0.22859999537467957 }, { "x": 0.461188942193985, "y": 0.22859999537467957 } ], "category": "paragraph", "id": 535, "content": { "text": "Business characteristics. Business size was\ndetermined by the number of staff at the time of\ninterview. Following Government Decree number 25/\nGOV, firms with five or less staff are microenterprises,\nthose with six - 50 staff are small, and those with 51\n- 99 staff are medium.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.46187448501586914, "y": 0.24789471924304962 }, { "x": 0.8408768475055695, "y": 0.24789471924304962 }, { "x": 0.8408768475055695, "y": 0.2878699563443661 }, { "x": 0.46187448501586914, "y": 0.2878699563443661 } ], "category": "paragraph", "id": 536, "content": { "text": "Micro and small enterprises made up most of\nthe respondents. Approximately 58% were\nmicroenterprises, 40% were small, and only two\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.06811775267124176, "y": 0.3037278354167938 }, { "x": 0.480828657746315, "y": 0.3037278354167938 }, { "x": 0.480828657746315, "y": 0.31543863844126463 }, { "x": 0.06811775267124176, "y": 0.31543863844126463 } ], "category": "paragraph", "id": 537, "content": { "text": "Figure 2.1: Surveyed MSMEs by size across sectors (%)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.2003970742225647, "y": 0.329654723405838 }, { "x": 0.7088945508003235, "y": 0.329654723405838 }, { "x": 0.7088945508003235, "y": 0.5572469681501389 }, { "x": 0.2003970742225647, "y": 0.5572469681501389 } ], "category": "figure", "id": 538, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.06730656325817108, "y": 0.5750409364700317 }, { "x": 0.4477548450231552, "y": 0.5750409364700317 }, { "x": 0.4477548450231552, "y": 0.6696289926767349 }, { "x": 0.06730656325817108, "y": 0.6696289926767349 } ], "category": "paragraph", "id": 539, "content": { "text": "percent were medium. The tourism MSME sample\nincluded a higher percentage of microenterprises than\nthe other two sectors. All of the tourism and handicraft/\ntextile MSMEs interviewed were registered, or formal,\nconstituting approximately 71% of the sample. The\nremainder (agriculture MSMEs) were informal, as they\nwere individual farmers.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.06733240187168121, "y": 0.6889426112174988 }, { "x": 0.4476384073495865, "y": 0.6889426112174988 }, { "x": 0.4476384073495865, "y": 0.8002012819051743 }, { "x": 0.06733240187168121, "y": 0.8002012819051743 } ], "category": "paragraph", "id": 540, "content": { "text": "The geographic focus of sampling sought to emulate\nthe concentration of businesses nationwide.\nInterviewed MSMEs in the tourism and handicraft/\ntextile sectors were mainly based in Vientiane Capital,\nLuang Prabang, and Champasack provinces. For the\nagriculture sector, MSMEs were based in 12 provinces\nand the capital. Annex 1 provides the locations of\nrespondents who participated in all three phases.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.06710708886384964, "y": 0.8171557188034058 }, { "x": 0.4467041566967964, "y": 0.8171557188034058 }, { "x": 0.4467041566967964, "y": 0.87138357385993 }, { "x": 0.06710708886384964, "y": 0.87138357385993 } ], "category": "paragraph", "id": 541, "content": { "text": "The tourism sub-sectors interviewed included\nlodging, restaurants and bars, and tour operators.\nMost handicraft/textile respondents were involved\nin production, with the remaining in sales. The\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.4620667099952698, "y": 0.5750918388366699 }, { "x": 0.8409702181816101, "y": 0.5750918388366699 }, { "x": 0.8409702181816101, "y": 0.6708971261978149 }, { "x": 0.4620667099952698, "y": 0.6708971261978149 } ], "category": "paragraph", "id": 542, "content": { "text": "main products are silk and cotton products such as\nbags, clothes, and scarves, bamboo wicker, pottery,\ncarvings, and mulberry paper products. MSMEs\ninterviewed in the agriculture sector focused on the\ncultivation and trade of cash crops such as vegetables,\ncassava, banana, sugar cane, tea and coffee, livestock\nor fish, and rice.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.4617045819759369, "y": 0.6888726949691772 }, { "x": 0.8420882225036621, "y": 0.6888726949691772 }, { "x": 0.8420882225036621, "y": 0.8569783270359039 }, { "x": 0.4617045819759369, "y": 0.8569783270359039 } ], "category": "paragraph", "id": 543, "content": { "text": "Demographics of respondents. The overall gender\nratio of interviewees was slightly skewed towards\nmen (52%). Within the handicraft/textile sector,\n80% were women, while the agriculture sector\nwas dominated by male representatives (74%). The\ntourism sector respondents were 51% men. Most\nof the interviewees were MSME owners (80%),\nfollowed by managers (17%), while the other three\npercent comprised positions such as accountant,\nassistant, and deputy manager. More than half (58%)\nof interviewees were 36 to 55 years old; the youngest\nrespondent was 23 and the eldest was 83.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.9272695183753967, "y": 0.9403039813041687 }, { "x": 0.9339231643825769, "y": 0.9403039813041687 }, { "x": 0.9339231643825769, "y": 0.9475362682715058 }, { "x": 0.9272695183753967, "y": 0.9475362682715058 } ], "category": "paragraph", "id": 544, "content": { "text": "6\n", "html": "", "markdown": "" } } ] }, "01030000000062.pdf": { "elements": [ { "coordinates": [ { "x": 0.11336665600538254, "y": 0.16290169954299927 }, { "x": 0.8988145515322685, "y": 0.16290169954299927 }, { "x": 0.8988145515322685, "y": 0.5434099733829498 }, { "x": 0.11336665600538254, "y": 0.5434099733829498 } ], "category": "table", "id": 303, "content": { "text": "", "html": "
Shipping remains as the only scientifically
documented pathway for marine biological invasion in the Philippines with the introduction and invasion of the South American mussel Mytella strigata (Vallejo et al. 2017). This invasive was first recorded from the South Harbor of Manila in 2014 and has been known to have spread throughout Manila Bay, to Lingayen Gulf, Aparri, Cagayan and Batangas Port in the Philippines. It has since then reported in Singapore, Taiwan,
Hong Kong, India, Malaysia, the Gulf ofFigure 2. Foulers from the South Harbor of Manila Bay. Photo by SAILS-PORTEC Manila Bay
", "markdown": "" } }, { "coordinates": [ { "x": 0.14690959453582764, "y": 0.12170439213514328 }, { "x": 0.46399813890457153, "y": 0.12170439213514328 }, { "x": 0.46399813890457153, "y": 0.13653213065117598 }, { "x": 0.14690959453582764, "y": 0.13653213065117598 } ], "category": "heading1", "id": 312, "content": { "text": "1. Shipping as a vector for marine IAS\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11586376279592514, "y": 0.1495446264743805 }, { "x": 0.44669993966817856, "y": 0.1495446264743805 }, { "x": 0.44669993966817856, "y": 0.552027553319931 }, { "x": 0.11586376279592514, "y": 0.552027553319931 } ], "category": "paragraph", "id": 313, "content": { "text": "List of Philippine Ports is in Appendix 3\nShipping remains as the only scientifically\ndocumented pathway for marine\nbiological invasion in the Philippines with\nthe introduction and invasion of the\nSouth American mussel Mytella strigata\n(Vallejo et al. 2017). This invasive was first\nrecorded from the South Harbor of\nManila in 2014 and has been known to\nhave spread throughout Manila Bay, to\nLingayen Gulf, Aparri, Cagayan and\nBatangas Port in the Philippines. It has\nsince then reported in Singapore, Taiwan,\nHong Kong, India, Malaysia, the Gulf of\nThailand, and Sri Lanka.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.4577171206474304, "y": 0.17370176315307617 }, { "x": 0.8991135954856873, "y": 0.17370176315307617 }, { "x": 0.8991135954856873, "y": 0.5116526484489441 }, { "x": 0.4577171206474304, "y": 0.5116526484489441 } ], "category": "figure", "id": 314, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.45610374212265015, "y": 0.5129023194313049 }, { "x": 0.8534623384475708, "y": 0.5129023194313049 }, { "x": 0.8534623384475708, "y": 0.5445096679031849 }, { "x": 0.45610374212265015, "y": 0.5445096679031849 } ], "category": "paragraph", "id": 315, "content": { "text": "Figure 2. Foulers from the South Harbor of Manila Bay.\nPhoto by SAILS-PORTEC Manila Bay\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11725322902202606, "y": 0.5922120213508606 }, { "x": 0.8820537179708481, "y": 0.5922120213508606 }, { "x": 0.8820537179708481, "y": 0.746106743812561 }, { "x": 0.11725322902202606, "y": 0.746106743812561 } ], "category": "paragraph", "id": 316, "content": { "text": "Mytella was likely spread through hull fouling and ballast water release. In the Philippines its\nspread to other ports was likely through small vessel hull fouling as the first adult samples were\nrecorded from the fishing boat FV Ocean in 2015 which was docked in Manila Bay. An intensive\nmonitoring of the South Harbor area in 2014 resulted in the detection of the first cohort of\nrecruits in Manila Bay. The likely first introduction by ballast water release or by biofouling was\nin\nDecember 2013 and the first cohort of recruits was detected in July 2014.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11670788377523422, "y": 0.7866951823234558 }, { "x": 0.8819195255637169, "y": 0.7866951823234558 }, { "x": 0.8819195255637169, "y": 0.8863318488001823 }, { "x": 0.11670788377523422, "y": 0.8863318488001823 } ], "category": "paragraph", "id": 317, "content": { "text": "There are at least 15 marine non-indigenous species ship hull fouling recorded from Manila Bay's\nSouth Harbor (Vallejo et al. 2019; Trinidad et al 2017.) Only Mytella is considered invasive enough\nto have wide scale ecological and economic impacts. The most numerous species is the well-\nstudied Hydroides elegans, which is a known ship fouler with a present pantropical distribution.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.872165858745575, "y": 0.9222692251205444 }, { "x": 0.8816296188160777, "y": 0.9222692251205444 }, { "x": 0.8816296188160777, "y": 0.9330381061881781 }, { "x": 0.872165858745575, "y": 0.9330381061881781 } ], "category": "paragraph", "id": 318, "content": { "text": "6\n", "html": "", "markdown": "" } } ] }, "01030000000076.pdf": { "elements": [ { "coordinates": [ { "x": 0.18853653967380524, "y": 0.08166905492544174 }, { "x": 0.7893241196870804, "y": 0.08166905492544174 }, { "x": 0.7893241196870804, "y": 0.30975379794836044 }, { "x": 0.18853653967380524, "y": 0.30975379794836044 } ], "category": "figure", "id": 167, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.19001583755016327, "y": 0.31656166911125183 }, { "x": 0.5865285843610764, "y": 0.31656166911125183 }, { "x": 0.5865285843610764, "y": 0.3303641313686967 }, { "x": 0.19001583755016327, "y": 0.3303641313686967 } ], "category": "paragraph", "id": 168, "content": { "text": "Source: Department of Employment, Thailand (2022)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.19071641564369202, "y": 0.3447915017604828 }, { "x": 0.7461802661418915, "y": 0.3447915017604828 }, { "x": 0.7461802661418915, "y": 0.3622525166720152 }, { "x": 0.19071641564369202, "y": 0.3622525166720152 } ], "category": "paragraph", "id": 169, "content": { "text": "Figure 1.7. Non-citizen population in Malaysia (in thousands)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.18854254484176636, "y": 0.3717999756336212 }, { "x": 0.7892948985099792, "y": 0.3717999756336212 }, { "x": 0.7892948985099792, "y": 0.5945723354816437 }, { "x": 0.18854254484176636, "y": 0.5945723354816437 } ], "category": "figure", "id": 170, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.18988794088363647, "y": 0.6012155413627625 }, { "x": 0.8036698698997498, "y": 0.6012155413627625 }, { "x": 0.8036698698997498, "y": 0.6164145413786173 }, { "x": 0.18988794088363647, "y": 0.6164145413786173 } ], "category": "paragraph", "id": 171, "content": { "text": "Source: Department of Statistics, Malaysia (2022). Figure for 2021 is an estimate.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.19074587523937225, "y": 0.6298515200614929 }, { "x": 0.7450925558805466, "y": 0.6298515200614929 }, { "x": 0.7450925558805466, "y": 0.6473280321806669 }, { "x": 0.19074587523937225, "y": 0.6473280321806669 } ], "category": "paragraph", "id": 172, "content": { "text": "Figure 1.8. Singapore foreign workforce stock (in thousands)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.18760260939598083, "y": 0.6565070748329163 }, { "x": 0.7878654897212982, "y": 0.6565070748329163 }, { "x": 0.7878654897212982, "y": 0.8795362859964371 }, { "x": 0.18760260939598083, "y": 0.8795362859964371 } ], "category": "figure", "id": 173, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.19026391208171844, "y": 0.8871109485626221 }, { "x": 0.8797225207090378, "y": 0.8871109485626221 }, { "x": 0.8797225207090378, "y": 0.9174588564783335 }, { "x": 0.19026391208171844, "y": 0.9174588564783335 } ], "category": "paragraph", "id": 174, "content": { "text": "Source: Compilation by Manpower Research & Statistics Department (Ministry of Manpower,\nSingapore, 2022).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14080198109149933, "y": 0.9516775012016296 }, { "x": 0.4204018861055374, "y": 0.9516775012016296 }, { "x": 0.4204018861055374, "y": 0.9670859994366765 }, { "x": 0.14080198109149933, "y": 0.9670859994366765 } ], "category": "footer", "id": 175, "content": { "text": "ASEAN Migration Outlook\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.9295636415481567, "y": 0.9527303576469421 }, { "x": 0.951291736215353, "y": 0.9527303576469421 }, { "x": 0.951291736215353, "y": 0.9637274770066142 }, { "x": 0.9295636415481567, "y": 0.9637274770066142 } ], "category": "paragraph", "id": 176, "content": { "text": "19\n", "html": "", "markdown": "" } } ] }, "01030000000003.pdf": { "elements": [ { "coordinates": [ { "x": 0.11531402170658112, "y": 0.055896926671266556 }, { "x": 0.5259968489408493, "y": 0.055896926671266556 }, { "x": 0.5259968489408493, "y": 0.0664987713098526 }, { "x": 0.11531402170658112, "y": 0.0664987713098526 } ], "category": "header", "id": 465, "content": { "text": "INTERPRETING SIMULTANEITY JUDGEMENTS\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8301887512207031, "y": 0.05540113523602486 }, { "x": 0.8573497273027897, "y": 0.05540113523602486 }, { "x": 0.8573497273027897, "y": 0.0640081325545907 }, { "x": 0.8301887512207031, "y": 0.0640081325545907 } ], "category": "paragraph", "id": 466, "content": { "text": "321\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11557705700397491, "y": 0.09200027585029602 }, { "x": 0.8590074330568314, "y": 0.09200027585029602 }, { "x": 0.8590074330568314, "y": 0.20972265303134918 }, { "x": 0.11557705700397491, "y": 0.20972265303134918 } ], "category": "paragraph", "id": 467, "content": { "text": "model (discussed for a binary fit in Section 6.2). Because there are three pos-\nsible choices, the appropriate data model (applied at each SOA) is no longer\nthe binomial distribution, but rather the multinomial distribution, which can\nprovide an exact likelihood of obtaining any particular combination of prob-\nabilities that divide N choices into three bins when the actual probabilities of\nselecting each bin are known (or rather, for fitting purposes, predicted).22\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11582325398921967, "y": 0.25459375977516174 }, { "x": 0.4513181298971176, "y": 0.25459375977516174 }, { "x": 0.4513181298971176, "y": 0.2692525051534176 }, { "x": 0.11582325398921967, "y": 0.2692525051534176 } ], "category": "heading1", "id": 468, "content": { "text": "11\nDual-Presentation SJ Data\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11488062143325806, "y": 0.2944074273109436 }, { "x": 0.8580592274665833, "y": 0.2944074273109436 }, { "x": 0.8580592274665833, "y": 0.55295729637146 }, { "x": 0.11488062143325806, "y": 0.55295729637146 } ], "category": "paragraph", "id": 469, "content": { "text": "Several authors have investigated the use of a dual-presentation SJ task in\nwhich two bimodal stimuli are presented (one after another) and compared,\nfor example by reporting which one was (most) synchronous (Allan & Kristof-\nferson, 1974; Powers, Hillock, & Wallace, 2009; Roseboom, Nishida, Fujisaki, &\nArnold, 2011). This is a form of what would, in classical signal detection theory,\nbe described as a two-alternative forced choice (specifically the two-interval\nforced choice variant). However, that designation is ambiguous (about wheth-\ner there are two presentations or two response categories) and has been ap-\nplied to cases where either or both of the possible qualifying conditions are\nmet, which is probably why the dual-presentation SJ task has ended up being\ngiven a variety of names (e.g., temporal 2AFC; forced-choice successiveness\ndiscrimination; 2IFC SJ, where the classic SJ is referred to as 2AFC SJ in the\nsame paper). I will label it the 2xSJ.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11547326296567917, "y": 0.5569155812263489 }, { "x": 0.8585153147578239, "y": 0.5569155812263489 }, { "x": 0.8585153147578239, "y": 0.7548211514949799 }, { "x": 0.11547326296567917, "y": 0.7548211514949799 } ], "category": "paragraph", "id": 470, "content": { "text": "The simplest form of the 2xSJ would have a synchronous standard on every\ntrial along with a non-synchronous test pair. Based on the kind of observer\nmodels discussed in this chapter, the resulting psychometric function (plotting\nthe probability of judging the standard more synchronous than the test against\nthe test's SOA) is U-shaped and centred over the PSS. This approach represents\na reasonable way to derive estimates of inverse precision (i.e., OAt) but a fairly\npoor way to estimate the PSS, because having a synchronous standard on every\ntrial provides feedback about objective synchrony. A simple solution is to also\ninclude a range of standards as well as a range of tests, in a roving standard\ndesign.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11542629450559616, "y": 0.7590541243553162 }, { "x": 0.8582880422472954, "y": 0.7590541243553162 }, { "x": 0.8582880422472954, "y": 0.8567428141832352 }, { "x": 0.11542629450559616, "y": 0.8567428141832352 } ], "category": "paragraph", "id": 471, "content": { "text": "The observer model can be fitted to data even when both standard and test\nare non-zero, as described in detail by Yarrow et al. (2016; see also García-Pérez\n& Peli, 2014). To present all of the data, it is necessary to plot a function for\neach standard SOA (using several standard plots, or a single 3D plot), which is\nsomewhat cumbersome, but not a major obstacle to using the task. A simple\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11621777713298798, "y": 0.8861900568008423 }, { "x": 0.1348487138748169, "y": 0.8861900568008423 }, { "x": 0.1348487138748169, "y": 0.8929844186641276 }, { "x": 0.11621777713298798, "y": 0.8929844186641276 } ], "category": "paragraph", "id": 472, "content": { "text": "22\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16791735589504242, "y": 0.8827950358390808 }, { "x": 0.38667671382427216, "y": 0.8827950358390808 }, { "x": 0.38667671382427216, "y": 0.895199915394187 }, { "x": 0.16791735589504242, "y": 0.895199915394187 } ], "category": "footer", "id": 473, "content": { "text": ".\n", "html": "", "markdown": "" } } ] }, "01030000000126.pdf": { "elements": [ { "coordinates": [ { "x": 0.16457787156105042, "y": 0.09933408349752426 }, { "x": 0.6858815252780914, "y": 0.09933408349752426 }, { "x": 0.6858815252780914, "y": 0.3620591387152672 }, { "x": 0.16457787156105042, "y": 0.3620591387152672 } ], "category": "figure", "id": 175, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.7312429547309875, "y": 0.09447378665208817 }, { "x": 0.8564431071281433, "y": 0.09447378665208817 }, { "x": 0.8564431071281433, "y": 0.23299776762723923 }, { "x": 0.7312429547309875, "y": 0.23299776762723923 } ], "category": "paragraph", "id": 176, "content": { "text": "Figure 4.3-\nOntario\narea (in\nsquare feet)\nused to\nharvest\nmushroom\nS over the\nyears.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1434294730424881, "y": 0.4499095380306244 }, { "x": 0.28407829999923706, "y": 0.4499095380306244 }, { "x": 0.28407829999923706, "y": 0.4690476283431053 }, { "x": 0.1434294730424881, "y": 0.4690476283431053 } ], "category": "heading1", "id": 177, "content": { "text": "Closure\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1417653113603592, "y": 0.5120053887367249 }, { "x": 0.857316866517067, "y": 0.5120053887367249 }, { "x": 0.857316866517067, "y": 0.6433807164430618 }, { "x": 0.1417653113603592, "y": 0.6433807164430618 } ], "category": "paragraph", "id": 178, "content": { "text": "Closure refers to our mind completing missing portions of a\ndesign. There must be enough parts available for the image\nto be \"filled in\"; if the image is too abstract, there are minimal\nreference points for the mind to complete it. See Figure 4.44\n4\nfor an example of how our mind automatically imagine a line\nconnecting the 2 broken ones.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11980095505714417, "y": 0.788356602191925 }, { "x": 0.8517759740352631, "y": 0.788356602191925 }, { "x": 0.8517759740352631, "y": 0.9034690484404564 }, { "x": 0.11980095505714417, "y": 0.9034690484404564 } ], "category": "paragraph", "id": 179, "content": { "text": "4. Statistics Canada. Table 18-10-0002-01 Monthly average retail prices for\nfood and other selected products. Data is reproduced and distributed\non an \"as is\" basis with the permission of Statistics Canada. Retrieved\nFebruary 2nd, 2022. DOI: https://doi.org/10.25318/1810000201-eng.\nStatistics Canada Open Licence: https://www.statcan.gc.ca/en/\nreference/licence\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.614632785320282, "y": 0.9345943927764893 }, { "x": 0.8560900092124939, "y": 0.9345943927764893 }, { "x": 0.8560900092124939, "y": 0.9483423931524158 }, { "x": 0.614632785320282, "y": 0.9483423931524158 } ], "category": "footer", "id": 180, "content": { "text": "Gestalt's Principles 89\n", "html": "", "markdown": "" } } ] }, "01030000000102.pdf": { "elements": [ { "coordinates": [ { "x": 0.11889377981424332, "y": 0.07399608939886093 }, { "x": 0.8788631930947304, "y": 0.07399608939886093 }, { "x": 0.8788631930947304, "y": 0.38112839311361313 }, { "x": 0.11889377981424332, "y": 0.38112839311361313 } ], "category": "figure", "id": 584, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11295231431722641, "y": 0.3989922106266022 }, { "x": 0.21762778609991074, "y": 0.3989922106266022 }, { "x": 0.21762778609991074, "y": 0.40955963265150785 }, { "x": 0.11295231431722641, "y": 0.40955963265150785 } ], "category": "paragraph", "id": 585, "content": { "text": "(Kaza et al. 2018)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09216760843992233, "y": 0.4254471957683563 }, { "x": 0.9080537483096123, "y": 0.4254471957683563 }, { "x": 0.9080537483096123, "y": 0.5344260782003403 }, { "x": 0.09216760843992233, "y": 0.5344260782003403 } ], "category": "paragraph", "id": 586, "content": { "text": "Canada is currently the world's largest producer of MSW per capita. At slightly more than 36 metric\ntons per person per year, Canadians generate roughly 10 tons more MSW per person annually than\nthe next highest garbage producers, Bulgarians and Americans (Tiseo, 2021). Summiting a list like this\nis obviously not in any country's best interest-there are no kudos for reaching the top of the heap,\nSO to speak. Is it therefore possible that those nations reaching the top will take the lead in reversing\ncourse?\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09196576476097107, "y": 0.5420653820037842 }, { "x": 0.9074024856090546, "y": 0.5420653820037842 }, { "x": 0.9074024856090546, "y": 0.7714342921972275 }, { "x": 0.09196576476097107, "y": 0.7714342921972275 } ], "category": "paragraph", "id": 587, "content": { "text": "Halifax is one Canadian city that apparently has. On August 1st, 2015, the city began providing a\n\"green nudge\" to citizens living in its urban core area with the introduction of the Clear Bag Policy, a\npolicy designed to nudge households toward more responsible sorting of their waste, which, in turn,\nwould result in an overall reduction in the total amount of waste generated. As Akbulut-Yuksel and\nBoulatoff point out, under the new policy, households were mandated to replace their black garbage\nbags, traditionally used for the disposal of their refuse, with clear, transparent bags. The Clear Bag\nPolicy allowed households to put out the same number of garbage bags at the curb (six every other\nweek), but all waste destined for the landfill was required to be disposed of in a clear bag (except for\none dark bag permitted for privacy's sake). This allowed waste collectors to screen and refuse any bags\ncontaining materials that should otherwise have been diverted from the landfill, such as recyclables,\nfood waste, and hazardous waste. Clear bags also made apparent to everyone, neighbors and passersby\n33\nalike, a given household's waste-generation and disposal habits.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09193126857280731, "y": 0.7755603790283203 }, { "x": 0.9072459191083908, "y": 0.7755603790283203 }, { "x": 0.9072459191083908, "y": 0.8492226228117943 }, { "x": 0.09193126857280731, "y": 0.8492226228117943 } ], "category": "paragraph", "id": 588, "content": { "text": "To test the Clear Bag Policy's impact on a typical household's generation of MSW, Akbulut-Yuksel\nand Boulatoff designed a quasi-experiment spanning the period from January 6, 2014, to July 28,\n2017, with January 6, 2014, to July 31, 2015, serving as the pre-treatment period and August 1, 2015,\nto July 28, 2017, serving as the post-treatment period. MSW data collected during this time span\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.06887117773294449, "y": 0.8672546744346619 }, { "x": 0.9034327045083046, "y": 0.8672546744346619 }, { "x": 0.9034327045083046, "y": 0.9440674558281898 }, { "x": 0.06887117773294449, "y": 0.9440674558281898 } ], "category": "paragraph", "id": 589, "content": { "text": "33. As Akbulut-Yuksel and Boulatoff point out, Halifax households are required to sort waste in four ways: (1) recyclable\ncontainers (plastics, glass, and aluminum) are put in a transparent blue bag, (2) paper and cardboard are put in a separate\nbag, (3) organic food waste goes in a green bin provided by the city, and (4) the remaining waste (refuse) goes into garbage\nbags. Recyclable materials are collected each week, while garbage and organic waste are each collected every other week on\nopposite weeks (except in the summer months when, thank goodness, organic waste is collected on a weekly basis).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09217444807291031, "y": 0.9510509967803955 }, { "x": 0.2367662861943245, "y": 0.9510509967803955 }, { "x": 0.2367662861943245, "y": 0.9587354226969182 }, { "x": 0.09217444807291031, "y": 0.9587354226969182 } ], "category": "footer", "id": 590, "content": { "text": "234 ARTHUR J. CAPLAN\n", "html": "", "markdown": "" } } ] }, "01030000000065.pdf": { "elements": [ { "coordinates": [ { "x": 0.11539088189601898, "y": 0.09026636928319931 }, { "x": 0.8858897536993027, "y": 0.09026636928319931 }, { "x": 0.8858897536993027, "y": 0.42448269575834274 }, { "x": 0.11539088189601898, "y": 0.42448269575834274 } ], "category": "table", "id": 227, "content": { "text": "", "html": "
SPORT Hard
\" (1. in
", "markdown": "" } }, { "coordinates": [ { "x": 0.11692161113023758, "y": 0.08992880582809448 }, { "x": 0.8839846923947334, "y": 0.08992880582809448 }, { "x": 0.8839846923947334, "y": 0.42332690954208374 }, { "x": 0.11692161113023758, "y": 0.42332690954208374 } ], "category": "figure", "id": 275, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11783286184072495, "y": 0.4262363016605377 }, { "x": 0.8624076470732689, "y": 0.4262363016605377 }, { "x": 0.8624076470732689, "y": 0.4565560221672058 }, { "x": 0.11783286184072495, "y": 0.4565560221672058 } ], "category": "paragraph", "id": 276, "content": { "text": "Figure 6. Mytella strigata biofouling green mussel farms in Bacoor City, Cavite, Manila Bay Photo from\nhttps://businessmirror.com.ph/2020/02/17/fake-tahong-invades-bacoor-mussel-farms/\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14669851958751678, "y": 0.5011966824531555 }, { "x": 0.3142755776643753, "y": 0.5011966824531555 }, { "x": 0.3142755776643753, "y": 0.5150081366300583 }, { "x": 0.14669851958751678, "y": 0.5150081366300583 } ], "category": "heading1", "id": 277, "content": { "text": "5. Natural dispersal\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11629848927259445, "y": 0.5563758611679077 }, { "x": 0.8825942203402519, "y": 0.5563758611679077 }, { "x": 0.8825942203402519, "y": 0.8200203478336334 }, { "x": 0.11629848927259445, "y": 0.8200203478336334 } ], "category": "paragraph", "id": 278, "content": { "text": "Dispersal by purely natural means is not included as a pathway of biological invasions (Gaston\n1996). Examples include range expansion by flight or any other medium of natural locomotion or\ntransport. However if human created or crafted material is involved in rafting dispersal of IAS,\nthen this may be considered as a case of biological invasion. The 2011 Great East Japan\nearthquake generated a large tsunami that caused an unprecedented biological transoceanic\nrafting event from the northwestern Pacific coastline of Japan towards North America on the\neastern Pacific(Carlton et al. 2017). Millions of human made objects from small plastics to large\ndocks and whole ships were cast adrift in the Pacific (Murray et al. 2018). This provided a\nsubstrate for biofoulers. Large debris could carry up to 20 to 30 mega-species of biofoulers\n(Carlton et al. 2017). These biofouled debris can constitute an IAS risk (Therriault 2017).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1170172467827797, "y": 0.8615286946296692 }, { "x": 0.8818761482834816, "y": 0.8615286946296692 }, { "x": 0.8818761482834816, "y": 0.9033813327550888 }, { "x": 0.1170172467827797, "y": 0.9033813327550888 } ], "category": "paragraph", "id": 279, "content": { "text": "While a tsunami is a relatively rare event, a more common one is fouler dispersal by rafting on\ncoastal currents of floating plastic debris, wood and, bamboo. Marine litter often originate from\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8633445501327515, "y": 0.9224846959114075 }, { "x": 0.8821969758719206, "y": 0.9224846959114075 }, { "x": 0.8821969758719206, "y": 0.9329884545877576 }, { "x": 0.8633445501327515, "y": 0.9329884545877576 } ], "category": "paragraph", "id": 280, "content": { "text": "14\n", "html": "", "markdown": "" } } ] }, "01030000000166.pdf": { "elements": [ { "coordinates": [ { "x": 0.09040644019842148, "y": 0.5146045684814453 }, { "x": 0.40088339895009995, "y": 0.5146045684814453 }, { "x": 0.40088339895009995, "y": 0.6598532497882843 }, { "x": 0.09040644019842148, "y": 0.6598532497882843 } ], "category": "table", "id": 297, "content": { "text": "", "html": "
Mineral or colloid typeCEC of pure colloid
cmolc/kg
kaolinite10
illite30
montmorillonite/smectite100
vermiculite150
humus200
", "markdown": "" } }, { "coordinates": [ { "x": 0.09199046343564987, "y": 0.07417865097522736 }, { "x": 0.5165089890360832, "y": 0.07417865097522736 }, { "x": 0.5165089890360832, "y": 0.09321201220154762 }, { "x": 0.09199046343564987, "y": 0.09321201220154762 } ], "category": "heading1", "id": 313, "content": { "text": "Activity 5. Calculating versus estimating CEC\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09139379858970642, "y": 0.12254905700683594 }, { "x": 0.7940567433834076, "y": 0.12254905700683594 }, { "x": 0.7940567433834076, "y": 0.1360490769147873 }, { "x": 0.09139379858970642, "y": 0.1360490769147873 } ], "category": "paragraph", "id": 314, "content": { "text": "There are two ways you can calculate the CEC: the sum of cations method and the mineralogy method.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09218904376029968, "y": 0.17841053009033203 }, { "x": 0.3585145175457001, "y": 0.17841053009033203 }, { "x": 0.3585145175457001, "y": 0.1933843744918704 }, { "x": 0.09218904376029968, "y": 0.1933843744918704 } ], "category": "paragraph", "id": 315, "content": { "text": "The Sum-of-Cations Method\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09219886362552643, "y": 0.22695206105709076 }, { "x": 0.9065866023302078, "y": 0.22695206105709076 }, { "x": 0.9065866023302078, "y": 0.2580425050109625 }, { "x": 0.09219886362552643, "y": 0.2580425050109625 } ], "category": "paragraph", "id": 316, "content": { "text": "If you have a soil analysis where the quantities of all cations in the soil are listed, simply summing all those exchangeable\nquantities will yield the CEC you found in the preceding problems.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09207823127508163, "y": 0.301254004240036 }, { "x": 0.3329271748661995, "y": 0.301254004240036 }, { "x": 0.3329271748661995, "y": 0.319772457703948 }, { "x": 0.09207823127508163, "y": 0.319772457703948 } ], "category": "paragraph", "id": 317, "content": { "text": "The \"Mineralogy\" Method\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0916634127497673, "y": 0.34920093417167664 }, { "x": 0.908295564353466, "y": 0.34920093417167664 }, { "x": 0.908295564353466, "y": 0.3806289844214916 }, { "x": 0.0916634127497673, "y": 0.3806289844214916 } ], "category": "paragraph", "id": 318, "content": { "text": "As you know from your reading and class discussion, clay minerals have a range of values for CEC. If the mineralogy of\nthe clay fraction is known (that is, the type and amounts of each clay mineral), then the CEC can be approximated.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09138435870409012, "y": 0.396052747964859 }, { "x": 0.906662292778492, "y": 0.396052747964859 }, { "x": 0.906662292778492, "y": 0.42703009583055973 }, { "x": 0.09138435870409012, "y": 0.42703009583055973 } ], "category": "paragraph", "id": 319, "content": { "text": "To make these calculations easier, Table 13.4 contains representative values for CEC to use in all calculations for this\nclass unless otherwise noted. In nature, however, these soil colloids will have a range of values.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09228072315454483, "y": 0.46976372599601746 }, { "x": 0.5254763439297676, "y": 0.46976372599601746 }, { "x": 0.5254763439297676, "y": 0.48883094266057014 }, { "x": 0.09228072315454483, "y": 0.48883094266057014 } ], "category": "paragraph", "id": 320, "content": { "text": "Table 13.4. Typical CEC of various soil colloids.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09169244766235352, "y": 0.678482711315155 }, { "x": 0.9065955281257629, "y": 0.678482711315155 }, { "x": 0.9065955281257629, "y": 0.72710932046175 }, { "x": 0.09169244766235352, "y": 0.72710932046175 } ], "category": "paragraph", "id": 322, "content": { "text": "As an example of this mineralogy approach to CEC calculations, consider a soil having 100% clay where the clay is 100%\nkaolinite. The CEC would then be 10 cmolc/kg. If a soil contains only 10% kaolinite (or 10 kg clay in 100 kg soil), however,\nthis clay would contribute\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.20004504919052124, "y": 0.740894079208374 }, { "x": 0.6630668640136719, "y": 0.740894079208374 }, { "x": 0.6630668640136719, "y": 0.767117066308856 }, { "x": 0.20004504919052124, "y": 0.767117066308856 } ], "category": "paragraph", "id": 323, "content": { "text": "cmol\nclay\nTotal CEC of the soil\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09142983704805374, "y": 0.7986702919006348 }, { "x": 0.9065466597676277, "y": 0.7986702919006348 }, { "x": 0.9065466597676277, "y": 0.8294000271707773 }, { "x": 0.09142983704805374, "y": 0.8294000271707773 } ], "category": "paragraph", "id": 324, "content": { "text": "A prairie soil contains 30% clay. This clay sized fraction is dominantly montmorillonite. The soil also contains 5% humus\n(organic matter).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09211656451225281, "y": 0.847275972366333 }, { "x": 0.12312529236078262, "y": 0.847275972366333 }, { "x": 0.12312529236078262, "y": 0.8719868157058954 }, { "x": 0.09211656451225281, "y": 0.8719868157058954 } ], "category": "figure", "id": 325, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1451529711484909, "y": 0.8451310992240906 }, { "x": 0.8177332729101181, "y": 0.8451310992240906 }, { "x": 0.8177332729101181, "y": 0.858734336681664 }, { "x": 0.1451529711484909, "y": 0.858734336681664 } ], "category": "paragraph", "id": 326, "content": { "text": "Using the mineralogy method, what is the cation exchange capacity (CEC) contributed by the clay?\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09204268455505371, "y": 0.9412393569946289 }, { "x": 0.20367290824651718, "y": 0.9412393569946289 }, { "x": 0.20367290824651718, "y": 0.9501921674236655 }, { "x": 0.09204268455505371, "y": 0.9501921674236655 } ], "category": "footer", "id": 327, "content": { "text": "120 Soil Colloids\n", "html": "", "markdown": "" } } ] }, "01030000000095.pdf": { "elements": [ { "coordinates": [ { "x": 0.33702602982521057, "y": 0.07962685078382492 }, { "x": 0.6682535111904144, "y": 0.07962685078382492 }, { "x": 0.6682535111904144, "y": 0.26691287010908127 }, { "x": 0.33702602982521057, "y": 0.26691287010908127 } ], "category": "figure", "id": 419, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3170126974582672, "y": 0.29025155305862427 }, { "x": 0.5015595555305481, "y": 0.29025155305862427 }, { "x": 0.5015595555305481, "y": 0.3009377084672451 }, { "x": 0.3170126974582672, "y": 0.3009377084672451 } ], "category": "paragraph", "id": 420, "content": { "text": "(Niederle and Vesterlund 2007)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0922989696264267, "y": 0.3164203464984894 }, { "x": 0.727717861533165, "y": 0.3164203464984894 }, { "x": 0.727717861533165, "y": 0.33215940929949284 }, { "x": 0.0922989696264267, "y": 0.33215940929949284 } ], "category": "paragraph", "id": 421, "content": { "text": "In other words, while women shy away from competition, men are drawn to it.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09181186556816101, "y": 0.3356149196624756 }, { "x": 0.9079406559467316, "y": 0.3356149196624756 }, { "x": 0.9079406559467316, "y": 0.5267517864704132 }, { "x": 0.09181186556816101, "y": 0.5267517864704132 } ], "category": "paragraph", "id": 422, "content": { "text": "Turning to Task 4, recall that although this choice is very similar to that of Task 3, Task 4's choice\neliminates the prospect of having to subsequently participate in a competition. Thus, only in Task 3\ncould a gender gap in preference for competition have played a role in the choice of compensation\nscheme. As the figure below shows, there is no statistically significant gender gap in the choice of\ncompensation scheme in Task 4 based upon perceived ranking in Task 1. A higher percentage of\nwomen than men who guessed their Task 1 ranking to be low (i.e., at level \"3\") chose the tournament\nscheme in Task 4, while the percentages were reversed for those participants who guessed their Task 1\nrankings to be high (at levels \"1\" and \"2\"). But because the two lines in the figure remain close together,\nthese differences are not statistically significant (i.e., we should treat the groups' respective choices as\nbeing no different from one another).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3318614065647125, "y": 0.5494804382324219 }, { "x": 0.6520970463752747, "y": 0.5494804382324219 }, { "x": 0.6520970463752747, "y": 0.738484650850296 }, { "x": 0.3318614065647125, "y": 0.738484650850296 } ], "category": "figure", "id": 423, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.31924864649772644, "y": 0.756026029586792 }, { "x": 0.5040397793054581, "y": 0.756026029586792 }, { "x": 0.5040397793054581, "y": 0.7667481880635023 }, { "x": 0.31924864649772644, "y": 0.7667481880635023 } ], "category": "paragraph", "id": 424, "content": { "text": "(Niederle and Vesterlund 2007)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09153883904218674, "y": 0.7818561792373657 }, { "x": 0.9083657786250114, "y": 0.7818561792373657 }, { "x": 0.9083657786250114, "y": 0.8368392586708069 }, { "x": 0.09153883904218674, "y": 0.8368392586708069 } ], "category": "paragraph", "id": 425, "content": { "text": "This result from Task 4 cements the authors' finding that women shy away from actual competition\nslated to occur at a future point in time, not implicit competition based upon their interpretations of\n10\nhow their past performance compares with others.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.06995241343975067, "y": 0.8669887185096741 }, { "x": 0.9001890867948532, "y": 0.8669887185096741 }, { "x": 0.9001890867948532, "y": 0.9443128854036331 }, { "x": 0.06995241343975067, "y": 0.9443128854036331 } ], "category": "paragraph", "id": 426, "content": { "text": "10. In a related study of the performances of men and women in professional judo fights for bronze medals (of all things!),\nCohen-Zada et al. (2017) find that men's performances are significantly affected by what the authors' call \"psychological\nmomentum\", while women's is not. Psychological momentum is defined as the tendency of an outcome (such as a win in an\ninitial judo match) to be followed by a similar outcome (a win in a subsequent match) that is not caused by any strategic\nincentives of the players. The authors point out that this result is consistent with evidence in the biological literature that\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.6404224038124084, "y": 0.9511243104934692 }, { "x": 0.9058217704296112, "y": 0.9511243104934692 }, { "x": 0.9058217704296112, "y": 0.9588738051243126 }, { "x": 0.6404224038124084, "y": 0.9588738051243126 } ], "category": "footer", "id": 427, "content": { "text": "BEHAVIORAL ECONOMICS PRACTICUM 111\n", "html": "", "markdown": "" } } ] }, "01030000000079.pdf": { "elements": [ { "coordinates": [ { "x": 0.16612236201763153, "y": 0.11553652584552765 }, { "x": 0.42686446011066437, "y": 0.11553652584552765 }, { "x": 0.42686446011066437, "y": 0.20515239983797073 }, { "x": 0.16612236201763153, "y": 0.20515239983797073 } ], "category": "heading1", "id": 241, "content": { "text": "Executive\nSummary\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5128450989723206, "y": 0.11648024618625641 }, { "x": 0.8327617943286896, "y": 0.11648024618625641 }, { "x": 0.8327617943286896, "y": 0.31716012954711914 }, { "x": 0.5128450989723206, "y": 0.31716012954711914 } ], "category": "paragraph", "id": 242, "content": { "text": "I\nndia suffers from 'regulatory\ncholesterol' that is getting in\nthe way of doing business. The\nlegislations, rules and regulations\nenacted by the Union and State\ngovernments have over time created\nbarriers to the smooth flow of ideas,\norganisation, money, entrepreneurship\nand through them the creation of jobs,\nwealth and GDP.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5144399404525757, "y": 0.3451598882675171 }, { "x": 0.8326675891876221, "y": 0.3451598882675171 }, { "x": 0.8326675891876221, "y": 0.5473379045724869 }, { "x": 0.5144399404525757, "y": 0.5473379045724869 } ], "category": "paragraph", "id": 243, "content": { "text": "The presence of hostile clauses in these\nlaws, rules and regulations has grown\nsince Independence, surviving three\ndecades of economic reforms initiated in\n1991. The biggest challenges come from\nthe continuance of imprisonment as a tool\nof control. As automation increases in\nthe coming years, the pre-Independence\n1940s-style administrative controls\nmeant to protect labour will prove\ncounter-productive in 21st-century India.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5140157341957092, "y": 0.573057234287262 }, { "x": 0.8334484100341797, "y": 0.573057234287262 }, { "x": 0.8334484100341797, "y": 0.7556735277175903 }, { "x": 0.5140157341957092, "y": 0.7556735277175903 } ], "category": "paragraph", "id": 244, "content": { "text": "There are 1,536 laws that govern\ndoing business in India, of which 678\nare implemented at the Union level.\nWithin these laws is a web of 69,233\ncompliances, of which 25,537 are at the\nUnion level. These compliances need to\nbe communicated to the governments\nthrough 6,618 annual filings, 2,282\n(34.5 percent) at the Union level and at\nthe states, 4,336.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5142786502838135, "y": 0.7823382019996643 }, { "x": 0.8329044878482819, "y": 0.7823382019996643 }, { "x": 0.8329044878482819, "y": 0.8704861924052238 }, { "x": 0.5142786502838135, "y": 0.8704861924052238 } ], "category": "paragraph", "id": 245, "content": { "text": "These changes in compliance\nrequirements occur constantly and\nadd to business uncertainty. In the 12\nmonths up to 31 December 2021, there\nhave been 3,577 regulatory changes;\n", "html": "", "markdown": "" } } ] }, "01030000000029.pdf": { "elements": [ { "coordinates": [ { "x": 0.14625874161720276, "y": 0.027396289631724358 }, { "x": 0.4867408275604248, "y": 0.027396289631724358 }, { "x": 0.4867408275604248, "y": 0.055364903062582016 }, { "x": 0.14625874161720276, "y": 0.055364903062582016 } ], "category": "header", "id": 634, "content": { "text": "Combinatorial Cosmology\nDOI: http://dx.doi.org/10.5772/intechopen.90696\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14663027226924896, "y": 0.07473926246166229 }, { "x": 0.3069392144680023, "y": 0.07473926246166229 }, { "x": 0.3069392144680023, "y": 0.0901351198554039 }, { "x": 0.14663027226924896, "y": 0.0901351198554039 } ], "category": "heading1", "id": 635, "content": { "text": "5. The dynamics\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14641320705413818, "y": 0.10753875970840454 }, { "x": 0.8504499793052673, "y": 0.10753875970840454 }, { "x": 0.8504499793052673, "y": 0.2522898316383362 }, { "x": 0.14641320705413818, "y": 0.2522898316383362 } ], "category": "paragraph", "id": 636, "content": { "text": "The next step is to construct a model for the dynamics. The idea, which essen-\ntially goes back to Boltzmann (see [12]), is that any given macro-state at any given\ntime is extremely likely to develop into a state with higher entropy at the next\nmoment of time, simply because there are SO many more states with higher entropy\nthan with lower entropy (compare with (3)). The problem with this in the present\nsituation, however, is that this way of thinking in fact presupposes a preferred\ndirection of time. Otherwise, given that the dynamical laws are time symmetric,\nwhy can we not similarly argue that the entropy should also grow when we go\nbackward in time? (compare [9]).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14614418148994446, "y": 0.2533315122127533 }, { "x": 0.8498418033123016, "y": 0.2533315122127533 }, { "x": 0.8498418033123016, "y": 0.3012283034622669 }, { "x": 0.14614418148994446, "y": 0.3012283034622669 } ], "category": "paragraph", "id": 637, "content": { "text": "There have been many attempts to avoid this problem by looking for defects in\nthe symmetries. But my conclusion here is that we must actually accept Boltzmann's\nargument in both directions of time and hence we are led to the following:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1462610363960266, "y": 0.3023702800273895 }, { "x": 0.850200891494751, "y": 0.3023702800273895 }, { "x": 0.850200891494751, "y": 0.3788866922259331 }, { "x": 0.1462610363960266, "y": 0.3788866922259331 } ], "category": "paragraph", "id": 638, "content": { "text": "Principle 1. At every moment of time t and for every state with entropy S, there\nare very many \"accessible states\" with higher entropy, both at the previous moment\nof time t - 1 and at the next one t + 1. On the other hand, the chance for finding\nsuch accessible states with lower entropy, both at times t - 1 and t + 1, is extremely\nsmall.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14671236276626587, "y": 0.38332265615463257 }, { "x": 0.8499724268913269, "y": 0.38332265615463257 }, { "x": 0.8499724268913269, "y": 0.443820022046566 }, { "x": 0.14671236276626587, "y": 0.443820022046566 } ], "category": "paragraph", "id": 639, "content": { "text": "This principle also implies a shift of perspective in the search for time's arrow.\nRather than trying to find the reason for the asymmetry, we must concentrate on\nunderstanding why we cannot observe the symmetric structure of the multiverse as\na whole.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14628247916698456, "y": 0.44830384850502014 }, { "x": 0.8522165268659592, "y": 0.44830384850502014 }, { "x": 0.8522165268659592, "y": 0.5608130693435669 }, { "x": 0.14628247916698456, "y": 0.5608130693435669 } ], "category": "paragraph", "id": 640, "content": { "text": "As still one more simplification, let us assume that the entropy can only change\nby 1 during each unit of time. This assumption, however, has to be modified near\nthe endpoints (BB and BC) for the following reason: it is a very important aspect of\nthis approach to assume that physics during the first and last moments is very\ndifferent from the rest of the time, since at these moments quantum phenomena\ncan be expected to become global. To model this in a simple way, we can split the\nlife-span of our multiverse up into three parts:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.36165651679039, "y": 0.5761613845825195 }, { "x": 0.8283088803291321, "y": 0.5761613845825195 }, { "x": 0.8283088803291321, "y": 0.5910484027117491 }, { "x": 0.36165651679039, "y": 0.5910484027117491 } ], "category": "paragraph", "id": 641, "content": { "text": "[-To,-T1]u[-T1,T1]UT1,To].\n(4)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14671571552753448, "y": 0.6068145632743835 }, { "x": 0.833632305264473, "y": 0.6068145632743835 }, { "x": 0.833632305264473, "y": 0.6710752248764038 }, { "x": 0.14671571552753448, "y": 0.6710752248764038 } ], "category": "paragraph", "id": 642, "content": { "text": "Here the first and last parts may be called \"the extreme phases,\" which are\ncharacterized by the property that transition between very different states can be\npossible. During the \"normal phase\" in between on the other hand, physics is\nsupposed to behave more or less as we are used to.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14697322249412537, "y": 0.7096943855285645 }, { "x": 0.400370717048645, "y": 0.7096943855285645 }, { "x": 0.400370717048645, "y": 0.7255346644669771 }, { "x": 0.14697322249412537, "y": 0.7255346644669771 } ], "category": "heading1", "id": 643, "content": { "text": "6. Modeling the dynamics\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14671190083026886, "y": 0.7427776455879211 }, { "x": 0.8503942042589188, "y": 0.7427776455879211 }, { "x": 0.8503942042589188, "y": 0.8348256722092628 }, { "x": 0.14671190083026886, "y": 0.8348256722092628 } ], "category": "paragraph", "id": 644, "content": { "text": "To construct a miniature multiverse for computational purposes, one can pro-\nceed as follows: first of all, in the very small multiverses studied here, the extreme\nphases will only last for one single unit of time. Also, for ease of notation, let us put\nT1 = m, SO that the moments of time can in this context be denoted as\n-m - 1, m, m + 1, , m - + 1.\n(5)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14642249047756195, "y": 0.8527779579162598 }, { "x": 0.8501725643873215, "y": 0.8527779579162598 }, { "x": 0.8501725643873215, "y": 0.9328102171421051 }, { "x": 0.14642249047756195, "y": 0.9328102171421051 } ], "category": "paragraph", "id": 645, "content": { "text": "The dynamics is specified by randomly choosing for each state at time t with\nentropy S, K edges to states at time + 1 with entropy S + 1, and similarly K edges to\nstates at time t - 1 with entropy S+1 (with obvious modifications at the end-\npoints). In this section, again to make everything as simple as possible, K will be set\nequal to 2. These random choices are in practice carried out by the random number\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1464182585477829, "y": 0.9596924185752869 }, { "x": 0.1696963794529438, "y": 0.9596924185752869 }, { "x": 0.1696963794529438, "y": 0.9683752665296197 }, { "x": 0.1464182585477829, "y": 0.9683752665296197 } ], "category": "paragraph", "id": 646, "content": { "text": "313\n", "html": "", "markdown": "" } } ] }, "01030000000016.pdf": { "elements": [ { "coordinates": [ { "x": 0.12056836485862732, "y": 0.1975812464952469 }, { "x": 0.8819763362407684, "y": 0.1975812464952469 }, { "x": 0.8819763362407684, "y": 0.8754252344369888 }, { "x": 0.12056836485862732, "y": 0.8754252344369888 } ], "category": "table", "id": 232, "content": { "text": "", "html": "
Introduction7
I. Changing Practices, Shifting Sites7
2. Core and Periphery of Play12
Part I: New Children, Different Toys21
3. The Child as Consumer26
4. Domesticating Play30
5. The Child in the City35
6. Toys as Containers, Mediators and Promoters39
Part II: From Solitary to Networked Geographies of Play45
7. LEGO Toys: from Wooden Blocks to Plastic Bricks50
8. Brand Extension & Product Differentiation58
9. Bringing the Fans into the Company62
IO. Many-to-Many Geographies of Play66
Part III: Commercial Geographies of Play71
II. Toy Towns and Simulated Cities73
I2. A 21st-century Dollhouse: The Sims83
I3. Unwanted Play Practices in The Sims Online94
14. Commodified Geographies of Play103
Part IV: Serious Geographies of Play107
I5. Participation Tools111
16. Participation Processes119
I7. Purposeful Play122
18. Serious Geographies of Play124
Conclusion127
19. Changing Geographies of Play127
20. Making Do132
Notes137
Bibliography139
Index153
", "markdown": "" } }, { "coordinates": [ { "x": 0.343392550945282, "y": 0.14337259531021118 }, { "x": 0.6545050740242004, "y": 0.14337259531021118 }, { "x": 0.6545050740242004, "y": 0.16716672480106354 }, { "x": 0.343392550945282, "y": 0.16716672480106354 } ], "category": "heading1", "id": 292, "content": { "text": "Table of contents\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1291240006685257, "y": 0.21048492193222046 }, { "x": 0.2637292742729187, "y": 0.21048492193222046 }, { "x": 0.2637292742729187, "y": 0.22376997862011194 }, { "x": 0.1291240006685257, "y": 0.22376997862011194 } ], "category": "heading1", "id": 293, "content": { "text": "Introduction\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8606373071670532, "y": 0.21555206179618835 }, { "x": 0.8712717369198799, "y": 0.21555206179618835 }, { "x": 0.8712717369198799, "y": 0.22641445510089397 }, { "x": 0.8606373071670532, "y": 0.22641445510089397 } ], "category": "paragraph", "id": 294, "content": { "text": "7\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12858229875564575, "y": 0.2313346266746521 }, { "x": 0.470551460981369, "y": 0.2313346266746521 }, { "x": 0.470551460981369, "y": 0.24677854496985674 }, { "x": 0.12858229875564575, "y": 0.24677854496985674 } ], "category": "paragraph", "id": 295, "content": { "text": "I. Changing Practices, Shifting Sites\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12868590652942657, "y": 0.2508370578289032 }, { "x": 0.403960183262825, "y": 0.2508370578289032 }, { "x": 0.403960183262825, "y": 0.2663851734250784 }, { "x": 0.12868590652942657, "y": 0.2663851734250784 } ], "category": "paragraph", "id": 296, "content": { "text": "2. Core and Periphery of Play\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8606575727462769, "y": 0.23511183261871338 }, { "x": 0.8711952473968267, "y": 0.23511183261871338 }, { "x": 0.8711952473968267, "y": 0.2460065046325326 }, { "x": 0.8606575727462769, "y": 0.2460065046325326 } ], "category": "paragraph", "id": 297, "content": { "text": "7\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8512865304946899, "y": 0.2542717754840851 }, { "x": 0.8703225143253803, "y": 0.2542717754840851 }, { "x": 0.8703225143253803, "y": 0.2630161102861166 }, { "x": 0.8512865304946899, "y": 0.2630161102861166 } ], "category": "paragraph", "id": 298, "content": { "text": "12\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12947416305541992, "y": 0.28114187717437744 }, { "x": 0.5191718637943268, "y": 0.28114187717437744 }, { "x": 0.5191718637943268, "y": 0.2989217471331358 }, { "x": 0.12947416305541992, "y": 0.2989217471331358 } ], "category": "heading1", "id": 299, "content": { "text": "Part I: New Children, Different Toys\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8509028553962708, "y": 0.2865404188632965 }, { "x": 0.8688483890146017, "y": 0.2865404188632965 }, { "x": 0.8688483890146017, "y": 0.2951880171895027 }, { "x": 0.8509028553962708, "y": 0.2951880171895027 } ], "category": "paragraph", "id": 300, "content": { "text": "21\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12771667540073395, "y": 0.30243468284606934 }, { "x": 0.37679436802864075, "y": 0.30243468284606934 }, { "x": 0.37679436802864075, "y": 0.3181134480983019 }, { "x": 0.12771667540073395, "y": 0.3181134480983019 } ], "category": "paragraph", "id": 302, "content": { "text": "3. The Child as Consumer\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12784196436405182, "y": 0.3224080204963684 }, { "x": 0.33491335809230804, "y": 0.3224080204963684 }, { "x": 0.33491335809230804, "y": 0.33768316078931093 }, { "x": 0.12784196436405182, "y": 0.33768316078931093 } ], "category": "paragraph", "id": 303, "content": { "text": "4. Domesticating Play\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12830659747123718, "y": 0.34146809577941895 }, { "x": 0.3497924208641052, "y": 0.34146809577941895 }, { "x": 0.3497924208641052, "y": 0.35742806270718575 }, { "x": 0.12830659747123718, "y": 0.35742806270718575 } ], "category": "paragraph", "id": 304, "content": { "text": "5. The Child in the City\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1279570460319519, "y": 0.3614206612110138 }, { "x": 0.5858534276485443, "y": 0.3614206612110138 }, { "x": 0.5858534276485443, "y": 0.37641932163387537 }, { "x": 0.1279570460319519, "y": 0.37641932163387537 } ], "category": "paragraph", "id": 305, "content": { "text": "6. Toys as Containers, Mediators and Promoters\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8473587036132812, "y": 0.30338379740715027 }, { "x": 0.8700233958661556, "y": 0.30338379740715027 }, { "x": 0.8700233958661556, "y": 0.31474893260747194 }, { "x": 0.8473587036132812, "y": 0.31474893260747194 } ], "category": "paragraph", "id": 306, "content": { "text": "26\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8478479981422424, "y": 0.32581180334091187 }, { "x": 0.8706611599773169, "y": 0.32581180334091187 }, { "x": 0.8706611599773169, "y": 0.3376351650804281 }, { "x": 0.8478479981422424, "y": 0.3376351650804281 } ], "category": "paragraph", "id": 307, "content": { "text": "30\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8513404726982117, "y": 0.3453364670276642 }, { "x": 0.8706790916621685, "y": 0.3453364670276642 }, { "x": 0.8706790916621685, "y": 0.35694440081715584 }, { "x": 0.8513404726982117, "y": 0.35694440081715584 } ], "category": "paragraph", "id": 308, "content": { "text": "35\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8481547236442566, "y": 0.364884614944458 }, { "x": 0.8701052684336901, "y": 0.364884614944458 }, { "x": 0.8701052684336901, "y": 0.37638045847415924 }, { "x": 0.8481547236442566, "y": 0.37638045847415924 } ], "category": "paragraph", "id": 309, "content": { "text": "39\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12936407327651978, "y": 0.39128828048706055 }, { "x": 0.7392359375953674, "y": 0.39128828048706055 }, { "x": 0.7392359375953674, "y": 0.40936405397951603 }, { "x": 0.12936407327651978, "y": 0.40936405397951603 } ], "category": "paragraph", "id": 310, "content": { "text": "Part II: From Solitary to Networked Geographies of Play\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8490210771560669, "y": 0.3970463275909424 }, { "x": 0.8709437381476164, "y": 0.3970463275909424 }, { "x": 0.8709437381476164, "y": 0.40896506421267986 }, { "x": 0.8490210771560669, "y": 0.40896506421267986 } ], "category": "paragraph", "id": 311, "content": { "text": "45\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1273822784423828, "y": 0.41284364461898804 }, { "x": 0.6317074298858643, "y": 0.41284364461898804 }, { "x": 0.6317074298858643, "y": 0.42841645423322916 }, { "x": 0.1273822784423828, "y": 0.42841645423322916 } ], "category": "paragraph", "id": 312, "content": { "text": "7. LEGO Toys: from Wooden Blocks to Plastic Bricks\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8482624888420105, "y": 0.41623276472091675 }, { "x": 0.8707773070782423, "y": 0.41623276472091675 }, { "x": 0.8707773070782423, "y": 0.42840348836034536 }, { "x": 0.8482624888420105, "y": 0.42840348836034536 } ], "category": "paragraph", "id": 313, "content": { "text": "50\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12814292311668396, "y": 0.43256235122680664 }, { "x": 0.5560446977615356, "y": 0.43256235122680664 }, { "x": 0.5560446977615356, "y": 0.44524380285292864 }, { "x": 0.12814292311668396, "y": 0.44524380285292864 } ], "category": "paragraph", "id": 314, "content": { "text": "8. Brand Extension & Product Differentiation\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1277819722890854, "y": 0.45230308175086975 }, { "x": 0.49950815737247467, "y": 0.45230308175086975 }, { "x": 0.49950815737247467, "y": 0.46771375741809607 }, { "x": 0.1277819722890854, "y": 0.46771375741809607 } ], "category": "paragraph", "id": 315, "content": { "text": "9. Bringing the Fans into the Company\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8501572012901306, "y": 0.43316033482551575 }, { "x": 0.8708020132035017, "y": 0.43316033482551575 }, { "x": 0.8708020132035017, "y": 0.4476664690300822 }, { "x": 0.8501572012901306, "y": 0.4476664690300822 } ], "category": "paragraph", "id": 316, "content": { "text": "58\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12844203412532806, "y": 0.4714404046535492 }, { "x": 0.49626265466213226, "y": 0.4714404046535492 }, { "x": 0.49626265466213226, "y": 0.48706206399947405 }, { "x": 0.12844203412532806, "y": 0.48706206399947405 } ], "category": "paragraph", "id": 317, "content": { "text": "IO. Many-to-Many Geographies of Play\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8477250933647156, "y": 0.45281991362571716 }, { "x": 0.8702996801584959, "y": 0.45281991362571716 }, { "x": 0.8702996801584959, "y": 0.46439244505017996 }, { "x": 0.8477250933647156, "y": 0.46439244505017996 } ], "category": "paragraph", "id": 318, "content": { "text": "62\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12948213517665863, "y": 0.5017028450965881 }, { "x": 0.5761245936155319, "y": 0.5017028450965881 }, { "x": 0.5761245936155319, "y": 0.5199213195592165 }, { "x": 0.12948213517665863, "y": 0.5199213195592165 } ], "category": "paragraph", "id": 319, "content": { "text": "Part III: Commercial Geographies of Play\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8464900851249695, "y": 0.47209492325782776 }, { "x": 0.8702425807714462, "y": 0.47209492325782776 }, { "x": 0.8702425807714462, "y": 0.4837344912812114 }, { "x": 0.8464900851249695, "y": 0.4837344912812114 } ], "category": "paragraph", "id": 320, "content": { "text": "66\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12820973992347717, "y": 0.5231971740722656 }, { "x": 0.4647941291332245, "y": 0.5231971740722656 }, { "x": 0.4647941291332245, "y": 0.5384757174178958 }, { "x": 0.12820973992347717, "y": 0.5384757174178958 } ], "category": "paragraph", "id": 322, "content": { "text": "II. Toy Towns and Simulated Cities\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12847070395946503, "y": 0.5431922674179077 }, { "x": 0.4879836291074753, "y": 0.5431922674179077 }, { "x": 0.4879836291074753, "y": 0.558255928568542 }, { "x": 0.12847070395946503, "y": 0.558255928568542 } ], "category": "paragraph", "id": 323, "content": { "text": "I2. A 21st-century Dollhouse: The Sims\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12832419574260712, "y": 0.5623791813850403 }, { "x": 0.5590106397867203, "y": 0.5623791813850403 }, { "x": 0.5590106397867203, "y": 0.5783279184252024 }, { "x": 0.12832419574260712, "y": 0.5783279184252024 } ], "category": "paragraph", "id": 324, "content": { "text": "I3. Unwanted Play Practices in The Sims Online\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1281779557466507, "y": 0.581865131855011 }, { "x": 0.4893069714307785, "y": 0.581865131855011 }, { "x": 0.4893069714307785, "y": 0.5978628005832434 }, { "x": 0.1281779557466507, "y": 0.5978628005832434 } ], "category": "paragraph", "id": 325, "content": { "text": "14. 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Participation Tools\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12875108420848846, "y": 0.6535355448722839 }, { "x": 0.3789587467908859, "y": 0.6535355448722839 }, { "x": 0.3789587467908859, "y": 0.6686121840029955 }, { "x": 0.12875108420848846, "y": 0.6686121840029955 } ], "category": "paragraph", "id": 334, "content": { "text": "16. 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Purposeful Play\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8409669995307922, "y": 0.6567530035972595 }, { "x": 0.8701779432594776, "y": 0.6567530035972595 }, { "x": 0.8701779432594776, "y": 0.6684370739385486 }, { "x": 0.8409669995307922, "y": 0.6684370739385486 } ], "category": "paragraph", "id": 337, "content": { "text": "119\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1285264790058136, "y": 0.6921172142028809 }, { "x": 0.4281112551689148, "y": 0.6921172142028809 }, { "x": 0.4281112551689148, "y": 0.7077708635479212 }, { "x": 0.1285264790058136, "y": 0.7077708635479212 } ], "category": "paragraph", "id": 338, "content": { "text": "18. Serious Geographies of Play\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8393304944038391, "y": 0.6763701438903809 }, { "x": 0.8700230140239, "y": 0.6763701438903809 }, { "x": 0.8700230140239, "y": 0.6851707631722093 }, { "x": 0.8393304944038391, "y": 0.6851707631722093 } ], "category": "paragraph", "id": 339, "content": { "text": "122\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8387781977653503, "y": 0.6957927942276001 }, { "x": 0.870940774679184, "y": 0.6957927942276001 }, { "x": 0.870940774679184, "y": 0.7071861447766423 }, { "x": 0.8387781977653503, "y": 0.7071861447766423 } ], "category": "paragraph", "id": 340, "content": { "text": "124\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.83860844373703, "y": 0.6175251007080078 }, { "x": 0.8711267001926899, "y": 0.6175251007080078 }, { "x": 0.8711267001926899, "y": 0.6285240789875388 }, { "x": 0.83860844373703, "y": 0.6285240789875388 } ], "category": "paragraph", "id": 341, "content": { "text": "107\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12812888622283936, "y": 0.7229884266853333 }, { "x": 0.24999253451824188, "y": 0.7229884266853333 }, { "x": 0.24999253451824188, "y": 0.7369088400155306 }, { "x": 0.12812888622283936, "y": 0.7369088400155306 } ], "category": "paragraph", "id": 342, "content": { "text": "Conclusion\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12831607460975647, "y": 0.7438806295394897 }, { "x": 0.4514681398868561, "y": 0.7438806295394897 }, { "x": 0.4514681398868561, "y": 0.7596043162047863 }, { "x": 0.12831607460975647, "y": 0.7596043162047863 } ], "category": "paragraph", "id": 343, "content": { "text": "19. Changing Geographies of Play\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8402671217918396, "y": 0.7279489636421204 }, { "x": 0.8709866404533386, "y": 0.7279489636421204 }, { "x": 0.8709866404533386, "y": 0.7393163861706853 }, { "x": 0.8402671217918396, "y": 0.7393163861706853 } ], "category": "paragraph", "id": 344, "content": { "text": "127\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12858137488365173, "y": 0.7639027833938599 }, { "x": 0.2694981247186661, "y": 0.7639027833938599 }, { "x": 0.2694981247186661, "y": 0.7790608769282699 }, { "x": 0.12858137488365173, "y": 0.7790608769282699 } ], "category": "paragraph", "id": 345, "content": { "text": "20. Making Do\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8403345346450806, "y": 0.747463047504425 }, { "x": 0.870864437893033, "y": 0.747463047504425 }, { "x": 0.870864437893033, "y": 0.7588180042803288 }, { "x": 0.8403345346450806, "y": 0.7588180042803288 } ], "category": "paragraph", "id": 346, "content": { "text": "127\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1294979751110077, "y": 0.7954397201538086 }, { "x": 0.1936139464378357, "y": 0.7954397201538086 }, { "x": 0.1936139464378357, "y": 0.8082253159955144 }, { "x": 0.1294979751110077, "y": 0.8082253159955144 } ], "category": "paragraph", "id": 347, "content": { "text": "Notes\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8413709998130798, "y": 0.7670914530754089 }, { "x": 0.8701725360006094, "y": 0.7670914530754089 }, { "x": 0.8701725360006094, "y": 0.7786956131458282 }, { "x": 0.8413709998130798, "y": 0.7786956131458282 } ], "category": "paragraph", "id": 348, "content": { "text": "132\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8418467044830322, "y": 0.7991881966590881 }, { "x": 0.8706824909895658, "y": 0.7991881966590881 }, { "x": 0.8706824909895658, "y": 0.8111277399584651 }, { "x": 0.8418467044830322, "y": 0.8111277399584651 } ], "category": "paragraph", "id": 349, "content": { "text": "137\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1294776052236557, "y": 0.8263832926750183 }, { "x": 0.2663491368293762, "y": 0.8263832926750183 }, { "x": 0.2663491368293762, "y": 0.844145767390728 }, { "x": 0.1294776052236557, "y": 0.844145767390728 } ], "category": "paragraph", "id": 350, "content": { "text": "Bibliography\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8399350047111511, "y": 0.8315522074699402 }, { "x": 0.8702319301664829, "y": 0.8315522074699402 }, { "x": 0.8702319301664829, "y": 0.8433844316750765 }, { "x": 0.8399350047111511, "y": 0.8433844316750765 } ], "category": "paragraph", "id": 351, "content": { "text": "139\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12922638654708862, "y": 0.8591391444206238 }, { "x": 0.1890437826514244, "y": 0.8591391444206238 }, { "x": 0.1890437826514244, "y": 0.8729503806680441 }, { "x": 0.12922638654708862, "y": 0.8729503806680441 } ], "category": "paragraph", "id": 352, "content": { "text": "Index\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8430793881416321, "y": 0.8640709519386292 }, { "x": 0.870042335242033, "y": 0.8640709519386292 }, { "x": 0.870042335242033, "y": 0.8758444469422102 }, { "x": 0.8430793881416321, "y": 0.8758444469422102 } ], "category": "paragraph", "id": 353, "content": { "text": "153\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8622110486030579, "y": 0.9486733675003052 }, { "x": 0.8707734774798155, "y": 0.9486733675003052 }, { "x": 0.8707734774798155, "y": 0.9596572313457727 }, { "x": 0.8622110486030579, "y": 0.9596572313457727 } ], "category": "paragraph", "id": 354, "content": { "text": "5\n", "html": "", "markdown": "" } } ] }, "01030000000063.pdf": { "elements": [ { "coordinates": [ { "x": 0.11676088720560074, "y": 0.09386713802814484 }, { "x": 0.8826265707612038, "y": 0.09386713802814484 }, { "x": 0.8826265707612038, "y": 0.1895812749862671 }, { "x": 0.11676088720560074, "y": 0.1895812749862671 } ], "category": "paragraph", "id": 150, "content": { "text": "The other potentially invasive fouler is the tropical American Mytilopsis sallei and M. adamsi\nwhich has been recorded invasive in Singapore, Australia, Thailand among other regions. While\nthey are recorded from the Manila South Harbor, there is no evidence that it is invasive as it exists\nin low abundances.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1480395644903183, "y": 0.2448728233575821 }, { "x": 0.8411199301481247, "y": 0.2448728233575821 }, { "x": 0.8411199301481247, "y": 0.4198485463857651 }, { "x": 0.1480395644903183, "y": 0.4198485463857651 } ], "category": "figure", "id": 151, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11745458096265793, "y": 0.4379585087299347 }, { "x": 0.8657626435160637, "y": 0.4379585087299347 }, { "x": 0.8657626435160637, "y": 0.47810424864292145 }, { "x": 0.11745458096265793, "y": 0.47810424864292145 } ], "category": "paragraph", "id": 152, "content": { "text": "Figure 3. Non-indigenous macrofoulers from Manila Bay with IAS, Mytilopsis sallei and Mytella strigata\n(=charruana). (From Trinidad et aL 2019)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11732488870620728, "y": 0.5171640515327454 }, { "x": 0.8626508116722107, "y": 0.5171640515327454 }, { "x": 0.8626508116722107, "y": 0.6158894523978233 }, { "x": 0.11732488870620728, "y": 0.6158894523978233 } ], "category": "paragraph", "id": 153, "content": { "text": "Newer estimates (2021) on the number of possible IAS in Manila Bay is likely more than 30\nspecies based on more intensive biofouling ecological monitoring and the use environmental\nDNA in detecting species. When research started in 2006 on IAS in Manila Bay, 3 species were\ninitially observed.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8722172379493713, "y": 0.9224306344985962 }, { "x": 0.8817069232463837, "y": 0.9224306344985962 }, { "x": 0.8817069232463837, "y": 0.9327002633363008 }, { "x": 0.8722172379493713, "y": 0.9327002633363008 } ], "category": "paragraph", "id": 154, "content": { "text": "7\n", "html": "", "markdown": "" } } ] }, "01030000000002.pdf": { "elements": [ { "coordinates": [ { "x": 0.14146023988723755, "y": 0.0553143247961998 }, { "x": 0.16897930763661861, "y": 0.0553143247961998 }, { "x": 0.16897930763661861, "y": 0.0641276529058814 }, { "x": 0.14146023988723755, "y": 0.0641276529058814 } ], "category": "paragraph", "id": 480, "content": { "text": "316\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8063533306121826, "y": 0.055937767028808594 }, { "x": 0.8832463398575783, "y": 0.055937767028808594 }, { "x": 0.8832463398575783, "y": 0.06400234159082174 }, { "x": 0.8063533306121826, "y": 0.06400234159082174 } ], "category": "header", "id": 481, "content": { "text": "YARROW\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1409352570772171, "y": 0.09195401519536972 }, { "x": 0.8836676627397537, "y": 0.09195401519536972 }, { "x": 0.8836676627397537, "y": 0.14838847145438194 }, { "x": 0.1409352570772171, "y": 0.14838847145438194 } ], "category": "paragraph", "id": 482, "content": { "text": "where SOAS below some threshold cannot be recovered, SO that an observer\ncan only guess about order.19 However, either kind of model can easily be fitted\nand interpreted from either theoretical perspective.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14164362847805023, "y": 0.19327601790428162 }, { "x": 0.8379883617162704, "y": 0.19327601790428162 }, { "x": 0.8379883617162704, "y": 0.20971192605793476 }, { "x": 0.14164362847805023, "y": 0.20971192605793476 } ], "category": "heading1", "id": 483, "content": { "text": "8\nChoosing between Observer Models and Rejecting Participants\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14081493020057678, "y": 0.2335512936115265 }, { "x": 0.883965939283371, "y": 0.2335512936115265 }, { "x": 0.883965939283371, "y": 0.33070485293865204 }, { "x": 0.14081493020057678, "y": 0.33070485293865204 } ], "category": "paragraph", "id": 484, "content": { "text": "Two further reasonable questions one might ask are: 1) could my observer\nmodel have generated these data? and 2) does another observer model de-\nscribe the data better? Model comparison is a large and complex topic, SO once\nagain, what I have to say here should be treated as a brief introduction rather\nthan a comprehensive summary.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1405801624059677, "y": 0.334850013256073 }, { "x": 0.8835633248090744, "y": 0.334850013256073 }, { "x": 0.8835633248090744, "y": 0.6742098033428192 }, { "x": 0.1405801624059677, "y": 0.6742098033428192 } ], "category": "paragraph", "id": 485, "content": { "text": "Let's begin by considering a metric I have not yet mentioned: Deviance. De-\nviance (sometimes called G2) is a measure based on log likelihood, but which\nlooks rather more like summed squared error, in that it is zero for a perfectly\nfitting model and large/positive for a poorly fitting model. Formally, deviance\nis two times the difference in log likelihood between the saturated model and\nthe model with our current set of parameters. A saturated model is one that\nexactly predicts the data (which can always be accomplished by a model that\nhas one parameter per data point). Hence it represents the situation with the\nmaximum possible log-likelihood when predicting this particular set of data.\nDeviance is closely related to a simpler calculation (-2 X log likelihood) that\nforms the basis of a couple of well-known metrics for model comparison (the\nAkaike information criterion, AIC, and the Bayesian information criterion,\nBIC) and indeed is occasionally defined this way. That's because we are of-\nten only really interested in differences (in Deviance, or AIC, or BIC) between\nmodels, and the log-likelihood of the saturated model gets subtracted out in a\ncomparison between two models (because it has contributed to the deviance\nin the same way for both) SO calculating it is not necessary.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14044690132141113, "y": 0.6783859133720398 }, { "x": 0.8835555911064148, "y": 0.6783859133720398 }, { "x": 0.8835555911064148, "y": 0.7956254929304123 }, { "x": 0.14044690132141113, "y": 0.7956254929304123 } ], "category": "paragraph", "id": 486, "content": { "text": "However, if you want to say something about the goodness of fit of a model\nwithout relating it to any other model, based on asymptotic statistical theory,\nyou do need to calculate deviance properly. Asymptotically, it turns out that\nthe deviance of a model fitted to data when that model actually generated those\ndata follows a chi-square (x2) distribution, with degrees of freedom equal to\nthe number of data points minus the number of model parameters (note: for\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14277416467666626, "y": 0.8281773924827576 }, { "x": 0.8835122585296631, "y": 0.8281773924827576 }, { "x": 0.8835122585296631, "y": 0.8961969539523125 }, { "x": 0.14277416467666626, "y": 0.8961969539523125 } ], "category": "footer", "id": 487, "content": { "text": "19\nGarcía-Pérez and Alcalá-Quintana's commitment to this account is a little unclear, be-\ncause they often let 8 vary across experimental conditions, suggesting flexibility more\nakin to a criterion-based account. It may be that they believe a low-threshold exists, but\nthat synchrony is often additionally reported beyond this hard limit.\n", "html": "", "markdown": "" } } ] }, "01030000000129.pdf": { "elements": [ { "coordinates": [ { "x": 0.0886685699224472, "y": 0.09771489351987839 }, { "x": 0.13196957483887672, "y": 0.09771489351987839 }, { "x": 0.13196957483887672, "y": 0.11048516910523176 }, { "x": 0.0886685699224472, "y": 0.11048516910523176 } ], "category": "paragraph", "id": 378, "content": { "text": "(15.19)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08775736391544342, "y": 0.1403363198041916 }, { "x": 0.9113696962594986, "y": 0.1403363198041916 }, { "x": 0.9113696962594986, "y": 0.22945238649845123 }, { "x": 0.08775736391544342, "y": 0.22945238649845123 } ], "category": "paragraph", "id": 379, "content": { "text": "n the case that the distributions were identically distributed with expected value and variance of Ux\nand o2 each partner would face the same expected value as before, Ux. But, the variance of their\nindividual earnings would be = half of what it was before without combining\ntheir businesses. Furthermore, the standard deviation of the earnings each partner would face would\nbe:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08871188759803772, "y": 0.28109875321388245 }, { "x": 0.13641753047704697, "y": 0.28109875321388245 }, { "x": 0.13641753047704697, "y": 0.2937129382044077 }, { "x": 0.08871188759803772, "y": 0.2937129382044077 } ], "category": "paragraph", "id": 380, "content": { "text": "(15.20)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08715366572141647, "y": 0.3252977132797241 }, { "x": 0.9113901183009148, "y": 0.3252977132797241 }, { "x": 0.9113901183009148, "y": 0.36074717342853546 }, { "x": 0.08715366572141647, "y": 0.36074717342853546 } ], "category": "paragraph", "id": 381, "content": { "text": "And if n partners joined together, then they would each face the same expected value as before, but\nthe variance each partner would receive is Ox/Vn. We now illustrate these important results.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08720327168703079, "y": 0.3774752914905548 }, { "x": 0.9110521748661995, "y": 0.3774752914905548 }, { "x": 0.9110521748661995, "y": 0.44921059906482697 }, { "x": 0.08720327168703079, "y": 0.44921059906482697 } ], "category": "paragraph", "id": 382, "content": { "text": "Assume that business one's earnings are determined by outcomes associated with the toss of a fair\ncoin. If the outcome of the coin toss is tails, the firm pays (loses) $5,000. If the toss is a heads, the\nfirm wins $8,000. Thus, the firm wins either $8,000 or loses $5,000 and earns on average (.5) (-5,000) +\n(.5) (8,000) = $1500.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08720547705888748, "y": 0.4687708020210266 }, { "x": 0.47813306003808975, "y": 0.4687708020210266 }, { "x": 0.47813306003808975, "y": 0.529437642544508 }, { "x": 0.08720547705888748, "y": 0.529437642544508 } ], "category": "paragraph", "id": 383, "content": { "text": "The standard deviation of this risky outcomes is:\n(15.21)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0877041295170784, "y": 0.5548856258392334 }, { "x": 0.9107498005032539, "y": 0.5548856258392334 }, { "x": 0.9107498005032539, "y": 0.6066748164594173 }, { "x": 0.0877041295170784, "y": 0.6066748164594173 } ], "category": "paragraph", "id": 384, "content": { "text": "Furthermore, assuming a normal distribution, 68% of the time, the average outcome will be between\nthe mean and plus or minus one standard deviation: ($1,500 + $6,500) = $8,000 and\n($1,500 - $6,500) = -$5,000.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08780263364315033, "y": 0.6263942718505859 }, { "x": 0.9114543050527573, "y": 0.6263942718505859 }, { "x": 0.9114543050527573, "y": 0.7375611290335655 }, { "x": 0.08780263364315033, "y": 0.7375611290335655 } ], "category": "paragraph", "id": 385, "content": { "text": "Now suppose that two persons decide to combine their operations and share the average of the\noutcomes. Then the possible outcomes of two coin tosses are two heads (H, H) which earns on\naverage $16,000/2 = $8,000 and occurs with a probability of .25; two tails (T,T) which earns on average\n-$10,000/2=-$5,000 = and occurs with a probability of .25, and one head and one tail (H, T) or one tail\nand one head (T, H) which both earn on average $3,000/2 = $1,500 and each occurs with a probability\nof .25. The expected value for each of the two players can now can be expressed as:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0886656865477562, "y": 0.75204998254776 }, { "x": 0.7686400040984154, "y": 0.75204998254776 }, { "x": 0.7686400040984154, "y": 0.7718615513294935 }, { "x": 0.0886656865477562, "y": 0.7718615513294935 } ], "category": "paragraph", "id": 386, "content": { "text": "(15.22) + (.25) )(-$5,000) + (.25) ($1,500) + (.25) ($1,50 =\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08715565502643585, "y": 0.7897613644599915 }, { "x": 0.910624161362648, "y": 0.7897613644599915 }, { "x": 0.910624161362648, "y": 0.822601068764925 }, { "x": 0.08715565502643585, "y": 0.822601068764925 } ], "category": "paragraph", "id": 387, "content": { "text": "The two players now receive on average the same as before, $1,500, but consider the standard\ndeviation of the average outcome:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12023267149925232, "y": 0.9510847926139832 }, { "x": 0.12287482619285583, "y": 0.9510847926139832 }, { "x": 0.12287482619285583, "y": 0.9611556082963943 }, { "x": 0.12023267149925232, "y": 0.9611556082963943 } ], "category": "paragraph", "id": 388, "content": { "text": "I\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08750518411397934, "y": 0.9514905214309692 }, { "x": 0.11218217015266418, "y": 0.9514905214309692 }, { "x": 0.11218217015266418, "y": 0.9595254762098193 }, { "x": 0.08750518411397934, "y": 0.9595254762098193 } ], "category": "paragraph", "id": 389, "content": { "text": "340\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.13033781945705414, "y": 0.951378345489502 }, { "x": 0.36727192997932434, "y": 0.951378345489502 }, { "x": 0.36727192997932434, "y": 0.9616122068837285 }, { "x": 0.13033781945705414, "y": 0.9616122068837285 } ], "category": "footer", "id": 390, "content": { "text": "Ch. 15. Homogeneous Risk Measures\n", "html": "", "markdown": "" } } ] }, "01030000000066.pdf": { "elements": [ { "coordinates": [ { "x": 0.15838809311389923, "y": 0.10434657335281372 }, { "x": 0.8077626377344131, "y": 0.10434657335281372 }, { "x": 0.8077626377344131, "y": 0.15645833685994148 }, { "x": 0.15838809311389923, "y": 0.15645833685994148 } ], "category": "paragraph", "id": 367, "content": { "text": "consumption onsite or offsite. Food Service Establishments (FSE) refers to the business\nengaged in the Food Service Industry. For purposes of the survey, the FSE is segmented\ninto:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16099974513053894, "y": 0.1648971438407898 }, { "x": 0.6354048550128937, "y": 0.1648971438407898 }, { "x": 0.6354048550128937, "y": 0.17876009177416563 }, { "x": 0.16099974513053894, "y": 0.17876009177416563 } ], "category": "paragraph", "id": 369, "content": { "text": "full-service restaurants, with full menu and waiting service;\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16151143610477448, "y": 0.1851656585931778 }, { "x": 0.7946687489748001, "y": 0.1851656585931778 }, { "x": 0.7946687489748001, "y": 0.2196231707930565 }, { "x": 0.16151143610477448, "y": 0.2196231707930565 } ], "category": "paragraph", "id": 370, "content": { "text": "limited-service restaurants or quick service restaurants (QSR), with full menu but\npay-as-you-order such as fast food or turo-turo type8;\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16128180921077728, "y": 0.2255067676305771 }, { "x": 0.6692113727331161, "y": 0.2255067676305771 }, { "x": 0.6692113727331161, "y": 0.2391473464667797 }, { "x": 0.16128180921077728, "y": 0.2391473464667797 } ], "category": "paragraph", "id": 371, "content": { "text": "cafes/bars/pop-ups (selected menu with few chairs and tables);\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1612675040960312, "y": 0.24586409330368042 }, { "x": 0.6652082651853561, "y": 0.24586409330368042 }, { "x": 0.6652082651853561, "y": 0.25975275598466396 }, { "x": 0.1612675040960312, "y": 0.25975275598466396 } ], "category": "paragraph", "id": 372, "content": { "text": "kiosks and stalls (purely retail, to be consumed elsewhere); and\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1614692658185959, "y": 0.2663910686969757 }, { "x": 0.43910934031009674, "y": 0.2663910686969757 }, { "x": 0.43910934031009674, "y": 0.2800700645893812 }, { "x": 0.1614692658185959, "y": 0.2800700645893812 } ], "category": "paragraph", "id": 373, "content": { "text": "catering or 100% home delivery.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16176962852478027, "y": 0.3061879873275757 }, { "x": 0.7893654108047485, "y": 0.3061879873275757 }, { "x": 0.7893654108047485, "y": 0.34099169820547104 }, { "x": 0.16176962852478027, "y": 0.34099169820547104 } ], "category": "paragraph", "id": 374, "content": { "text": "Full-service restaurants, limited-service restaurants and cafes/bars/pop-ups may also\noffer \"to go\" or \"take away\" services.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1351976841688156, "y": 0.3788457214832306 }, { "x": 0.2643247991800308, "y": 0.3788457214832306 }, { "x": 0.2643247991800308, "y": 0.4767107293009758 }, { "x": 0.1351976841688156, "y": 0.4767107293009758 } ], "category": "figure", "id": 375, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.27138563990592957, "y": 0.37794631719589233 }, { "x": 0.4008485972881317, "y": 0.37794631719589233 }, { "x": 0.4008485972881317, "y": 0.47581591457128525 }, { "x": 0.27138563990592957, "y": 0.47581591457128525 } ], "category": "figure", "id": 376, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.4083411693572998, "y": 0.3757126033306122 }, { "x": 0.5371695160865784, "y": 0.3757126033306122 }, { "x": 0.5371695160865784, "y": 0.47592198103666306 }, { "x": 0.4083411693572998, "y": 0.47592198103666306 } ], "category": "figure", "id": 377, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5444447994232178, "y": 0.37848374247550964 }, { "x": 0.6715544909238815, "y": 0.37848374247550964 }, { "x": 0.6715544909238815, "y": 0.4760265424847603 }, { "x": 0.5444447994232178, "y": 0.4760265424847603 } ], "category": "figure", "id": 378, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.38375604152679443, "y": 0.4877486824989319 }, { "x": 0.5446241945028305, "y": 0.4877486824989319 }, { "x": 0.5446241945028305, "y": 0.49890604987740517 }, { "x": 0.38375604152679443, "y": 0.49890604987740517 } ], "category": "paragraph", "id": 379, "content": { "text": "Figure 1. FSI Segmentation\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.6818569898605347, "y": 0.3789199888706207 }, { "x": 0.8098424971103668, "y": 0.3789199888706207 }, { "x": 0.8098424971103668, "y": 0.47613413631916046 }, { "x": 0.6818569898605347, "y": 0.47613413631916046 } ], "category": "figure", "id": 380, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11748077720403671, "y": 0.5396525859832764 }, { "x": 0.815504215657711, "y": 0.5396525859832764 }, { "x": 0.815504215657711, "y": 0.7356688678264618 }, { "x": 0.11748077720403671, "y": 0.7356688678264618 } ], "category": "paragraph", "id": 381, "content": { "text": "b.\nPlastic. The Baseline Study looked into the extent of Plastic use of FSEs in Dasmariñas\nCity. Plastics are categorized by food grade. The six food grades are 1) Polyethylene\nTerephthalate: clear, tough plastic such as soft drinks, juice and water, (2) High Density\nPolyethylene: white or colored plastic such as milk containers, (3) Polyvinyl Chloride:\nhard rigid clear plastic such as cordial bottles; (4) Low Density Polyethylene: soft,\nflexible such as squeezable bottles; 5) Polypropylene: hard but flexible plastics such as\nmicrowave ware; takeaway containers, some yogurt or jam containers and hinged lunch\nboxes, and (6) Polystyrene: rigid, brittle plastics such as small tubes and margarine or\nbutter container. See Figure 1. Plastic litter found in the rivers are of categories 1-6. There\nare also other plastics that do not fall under food grade 1-6.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11843636631965637, "y": 0.825494647026062 }, { "x": 0.8222257196903229, "y": 0.825494647026062 }, { "x": 0.8222257196903229, "y": 0.8841634765267372 }, { "x": 0.11843636631965637, "y": 0.8841634765267372 } ], "category": "footer", "id": 382, "content": { "text": "8\nFilipino word for restaurants where a menu of cooked or ready-to-eat food are on display and clients point to their choice of food and\npay as they take their food to their tables or ask for take-out packaging.\n9\nFood grade plastics refer to plastic containers, tools or other supplies made of plastics that are cleared to be used for food\npreparation, handling, and service.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.03219043090939522, "y": 0.9456509351730347 }, { "x": 0.05396519787609577, "y": 0.9456509351730347 }, { "x": 0.05396519787609577, "y": 0.958944546058774 }, { "x": 0.03219043090939522, "y": 0.958944546058774 } ], "category": "paragraph", "id": 383, "content": { "text": "18\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08475057035684586, "y": 0.9476402401924133 }, { "x": 0.5654876306653023, "y": 0.9476402401924133 }, { "x": 0.5654876306653023, "y": 0.9605842772871256 }, { "x": 0.08475057035684586, "y": 0.9605842772871256 } ], "category": "footer", "id": 384, "content": { "text": "Study on Plastics Use and Waste Management in the Food Service Industry\n", "html": "", "markdown": "" } } ] }, "01030000000121.pdf": { "elements": [ { "coordinates": [ { "x": 0.11739519238471985, "y": 0.4732123613357544 }, { "x": 0.88104447722435, "y": 0.4732123613357544 }, { "x": 0.88104447722435, "y": 0.6168432682752609 }, { "x": 0.11739519238471985, "y": 0.6168432682752609 } ], "category": "table", "id": 473, "content": { "text": "", "html": "
ReagentsSupplies and Equipment
At each student station: Resuspended DNA or ethanol precipitates from Part 1* To be shared by all groups: \"Evidence A\" DNA* \"Evidence B\" DNA* Restriction Buffer-RNase A* BamHI-HindIII restriction enzyme mixture* Sterile distilled or deionized waterMicrocentrifuge tube rack 3 1.5-mL microcentrifuge tubes Micropipet, -20 uL Micropipet tips Beaker or similar container for waste Beaker or similar container filled with ice Permanent marker Water bath at 37°C
", "markdown": "" } }, { "coordinates": [ { "x": 0.11732808500528336, "y": 0.049614738672971725 }, { "x": 0.3928717151284218, "y": 0.049614738672971725 }, { "x": 0.3928717151284218, "y": 0.06350523419678211 }, { "x": 0.11732808500528336, "y": 0.06350523419678211 } ], "category": "header", "id": 481, "content": { "text": "MOHAVE COMMUNITY COLLEGE\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.7974461913108826, "y": 0.05097561329603195 }, { "x": 0.8668214082717896, "y": 0.05097561329603195 }, { "x": 0.8668214082717896, "y": 0.063381209038198 }, { "x": 0.7974461913108826, "y": 0.063381209038198 } ], "category": "header", "id": 482, "content": { "text": "BIO181\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11822210997343063, "y": 0.09295136481523514 }, { "x": 0.7620451375842094, "y": 0.09295136481523514 }, { "x": 0.7620451375842094, "y": 0.10594693850725889 }, { "x": 0.11822210997343063, "y": 0.10594693850725889 } ], "category": "paragraph", "id": 483, "content": { "text": "16. Place the tubes in a balanced configuration in the microcentrifuge and spin for 3 minutes.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11841996759176254, "y": 0.1266050934791565 }, { "x": 0.8397082909941673, "y": 0.1266050934791565 }, { "x": 0.8397082909941673, "y": 0.15461183339357376 }, { "x": 0.11841996759176254, "y": 0.15461183339357376 } ], "category": "paragraph", "id": 485, "content": { "text": "17. Carefully pour off the supernatant from both tubes. Do not disturb the nucleic acid pellets. Invert the\ntubes and tap them gently on the surface of a clean paper towel to drain them thoroughly.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11818937957286835, "y": 0.1737411469221115 }, { "x": 0.8788431137800217, "y": 0.1737411469221115 }, { "x": 0.8788431137800217, "y": 0.2166542261838913 }, { "x": 0.11818937957286835, "y": 0.2166542261838913 } ], "category": "paragraph", "id": 486, "content": { "text": "18. Briefly spin the tubes in a balanced configuration in the microcentrifuge to bring any remaining ethanol to\nthe bottom of the tube. Then use the micropipette to remove any remaining ethanol. Use a fresh tip for each\ntube. Be careful not to disturb the nucleic acid pellet.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11839423328638077, "y": 0.23600803315639496 }, { "x": 0.8304741755127907, "y": 0.23600803315639496 }, { "x": 0.8304741755127907, "y": 0.2638868745416403 }, { "x": 0.11839423328638077, "y": 0.2638868745416403 } ], "category": "paragraph", "id": 487, "content": { "text": "19. Allow the tubes to dry by leaving the tube caps open for 3-5 minutes. Inspect each tube carefully to\nensure that the tube interior is completely dry.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.197423055768013, "y": 0.28315457701683044 }, { "x": 0.7920823246240616, "y": 0.28315457701683044 }, { "x": 0.7920823246240616, "y": 0.29651268664747477 }, { "x": 0.197423055768013, "y": 0.29651268664747477 } ], "category": "paragraph", "id": 488, "content": { "text": "***Congratulations, you have just completed the miniprep plasmid DNA extraction!!!**\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11695752292871475, "y": 0.3158119022846222 }, { "x": 0.6312495842576027, "y": 0.3158119022846222 }, { "x": 0.6312495842576027, "y": 0.3287876322865486 }, { "x": 0.11695752292871475, "y": 0.3287876322865486 } ], "category": "heading1", "id": 489, "content": { "text": "Restriction Enzyme Digest Prep (switch to the 1- 20-uL micropipette):\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15222956240177155, "y": 0.34778615832328796 }, { "x": 0.8741935640573502, "y": 0.34778615832328796 }, { "x": 0.8741935640573502, "y": 0.41810646653175354 }, { "x": 0.15222956240177155, "y": 0.41810646653175354 } ], "category": "paragraph", "id": 490, "content": { "text": "20. Use a micropipette to add 10 uL of tris-EDTA solution (TE) to each tube. Use a new tip for each tube.\nDissolve the pellets by pipetting in and out. Rinse the sides of the tube several times, concentrating on\nthe area where the nucleic acid pellet or particles were observed. Check that no particles remain in the\npipet tip or on the side of the tube. Use the entire contents of each tube in the restriction digest that\nfollows.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11752606928348541, "y": 0.44063398241996765 }, { "x": 0.7332890778779984, "y": 0.44063398241996765 }, { "x": 0.7332890778779984, "y": 0.4562535220757127 }, { "x": 0.11752606928348541, "y": 0.4562535220757127 } ], "category": "paragraph", "id": 491, "content": { "text": "II. Set Up the Restriction Digests of the \"Suspect\" and \"Evidence\" DNA\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11723555624485016, "y": 0.63694828748703 }, { "x": 0.1969517469406128, "y": 0.63694828748703 }, { "x": 0.1969517469406128, "y": 0.6461551198735833 }, { "x": 0.11723555624485016, "y": 0.6461551198735833 } ], "category": "paragraph", "id": 493, "content": { "text": "*Store on ice\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11773516237735748, "y": 0.6678038239479065 }, { "x": 0.7272516041994095, "y": 0.6678038239479065 }, { "x": 0.7272516041994095, "y": 0.6808949233964086 }, { "x": 0.11773516237735748, "y": 0.6808949233964086 } ], "category": "paragraph", "id": 494, "content": { "text": "NOTE: Your instructor will assign you to use either \"Evidence A\" DNA or \"Evidence B\" DNA\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11805804073810577, "y": 0.7311275601387024 }, { "x": 0.8694567233324051, "y": 0.7311275601387024 }, { "x": 0.8694567233324051, "y": 0.774130504578352 }, { "x": 0.11805804073810577, "y": 0.774130504578352 } ], "category": "paragraph", "id": 496, "content": { "text": "1. Label the three 1.5-mL microcentrifuge tubes in which you will perform the restriction digests: \"S1\" for\nSuspect 1, \"S2\" for Suspect 2, and either \"EA\" for Evidence A or \"EB\" for Evidence B. All three samples will be\ndigested by the restriction enzymes BamHI and HindIII.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11750330775976181, "y": 0.7932201623916626 }, { "x": 0.8712456449866295, "y": 0.7932201623916626 }, { "x": 0.8712456449866295, "y": 0.8362462744116783 }, { "x": 0.11750330775976181, "y": 0.8362462744116783 } ], "category": "paragraph", "id": 497, "content": { "text": "2.\nUse the table below (next page) as a checklist while adding reagents to each reaction. Read down each\ncolumn, adding the same reagent to all appropriate tubes. To avoid cross contamination, use a fresh pipet tip\neach time you add a reagent to a tube.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.48560836911201477, "y": 0.9251266121864319 }, { "x": 0.5142652466893196, "y": 0.9251266121864319 }, { "x": 0.5142652466893196, "y": 0.9357645250856876 }, { "x": 0.48560836911201477, "y": 0.9357645250856876 } ], "category": "paragraph", "id": 498, "content": { "text": "132\n", "html": "", "markdown": "" } } ] }, "01030000000176.pdf": { "elements": [ { "coordinates": [ { "x": 0.14184343814849854, "y": 0.09702857583761215 }, { "x": 0.8578086495399475, "y": 0.09702857583761215 }, { "x": 0.8578086495399475, "y": 0.1585264466702938 }, { "x": 0.14184343814849854, "y": 0.1585264466702938 } ], "category": "paragraph", "id": 275, "content": { "text": "vapor and other gases, making it useless. Only in the vacuum of\nspace can optical elements be cooled to hundreds of degrees below\nfreezing and still remain operational.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14213819801807404, "y": 0.1658615916967392 }, { "x": 0.8563614040613174, "y": 0.1658615916967392 }, { "x": 0.8563614040613174, "y": 0.5476295202970505 }, { "x": 0.14213819801807404, "y": 0.5476295202970505 } ], "category": "paragraph", "id": 276, "content": { "text": "The first orbiting infrared observatory, launched in 1983, was the\nInfrared Astronomical Satellite (IRAS), built as a joint project by\nthe United States, the Netherlands, and Britain. IRAS was equipped\nwith a 0.6-meter telescope cooled to a temperature of less than 10\nK. For the first time, the infrared sky could be seen as if it were\nnight, rather than through a bright foreground of atmospheric and\ntelescope emissions. IRAS carried out a rapid but comprehensive\nsurvey of the entire infrared sky over a 10-month period, cataloging\nabout 350,000 sources of infrared radiation. Since then, several\nother infrared telescopes have operated in space with much better\nsensitivity and resolution due to improvements in infrared\ndetectors. The most powerful of these infrared telescopes is the\n0.85-meter Spitzer Space Telescope, which launched in 2003. A\nfew of its observations are shown in Figure 2. With infrared\nobservations, astronomers can detect cooler parts of cosmic\nobjects, such as the dust clouds around star nurseries and the\nremnants of dying stars, that visible-light images don't reveal.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16834087669849396, "y": 0.603997528553009 }, { "x": 0.8305204063653946, "y": 0.603997528553009 }, { "x": 0.8305204063653946, "y": 0.6529007218778133 }, { "x": 0.16834087669849396, "y": 0.6529007218778133 } ], "category": "heading1", "id": 277, "content": { "text": "Observations from the Spitzer Space Telescope\n(SST).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14215119183063507, "y": 0.6908164024353027 }, { "x": 0.3523958772420883, "y": 0.6908164024353027 }, { "x": 0.3523958772420883, "y": 0.8262483477592468 }, { "x": 0.14215119183063507, "y": 0.8262483477592468 } ], "category": "figure", "id": 278, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.20576980710029602, "y": 0.8340831995010376 }, { "x": 0.2889470234513283, "y": 0.8340831995010376 }, { "x": 0.2889470234513283, "y": 0.8416230948641896 }, { "x": 0.20576980710029602, "y": 0.8416230948641896 } ], "category": "paragraph", "id": 279, "content": { "text": "Flame nebula\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3917773365974426, "y": 0.6900831460952759 }, { "x": 0.6075338870286942, "y": 0.6900831460952759 }, { "x": 0.6075338870286942, "y": 0.8263138681650162 }, { "x": 0.3917773365974426, "y": 0.8263138681650162 } ], "category": "figure", "id": 280, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.4599784314632416, "y": 0.8342413306236267 }, { "x": 0.5403908938169479, "y": 0.8342413306236267 }, { "x": 0.5403908938169479, "y": 0.8432074012234807 }, { "x": 0.4599784314632416, "y": 0.8432074012234807 } ], "category": "paragraph", "id": 281, "content": { "text": "Cassiopeia A\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.6484284400939941, "y": 0.6909210085868835 }, { "x": 0.8566505163908005, "y": 0.6909210085868835 }, { "x": 0.8566505163908005, "y": 0.8255927860736847 }, { "x": 0.6484284400939941, "y": 0.8255927860736847 } ], "category": "figure", "id": 282, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.7145559787750244, "y": 0.8341606855392456 }, { "x": 0.7897257804870605, "y": 0.8341606855392456 }, { "x": 0.7897257804870605, "y": 0.8416902162134647 }, { "x": 0.7145559787750244, "y": 0.8416902162134647 } ], "category": "paragraph", "id": 283, "content": { "text": "Helix nebula\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1729806810617447, "y": 0.8555821180343628 }, { "x": 0.8429785519838333, "y": 0.8555821180343628 }, { "x": 0.8429785519838333, "y": 0.8945405185222626 }, { "x": 0.1729806810617447, "y": 0.8945405185222626 } ], "category": "paragraph", "id": 284, "content": { "text": "Figure 2. These infrared images-a region of star formation, the\nremnant of an exploded star, and a region where an old star is\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14300431311130524, "y": 0.9242676496505737 }, { "x": 0.1758676841855049, "y": 0.9242676496505737 }, { "x": 0.1758676841855049, "y": 0.93441266939044 }, { "x": 0.14300431311130524, "y": 0.93441266939044 } ], "category": "paragraph", "id": 285, "content": { "text": "336\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.2033425122499466, "y": 0.9238237142562866 }, { "x": 0.8039126545190811, "y": 0.9238237142562866 }, { "x": 0.8039126545190811, "y": 0.9380489094182849 }, { "x": 0.2033425122499466, "y": 0.9380489094182849 } ], "category": "footer", "id": 286, "content": { "text": "Chapter 6 Section 6.5: Observations outside Earth's Atmosphere\n", "html": "", "markdown": "" } } ] }, "01030000000085.pdf": { "elements": [ { "coordinates": [ { "x": 0.11493481695652008, "y": 0.09639890491962433 }, { "x": 0.2855408191680908, "y": 0.09639890491962433 }, { "x": 0.2855408191680908, "y": 0.21541579067707062 }, { "x": 0.11493481695652008, "y": 0.21541579067707062 } ], "category": "header", "id": 47, "content": { "text": "LAW\nLIBRARY\nLIBRARY OF CONGRESS\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.18115094304084778, "y": 0.3454506993293762 }, { "x": 0.810966819524765, "y": 0.3454506993293762 }, { "x": 0.810966819524765, "y": 0.45660635828971863 }, { "x": 0.18115094304084778, "y": 0.45660635828971863 } ], "category": "paragraph", "id": 48, "content": { "text": "Restrictions on Land Ownership\nby Foreigners in Selected\nJurisdictions\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.44581955671310425, "y": 0.4998226463794708 }, { "x": 0.5509278997778893, "y": 0.4998226463794708 }, { "x": 0.5509278997778893, "y": 0.5178322046995163 }, { "x": 0.44581955671310425, "y": 0.5178322046995163 } ], "category": "paragraph", "id": 49, "content": { "text": "June 2023\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.40428492426872253, "y": 0.7861417531967163 }, { "x": 0.5939605385065079, "y": 0.7861417531967163 }, { "x": 0.5939605385065079, "y": 0.8134141191840172 }, { "x": 0.40428492426872253, "y": 0.8134141191840172 } ], "category": "paragraph", "id": 50, "content": { "text": "LL File No. 2023-022255\nLRA-D-PUB-002612\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.25463762879371643, "y": 0.923646867275238 }, { "x": 0.743439257144928, "y": 0.923646867275238 }, { "x": 0.743439257144928, "y": 0.9549548178911209 }, { "x": 0.25463762879371643, "y": 0.9549548178911209 } ], "category": "footer", "id": 51, "content": { "text": "The Law Library of Congress, Global Legal Research Directorate\n(202) 707-5080 . law@loc.gov http://www.law.gov\n", "html": "", "markdown": "" } } ] }, "01030000000094.pdf": { "elements": [ { "coordinates": [ { "x": 0.19858567416667938, "y": 0.06949901580810547 }, { "x": 0.8396195024251938, "y": 0.06949901580810547 }, { "x": 0.8396195024251938, "y": 0.37503549456596375 }, { "x": 0.19858567416667938, "y": 0.37503549456596375 } ], "category": "figure", "id": 290, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.17102855443954468, "y": 0.3957608640193939 }, { "x": 0.8944607377052307, "y": 0.3957608640193939 }, { "x": 0.8944607377052307, "y": 0.49591730535030365 }, { "x": 0.17102855443954468, "y": 0.49591730535030365 } ], "category": "paragraph", "id": 292, "content": { "text": "6. Warning: This question concerns a politically charged event that occurred on January\n18, 2019, at the Indigenous People's March in Washington, D.C. After reading this\naccount of what happened at the march, and viewing this video of the event, which of\nthe effects presented in this chapter do you think best describes this episode in our\nnation's history?\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.17124046385288239, "y": 0.5146101117134094 }, { "x": 0.9011945277452469, "y": 0.5146101117134094 }, { "x": 0.9011945277452469, "y": 0.5970002114772797 }, { "x": 0.17124046385288239, "y": 0.5970002114772797 } ], "category": "paragraph", "id": 293, "content": { "text": "7. Think of a situation in your own life when you framed information (either wittingly or\nunwittingly) in such a way that helped pre-determine an outcome. Describe the\nsituation and how you framed the information. Was the outcome improved or\nworsened as a result of how you framed the information?\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.17208416759967804, "y": 0.6146894097328186 }, { "x": 0.8923184424638748, "y": 0.6146894097328186 }, { "x": 0.8923184424638748, "y": 0.6582273952662945 }, { "x": 0.17208416759967804, "y": 0.6582273952662945 } ], "category": "paragraph", "id": 294, "content": { "text": "8. After having learned about the Anchoring Effect in this chapter, do you think you will\never fall for something like this again?\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1706985980272293, "y": 0.6755284070968628 }, { "x": 0.9072432070970535, "y": 0.6755284070968628 }, { "x": 0.9072432070970535, "y": 0.7427085712552071 }, { "x": 0.1706985980272293, "y": 0.7427085712552071 } ], "category": "paragraph", "id": 295, "content": { "text": "9. When someone admonishes you \"not to judge a book by its cover,\" or as British\nmanagement journalist Robert Heller once noted, \"Never ignore a gut feeling, but never\nbelieve that it's enough,\" what heuristic(s) is he unwittingly advising you to avoid using?\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16327054798603058, "y": 0.7565283179283142 }, { "x": 0.8763434439897537, "y": 0.7565283179283142 }, { "x": 0.8763434439897537, "y": 0.8169406875967979 }, { "x": 0.16327054798603058, "y": 0.8169406875967979 } ], "category": "paragraph", "id": 296, "content": { "text": "10. Browse the internet for information about an effect that was not discussed in this\nchapter. Can you classify this effect as a special case of a Priming or Framing Effect?\nExplain.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16321225464344025, "y": 0.8369156122207642 }, { "x": 0.8677567392587662, "y": 0.8369156122207642 }, { "x": 0.8677567392587662, "y": 0.8796649426221848 }, { "x": 0.16321225464344025, "y": 0.8796649426221848 } ], "category": "paragraph", "id": 297, "content": { "text": "11. Browse the internet for a heuristic other than the Affect and Availability Heuristics\ndescribed in this chapter. Explain the heuristic.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16431105136871338, "y": 0.8972420692443848 }, { "x": 0.8766883015632629, "y": 0.8972420692443848 }, { "x": 0.8766883015632629, "y": 0.9234457835555077 }, { "x": 0.16431105136871338, "y": 0.9234457835555077 } ], "category": "paragraph", "id": 298, "content": { "text": "12. It's one thing to detect the existence of a Silo Effect and quite another to measure its\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09214959293603897, "y": 0.9498514533042908 }, { "x": 0.22996971756219864, "y": 0.9498514533042908 }, { "x": 0.22996971756219864, "y": 0.9598653241991997 }, { "x": 0.09214959293603897, "y": 0.9598653241991997 } ], "category": "footer", "id": 299, "content": { "text": "24 ARTHUR J. CAPLAN\n", "html": "", "markdown": "" } } ] }, "01030000000022.pdf": { "elements": [ { "coordinates": [ { "x": 0.15515299141407013, "y": 0.08684885501861572 }, { "x": 0.2821691185235977, "y": 0.08684885501861572 }, { "x": 0.2821691185235977, "y": 0.09637482278048992 }, { "x": 0.15515299141407013, "y": 0.09637482278048992 } ], "category": "header", "id": 454, "content": { "text": "At Home in Exile\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15574043989181519, "y": 0.1190415695309639 }, { "x": 0.8690356612205505, "y": 0.1190415695309639 }, { "x": 0.8690356612205505, "y": 0.3155299499630928 }, { "x": 0.15574043989181519, "y": 0.3155299499630928 } ], "category": "paragraph", "id": 455, "content": { "text": "To prepare myself for the journey from my home in Canberra, Australia,\nI visited the National Library's vast collection of maps. But I could not\nfind Steinkirche, even in old German records of Silesia. The Polish-\nGerman Gazeteer, which has a remarkable list of old German place-names\nin relation to their Polish replacements, and vice versa, gave the names\nfor many places, including Märzdorf where my mother had worked as\na young woman, on an estate near the Oder River. But there was nothing\nfor Steinkirche. The people assembling the directory must have thought it\nsimply the description of a stone church, as the name suggests, rather than\nthe actual name for the place where the church stood.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15632809698581696, "y": 0.3308832049369812 }, { "x": 0.8691134005784988, "y": 0.3308832049369812 }, { "x": 0.8691134005784988, "y": 0.48739753663539886 }, { "x": 0.15632809698581696, "y": 0.48739753663539886 } ], "category": "paragraph", "id": 456, "content": { "text": "Obviously it was not an important village. No one in our extended family\ncould give me the Polish names for rural Steinkirche or of Neumarkt Platz\nin the Silesian metropolis. Had Steinkirche been north, east, west or south\nof Breslau? In my mind's eye I assumed it to be east-towards Posen-\nmistakenly, SO I was to discover. In answer to one of my many questions,\nI recalled that my mother had once told me that it had taken her about an\nhour by train to travel to the school she attended briefly in Breslau. It was\nan important clue.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15609484910964966, "y": 0.5027672648429871 }, { "x": 0.8719088435173035, "y": 0.5027672648429871 }, { "x": 0.8719088435173035, "y": 0.6588393598794937 }, { "x": 0.15609484910964966, "y": 0.6588393598794937 } ], "category": "paragraph", "id": 457, "content": { "text": "I then rang my cousin, Peter Erlanger, but neither he nor his older sister\ncould help me. Peter advised me to try to find Steinkirche using my\ncomputer's Internet search engine. It was enlightened advice, and was to\nprovide me with a key clue. The website yielded a huge list of entries,\nmostly concerning stone churches in present-day Germany. But there was\nalso a reference to a 1928 visit by a church official inspecting a number of\ncommunities overseen by the Lutheran Church at Strehlen. I had often\nheard my mother and her sister refer to acquaintances in Strehlen.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.155912384390831, "y": 0.675362765789032 }, { "x": 0.8716153353452682, "y": 0.675362765789032 }, { "x": 0.8716153353452682, "y": 0.8513337075710297 }, { "x": 0.155912384390831, "y": 0.8513337075710297 } ], "category": "paragraph", "id": 458, "content": { "text": "The article about Steinkirche described it as having a 1264 Polish Catholic\nfoundation, on a site where pagan sacrifices had taken place. This\nseemed to have the ring of truth. The description offered a brief history\nof the church and gave illustrations of it in various stages of alteration.\nBy the seventeenth century, the place had become Lutheran and in the\nfollowing 200 years the community's religious confidence expressed itself\narchitecturally, through continual improvements. A church tower with\nbaroque spire was raised and the interior refurbished with an upper-storey\nbalcony with pews on three sides.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09147489815950394, "y": 0.9319766163825989 }, { "x": 0.09977824613451958, "y": 0.9319766163825989 }, { "x": 0.09977824613451958, "y": 0.9405221790075302 }, { "x": 0.09147489815950394, "y": 0.9405221790075302 } ], "category": "paragraph", "id": 459, "content": { "text": "8\n", "html": "", "markdown": "" } } ] }, "01030000000134.pdf": { "elements": [ { "coordinates": [ { "x": 0.09745077788829803, "y": 0.0823872908949852 }, { "x": 0.9015337079763412, "y": 0.0823872908949852 }, { "x": 0.9015337079763412, "y": 0.17427046597003937 }, { "x": 0.09745077788829803, "y": 0.17427046597003937 } ], "category": "paragraph", "id": 290, "content": { "text": "What's unique about the growth of Alligator Gars is their fast growth in the first years of life followed by slower\ngrowth (Figure 8.6; Figure 8.7). Juvenile Alligator Gars quickly transition to fish-eating habits (Butler et al. 2018).\nA fish diet means the juveniles grow at 4-5 mm per day in the first three months of life, SO that by the end of the\nfirst growing season they may reach 1.5 to 2 feet in length (~40-70 cm) and 8-10 pounds in weight (Sakaris et al.\n2019). Despite their fast growth, young Alligator Gars are preyed upon by many larger fish.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.20505718886852264, "y": 0.19840769469738007 }, { "x": 0.7961509078741074, "y": 0.19840769469738007 }, { "x": 0.7961509078741074, "y": 0.47310371696949005 }, { "x": 0.20505718886852264, "y": 0.47310371696949005 } ], "category": "figure", "id": 291, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.19723987579345703, "y": 0.4879043400287628 }, { "x": 0.7962462902069092, "y": 0.4879043400287628 }, { "x": 0.7962462902069092, "y": 0.5137000232934952 }, { "x": 0.19723987579345703, "y": 0.5137000232934952 } ], "category": "paragraph", "id": 292, "content": { "text": "Figure 8.6: Growth in length of Alligator Gar in Texas. Figure 8.7: Growth in weight of Alligator\nGar in Texas. Long description.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.22132129967212677, "y": 0.5850711464881897 }, { "x": 0.7794517427682877, "y": 0.5850711464881897 }, { "x": 0.7794517427682877, "y": 0.8449916839599609 }, { "x": 0.22132129967212677, "y": 0.8449916839599609 } ], "category": "figure", "id": 293, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.2097754180431366, "y": 0.8583696484565735 }, { "x": 0.5502572059631348, "y": 0.8583696484565735 }, { "x": 0.5502572059631348, "y": 0.8716329084709287 }, { "x": 0.2097754180431366, "y": 0.8716329084709287 } ], "category": "paragraph", "id": 294, "content": { "text": "Figure 8.7: Growth in weight of Alligator Gar in Texas.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5351362228393555, "y": 0.9350046515464783 }, { "x": 0.877175897359848, "y": 0.9350046515464783 }, { "x": 0.877175897359848, "y": 0.9481025049462914 }, { "x": 0.5351362228393555, "y": 0.9481025049462914 } ], "category": "footer", "id": 295, "content": { "text": "Angling and Conservation of Living Fishy Dinosaurs I\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8842992186546326, "y": 0.9361100792884827 }, { "x": 0.9012443199753761, "y": 0.9361100792884827 }, { "x": 0.9012443199753761, "y": 0.9448324916884303 }, { "x": 0.8842992186546326, "y": 0.9448324916884303 } ], "category": "paragraph", "id": 296, "content": { "text": "171\n", "html": "", "markdown": "" } } ] }, "01030000000173.pdf": { "elements": [ { "coordinates": [ { "x": 0.3311939537525177, "y": 0.09789614379405975 }, { "x": 0.6677041351795197, "y": 0.09789614379405975 }, { "x": 0.6677041351795197, "y": 0.12030409649014473 }, { "x": 0.3311939537525177, "y": 0.12030409649014473 } ], "category": "heading1", "id": 175, "content": { "text": "Humanity's Home Base.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1425444334745407, "y": 0.15450812876224518 }, { "x": 0.85933618247509, "y": 0.15450812876224518 }, { "x": 0.85933618247509, "y": 0.38647985458374023 }, { "x": 0.1425444334745407, "y": 0.38647985458374023 } ], "category": "figure", "id": 176, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15370842814445496, "y": 0.3967196047306061 }, { "x": 0.8456659018993378, "y": 0.3967196047306061 }, { "x": 0.8456659018993378, "y": 0.5040398687124252 }, { "x": 0.15370842814445496, "y": 0.5040398687124252 } ], "category": "paragraph", "id": 177, "content": { "text": "Figure 1. This image shows the Western hemisphere as viewed\nfrom space 35,400 kilometers (about 22,000 miles) above Earth.\nData about the land surface from one satellite was combined with\nanother satellite's data about the clouds to create the image.\n(credit: modification of work by R. Stockli, A. Nelson, F. Hasler,\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3400377035140991, "y": 0.5108691453933716 }, { "x": 0.6555630564689636, "y": 0.5108691453933716 }, { "x": 0.6555630564689636, "y": 0.5267028957605362 }, { "x": 0.3400377035140991, "y": 0.5267028957605362 } ], "category": "paragraph", "id": 178, "content": { "text": "NASA/GSFC/NOAA/USGS)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14223192632198334, "y": 0.5337808132171631 }, { "x": 0.8568661063909531, "y": 0.5337808132171631 }, { "x": 0.8568661063909531, "y": 0.7084801495075226 }, { "x": 0.14223192632198334, "y": 0.7084801495075226 } ], "category": "paragraph", "id": 179, "content": { "text": "Our nearest astronomical neighbor is Earth's satellite, commonly\ncalled the Moon. Figure 2 shows Earth and the Moon drawn to scale\non the same diagram. Notice how small we have to make these\nbodies to fit them on the page with the right scale. The Moon's\ndistance from Earth is about 30 times Earth's diameter, or\napproximately 384,000 kilometers, and it takes about a month for\nthe Moon to revolve around Earth. The Moon's diameter is 3476\nkilometers, about one fourth the size of Earth.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.26554399728775024, "y": 0.7664700746536255 }, { "x": 0.7340132296085358, "y": 0.7664700746536255 }, { "x": 0.7340132296085358, "y": 0.7883846387267113 }, { "x": 0.26554399728775024, "y": 0.7883846387267113 } ], "category": "paragraph", "id": 180, "content": { "text": "Earth and Moon, Drawn to Scale.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14242789149284363, "y": 0.9242790341377258 }, { "x": 0.16203459165990353, "y": 0.9242790341377258 }, { "x": 0.16203459165990353, "y": 0.9347678264603019 }, { "x": 0.14242789149284363, "y": 0.9347678264603019 } ], "category": "paragraph", "id": 181, "content": { "text": "10\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.188639298081398, "y": 0.9236792325973511 }, { "x": 0.6037068217992783, "y": 0.9236792325973511 }, { "x": 0.6037068217992783, "y": 0.9379374422132969 }, { "x": 0.188639298081398, "y": 0.9379374422132969 } ], "category": "footer", "id": 182, "content": { "text": "Chapter 1 Section 1.6: A Tour of the Universe\n", "html": "", "markdown": "" } } ] }, "01030000000047.pdf": { "elements": [ { "coordinates": [ { "x": 0.07590318471193314, "y": 0.13272172212600708 }, { "x": 0.9122079089283943, "y": 0.13272172212600708 }, { "x": 0.9122079089283943, "y": 0.6149223744869232 }, { "x": 0.07590318471193314, "y": 0.6149223744869232 } ], "category": "table", "id": 189, "content": { "text": "", "html": "
No. Political party Provisional result on registration 7 MarchOfficial registration 29 result on AprilDifference in the number of candidates
Number of commune/ sangkatNumber of candidatesNumber of commune/ sangkatNumber of candidates
11Khmer United Party3549830457-41
12Grassroots Democracy Party3243532481+46
13Beehive Social Democratic Party2542523392-33
14Cambodian Indigeneous Peoples Democracy Party1919419202+8
15Ekpheap Cheat Khmer Party1517514178+3
16Reaksmey Khemara Party779688+9
17Khmer Economic Development Party465464-1
Total84,20886,092+1,884
", "markdown": "" } }, { "coordinates": [ { "x": 0.07772000133991241, "y": 0.0845259428024292 }, { "x": 0.37777455151081085, "y": 0.0845259428024292 }, { "x": 0.37777455151081085, "y": 0.10361487790942192 }, { "x": 0.07772000133991241, "y": 0.10361487790942192 } ], "category": "paragraph", "id": 266, "content": { "text": "ANFREL Pre-Election Assessment Mission Report\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.07812324166297913, "y": 0.8993285298347473 }, { "x": 0.09293599426746368, "y": 0.8993285298347473 }, { "x": 0.09293599426746368, "y": 0.9144253889098763 }, { "x": 0.07812324166297913, "y": 0.9144253889098763 } ], "category": "paragraph", "id": 268, "content": { "text": "24\n", "html": "", "markdown": "" } } ] }, "01030000000093.pdf": { "elements": [ { "coordinates": [ { "x": 0.0921320989727974, "y": 0.0726272463798523 }, { "x": 0.9066242054104805, "y": 0.0726272463798523 }, { "x": 0.9066242054104805, "y": 0.14644207060337067 }, { "x": 0.0921320989727974, "y": 0.14644207060337067 } ], "category": "paragraph", "id": 581, "content": { "text": "survey responses and outcomes from the experiments and games. This spreadsheet is linked to the\nstudents' randomly assigned course ID (CID) numbers. The other spreadsheet, which is linked to their\nuniversity student ID numbers and their names, compiles their performances on quizzes, homework,\nand exams assigned throughout the semester.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09206819534301758, "y": 0.15033221244812012 }, { "x": 0.9080179929733276, "y": 0.15033221244812012 }, { "x": 0.9080179929733276, "y": 0.3021543174982071 }, { "x": 0.09206819534301758, "y": 0.3021543174982071 } ], "category": "paragraph", "id": 582, "content": { "text": "At the risk of sounding draconian, this is a course where it may make sense to base upwards of\n50% of a student's grade upon their in-person attendance, which would entail carefully taking role at\nthe beginning of each class. If the class meets 30 times face-to-face during the semester, for example,\ntheir grade attributable to attendance would then drop by 3.33 percentage points for each missed\nclass (excused absences withstanding). Granted, students who foresee having difficulty attending class\nin-person throughout the semester would likely choose to drop the course immediately. For those\nstudents who remain, the remaining 50% of their course grade would then be based upon their\nquizzes, homework, and exam scores.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09204628318548203, "y": 0.30606117844581604 }, { "x": 0.9080630764365196, "y": 0.30606117844581604 }, { "x": 0.9080630764365196, "y": 0.5351392924785614 }, { "x": 0.09204628318548203, "y": 0.5351392924785614 } ], "category": "paragraph", "id": 583, "content": { "text": "The issue of how best to convey written information to the student a priori (i.e., before conducting\na\ngiven experiment or game) also looms large in a participatory-learning setting such as this, especially\nif the instructor desires to obtain unbiased responses from the students (or more practically, to\ncontrol for potential biases). For example, the first set of thought experiments presented in Section 1\nis meant to demonstrate firsthand to the students the extent to which automatic, knee-jerk responses\nfrom what Kahneman (2011) identifies as the System 1 portion of the brain can result in\nmiscalculations. Students who choose to read ahead (small in number though these types of students\nmay be) potentially skew the distribution of responses away from its otherwise true representation\nof these miscalculations. Such skewness may be tolerable for strictly educational purposes, where the\ngoal is to demonstrate that at least a certain percentage of students are prone to miscalculation. But if\nthe instructor also hopes to compile student responses into a dataset amenable for statistical analysis,\nthen this type of potential bias draws into question the validity of the data.\n2\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09233959019184113, "y": 0.5392964482307434 }, { "x": 0.9079555422067642, "y": 0.5392964482307434 }, { "x": 0.9079555422067642, "y": 0.6289965361356735 }, { "x": 0.09233959019184113, "y": 0.6289965361356735 } ], "category": "paragraph", "id": 584, "content": { "text": "To help control for potential biases associated with students having read ahead about the game or\nexperiment they are now participating in, I recommend including the following question on each\nResponse Card: \"Did you read about this topic ahead of time?\" (see Appendix A). Answers to this\nquestion provide a control for the level of student foreknowledge, which is the potential bias of\nconcern.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09216349571943283, "y": 0.6363333463668823 }, { "x": 0.906630389392376, "y": 0.6363333463668823 }, { "x": 0.906630389392376, "y": 0.7683303654193878 }, { "x": 0.09216349571943283, "y": 0.7683303654193878 } ], "category": "paragraph", "id": 585, "content": { "text": "I am personally unaware of any studies that have looked at how well students learn the lessons\nof behavioral economics in a cumulative sense over a span of time (e.g., an entire semester) and\nacross a variety of experiments and games. In other words, I know of no studies that estimate the\nextent to which individuals who begin a course in behavioral economics as bona fide Homo sapiens\nevolve toward \"Homo economism\" in their individual and social choices. The pedagogy promoted in\nthis textbook-in particular, the data it generates-offers instructors the opportunity to empirically\ntest the hypothesis that students make this evolution.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.07700911909341812, "y": 0.9311597347259521 }, { "x": 0.9054323211312294, "y": 0.9311597347259521 }, { "x": 0.9054323211312294, "y": 0.9439710360020399 }, { "x": 0.07700911909341812, "y": 0.9439710360020399 } ], "category": "footer", "id": 586, "content": { "text": "2. Note that this potential biasedness problem also extends to the laboratory experiments of Section 2 and games of Section 3.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.6375802755355835, "y": 0.951104998588562 }, { "x": 0.9065471887588501, "y": 0.951104998588562 }, { "x": 0.9065471887588501, "y": 0.9586387583985925 }, { "x": 0.6375802755355835, "y": 0.9586387583985925 } ], "category": "footer", "id": 587, "content": { "text": "BEHAVIORAL ECONOMICS PRACTICUM XXV\n", "html": "", "markdown": "" } } ] }, "01030000000188.pdf": { "elements": [ { "coordinates": [ { "x": 0.17504017055034637, "y": 0.08359555900096893 }, { "x": 0.8229483217000961, "y": 0.08359555900096893 }, { "x": 0.8229483217000961, "y": 0.22749824821949005 }, { "x": 0.17504017055034637, "y": 0.22749824821949005 } ], "category": "table", "id": 951, "content": { "text": "", "html": "
ModelSizeTypeH6 (Avg.)ARCHellaSwagMMLUTruthfulQAWinograndeGSM8K
SOLAR 10.7B-Instruct~11BAlignment-tuned74.2071.0888.1666.2171.4383.5864.75
Qwen 72B~72BPretrained73.6065.1985.9477.3760.1982.4870.43
Mixtral 8x7B-Instruct-v0.1~47BInstruction-tuned72.6270.2287.6371.1664.5881.3760.73
Yi 34B-200K~34BPretrained70.8165.3685.5876.0653.64
", "markdown": "" } }, { "coordinates": [ { "x": 0.11769933253526688, "y": 0.24025830626487732 }, { "x": 0.8826014474034309, "y": 0.24025830626487732 }, { "x": 0.8826014474034309, "y": 0.30853183567523956 }, { "x": 0.11769933253526688, "y": 0.30853183567523956 } ], "category": "paragraph", "id": 94, "content": { "text": "Table 2: Evaluation results for SOLAR 10.7B and SOLAR 10.7B-Instruct along with other top-performing models.\nWe report the scores for the six tasks mentioned in Sec. 4.1 along with the H6 score (average of six tasks). We also\nreport the size of the models in units of billions of parameters. The type indicates the training stage of the model\nand is chosen from {Pretrained, Instruction-tuned, Alignment-tuned}. Models based on SOLAR 10.7B are colored\npurple. The best scores for H6 and the individual tasks are shown in bold.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11770407110452652, "y": 0.3373868763446808 }, { "x": 0.48784825950860977, "y": 0.3373868763446808 }, { "x": 0.48784825950860977, "y": 0.4786480665206909 }, { "x": 0.11770407110452652, "y": 0.4786480665206909 } ], "category": "paragraph", "id": 95, "content": { "text": "We reformatted the instruction datasets with an\nAlpaca-styled chat template. For datasets such as\nOpenOrca, which are derived from FLAN (Long-\npre et al., 2023), we filter data that overlaps with\nthe benchmark datasets (see Tab. 8 in Appendix. C\nfor more information). The alignment datasets are\nin the {prompt, chosen, rejected} triplet format.\nWe preprocess the alignment datasets following\nZephyr (Tunstall et al., 2023).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1179465502500534, "y": 0.49078354239463806 }, { "x": 0.4877496510744095, "y": 0.49078354239463806 }, { "x": 0.4877496510744095, "y": 0.6320207566022873 }, { "x": 0.1179465502500534, "y": 0.6320207566022873 } ], "category": "paragraph", "id": 96, "content": { "text": "Evaluation. In the HuggingFace Open LLM\nLeaderboard (Beeching et al., 2023), six types of\nevaluation methods are presented: ARC (Clark\net al., 2018), HellaSWAG (Zellers et al., 2019),\nMMLU (Hendrycks et al., 2020), TruthfulQA (Lin\net al., 2022), Winogrande (Sakaguchi et al., 2021),\nand GSM8K (Cobbe et al., 2021). We utilize these\ndatasets as benchmarks for evaluation and also re-\nport the average scores for the six tasks, e.g., H6.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11810475587844849, "y": 0.6436597108840942 }, { "x": 0.48778197169303894, "y": 0.6436597108840942 }, { "x": 0.48778197169303894, "y": 0.7527707368135452 }, { "x": 0.11810475587844849, "y": 0.7527707368135452 } ], "category": "paragraph", "id": 97, "content": { "text": "Model merging. Model merging methods such\nas Yadav et al. (2023) can boost model perfor-\nmance without further training. We merge some\nof the models that we trained in both the instruc-\ntion and alignment tuning stages. We implement\nour own merging methods although popular open\nsource also exist such as MergeKit3.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11823403090238571, "y": 0.7668142318725586 }, { "x": 0.26304688304662704, "y": 0.7668142318725586 }, { "x": 0.26304688304662704, "y": 0.776909695006907 }, { "x": 0.11823403090238571, "y": 0.776909695006907 } ], "category": "heading1", "id": 98, "content": { "text": "4.2 Main Results\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11753211915493011, "y": 0.7876775860786438 }, { "x": 0.487409844994545, "y": 0.7876775860786438 }, { "x": 0.487409844994545, "y": 0.8966840654611588 }, { "x": 0.11753211915493011, "y": 0.8966840654611588 } ], "category": "paragraph", "id": 99, "content": { "text": "We present evaluation results for our SOLAR\n10.7B and SOLAR 10.7B-Instruct models along\nwith other top-performing models in Tab. 2. SO-\nLAR 10.7B outperforms other pretrained models\nof similar sizes, such as Qwen 14B and Mistral\n7B, which shows that DUS is an effective method\nto up-scale base LLMs. Furthermore, despite the\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5133141279220581, "y": 0.3373233377933502 }, { "x": 0.8830066621303558, "y": 0.3373233377933502 }, { "x": 0.8830066621303558, "y": 0.46265509724617004 }, { "x": 0.5133141279220581, "y": 0.46265509724617004 } ], "category": "paragraph", "id": 100, "content": { "text": "smaller size, SOLAR 10.7B-Instruct scores the\nhighest in terms of H6, even surpassing the recent\ntop-performing open-source LLM Mixtral 8x7B-\nInstruct-v0.1 or Qwen 72B. The above results indi-\ncate DUS can up-scale models that are capable of\nachieving state-of-the-art performance when fine-\ntuned. We also report data contamination results\nfor SOLAR 10.7B-Instruct in Appendix C.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5132715106010437, "y": 0.4797254800796509 }, { "x": 0.6849122643470764, "y": 0.4797254800796509 }, { "x": 0.6849122643470764, "y": 0.4895869055762887 }, { "x": 0.5132715106010437, "y": 0.4895869055762887 } ], "category": "heading1", "id": 101, "content": { "text": "4.3\nAblation Studies\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5124309659004211, "y": 0.5024687647819519 }, { "x": 0.8801800012588501, "y": 0.5024687647819519 }, { "x": 0.8801800012588501, "y": 0.53101871535182 }, { "x": 0.5124309659004211, "y": 0.53101871535182 } ], "category": "paragraph", "id": 102, "content": { "text": "We present ablation studies for both the instruction\nand alignment tuning stages.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5132229924201965, "y": 0.5461789965629578 }, { "x": 0.7160397171974182, "y": 0.5461789965629578 }, { "x": 0.7160397171974182, "y": 0.5587057359516621 }, { "x": 0.5132229924201965, "y": 0.5587057359516621 } ], "category": "heading1", "id": 103, "content": { "text": "4.3.1 Instruction Tuning\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5133850574493408, "y": 0.5670521259307861 }, { "x": 0.8826965391635895, "y": 0.5670521259307861 }, { "x": 0.8826965391635895, "y": 0.7243480384349823 }, { "x": 0.5133850574493408, "y": 0.7243480384349823 } ], "category": "paragraph", "id": 104, "content": { "text": "Ablation on the training datasets. We present\nablation studies using different training datasets\nfor the instruction tuning in Tab. 3. The ablated\nmodels are prefixed with SFT for supervised fine-\ntuning. 'SFT v1' only uses the Alpaca-GPT4\ndataset, whereas 'SFT v2' also uses the OpenOrca\ndataset. 'SFT v3' uses the Synth. Math-Instruct\ndataset along with the datasets used in 'SFT v2'.\nSimilarly, 'SFT v4' uses the Synth. Math-Instruct\ndataset along with the datasets used in 'SFT v1'.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5123069286346436, "y": 0.7292452454566956 }, { "x": 0.8832891583442688, "y": 0.7292452454566956 }, { "x": 0.8832891583442688, "y": 0.9188995361328125 }, { "x": 0.5123069286346436, "y": 0.9188995361328125 } ], "category": "paragraph", "id": 105, "content": { "text": "First, we analyze how Alpaca-GPT4 and\nOpenOrca affect the trained models. The first ab-\nlated model, 'SFT v1', which used only the Alpaca-\nGPT4 dataset for training, resulted in 69.15 for H6.\nWhen we add the OpenOrca dataset to train the\nsecond ablated model, 'SFT v2', the resulting H6\nscore is 69.21, which is little change from 69.15 of\n'SFT v1'. However, the task scores vary more as\n'SFT v2' gets a substantially higher GSM8K score\nof 57.32 compared to 52.24 of 'SFT v1' but also\ngets noticeably lower scores across the board for\nARC, HellaSwag, and TruthfulQA. This seems to\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1371627002954483, "y": 0.9065759181976318 }, { "x": 0.44110243022441864, "y": 0.9065759181976318 }, { "x": 0.44110243022441864, "y": 0.9183218386024237 }, { "x": 0.1371627002954483, "y": 0.9183218386024237 } ], "category": "footer", "id": 106, "content": { "text": "https://github.com/cg123/mergekit\n", "html": "", "markdown": "" } } ] }, "01030000000042.pdf": { "elements": [ { "coordinates": [ { "x": 0.11738406121730804, "y": 0.08589519560337067 }, { "x": 0.47098250687122345, "y": 0.08589519560337067 }, { "x": 0.47098250687122345, "y": 0.41905398666858673 }, { "x": 0.11738406121730804, "y": 0.41905398666858673 } ], "category": "paragraph", "id": 504, "content": { "text": "this content \"very often\", 71% were from\nIndonesia and 28.6% were from Thailand.\nWhen asked about how often participants\nhad heard of groups expressing the\nimportanceofmenaccompanying: women\nwhen travelling to conflict zones, more\nrespondents had heard this message\nwith a higher frequency (\"always\" or \"very\noften\", 37.1%) than those who had rarely or\nnever heard it (34%). Forty-six per cent of\nrespondents from Indonesia heard this\nmessage with a higher frequency, followed\nby the Philippines (38%) and Thailand\n(15%). When grouping the answer options\nof \"always\", \"very often\" and \"sometimes\",\n66% of respondents said they had heard\ngroups stress the importance of women\nbeing accompanied by men when\ntravelling to conflict areas.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11807309091091156, "y": 0.4580368101596832 }, { "x": 0.45808200538158417, "y": 0.4580368101596832 }, { "x": 0.45808200538158417, "y": 0.5063301473855972 }, { "x": 0.11807309091091156, "y": 0.5063301473855972 } ], "category": "paragraph", "id": 505, "content": { "text": "Figure 5: Importance of a male\nguardian accompanying women when\ntravelling to conflict zones\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1227138340473175, "y": 0.532124400138855 }, { "x": 0.4637627899646759, "y": 0.532124400138855 }, { "x": 0.4637627899646759, "y": 0.7591868191957474 }, { "x": 0.1227138340473175, "y": 0.7591868191957474 } ], "category": "figure", "id": 506, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5284045338630676, "y": 0.08716931939125061 }, { "x": 0.8804951012134552, "y": 0.08716931939125061 }, { "x": 0.8804951012134552, "y": 0.29570262134075165 }, { "x": 0.5284045338630676, "y": 0.29570262134075165 } ], "category": "paragraph", "id": 507, "content": { "text": "tremist groups. Most respondents (77%)\nagreed (combining both \"strongly agree\"\nand \"agree\") that they were worried about\nintolerance in their communities, partic-\nularly respondents from Indonesia and\nthe Philippines. Almost all respondents in\nthe sample (93%) agreed that they were\nworried about violent extremism in their\ncountries. This appeared to be a general\nconcern among both men and women\nas 85% of men and 95% of women agreed\nthat they were concerned.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12006913125514984, "y": 0.7973607778549194 }, { "x": 0.4692239314317703, "y": 0.7973607778549194 }, { "x": 0.4692239314317703, "y": 0.9169714823365211 }, { "x": 0.12006913125514984, "y": 0.9169714823365211 } ], "category": "paragraph", "id": 508, "content": { "text": "In the second part of the survey, using\na five-point Likert scale from \"strong-\nly agree\" to \"strongly disagree\", partic-\nipants were presented with a series of\nstatements regarding how worried they\nwere about intolerant content being es-\npoused in the offline space by violent ex-\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5285263657569885, "y": 0.3246476948261261 }, { "x": 0.8806267976760864, "y": 0.3246476948261261 }, { "x": 0.8806267976760864, "y": 0.5508713871240616 }, { "x": 0.5285263657569885, "y": 0.5508713871240616 } ], "category": "paragraph", "id": 509, "content": { "text": "Significantly, 89% of respondents agreed\nthat religious extremism would impede\nwomen's rights. Half of the participants\nin Indonesia agreed they were concerned\nthat religious extremism would hamper\nwomen's rights, 27% in Philippines and 16%\nin Thailand. Both men (84.6%) and women\n(89.2%) expressed their concerns on this\nissue. Furthermore, 91% of respondents\nagreed that religious extremism prioritizes\nmen's rights over women's rights - 93.1%\nof women strongly agreed with the\nstatement compared to 6.90% of men.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.528373658657074, "y": 0.5801329612731934 }, { "x": 0.8807522356510162, "y": 0.5801329612731934 }, { "x": 0.8807522356510162, "y": 0.7885361164808273 }, { "x": 0.528373658657074, "y": 0.7885361164808273 } ], "category": "paragraph", "id": 510, "content": { "text": "For example, one interviewee from\nIndonesia observed that the teachings\nof extremism have entered schools, such\nas high schools, and have also begun to\npenetrate student organizations. She\nobserved that the teachings \"spread from\nthe Middle East, bringing misogynistic\nteachings towards women as part of their\nsubjugation strategy\". She acknowledged\nthat it was part of the organizational\nstrategy where women appeared to look\nempowered:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5422207713127136, "y": 0.8193762302398682 }, { "x": 0.5724692586809397, "y": 0.8193762302398682 }, { "x": 0.5724692586809397, "y": 0.839445237070322 }, { "x": 0.5422207713127136, "y": 0.839445237070322 } ], "category": "figure", "id": 511, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5879986882209778, "y": 0.8327469825744629 }, { "x": 0.8769331276416779, "y": 0.8327469825744629 }, { "x": 0.8769331276416779, "y": 0.9162541404366493 }, { "x": 0.5879986882209778, "y": 0.9162541404366493 } ], "category": "paragraph", "id": 512, "content": { "text": "\"However,\nthis\nis\njust\nmanipulation; behind it is the\npractice of misogyny, women's\nconsciousness, their bodies and\nminds are controlled, even though\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.033042777329683304, "y": 0.9748004674911499 }, { "x": 0.7160701043903828, "y": 0.9748004674911499 }, { "x": 0.7160701043903828, "y": 0.9860702212899923 }, { "x": 0.033042777329683304, "y": 0.9860702212899923 } ], "category": "footer", "id": 513, "content": { "text": "Gender Analysis of Violent Extremism and the Impact of COVID-19 on Peace and Security in ASEAN\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.929033100605011, "y": 0.9761617183685303 }, { "x": 0.9419734422117472, "y": 0.9761617183685303 }, { "x": 0.9419734422117472, "y": 0.9837253298610449 }, { "x": 0.929033100605011, "y": 0.9837253298610449 } ], "category": "paragraph", "id": 514, "content": { "text": "31\n", "html": "", "markdown": "" } } ] }, "01030000000005.pdf": { "elements": [ { "coordinates": [ { "x": 0.15357357263565063, "y": 0.06442493945360184 }, { "x": 0.1627708077430725, "y": 0.06442493945360184 }, { "x": 0.1627708077430725, "y": 0.07434731721878052 }, { "x": 0.15357357263565063, "y": 0.07434731721878052 } ], "category": "paragraph", "id": 42, "content": { "text": "6\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.4605851173400879, "y": 0.06539487093687057 }, { "x": 0.5666821599006653, "y": 0.06539487093687057 }, { "x": 0.5666821599006653, "y": 0.07483854051679373 }, { "x": 0.4605851173400879, "y": 0.07483854051679373 } ], "category": "header", "id": 43, "content": { "text": "CHAPTER I\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15357869863510132, "y": 0.10463214665651321 }, { "x": 0.8756985664367676, "y": 0.10463214665651321 }, { "x": 0.8756985664367676, "y": 0.43853185325860977 }, { "x": 0.15357869863510132, "y": 0.43853185325860977 } ], "category": "figure", "id": 44, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.29208508133888245, "y": 0.44774070382118225 }, { "x": 0.737866997718811, "y": 0.44774070382118225 }, { "x": 0.737866997718811, "y": 0.4821806401014328 }, { "x": 0.29208508133888245, "y": 0.4821806401014328 } ], "category": "paragraph", "id": 45, "content": { "text": "FIGURE I.5. The San Mateo Ixtatán men's jacket, lopil\n(Spanish capixay). Photo by Elizabeth Purdum.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15170416235923767, "y": 0.5375860929489136 }, { "x": 0.8770487010478973, "y": 0.5375860929489136 }, { "x": 0.8770487010478973, "y": 0.8503938019275665 }, { "x": 0.15170416235923767, "y": 0.8503938019275665 } ], "category": "figure", "id": 46, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.28527209162712097, "y": 0.8587800860404968 }, { "x": 0.7416124939918518, "y": 0.8587800860404968 }, { "x": 0.7416124939918518, "y": 0.8937365226447582 }, { "x": 0.28527209162712097, "y": 0.8937365226447582 } ], "category": "paragraph", "id": 47, "content": { "text": "FIGURE 1.6. Vegetation along the trail from San Mateo\nIxtatán to Bulej, May 1965. Photo by author.\n", "html": "", "markdown": "" } } ] }, "01030000000023.pdf": { "elements": [ { "coordinates": [ { "x": 0.6804289817810059, "y": 0.0867920070886612 }, { "x": 0.8422032743692398, "y": 0.0867920070886612 }, { "x": 0.8422032743692398, "y": 0.09654932841658592 }, { "x": 0.6804289817810059, "y": 0.09654932841658592 } ], "category": "header", "id": 463, "content": { "text": "2. The Lost Homeland\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12983350455760956, "y": 0.11921486258506775 }, { "x": 0.8427713364362717, "y": 0.11921486258506775 }, { "x": 0.8427713364362717, "y": 0.2953450232744217 }, { "x": 0.12983350455760956, "y": 0.2953450232744217 } ], "category": "paragraph", "id": 464, "content": { "text": "This description told me that Steinkirche was somewhere in the vicinity\nof Strehlen. Then, according to Elfriede's stories about walking her\nanimals, ducks, geese and a goat to the railway station to meet visitors,\na station once existed near the village. I wondered whether it had survived\nthe bombing. I have seen films of the utter devastation along the Oder\nRiver in early May 1945, just before the War in Europe ended. Did the\nrailway still pass Steinkirche? My mother's father had been a railway line\npointsman, a signal attendant. From a station close to home he would\nhave undertaken the long journeys his work demanded.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1302267611026764, "y": 0.31083741784095764 }, { "x": 0.8424482047557831, "y": 0.31083741784095764 }, { "x": 0.8424482047557831, "y": 0.4272843152284622 }, { "x": 0.1302267611026764, "y": 0.4272843152284622 } ], "category": "paragraph", "id": 465, "content": { "text": "I went back to the old German maps in the National Library and located\nSteinkirche on one of several contiguous contour maps perhaps designed\nfor military purposes. They covered Lower Silesia in 1938 in-remarkable\ndetail, although such detail also helped obscure the printed names\nof villages, which were lost in the depictions of miniature hills, rivers,\nquarries, castles, lakes and even houses.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1298239380121231, "y": 0.4430355727672577 }, { "x": 0.8451004177331924, "y": 0.4430355727672577 }, { "x": 0.8451004177331924, "y": 0.5993350893259048 }, { "x": 0.1298239380121231, "y": 0.5993350893259048 } ], "category": "paragraph", "id": 466, "content": { "text": "Eventually I did locate the village through this superb map. Steinkirche\nwas off the main road near the second railway station south of Strehlen,\nprobably on a hill, something my mother had never mentioned. If one\npassed it, one could also locate it as station number two of the seven\nbetween Strehlen and Milnsterberg, on the railway running south of\nBreslau towards the Carpathian Mountains. Then I noted the Polish\nnames for the two townships south of Wroclaw (Breslau). In the German-\nto-Polish Gazeteer they are given as Strzelin and Ziebice.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12993423640727997, "y": 0.6155964732170105 }, { "x": 0.8427342027425766, "y": 0.6155964732170105 }, { "x": 0.8427342027425766, "y": 0.7318176999688148 }, { "x": 0.12993423640727997, "y": 0.7318176999688148 } ], "category": "paragraph", "id": 467, "content": { "text": "My intention was to take a train or a car to the new Polish ex-Steinkirche,\nvisit it discreetly, and search the old cemetery for family connections.\nI wanted to photograph my two-year-old granddaughter beside my own\ngrandfather Friedrich's grave. I wanted to look for other evidence of family\nhistory, and just savour the atmosphere of the place. I also wanted to see\nwhat had happened to Neumarkt Platz.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.13000039756298065, "y": 0.7472231984138489 }, { "x": 0.8428587764501572, "y": 0.7472231984138489 }, { "x": 0.8428587764501572, "y": 0.844056099653244 }, { "x": 0.13000039756298065, "y": 0.844056099653244 } ], "category": "paragraph", "id": 468, "content": { "text": "It was difficult to achieve anything in a hurry. In London, my daughter,\ngranddaughter and I visited the office of the Polish Consulate. Tourist\nbrochures were generously given to us, but none of the authoritative road\nmaps of Poland showed the villages between Strzelin and Ziebice. Did our\nvillage still exist? And by what name?\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1293308436870575, "y": 0.8597255349159241 }, { "x": 0.8428551852703094, "y": 0.8597255349159241 }, { "x": 0.8428551852703094, "y": 0.9165612645447254 }, { "x": 0.1293308436870575, "y": 0.9165612645447254 } ], "category": "paragraph", "id": 469, "content": { "text": "After flying to Berlin, we set out in a hire car for Wroclaw on 13 September\n2003. Beside the Hitler-era Autobahn, there are still extensive forests,\nbetween flat farmlands. It was raining when we entered Poland.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8984416127204895, "y": 0.9318864941596985 }, { "x": 0.9072674969211221, "y": 0.9318864941596985 }, { "x": 0.9072674969211221, "y": 0.9408349366858602 }, { "x": 0.8984416127204895, "y": 0.9408349366858602 } ], "category": "paragraph", "id": 470, "content": { "text": "9\n", "html": "", "markdown": "" } } ] }, "01030000000168.pdf": { "elements": [ { "coordinates": [ { "x": 0.15158799290657043, "y": 0.13470935821533203 }, { "x": 0.8441667258739471, "y": 0.13470935821533203 }, { "x": 0.8441667258739471, "y": 0.23846230655908585 }, { "x": 0.15158799290657043, "y": 0.23846230655908585 } ], "category": "table", "id": 425, "content": { "text": "", "html": "
increasebasic cations required from lime
40 cmolincreasecmolbasic cations required from lime
", "markdown": "" } }, { "coordinates": [ { "x": 0.09212898463010788, "y": 0.07520762085914612 }, { "x": 0.9068429991602898, "y": 0.07520762085914612 }, { "x": 0.9068429991602898, "y": 0.1229812391102314 }, { "x": 0.09212898463010788, "y": 0.1229812391102314 } ], "category": "paragraph", "id": 434, "content": { "text": "Soils with the same pH may require different amounts of limestone due to differences in CEC, which would imply\ndifferences in buffering capacities. For example, consider the amount of limestone necessary to raise the base saturation\nof two soils from 70% to 90% when one soil has a CEC of 15 cmolc/kg, and the other has a CEC of 40 cmolc/kg.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1615859419107437, "y": 0.14983239769935608 }, { "x": 0.8372810035943985, "y": 0.14983239769935608 }, { "x": 0.8372810035943985, "y": 0.2215394601225853 }, { "x": 0.1615859419107437, "y": 0.2215394601225853 } ], "category": "paragraph", "id": 435, "content": { "text": "increase\nbasic cations required from lime\n40 cmol increase cmol basic cations required from lime\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09191261231899261, "y": 0.25082430243492126 }, { "x": 0.9066222161054611, "y": 0.25082430243492126 }, { "x": 0.9066222161054611, "y": 0.29841386899352074 }, { "x": 0.09191261231899261, "y": 0.29841386899352074 } ], "category": "paragraph", "id": 436, "content": { "text": "Lastly, soil pH is governed by base saturation. If other factors are constant, the lower the pH, the more lime that is\nrequired to achieve a desired pH. This is because at a low pH, a larger percentage of the CEC is occupied by acid cations,\nwhich requires larger amounts of lime to neutralize.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09214308857917786, "y": 0.3417775630950928 }, { "x": 0.6961318552494049, "y": 0.3417775630950928 }, { "x": 0.6961318552494049, "y": 0.36088600382208824 }, { "x": 0.09214308857917786, "y": 0.36088600382208824 } ], "category": "heading1", "id": 437, "content": { "text": "Activity I: Determining pH With Indicator Strips (Field Method)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09164740890264511, "y": 0.39057257771492004 }, { "x": 0.9066360220313072, "y": 0.39057257771492004 }, { "x": 0.9066360220313072, "y": 0.4386323653161526 }, { "x": 0.09164740890264511, "y": 0.4386323653161526 } ], "category": "paragraph", "id": 438, "content": { "text": "Of the several techniques available for determining pH, one that can be used easily in the field is the indicator strip\nmethod. This technique uses the principle of pH sensitivity of certain dyes, which cause differences in color across a\nrange in pH. With the soils provided, complete the following pH determination:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09219218045473099, "y": 0.45505452156066895 }, { "x": 0.9063585475087166, "y": 0.45505452156066895 }, { "x": 0.9063585475087166, "y": 0.48521713353693485 }, { "x": 0.09219218045473099, "y": 0.48521713353693485 } ], "category": "paragraph", "id": 439, "content": { "text": "Weigh 10.0 g of soil into a small plastic cup. Add 20 ml of distilled water and stir. Allow to stand for 5 minutes,\noccasionally stirring.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09216254204511642, "y": 0.5019148588180542 }, { "x": 0.9072324559092522, "y": 0.5019148588180542 }, { "x": 0.9072324559092522, "y": 0.532096404582262 }, { "x": 0.09216254204511642, "y": 0.532096404582262 } ], "category": "paragraph", "id": 440, "content": { "text": "Using the pH indicator strips provided, dip the strip into the cup until the tip is wetted. Determine the pH by comparing\nthe color change of the pH test strip to the color chart.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09165044128894806, "y": 0.5497316122055054 }, { "x": 0.12332404032349586, "y": 0.5497316122055054 }, { "x": 0.12332404032349586, "y": 0.5744170155376196 }, { "x": 0.09165044128894806, "y": 0.5744170155376196 } ], "category": "figure", "id": 441, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14528463780879974, "y": 0.54864501953125 }, { "x": 0.35839225351810455, "y": 0.54864501953125 }, { "x": 0.35839225351810455, "y": 0.560638333670795 }, { "x": 0.14528463780879974, "y": 0.560638333670795 } ], "category": "paragraph", "id": 442, "content": { "text": "Record the soil pH in Table 14.1.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09227955341339111, "y": 0.6046478748321533 }, { "x": 0.5500863492488861, "y": 0.6046478748321533 }, { "x": 0.5500863492488861, "y": 0.6230963356792927 }, { "x": 0.09227955341339111, "y": 0.6230963356792927 } ], "category": "heading1", "id": 443, "content": { "text": "Activity 2: Determining Soil pH with a pH Meter\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09196565300226212, "y": 0.6511811017990112 }, { "x": 0.9081899300217628, "y": 0.6511811017990112 }, { "x": 0.9081899300217628, "y": 0.718680240213871 }, { "x": 0.09196565300226212, "y": 0.718680240213871 } ], "category": "paragraph", "id": 444, "content": { "text": "Laboratory pH meters are more accurate than pH dyes and strips. The pH meter measures the hydrogen ion activity [H+]\nby measuring the electric potential across a thin, porous glass membrane at the base of the electrode. This potential\nchanges in response to [H+], and by standardizing the instrument with buffers of known pH, we can measure the pH of\nany solution, including soil solutions.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09194936603307724, "y": 0.735190212726593 }, { "x": 0.9070489630103111, "y": 0.735190212726593 }, { "x": 0.9070489630103111, "y": 0.7804518006742001 }, { "x": 0.09194936603307724, "y": 0.7804518006742001 } ], "category": "paragraph", "id": 445, "content": { "text": "Using the samples prepared in Activity 1, carefully place the electrode in the suspension. Gently swirl the electrode in\nthe solution, and note the pH reading. Wait for the pH meter to reach a steady reading, indicated by the word \"ready\"\non the screen.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09166815876960754, "y": 0.8015446066856384 }, { "x": 0.12366826087236404, "y": 0.8015446066856384 }, { "x": 0.12366826087236404, "y": 0.8262355457991362 }, { "x": 0.09166815876960754, "y": 0.8262355457991362 } ], "category": "figure", "id": 446, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1453373283147812, "y": 0.7999462485313416 }, { "x": 0.5746298581361771, "y": 0.7999462485313416 }, { "x": 0.5746298581361771, "y": 0.8120794668793678 }, { "x": 0.1453373283147812, "y": 0.8120794668793678 } ], "category": "paragraph", "id": 447, "content": { "text": "Record the value for this 1:2 soil-water suspension in Table 14.1.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.6713517308235168, "y": 0.9412887096405029 }, { "x": 0.907120481133461, "y": 0.9412887096405029 }, { "x": 0.907120481133461, "y": 0.9524554619565606 }, { "x": 0.6713517308235168, "y": 0.9524554619565606 } ], "category": "footer", "id": 448, "content": { "text": "Soil Acidity and Adjusting Soil pH 127\n", "html": "", "markdown": "" } } ] }, "01030000000024.pdf": { "elements": [ { "coordinates": [ { "x": 0.15511389076709747, "y": 0.08670894801616669 }, { "x": 0.2824777513742447, "y": 0.08670894801616669 }, { "x": 0.2824777513742447, "y": 0.09637163672596216 }, { "x": 0.15511389076709747, "y": 0.09637163672596216 } ], "category": "header", "id": 452, "content": { "text": "At Home in Exile\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15579184889793396, "y": 0.11888886988162994 }, { "x": 0.8692381083965302, "y": 0.11888886988162994 }, { "x": 0.8692381083965302, "y": 0.27558633685112 }, { "x": 0.15579184889793396, "y": 0.27558633685112 } ], "category": "paragraph", "id": 453, "content": { "text": "We received the clear impression from grim customs officials and money-\nchangers at the border that we had entered a part of the world still not\nentirely recovered from post-War economic depression. Roadside stands\nsold plaster garden statues, especially gnomes, and other wares were also\nfor sale, judging by the surreptitious lifting of skirts to reveal totally bare\nflesh, from women sheltering under their umbrellas. I wondered where\nthey would take their truck driver customers in a place where there seemed\nto be only road and forest.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15578016638755798, "y": 0.29103976488113403 }, { "x": 0.8694375455379486, "y": 0.29103976488113403 }, { "x": 0.8694375455379486, "y": 0.40791184455156326 }, { "x": 0.15578016638755798, "y": 0.40791184455156326 } ], "category": "paragraph", "id": 454, "content": { "text": "Anthea's navigation skills took us promptly to the clean and pleasant\nTumski Hotel on the Sand Island near the oldest part of Wroclaw. I was\nimmensely moved when I found that my room overlooked a canal of the\nOder. This was a place of which mother had often spoken. Maria on the\nSand (die Sandkirche) is still there, one of the large old Gothic red-brick\nchurches that escaped bombing.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.155416801571846, "y": 0.4227970838546753 }, { "x": 0.869069829583168, "y": 0.4227970838546753 }, { "x": 0.869069829583168, "y": 0.5400027260184288 }, { "x": 0.155416801571846, "y": 0.5400027260184288 } ], "category": "paragraph", "id": 455, "content": { "text": "That Saturday afternoon, too late for lunch, we sampled Polish beer and\nvodka. We explored the famous Rynek, the central seventeenth-century\nmarket square with its famed Gothic town hall where American soldiers\nhad stolen the gold from the astrological clock. The bombed-out buildings\nhad been restored, but they were too garishly painted to revive a sense\nof their history. The adjoining salt square now mostly sells flowers.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15567757189273834, "y": 0.5555379390716553 }, { "x": 0.8692297488451004, "y": 0.5555379390716553 }, { "x": 0.8692297488451004, "y": 0.632627584040165 }, { "x": 0.15567757189273834, "y": 0.632627584040165 } ], "category": "paragraph", "id": 456, "content": { "text": "We wondered at how few smiling faces there were, and were puzzled\nby how little German or English anyone spoke. Why was there SO little\ntourism? Only a pair of elegant teenagers had fluent German. We turned\ndown their offers of pornographic pictures and sexual experiences.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15589185059070587, "y": 0.6477404236793518 }, { "x": 0.8693446666002274, "y": 0.6477404236793518 }, { "x": 0.8693446666002274, "y": 0.7047189921140671 }, { "x": 0.15589185059070587, "y": 0.7047189921140671 } ], "category": "paragraph", "id": 457, "content": { "text": "We covered enough of the area to get a strong impression of a once-\nlively city devastated by War and hastily repaired. These were convenient\nreconstructions, done without an eye to matching styles.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15509964525699615, "y": 0.7206199765205383 }, { "x": 0.8698158413171768, "y": 0.7206199765205383 }, { "x": 0.8698158413171768, "y": 0.8173422664403915 }, { "x": 0.15509964525699615, "y": 0.8173422664403915 } ], "category": "paragraph", "id": 458, "content": { "text": "I was especially anxious to find out where Neumarkt Platz had been.\nThat evening at the hotel, I kept going to the window and trying to\nimagine my mother as a young woman taking an evening stroll with\na companion along the banks of the Oder. But this was autumn. Thick\nmists hung above the water. Few people were out walking.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15552011132240295, "y": 0.8322709202766418 }, { "x": 0.8689157664775848, "y": 0.8322709202766418 }, { "x": 0.8689157664775848, "y": 0.9098236337304115 }, { "x": 0.15552011132240295, "y": 0.9098236337304115 } ], "category": "paragraph", "id": 459, "content": { "text": "On Sunday we set out seriously to find the location of the old square.\nWe walked through once-stately streets, past the Metropole Hotel from\nwhere Hitler had addressed the crowds, to the Ethnographic Museum.\nThis proved disappointing. The contents of two rooms were a mere\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09253610670566559, "y": 0.9318408370018005 }, { "x": 0.11022869311273098, "y": 0.9318408370018005 }, { "x": 0.11022869311273098, "y": 0.9406159054487944 }, { "x": 0.09253610670566559, "y": 0.9406159054487944 } ], "category": "paragraph", "id": 460, "content": { "text": "10\n", "html": "", "markdown": "" } } ] }, "01030000000151.pdf": { "elements": [ { "coordinates": [ { "x": 0.09228526800870895, "y": 0.14810901880264282 }, { "x": 0.20705463737249374, "y": 0.14810901880264282 }, { "x": 0.20705463737249374, "y": 0.15937296207994223 }, { "x": 0.09228526800870895, "y": 0.15937296207994223 } ], "category": "paragraph", "id": 241, "content": { "text": "CHAPTER 1.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09162239730358124, "y": 0.18634995818138123 }, { "x": 0.22274474799633026, "y": 0.18634995818138123 }, { "x": 0.22274474799633026, "y": 0.1983309853821993 }, { "x": 0.09162239730358124, "y": 0.1983309853821993 } ], "category": "paragraph", "id": 242, "content": { "text": "CALIFORNIA\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09208296984434128, "y": 0.3043159246444702 }, { "x": 0.3001892492175102, "y": 0.3043159246444702 }, { "x": 0.3001892492175102, "y": 0.31370087154209614 }, { "x": 0.09208296984434128, "y": 0.31370087154209614 } ], "category": "paragraph", "id": 243, "content": { "text": "JAMES GLAPA-GROSSKLAG\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.092430479824543, "y": 0.3759878873825073 }, { "x": 0.36189601570367813, "y": 0.3759878873825073 }, { "x": 0.36189601570367813, "y": 0.38751442451030016 }, { "x": 0.092430479824543, "y": 0.38751442451030016 } ], "category": "heading1", "id": 244, "content": { "text": "COURSE MARKING DRIVERS\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09227873384952545, "y": 0.4058399796485901 }, { "x": 0.907135620713234, "y": 0.4058399796485901 }, { "x": 0.907135620713234, "y": 0.49932700395584106 }, { "x": 0.09227873384952545, "y": 0.49932700395584106 } ], "category": "paragraph", "id": 245, "content": { "text": "SB1359 was passed in September 2016, going into force in January 2018. The law \"requires California\nCommunity Colleges and California State Universities and requests the University of California\nsystem to include a symbol/logo in the online campus course schedule by January 1, 2018 for courses\nthat exclusively use digital course materials that are free of charge to students and therefore not\nrequired to be purchased.\"\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09129542857408524, "y": 0.5164058804512024 }, { "x": 0.9073443487286568, "y": 0.5164058804512024 }, { "x": 0.9073443487286568, "y": 0.6108276695013046 }, { "x": 0.09129542857408524, "y": 0.6108276695013046 } ], "category": "paragraph", "id": 246, "content": { "text": "The potential scale of impact is significant. With 114 colleges serving 2.1 million students, the\nCalifornia Community Colleges (CCCs) comprise the largest public system of higher education in the\nUS. The California State University (CSU) with 23 campuses serving nearly 500,000 students, is the\nlargest four-year public university system in the US. Notably, the law does not apply to the state's\nresearch-focused University of California.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.4034990668296814, "y": 0.6198394894599915 }, { "x": 0.5966031402349472, "y": 0.6198394894599915 }, { "x": 0.5966031402349472, "y": 0.7279586791992188 }, { "x": 0.4034990668296814, "y": 0.7279586791992188 } ], "category": "figure", "id": 247, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.4041299521923065, "y": 0.7419170141220093 }, { "x": 0.5814975500106812, "y": 0.7419170141220093 }, { "x": 0.5814975500106812, "y": 0.768336171284318 }, { "x": 0.4041299521923065, "y": 0.768336171284318 } ], "category": "paragraph", "id": 248, "content": { "text": "Figure 1.1: Zero Cost Textbook\nLogo\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09302186220884323, "y": 0.7933060526847839 }, { "x": 0.26589102298021317, "y": 0.7933060526847839 }, { "x": 0.26589102298021317, "y": 0.8044889010488987 }, { "x": 0.09302186220884323, "y": 0.8044889010488987 } ], "category": "heading1", "id": 249, "content": { "text": "IMPLEMENTATION\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09190935641527176, "y": 0.8227576017379761 }, { "x": 0.9070897772908211, "y": 0.8227576017379761 }, { "x": 0.9070897772908211, "y": 0.915407344698906 }, { "x": 0.09190935641527176, "y": 0.915407344698906 } ], "category": "paragraph", "id": 250, "content": { "text": "Between the passage of the law in 2016 and the implementation of the law in 2018, both the CCCs\nand CSU systems engaged in outreach to the field. The CCCs' system office issued a memo to college\nleadership explaining the requirements and created a sample logo that colleges could choose to adopt.\nThe CSU system's Affordable Learning Solutions team engaged the field with a series of webinars and\nFAQs.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.7556752562522888, "y": 0.9510771036148071 }, { "x": 0.9062568098306656, "y": 0.9510771036148071 }, { "x": 0.9062568098306656, "y": 0.9588145795278251 }, { "x": 0.7556752562522888, "y": 0.9588145795278251 } ], "category": "footer", "id": 251, "content": { "text": "PRICE TRANSPARENCY 1\n", "html": "", "markdown": "" } } ] }, "01030000000193.pdf": { "elements": [ { "coordinates": [ { "x": 0.11211590468883514, "y": 0.09053071588277817 }, { "x": 0.8870740979909897, "y": 0.09053071588277817 }, { "x": 0.8870740979909897, "y": 0.9182716235518456 }, { "x": 0.11211590468883514, "y": 0.9182716235518456 } ], "category": "table", "id": 789, "content": { "text": "", "html": "
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Zephyr: Di-\nrect distillation of lm alignment. arXiv preprint\narXiv:2310.16944.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5135813355445862, "y": 0.4585406482219696 }, { "x": 0.8833425343036652, "y": 0.4585406482219696 }, { "x": 0.8833425343036652, "y": 0.5329826027154922 }, { "x": 0.5135813355445862, "y": 0.5329826027154922 } ], "category": "paragraph", "id": 834, "content": { "text": "Peihao Wang, Rameswar Panda, Lucas Torroba Hen-\nnigen, Philip Greengard, Leonid Karlinsky, Roge-\nrio Feris, David Daniel Cox, Zhangyang Wang, and\nYoon Kim. 2023. Learning to grow pretrained mod-\nels for efficient transformer training. arXiv preprint\narXiv:2303.00980.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5135125517845154, "y": 0.5457387566566467 }, { "x": 0.8831159174442291, "y": 0.5457387566566467 }, { "x": 0.8831159174442291, "y": 0.6090365499258041 }, { "x": 0.5135125517845154, "y": 0.6090365499258041 } ], "category": "paragraph", "id": 835, "content": { "text": "Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Al-\nisa Liu, Noah A Smith, Daniel Khashabi, and Han-\nnaneh Hajishirzi. 2022. Self-instruct: Aligning lan-\nguage model with self generated instructions. arXiv\npreprint arXiv:2212.10560.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5132407546043396, "y": 0.6195154190063477 }, { "x": 0.8834303915500641, "y": 0.6195154190063477 }, { "x": 0.8834303915500641, "y": 0.6811784021556377 }, { "x": 0.5132407546043396, "y": 0.6811784021556377 } ], "category": "paragraph", "id": 836, "content": { "text": "Jason Wei, Maarten Bosma, Vincent Y Zhao, Kelvin\nGuu, Adams Wei Yu, Brian Lester, Nan Du, An-\ndrew M Dai, and Quoc V Le. 2021. Finetuned lan-\nguage models are zero-shot learners. arXiv preprint\narXiv:2109.01652.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5134361982345581, "y": 0.693654477596283 }, { "x": 0.8830721974372864, "y": 0.693654477596283 }, { "x": 0.8830721974372864, "y": 0.757329635322094 }, { "x": 0.5134361982345581, "y": 0.757329635322094 } ], "category": "paragraph", "id": 837, "content": { "text": "Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel,\nBarret Zoph, Sebastian Borgeaud, Dani Yogatama,\nMaarten Bosma, Denny Zhou, Donald Metzler, et al.\n2022a. Emergent abilities of large language models.\narXiv preprint rXiv:2206.07682.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5133083462715149, "y": 0.7679065465927124 }, { "x": 0.8832537829875946, "y": 0.7679065465927124 }, { "x": 0.8832537829875946, "y": 0.8312373161315918 }, { "x": 0.5133083462715149, "y": 0.8312373161315918 } ], "category": "paragraph", "id": 838, "content": { "text": "Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten\nBosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou,\net al. 2022b. Chain-of-thought prompting elicits rea-\nsoning in large language models. Advances in Neural\nInformation Processing Systems, 35:24824-24837.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5135031342506409, "y": 0.8420345187187195 }, { "x": 0.8833158910274506, "y": 0.8420345187187195 }, { "x": 0.8833158910274506, "y": 0.9163724258542061 }, { "x": 0.5135031342506409, "y": 0.9163724258542061 } ], "category": "paragraph", "id": 839, "content": { "text": "Thomas Wolf, Lysandre Debut, Victor Sanh, Julien\nChaumond, Clement Delangue, Anthony Moi, Pier-\nric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz,\net al. 2019. Huggingface's transformers: State-of-\nthe-art natural language processing. arXiv preprint\narXiv: 1910.03771.\n", "html": "", "markdown": "" } } ] }, "01030000000167.pdf": { "elements": [ { "coordinates": [ { "x": 0.09167000651359558, "y": 0.07525166124105453 }, { "x": 0.9069871008396149, "y": 0.07525166124105453 }, { "x": 0.9069871008396149, "y": 0.14126047492027283 }, { "x": 0.09167000651359558, "y": 0.14126047492027283 } ], "category": "paragraph", "id": 580, "content": { "text": "The acidic cations adsorbed on the negative exchange sites are called the reserve (also residual or potential) and salt-\nreplaceable (also exchangeable) acidity. The reserve and salt-replaceable acidity controls the level of soluble or active\nacidity in the soil solution. Only the active acidity is measured in a routine pH determination. The reserve and salt-\nreplaceable acidity is always many times higher than the active acidity.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09178180247545242, "y": 0.15724565088748932 }, { "x": 0.9069788530468941, "y": 0.15724565088748932 }, { "x": 0.9069788530468941, "y": 0.2027123011648655 }, { "x": 0.09178180247545242, "y": 0.2027123011648655 } ], "category": "paragraph", "id": 581, "content": { "text": "A soil is acid when hydrogen ions predominate in the soil. The degree of acidity is expressed in terms of pH, which is\ndefined as the negative logarithm of the hydrogen ion activity. Therefore, the pH of a 0.01-molar hydrogen ion solution\nis\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09162614494562149, "y": 0.2762143611907959 }, { "x": 0.9070389047265053, "y": 0.2762143611907959 }, { "x": 0.9070389047265053, "y": 0.35965777188539505 }, { "x": 0.09162614494562149, "y": 0.35965777188539505 } ], "category": "paragraph", "id": 582, "content": { "text": "At pH 7, the concentration of H+ ions and OH- ions are equal, and the soil or solution is neutral. At pH values less than 7,\nthe soil is acid; at values more than 7, the soil is alkaline. Most soils vary in pH from about 4 to 10. Soils in areas with high\nrainfall are generally acid with a pH less than 7. Soils developed in high-lime deposits often will be alkaline. Soils high in\ncalcium seldom have pH values higher than 7.5, but the presence of large amounts of calcium carbonate may cause the\npH to be as high as 8.5. Where the pH is higher than 8.5, an excess of sodium is highly probable.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0916467234492302, "y": 0.37588512897491455 }, { "x": 0.9073165580630302, "y": 0.37588512897491455 }, { "x": 0.9073165580630302, "y": 0.40636054426431656 }, { "x": 0.0916467234492302, "y": 0.40636054426431656 } ], "category": "paragraph", "id": 583, "content": { "text": "The most desirable soil pH for most crops in Kansas is 6.8. However, crops like blueberries need a lower pH, and other\ncrops, like alfalfa, need a higher pH. At soil pH less than 5.8, several problems may occur:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10279936343431473, "y": 0.4276825189590454 }, { "x": 0.24619170278310776, "y": 0.4276825189590454 }, { "x": 0.24619170278310776, "y": 0.43992909882217646 }, { "x": 0.10279936343431473, "y": 0.43992909882217646 } ], "category": "paragraph", "id": 585, "content": { "text": "Al and Mn toxicity\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10324607789516449, "y": 0.4455149471759796 }, { "x": 0.374046191573143, "y": 0.4455149471759796 }, { "x": 0.374046191573143, "y": 0.4581199698150158 }, { "x": 0.10324607789516449, "y": 0.4581199698150158 } ], "category": "paragraph", "id": 586, "content": { "text": "Inhibited growth of N-fixing bacteria\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10288283228874207, "y": 0.4630115330219269 }, { "x": 0.3843258321285248, "y": 0.4630115330219269 }, { "x": 0.3843258321285248, "y": 0.47546359058469534 }, { "x": 0.10288283228874207, "y": 0.47546359058469534 } ], "category": "paragraph", "id": 587, "content": { "text": "Possible deficiencies in Mg and/or Ca.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10316724330186844, "y": 0.48046138882637024 }, { "x": 0.372712142765522, "y": 0.48046138882637024 }, { "x": 0.372712142765522, "y": 0.4932401105761528 }, { "x": 0.10316724330186844, "y": 0.4932401105761528 } ], "category": "paragraph", "id": 588, "content": { "text": "P deficiency (P reacts with Fe and Al)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10291241854429245, "y": 0.4985024631023407 }, { "x": 0.44859739392995834, "y": 0.4985024631023407 }, { "x": 0.44859739392995834, "y": 0.5111479219049215 }, { "x": 0.10291241854429245, "y": 0.5111479219049215 } ], "category": "paragraph", "id": 589, "content": { "text": "At more than pH 7.5, other problems may occur:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10303502529859543, "y": 0.5161550641059875 }, { "x": 0.33163078874349594, "y": 0.5161550641059875 }, { "x": 0.33163078874349594, "y": 0.5285903662443161 }, { "x": 0.10303502529859543, "y": 0.5285903662443161 } ], "category": "paragraph", "id": 590, "content": { "text": "Deficiency of Fe, Mn, Cu, or Zn\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10315758734941483, "y": 0.5336974263191223 }, { "x": 0.328160859644413, "y": 0.5336974263191223 }, { "x": 0.328160859644413, "y": 0.5460291849449277 }, { "x": 0.10315758734941483, "y": 0.5460291849449277 } ], "category": "paragraph", "id": 591, "content": { "text": "P deficiency (P reacts with Ca)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09321118891239166, "y": 0.5889560580253601 }, { "x": 0.26664139330387115, "y": 0.5889560580253601 }, { "x": 0.26664139330387115, "y": 0.6084658429026604 }, { "x": 0.09321118891239166, "y": 0.6084658429026604 } ], "category": "heading1", "id": 592, "content": { "text": "Buffering Capacity\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09191905707120895, "y": 0.6378293633460999 }, { "x": 0.9077371880412102, "y": 0.6378293633460999 }, { "x": 0.9077371880412102, "y": 0.7569837048649788 }, { "x": 0.09191905707120895, "y": 0.7569837048649788 } ], "category": "paragraph", "id": 593, "content": { "text": "Buffering capacity is a measure of the soil's ability to resist a change in pH, directly related to the magnitude of the\nexchange capacity. Small fluctuations in acid or base content can occur without a noticeable pH change as cations are\nadsorbed or released from the exchange complex. Soils with the largest cation exchange capacity have the greatest\nbuffering of a pH change. In other words, two soils may have the same pH (active acidity in soil solution), but the one\nwith the largest cation exchange capacity will have the most acidity stored in reserve and therefore the highest buffering\ncapacity or ability to resist a change in pH. For this reason, it takes less lime to increase the pH of a sandy soil (low CEC)\nby a given amount than it takes to increase the pH of a clay soil (higher CEC) the same amount.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09325503557920456, "y": 0.7997015714645386 }, { "x": 0.30177778750658035, "y": 0.7997015714645386 }, { "x": 0.30177778750658035, "y": 0.8189307693392038 }, { "x": 0.09325503557920456, "y": 0.8189307693392038 } ], "category": "heading1", "id": 594, "content": { "text": "Sources of Soil Acidity\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0920228436589241, "y": 0.8485241532325745 }, { "x": 0.907279796898365, "y": 0.8485241532325745 }, { "x": 0.907279796898365, "y": 0.9141630455851555 }, { "x": 0.0920228436589241, "y": 0.9141630455851555 } ], "category": "paragraph", "id": 595, "content": { "text": "Controlling soil pH is vital to optimal use and productivity of soils. Adding lime is the most effective and practical way\nto raise the pH of acid soils. Elemental sulfur, iron sulfate, or aluminum sulfate can be used to reduce soil pH. Because\nacidity is a concern in Kansas, we will focus on raising soil pH. Understanding the following equations should help you\nunderstand the sources of soil acidity and soil reactions to lime.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0922820121049881, "y": 0.9418616890907288 }, { "x": 0.11065422743558884, "y": 0.9418616890907288 }, { "x": 0.11065422743558884, "y": 0.949699486605823 }, { "x": 0.0922820121049881, "y": 0.949699486605823 } ], "category": "paragraph", "id": 596, "content": { "text": "124\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12750239670276642, "y": 0.9414671659469604 }, { "x": 0.3284365087747574, "y": 0.9414671659469604 }, { "x": 0.3284365087747574, "y": 0.9525658572092652 }, { "x": 0.12750239670276642, "y": 0.9525658572092652 } ], "category": "footer", "id": 597, "content": { "text": "Soil Acidity and Adjusting Soil pH\n", "html": "", "markdown": "" } } ] }, "01030000000018.pdf": { "elements": [ { "coordinates": [ { "x": 0.12422121316194534, "y": 0.3154641091823578 }, { "x": 0.8487181141972542, "y": 0.3154641091823578 }, { "x": 0.8487181141972542, "y": 0.8909057080745697 }, { "x": 0.12422121316194534, "y": 0.8909057080745697 } ], "category": "table", "id": 203, "content": { "text": "", "html": "
Author's Note to the 2021 Edition ix
Foreword to the 2021 Edition xi
Foreword and Acknowledgements XV
1. A Fountain in the Square 1
2. The Lost Homeland5
3. Steinkirche13
4. A Jewel in the Austrian Crown19
5. Meeting the Relatives37
6. For the Love of Iran41
7. To the Bottom of the World53
8. Das Lager65
9. His Majesty's Guests79
10. The Imaginary Homeland91
11. Shadows and Flames119
12. After the War123
13. Stranded in Exile127
14. Swimming for the Eucharist139
15. Ad Maiorem Dei Gloriam155
16. Mirror Without Identity173
17. The Wreck of the Deutschland191
18. Intelligence Testing209
19. A Banquet of Life223
20. Marriage in Rome249
21. Integration257
", "markdown": "" } }, { "coordinates": [ { "x": 0.38474926352500916, "y": 0.21004855632781982 }, { "x": 0.5877758860588074, "y": 0.21004855632781982 }, { "x": 0.5877758860588074, "y": 0.236622491851449 }, { "x": 0.38474926352500916, "y": 0.236622491851449 } ], "category": "heading1", "id": 257, "content": { "text": "Contents\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12901000678539276, "y": 0.31085899472236633 }, { "x": 0.43702365458011627, "y": 0.31085899472236633 }, { "x": 0.43702365458011627, "y": 0.32275241147726774 }, { "x": 0.12901000678539276, "y": 0.32275241147726774 } ], "category": "paragraph", "id": 258, "content": { "text": "Author's Note to the 2021 Edition\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8268564343452454, "y": 0.31207484006881714 }, { "x": 0.8426988702267408, "y": 0.31207484006881714 }, { "x": 0.8426988702267408, "y": 0.322137214243412 }, { "x": 0.8268564343452454, "y": 0.322137214243412 } ], "category": "paragraph", "id": 259, "content": { "text": "ix\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.13056989014148712, "y": 0.33566150069236755 }, { "x": 0.3973153978586197, "y": 0.33566150069236755 }, { "x": 0.3973153978586197, "y": 0.34719534777104855 }, { "x": 0.13056989014148712, "y": 0.34719534777104855 } ], "category": "paragraph", "id": 260, "content": { "text": "Foreword to the 2021 Edition\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8261200785636902, "y": 0.3367207646369934 }, { "x": 0.8427914921194315, "y": 0.3367207646369934 }, { "x": 0.8427914921194315, "y": 0.34696885850280523 }, { "x": 0.8261200785636902, "y": 0.34696885850280523 } ], "category": "paragraph", "id": 261, "content": { "text": "xi\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.13068178296089172, "y": 0.3599221110343933 }, { "x": 0.43171313405036926, "y": 0.3599221110343933 }, { "x": 0.43171313405036926, "y": 0.37493655923753977 }, { "x": 0.13068178296089172, "y": 0.37493655923753977 } ], "category": "paragraph", "id": 262, "content": { "text": "Foreword and Acknowledgements\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.13206620514392853, "y": 0.38545435667037964 }, { "x": 0.1469381395727396, "y": 0.38545435667037964 }, { "x": 0.1469381395727396, "y": 0.3957599839195609 }, { "x": 0.13206620514392853, "y": 0.3957599839195609 } ], "category": "paragraph", "id": 263, "content": { "text": "1.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8222633004188538, "y": 0.36408132314682007 }, { "x": 0.842836294323206, "y": 0.36408132314682007 }, { "x": 0.842836294323206, "y": 0.37138723488897085 }, { "x": 0.8222633004188538, "y": 0.37138723488897085 } ], "category": "paragraph", "id": 264, "content": { "text": "XV\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.18191474676132202, "y": 0.3844379484653473 }, { "x": 0.4076731652021408, "y": 0.3844379484653473 }, { "x": 0.4076731652021408, "y": 0.3994826627895236 }, { "x": 0.18191474676132202, "y": 0.3994826627895236 } ], "category": "paragraph", "id": 265, "content": { "text": "A Fountain in the Square\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8329137563705444, "y": 0.3854767680168152 }, { "x": 0.8401599605567753, "y": 0.3854767680168152 }, { "x": 0.8401599605567753, "y": 0.3959496794268489 }, { "x": 0.8329137563705444, "y": 0.3959496794268489 } ], "category": "paragraph", "id": 266, "content": { "text": "1\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.13049651682376862, "y": 0.4089311957359314 }, { "x": 0.3615717887878418, "y": 0.4089311957359314 }, { "x": 0.3615717887878418, "y": 0.4206225909292698 }, { "x": 0.13049651682376862, "y": 0.4206225909292698 } ], "category": "paragraph", "id": 267, "content": { "text": "2.\nThe Lost Homeland\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8316737413406372, "y": 0.40990546345710754 }, { "x": 0.8416155632585287, "y": 0.40990546345710754 }, { "x": 0.8416155632585287, "y": 0.4212571596726775 }, { "x": 0.8316737413406372, "y": 0.4212571596726775 } ], "category": "paragraph", "id": 268, "content": { "text": "5\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.130598783493042, "y": 0.4332088828086853 }, { "x": 0.2821562588214874, "y": 0.4332088828086853 }, { "x": 0.2821562588214874, "y": 0.4452374121174216 }, { "x": 0.130598783493042, "y": 0.4452374121174216 } ], "category": "paragraph", "id": 269, "content": { "text": "3.\nSteinkirche\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8216373324394226, "y": 0.433977872133255 }, { "x": 0.8415400348603725, "y": 0.433977872133255 }, { "x": 0.8415400348603725, "y": 0.4450793517753482 }, { "x": 0.8216373324394226, "y": 0.4450793517753482 } ], "category": "paragraph", "id": 270, "content": { "text": "13\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.13003608584403992, "y": 0.45765867829322815 }, { "x": 0.4547651410102844, "y": 0.45765867829322815 }, { "x": 0.4547651410102844, "y": 0.4721924578770995 }, { "x": 0.13003608584403992, "y": 0.4721924578770995 } ], "category": "paragraph", "id": 271, "content": { "text": "4.\nA Jewel in the Austrian Crown\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8214051723480225, "y": 0.45838019251823425 }, { "x": 0.841813288629055, "y": 0.45838019251823425 }, { "x": 0.841813288629055, "y": 0.46965289302170277 }, { "x": 0.8214051723480225, "y": 0.46965289302170277 } ], "category": "paragraph", "id": 272, "content": { "text": "19\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1306641548871994, "y": 0.4824357032775879 }, { "x": 0.3741411864757538, "y": 0.4824357032775879 }, { "x": 0.3741411864757538, "y": 0.4977139104157686 }, { "x": 0.1306641548871994, "y": 0.4977139104157686 } ], "category": "paragraph", "id": 273, "content": { "text": "5.\nMeeting the Relatives\n", "html": "", "markdown": "" } }, { "coordinates": [ { 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"" } }, { "coordinates": [ { "x": 0.18205121159553528, "y": 0.5311787128448486 }, { "x": 0.43390849232673645, "y": 0.5311787128448486 }, { "x": 0.43390849232673645, "y": 0.5429610321298242 }, { "x": 0.18205121159553528, "y": 0.5429610321298242 } ], "category": "paragraph", "id": 277, "content": { "text": "To the Bottom of the World\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.13000664114952087, "y": 0.5323105454444885 }, { "x": 0.14640676975250244, "y": 0.5323105454444885 }, { "x": 0.14640676975250244, "y": 0.5431724693626165 }, { "x": 0.13000664114952087, "y": 0.5431724693626165 } ], "category": "paragraph", "id": 278, "content": { "text": "7.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8201979994773865, "y": 0.5320501923561096 }, { "x": 0.8413275275379419, "y": 0.5320501923561096 }, { "x": 0.8413275275379419, "y": 0.5434152781963348 }, { "x": 0.8201979994773865, "y": 0.5434152781963348 } ], "category": "paragraph", "id": 279, "content": { "text": "53\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.13064371049404144, "y": 0.5562184453010559 }, { "x": 0.27050574123859406, "y": 0.5562184453010559 }, { "x": 0.27050574123859406, "y": 0.5712706875056028 }, { "x": 0.13064371049404144, "y": 0.5712706875056028 } ], "category": "paragraph", "id": 280, "content": { "text": "8.\nDas Lager\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8194543719291687, "y": 0.5563286542892456 }, { "x": 0.8416068833321333, "y": 0.5563286542892456 }, { "x": 0.8416068833321333, "y": 0.5680633541196585 }, { "x": 0.8194543719291687, "y": 0.5680633541196585 } ], "category": "paragraph", "id": 281, "content": { "text": "65\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1830902397632599, "y": 0.5809733271598816 }, { "x": 0.36529241502285004, "y": 0.5809733271598816 }, { "x": 0.36529241502285004, "y": 0.5956700397655368 }, { "x": 0.1830902397632599, "y": 0.5956700397655368 } ], "category": "paragraph", "id": 282, "content": { "text": "His Majesty's Guests\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1302666813135147, "y": 0.5814995765686035 }, { "x": 0.14658362045884132, "y": 0.5814995765686035 }, { "x": 0.14658362045884132, "y": 0.5925407456234097 }, { "x": 0.1302666813135147, "y": 0.5925407456234097 } ], "category": "paragraph", "id": 283, "content": { "text": "9.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8189159631729126, "y": 0.5814632177352905 }, { "x": 0.8418720625340939, "y": 0.5814632177352905 }, { "x": 0.8418720625340939, "y": 0.5926470588892698 }, { "x": 0.8189159631729126, "y": 0.5926470588892698 } ], "category": "paragraph", "id": 284, "content": { "text": "79\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1319383680820465, "y": 0.6048922538757324 }, { "x": 0.41361165046691895, "y": 0.6048922538757324 }, { "x": 0.41361165046691895, "y": 0.619824874214828 }, { "x": 0.1319383680820465, "y": 0.619824874214828 } ], "category": "paragraph", "id": 285, "content": { "text": "10.\nThe Imaginary Homeland\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1322629153728485, "y": 0.629314661026001 }, { "x": 0.3663482517004013, "y": 0.629314661026001 }, { "x": 0.3663482517004013, "y": 0.6410221895202994 }, { "x": 0.1322629153728485, "y": 0.6410221895202994 } ], "category": "paragraph", "id": 286, "content": { "text": "11.\nShadows and Flames\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8195030689239502, "y": 0.605778157711029 }, { "x": 0.8401927333325148, "y": 0.605778157711029 }, { "x": 0.8401927333325148, "y": 0.6165892276912928 }, { "x": 0.8195030689239502, "y": 0.6165892276912928 } ], "category": "paragraph", "id": 287, "content": { "text": "91\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8096945881843567, "y": 0.6303407549858093 }, { "x": 0.8417883105576038, "y": 0.6303407549858093 }, { "x": 0.8417883105576038, "y": 0.6414900654926896 }, { "x": 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{ "x": 0.402209535241127, "y": 0.7521380186080933 }, { "x": 0.402209535241127, "y": 0.7670096522197127 }, { "x": 0.13226453959941864, "y": 0.7670096522197127 } ], "category": "paragraph", "id": 297, "content": { "text": "16.\nMirror Without Identity\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8105829954147339, "y": 0.7527232766151428 }, { "x": 0.8412545192986727, "y": 0.7527232766151428 }, { "x": 0.8412545192986727, "y": 0.7639764174818993 }, { "x": 0.8105829954147339, "y": 0.7639764174818993 } ], "category": "paragraph", "id": 298, "content": { "text": "173\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1853078007698059, "y": 0.7760208249092102 }, { "x": 0.4373679459095001, "y": 0.7760208249092102 }, { "x": 0.4373679459095001, "y": 0.7916562408208847 }, { "x": 0.1853078007698059, "y": 0.7916562408208847 } ], "category": "paragraph", "id": 299, "content": { "text": "The Wreck of the Deutschland\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8104056119918823, "y": 0.7771617770195007 }, { "x": 0.8401820603758097, "y": 0.7771617770195007 }, { "x": 0.8401820603758097, "y": 0.7882069768384099 }, { "x": 0.8104056119918823, "y": 0.7882069768384099 } ], "category": "paragraph", "id": 300, "content": { "text": "191\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.13234853744506836, "y": 0.7773382663726807 }, { "x": 0.15766269527375698, "y": 0.7773382663726807 }, { "x": 0.15766269527375698, "y": 0.7881738413125277 }, { "x": 0.13234853744506836, "y": 0.7881738413125277 } ], "category": "paragraph", "id": 301, "content": { "text": "17.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8080631494522095, "y": 0.8017809987068176 }, { "x": 0.8417916931211948, "y": 0.8017809987068176 }, { "x": 0.8417916931211948, "y": 0.8128388896584511 }, { "x": 0.8080631494522095, "y": 0.8128388896584511 } ], "category": "paragraph", "id": 302, "content": { "text": "209\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.18254423141479492, "y": 0.8010915517807007 }, { "x": 0.354984849691391, "y": 0.8010915517807007 }, { "x": 0.354984849691391, "y": 0.8163119601085782 }, { "x": 0.18254423141479492, "y": 0.8163119601085782 } ], "category": "paragraph", "id": 303, "content": { "text": "Intelligence Testing\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.13210764527320862, "y": 0.8018979430198669 }, { "x": 0.1576982196420431, "y": 0.8018979430198669 }, { "x": 0.1576982196420431, "y": 0.8125282265245914 }, { "x": 0.13210764527320862, "y": 0.8125282265245914 } ], "category": "paragraph", "id": 304, "content": { "text": "18.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.13184931874275208, "y": 0.8255215883255005 }, { "x": 0.3411302864551544, "y": 0.8255215883255005 }, { "x": 0.3411302864551544, "y": 0.8407218093052506 }, { "x": 0.13184931874275208, "y": 0.8407218093052506 } ], "category": "paragraph", "id": 305, "content": { "text": "19.\nA Banquet 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"text": "20.\nMarriage in Rome\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8082446455955505, "y": 0.875247597694397 }, { "x": 0.8423297367990017, "y": 0.875247597694397 }, { "x": 0.8423297367990017, "y": 0.8865395719185472 }, { "x": 0.8082446455955505, "y": 0.8865395719185472 } ], "category": "paragraph", "id": 309, "content": { "text": "257\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.13062648475170135, "y": 0.8749800324440002 }, { "x": 0.2819833904504776, "y": 0.8749800324440002 }, { "x": 0.2819833904504776, "y": 0.8895603911951184 }, { "x": 0.13062648475170135, "y": 0.8895603911951184 } ], "category": "paragraph", "id": 310, "content": { "text": "21.\nIntegration\n", "html": "", "markdown": "" } } ] }, "01030000000107.pdf": { "elements": [ { "coordinates": [ { "x": 0.08908967673778534, "y": 0.08443597704172134 }, { "x": 0.2279595583677292, "y": 0.08443597704172134 }, { "x": 0.2279595583677292, "y": 0.09891349263489246 }, { "x": 0.08908967673778534, "y": 0.09891349263489246 } ], "category": "paragraph", "id": 174, "content": { "text": "Print VS. Digital\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0873018428683281, "y": 0.12456393986940384 }, { "x": 0.9107437059283257, "y": 0.12456393986940384 }, { "x": 0.9107437059283257, "y": 0.1629001460969448 }, { "x": 0.0873018428683281, "y": 0.1629001460969448 } ], "category": "paragraph", "id": 175, "content": { "text": "Why do some researchers abhor digital and favor print, or vice-versa? The classic print\nVS. digital debate was necessary for us to understand readers' preferences with each\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1695546656847, "y": 0.17748892307281494 }, { "x": 0.8311591893434525, "y": 0.17748892307281494 }, { "x": 0.8311591893434525, "y": 0.194929463788867 }, { "x": 0.1695546656847, "y": 0.194929463788867 } ], "category": "paragraph", "id": 176, "content": { "text": "Q11 What factors influence your choice of print? (select all that apply)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.2332184910774231, "y": 0.2060317099094391 }, { "x": 0.7355737090110779, "y": 0.2060317099094391 }, { "x": 0.7355737090110779, "y": 0.49455389380455017 }, { "x": 0.2332184910774231, "y": 0.49455389380455017 } ], "category": "figure", "id": 177, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08729176223278046, "y": 0.49437829852104187 }, { "x": 0.15561485290527344, "y": 0.49437829852104187 }, { "x": 0.15561485290527344, "y": 0.5059901727363467 }, { "x": 0.08729176223278046, "y": 0.5059901727363467 } ], "category": "paragraph", "id": 178, "content": { "text": "format.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09899550676345825, "y": 0.5228080749511719 }, { "x": 0.7808273434638977, "y": 0.5228080749511719 }, { "x": 0.7808273434638977, "y": 0.5405474361032248 }, { "x": 0.09899550676345825, "y": 0.5405474361032248 } ], "category": "paragraph", "id": 179, "content": { "text": "Q12 What factors influence your choice of digital? (select all that apply)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3722655177116394, "y": 0.5520465970039368 }, { "x": 0.5191285610198975, "y": 0.5520465970039368 }, { "x": 0.5191285610198975, "y": 0.5607204707339406 }, { "x": 0.3722655177116394, "y": 0.5607204707339406 } ], "category": "paragraph", "id": 180, "content": { "text": "Answered: 80\nSkipped: 24\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.17076365649700165, "y": 0.5762189030647278 }, { "x": 0.6797010749578476, "y": 0.5762189030647278 }, { "x": 0.6797010749578476, "y": 0.8430882096290588 }, { "x": 0.17076365649700165, "y": 0.8430882096290588 } ], "category": "figure", "id": 181, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.7872462272644043, "y": 0.9373438358306885 }, { "x": 0.9109955281019211, "y": 0.9373438358306885 }, { "x": 0.9109955281019211, "y": 0.9483078746125102 }, { "x": 0.7872462272644043, "y": 0.9483078746125102 } ], "category": "footer", "id": 182, "content": { "text": "Online Survey I 39\n", "html": "", "markdown": "" } } ] }, "01030000000015.pdf": { "elements": [ { "coordinates": [ { "x": 0.10306218266487122, "y": 0.049885135143995285 }, { "x": 0.28699444234371185, "y": 0.049885135143995285 }, { "x": 0.28699444234371185, "y": 0.05870167165994644 }, { "x": 0.10306218266487122, "y": 0.05870167165994644 } ], "category": "header", "id": 243, "content": { "text": "FROM CRADLE TO GRAVE\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.87049800157547, "y": 0.049807921051979065 }, { "x": 0.8956854902207851, "y": 0.049807921051979065 }, { "x": 0.8956854902207851, "y": 0.0580062810331583 }, { "x": 0.87049800157547, "y": 0.0580062810331583 } ], "category": "header", "id": 244, "content": { "text": "207\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09491168707609177, "y": 0.06841238588094711 }, { "x": 0.900106243789196, "y": 0.06841238588094711 }, { "x": 0.900106243789196, "y": 0.6679514274001122 }, { "x": 0.09491168707609177, "y": 0.6679514274001122 } ], "category": "figure", "id": 245, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10317153483629227, "y": 0.6657512187957764 }, { "x": 0.8868157938122749, "y": 0.6657512187957764 }, { "x": 0.8868157938122749, "y": 0.7346351966261864 }, { "x": 0.10317153483629227, "y": 0.7346351966261864 } ], "category": "paragraph", "id": 246, "content": { "text": "FIGURE 11.12\nA Bahraini bride in traditional green thobe. She wears a circular gold plate (hama or taasa) on her head, with\nthe chains of discs talaat suspended from the rim. Sweet basil (mishmun), jasmine, and rosebuds adorn her\nhair. Around her wrists she wears gold bangles, including the shmelat, studded with turquoise and pink glass.\nShe wears a murta'asha choker and a long murtahish necklace ending in a crescent element.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10136771947145462, "y": 0.7554923892021179 }, { "x": 0.4891066923737526, "y": 0.7554923892021179 }, { "x": 0.4891066923737526, "y": 0.8664632886648178 }, { "x": 0.10136771947145462, "y": 0.8664632886648178 } ], "category": "paragraph", "id": 247, "content": { "text": "central element. As seen in figure 11.11, a seytemi\nmay be added to this; it can be identified by the\nrow of gold coins running up the chain and \"it is\namong the most sought after pieces of jewellery by\nwomen in the U.A.E. \"72 All these pieces may vary in\nsize and weight. At her waist, the bride will wear a\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5097413063049316, "y": 0.7554128170013428 }, { "x": 0.8996503949165344, "y": 0.7554128170013428 }, { "x": 0.8996503949165344, "y": 0.903119370341301 }, { "x": 0.5097413063049316, "y": 0.903119370341301 } ], "category": "paragraph", "id": 248, "content": { "text": "gold belt (hizam), which is usually composed of\narticulated square or round elements with smaller\ndangling bells or tassels. On her hands, she will of-\nten have rings on each finger, especially the shahi-\nda ring, worn on both forefingers, and the marami\non the middle finger. The back of her hand may\nbe covered in the kaf or chef ornament, which runs\nfrom rings and is anchored to a bracelet. She also\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10303974151611328, "y": 0.8922199606895447 }, { "x": 0.11886543035507202, "y": 0.8922199606895447 }, { "x": 0.11886543035507202, "y": 0.9003632022067904 }, { "x": 0.10303974151611328, "y": 0.9003632022067904 } ], "category": "paragraph", "id": 249, "content": { "text": "72\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1445694863796234, "y": 0.8858682513237 }, { "x": 0.4567348062992096, "y": 0.8858682513237 }, { "x": 0.4567348062992096, "y": 0.904026985168457 }, { "x": 0.1445694863796234, "y": 0.904026985168457 } ], "category": "footer", "id": 250, "content": { "text": "Gubash and Lootah, Traditional Emirati Jewels, 62.\n", "html": "", "markdown": "" } } ] }, "01030000000091.pdf": { "elements": [ { "coordinates": [ { "x": 0.09198976308107376, "y": 0.07573659718036652 }, { "x": 0.35261116176843643, "y": 0.07573659718036652 }, { "x": 0.35261116176843643, "y": 0.0885798865929246 }, { "x": 0.09198976308107376, "y": 0.0885798865929246 } ], "category": "heading1", "id": 595, "content": { "text": "THIS BOOK'S APPROACH\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09168083965778351, "y": 0.18788041174411774 }, { "x": 0.9073826223611832, "y": 0.18788041174411774 }, { "x": 0.9073826223611832, "y": 0.3212713599205017 }, { "x": 0.09168083965778351, "y": 0.3212713599205017 } ], "category": "paragraph", "id": 596, "content": { "text": "This book's approach is premised on a simple assumption: because behavioral economics is foremost\na \"test-and-learn\" field of scientific inquiry that evolves according to experimental outcomes and\npractical, policy-orientated applications of the knowledge garnered from these outcomes, SO too\nshould students test-and-learn. Studying and practicing behavioral economics should occur\nsimultaneously, which, in turn, suggests a course taught more according to a practicum approach than\nin a traditionally styled lecture format. As such, the book's information and lessons are presented in a\nsuccinct and precise format.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09176742285490036, "y": 0.3241426348686218 }, { "x": 0.907259576022625, "y": 0.3241426348686218 }, { "x": 0.907259576022625, "y": 0.45795316994190216 }, { "x": 0.09176742285490036, "y": 0.45795316994190216 } ], "category": "paragraph", "id": 597, "content": { "text": "The goal of this textbook is to help students experience behavioral economics through actual\nparticipation in the same experiments and economic games that have served as the foundations for,\nand shaped the contours of, the field. With the help of this book, students have the opportunity to\nlearn behavioral economics firsthand and, in the process, create their own data and experiences. They\nwill learn about themselves-about how they make private and public choices under experimental\nconditions-at the same time as they learn about the field of behavioral economics itself. They will be\nboth the subjects and students of behavioral economics. What better way to learn?\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0924336239695549, "y": 0.4776685833930969 }, { "x": 0.4674988314509392, "y": 0.4776685833930969 }, { "x": 0.4674988314509392, "y": 0.489612634293735 }, { "x": 0.0924336239695549, "y": 0.489612634293735 } ], "category": "heading1", "id": 598, "content": { "text": "HOMO ECONOMICUS VS. HOMO SAPIENS\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09175799787044525, "y": 0.5075206160545349 }, { "x": 0.9069005697965622, "y": 0.5075206160545349 }, { "x": 0.9069005697965622, "y": 0.6200646385550499 }, { "x": 0.09175799787044525, "y": 0.6200646385550499 } ], "category": "paragraph", "id": 599, "content": { "text": "For ease of reference and exposition, we henceforth refer to the type of individual construed by the\ntraditional rational-choice model as Homo economicus, a peculiar subspecies of human beings that is\nunfailingly omniscient, dispassionate, and self-interested when it comes to making choices. Homo\nsapiens, on the other hand, represents the rest of us-the often-flawed reasoners and sometimes-\naltruistic competitors who are prone to making decisions based primarily on emotion and\n12\nheuristics. ,\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09169686585664749, "y": 0.641684353351593 }, { "x": 0.4758993461728096, "y": 0.641684353351593 }, { "x": 0.4758993461728096, "y": 0.6535139214247465 }, { "x": 0.09169686585664749, "y": 0.6535139214247465 } ], "category": "heading1", "id": 600, "content": { "text": "THE TEXTBOOK'S DIFFERENT SECTIONS\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09202554076910019, "y": 0.6715843081474304 }, { "x": 0.9071823582053185, "y": 0.6715843081474304 }, { "x": 0.9071823582053185, "y": 0.7082968503236771 }, { "x": 0.09202554076910019, "y": 0.7082968503236771 } ], "category": "paragraph", "id": 601, "content": { "text": "The textbook consists of four sections that, taken together, portray in full the eclectic methodologies\ncomprising the field of behavioral economics. Sections 1 and 2 present the thought and actual\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.07768100500106812, "y": 0.7348170280456543 }, { "x": 0.8997097611427307, "y": 0.7348170280456543 }, { "x": 0.8997097611427307, "y": 0.7966121844947338 }, { "x": 0.07768100500106812, "y": 0.7966121844947338 } ], "category": "paragraph", "id": 603, "content": { "text": "1. Homo economicus is Latin for \"economic man.\" Persky (1995) traces its use back to the late 1800s when it was used by critics\nof John Stuart Mill's work on political economy. In contrast (and, as we will see, with no small touch of irony) Homo sapiens\nis Latin for \"wise man.\" For a deep dive into evolution of Homo sapiens, particularly from the start of the Cognitive\nRevolution 70,000 years ago, see Harari (2015).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.07630107551813126, "y": 0.8026876449584961 }, { "x": 0.9024526253342628, "y": 0.8026876449584961 }, { "x": 0.9024526253342628, "y": 0.9445020407438278 }, { "x": 0.07630107551813126, "y": 0.9445020407438278 } ], "category": "paragraph", "id": 604, "content": { "text": "2. We have all heard the saying that \"words matter.\" The titles and descriptions we use to distinguish people and their\nbehaviors (e.g., Homo economicus VS. Homo sapiens) can reinforce or diminish behaviors such as pride in cultural heritage,\nrespect for the living world, and trust in community, a process known as \"crowding out\" of \"intrinsic motivation and\ncommitment.\" As an example of this phenomenon, Bauer et al. (2012) asked participants in an online survey to imagine\nthemselves as one of four households facing a water shortage due to a drought affecting their shared well. The survey\nassigned the label \"consumers\" to half of the participants and \"individuals\" to the other half. Those imagining themselves\nas\nconsumers reported feeling less personal responsibility to reduce their water demand, and less trust in others to do the\nsame, than did those referred to as individuals. As we are about to learn, behavioral economics is all about exposing these\ntypes of \"framing effects\" existing in the \"real world\" inhabited by Homo sapiens.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.6424582600593567, "y": 0.9508636593818665 }, { "x": 0.9068624079227448, "y": 0.9508636593818665 }, { "x": 0.9068624079227448, "y": 0.9589920183643699 }, { "x": 0.6424582600593567, "y": 0.9589920183643699 } ], "category": "footer", "id": 605, "content": { "text": "BEHAVIORAL ECONOMICS PRACTICUM XIX\n", "html": "", "markdown": "" } } ] }, "01030000000074.pdf": { "elements": [ { "coordinates": [ { "x": 0.18907196819782257, "y": 0.08368489146232605 }, { "x": 0.8800823837518692, "y": 0.08368489146232605 }, { "x": 0.8800823837518692, "y": 0.11579697951674461 }, { "x": 0.18907196819782257, "y": 0.11579697951674461 } ], "category": "paragraph", "id": 348, "content": { "text": "Thailand, Malaysia, and Singapore. In these three countries, per capita GDP\nfell between 4 percent to 7 percent. 3\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1906903237104416, "y": 0.13156121969223022 }, { "x": 0.5833061784505844, "y": 0.13156121969223022 }, { "x": 0.5833061784505844, "y": 0.1461429437622428 }, { "x": 0.1906903237104416, "y": 0.1461429437622428 } ], "category": "paragraph", "id": 349, "content": { "text": "Figure 1.2. Per capita GDP growth in 2020\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.18928591907024384, "y": 0.1569335013628006 }, { "x": 0.882534071803093, "y": 0.1569335013628006 }, { "x": 0.882534071803093, "y": 0.4404122084379196 }, { "x": 0.18928591907024384, "y": 0.4404122084379196 } ], "category": "figure", "id": 350, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.18991820514202118, "y": 0.44755202531814575 }, { "x": 0.4093933403491974, "y": 0.44755202531814575 }, { "x": 0.4093933403491974, "y": 0.4592634914442897 }, { "x": 0.18991820514202118, "y": 0.4592634914442897 } ], "category": "paragraph", "id": 351, "content": { "text": "Source: World Bank (2022a)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.19016827642917633, "y": 0.476118266582489 }, { "x": 0.8805881887674332, "y": 0.476118266582489 }, { "x": 0.8805881887674332, "y": 0.6276915520429611 }, { "x": 0.19016827642917633, "y": 0.6276915520429611 } ], "category": "paragraph", "id": 352, "content": { "text": "It is also noteworthy that in two of these major destination countries - Thailand\nand Malaysia - the most-affected sectors were also ones heavily reliant\non migrant workers. In Thailand, affected sectors include manufacturing,\nconstruction, agriculture, fishing, seafood processing, domestic work, and\nhospitality (United Nations Thematic Working Group, 2019; ILO, 2020). In\nMalaysia, migrant workers were, in 2019, especially prevalent in manufacturing\n(705,000), construction (435,000), services (306,000), plantation (282,000),\nagriculture (160,000), and domestic work (127,000) (Wahab, 2020a; Theng,\nNoor and Khalidi, 2020).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1893383115530014, "y": 0.6433961987495422 }, { "x": 0.8806397169828415, "y": 0.6433961987495422 }, { "x": 0.8806397169828415, "y": 0.8639877140522003 }, { "x": 0.1893383115530014, "y": 0.8639877140522003 } ], "category": "paragraph", "id": 353, "content": { "text": "The construction sector in Malaysia crashed in the second quarter of 2020\nand did not experience growth again until the second quarter of 2021,\nbefore suffering negative growth again the next quarter after a COVID-19\nresurgence. Accommodation and dining establishments which includes many\ntourism-related jobs, fared even worse. Furthermore, wholesale trade and\nrelated activities in Malaysia have not recovered to pre-pandemic levels, even\nafter growing in the first two quarters of 2021. In Thailand, the construction\nsector avoided a massive output decline similar to Malaysia's, although it did\ndecline in the first quarter of 2020. However, manufacturing, accommodation,\nand wholesale trade in Thailand all suffered large contractions due to travel\nrestrictions, supply chain disruptions, and weak aggregate demand, and,\ndespite some recovery in the second quarter of 2021, remain well below pre-\npandemic levels (Table 1.1).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14225135743618011, "y": 0.8960611820220947 }, { "x": 0.8803781718015671, "y": 0.8960611820220947 }, { "x": 0.8803781718015671, "y": 0.918704790994525 }, { "x": 0.14225135743618011, "y": 0.918704790994525 } ], "category": "footer", "id": 354, "content": { "text": "3\nThe Philippine economy was hit hardest because of the length and severity of the movement restrictions\nimposed in the country (Olanday and Rigby, 2020).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14068423211574554, "y": 0.951934278011322 }, { "x": 0.4194898456335068, "y": 0.951934278011322 }, { "x": 0.4194898456335068, "y": 0.9667056100443006 }, { "x": 0.14068423211574554, "y": 0.9667056100443006 } ], "category": "footer", "id": 355, "content": { "text": "ASEAN Migration Outlook\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.9292005300521851, "y": 0.9527336359024048 }, { "x": 0.9511301107704639, "y": 0.9527336359024048 }, { "x": 0.9511301107704639, "y": 0.9636186212301254 }, { "x": 0.9292005300521851, "y": 0.9636186212301254 } ], "category": "paragraph", "id": 356, "content": { "text": "13\n", "html": "", "markdown": "" } } ] }, "01030000000131.pdf": { "elements": [ { "coordinates": [ { "x": 0.09366405755281448, "y": 0.0696595311164856 }, { "x": 0.8275547102093697, "y": 0.0696595311164856 }, { "x": 0.8275547102093697, "y": 0.3450985550880432 }, { "x": 0.09366405755281448, "y": 0.3450985550880432 } ], "category": "figure", "id": 186, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.286744624376297, "y": 0.4106541872024536 }, { "x": 0.7131662666797638, "y": 0.4106541872024536 }, { "x": 0.7131662666797638, "y": 0.4235063409432769 }, { "x": 0.286744624376297, "y": 0.4235063409432769 } ], "category": "paragraph", "id": 187, "content": { "text": "Figure 17.2. Year-to-year changes in housing prices.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08958717435598373, "y": 0.48633480072021484 }, { "x": 0.8234314545989037, "y": 0.48633480072021484 }, { "x": 0.8234314545989037, "y": 0.7507611513137817 }, { "x": 0.08958717435598373, "y": 0.7507611513137817 } ], "category": "figure", "id": 188, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0869646966457367, "y": 0.7751903533935547 }, { "x": 0.9117704927921295, "y": 0.7751903533935547 }, { "x": 0.9117704927921295, "y": 0.9253712296485901 }, { "x": 0.0869646966457367, "y": 0.9253712296485901 } ], "category": "paragraph", "id": 189, "content": { "text": "Inflationary, nominal, and real interest rates. To understand price volatility of durables, it is necessary\nto describe inflationary, nominal, and real interest rates. Recall from your earlier training that the\ninflation rate i is equal to the rate of change in average prices, changes often linked to monetary or\nfiscal policies of governments. The nominal interest rate r depends on the rate of inflation and a real\ncomponent that is dependent on factors other than the rate of inflation such as changing market\nconditions or changes in productivity. To describe the effects of inflation on the nominal interest, let\none plus the nominal interest rate r equal one plus the real rate r times one plus the inflation rate\ni\nSO\nthat:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.7106746435165405, "y": 0.951325535774231 }, { "x": 0.9113201797008514, "y": 0.951325535774231 }, { "x": 0.9113201797008514, "y": 0.9613621402531862 }, { "x": 0.7106746435165405, "y": 0.9613621402531862 } ], "category": "footer", "id": 190, "content": { "text": "Ch. 17. Land Investments I 385\n", "html": "", "markdown": "" } } ] }, "01030000000185.pdf": { "elements": [ { "coordinates": [ { "x": 0.12173166126012802, "y": 0.08265306055545807 }, { "x": 0.8775198683142662, "y": 0.08265306055545807 }, { "x": 0.8775198683142662, "y": 0.11886100843548775 }, { "x": 0.12173166126012802, "y": 0.11886100843548775 } ], "category": "heading1", "id": 729, "content": { "text": "SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective\nDepth Up-Scaling\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14922858774662018, "y": 0.1272755265235901 }, { "x": 0.8556769639253616, "y": 0.1272755265235901 }, { "x": 0.8556769639253616, "y": 0.193427212536335 }, { "x": 0.14922858774662018, "y": 0.193427212536335 } ], "category": "paragraph", "id": 730, "content": { "text": "Dahyun Kim*, Chanjun Park*, Sanghoon Kim*t, Wonsung Lee*t, Wonho Song\nYunsu Kim, Hyeonwoo Kim, Yungi Kim, Hyeonju Lee, Jihoo Kim\nChangbae Ahn, Seonghoon Yang, Sukyung Lee, Hyunbyung Park, Gyoungjin Gim\nMikyoung Cha, Hwalsuk Lee Sunghun Kim\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.40084129571914673, "y": 0.21170160174369812 }, { "x": 0.6035511642694473, "y": 0.21170160174369812 }, { "x": 0.6035511642694473, "y": 0.22589456383138895 }, { "x": 0.40084129571914673, "y": 0.22589456383138895 } ], "category": "paragraph", "id": 731, "content": { "text": "Upstage AI, South Korea\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.07641398161649704, "y": 0.22943942248821259 }, { "x": 0.9204679057002068, "y": 0.22943942248821259 }, { "x": 0.9204679057002068, "y": 0.24219943955540657 }, { "x": 0.07641398161649704, "y": 0.24219943955540657 } ], "category": "paragraph", "id": 732, "content": { "text": "{kdahyun, chanjun park, limerobot, wonsung. lee, hwalsuk.lee hunkim} @upstage.a\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.2639455795288086, "y": 0.25512102246284485 }, { "x": 0.3395806550979614, "y": 0.25512102246284485 }, { "x": 0.3395806550979614, "y": 0.26592344231903553 }, { "x": 0.2639455795288086, "y": 0.26592344231903553 } ], "category": "heading1", "id": 733, "content": { "text": "Abstract\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14634482562541962, "y": 0.28163960576057434 }, { "x": 0.4597940593957901, "y": 0.28163960576057434 }, { "x": 0.4597940593957901, "y": 0.5752220749855042 }, { "x": 0.14634482562541962, "y": 0.5752220749855042 } ], "category": "paragraph", "id": 734, "content": { "text": "We introduce SOLAR 10.7B, a large language\nmodel (LLM) with 10.7 billion parameters,\ndemonstrating superior performance in various\nnatural language processing (NLP) tasks. In-\nspired by recent efforts to efficiently up-scale\nLLMs, we present a method for scaling LLMs\ncalled depth up-scaling (DUS), which encom-\npasses depthwise scaling and continued pre-\ntraining. In contrast to other LLM up-scaling\nmethods that use mixture-of-experts, DUS does\nnot require complex changes to train and infer-\nence efficiently. We show experimentally that\nDUS is simple yet effective in scaling up high-\nperformance LLMs from small ones. Building\non the DUS model, we additionally present SO-\nLAR 10.7B-Instruct, a variant fine-tuned for\ninstruction-following capabilities, surpassing\nMixtral-8x7B-Instruct. SOLAR 10.7B is pub-\nlicly available under the Apache 2.0 license,\npromoting broad access and application in the\nLLM field 1.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11910050362348557, "y": 0.5916247963905334 }, { "x": 0.25826097279787064, "y": 0.5916247963905334 }, { "x": 0.25826097279787064, "y": 0.603069543838501 }, { "x": 0.11910050362348557, "y": 0.603069543838501 } ], "category": "heading1", "id": 735, "content": { "text": "1 Introduction\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11710235476493835, "y": 0.6169295310974121 }, { "x": 0.4885757863521576, "y": 0.6169295310974121 }, { "x": 0.4885757863521576, "y": 0.8716132640838623 }, { "x": 0.11710235476493835, "y": 0.8716132640838623 } ], "category": "paragraph", "id": 736, "content": { "text": "The field of natural language processing (NLP)\nhas been significantly transformed by the introduc-\ntion of large language models (LLMs), which have\nenhanced our understanding and interaction with\nhuman language (Zhang et al., 2023a). These ad-\nvancements bring challenges such as the increased\nneed to train ever larger models (Rae et al., 2021;\nWang et al., 2023; Pan et al., 2023; Lian, 2023;\nYao et al., 2023; Gesmundo and Maile, 2023) ow-\ning to the performance scaling law (Kaplan et al.,\n2020; Hernandez et al., 2021; Anil et al., 2023;\nKaddour et al., 2023). To efficiently tackle the\nabove, recent works in scaling language models\nsuch as a mixture of experts (MoE) (Shazeer et al.,\n2017; Komatsuzaki et al., 2022) have been pro-\nposed. While those approaches are able to effi-\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5132016539573669, "y": 0.2556457221508026 }, { "x": 0.8836818337440491, "y": 0.2556457221508026 }, { "x": 0.8836818337440491, "y": 0.38064202666282654 }, { "x": 0.5132016539573669, "y": 0.38064202666282654 } ], "category": "paragraph", "id": 737, "content": { "text": "ciently and effectively scale-up LLMs, they often\nrequire non-trivial changes to the training and infer-\nence framework (Gale et al., 2023), which hinders\nwidespread applicability. Effectively and efficiently\nscaling up LLMs whilst also retaining the simplic-\nity for ease of use is an important problem (Alberts\net al., 2023; Fraiwan and Khasawneh, 2023; Sallam\net al., 2023; Bahrini et al., 2023).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5126124620437622, "y": 0.3863810896873474 }, { "x": 0.884068489074707, "y": 0.3863810896873474 }, { "x": 0.884068489074707, "y": 0.751060426235199 }, { "x": 0.5126124620437622, "y": 0.751060426235199 } ], "category": "paragraph", "id": 738, "content": { "text": "Inspired by Komatsuzaki et al. (2022), we\npresent depth up-scaling (DUS), an effective and\nefficient method to up-scale LLMs whilst also re-\nmaining straightforward to use. DUS consists of\nscaling the base model along the depth dimension\nand continually pretraining the scaled model. Un-\nlike (Komatsuzaki et al., 2022), DUS does not scale\nthe model using MoE and rather use a depthwise\nscaling method analogous to Tan and Le (2019)\nwhich is adapted for the LLM architecture. Thus,\nthere are no additional modules or dynamism as\nwith MoE, making DUS immediately compatible\nwith easy-to-use LLM frameworks such as Hug-\ngingFace (Wolf et al., 2019) with no changes to\nthe training or inference framework for maximal\nefficiency. Furthermore, DUS is applicable to all\ntransformer architectures, opening up new gate-\nways to effectively and efficiently scale-up LLMs\nin a simple manner. Using DUS, we release SO-\nLAR 10.7B, an LLM with 10.7 billion parameters,\nthat outperforms existing models like Llama 2 (Tou-\nvron et al., 2023) and Mistral 7B (Jiang et al., 2023)\nin various benchmarks.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5131702423095703, "y": 0.7588191628456116 }, { "x": 0.8841924965381622, "y": 0.7588191628456116 }, { "x": 0.8841924965381622, "y": 0.8685086593031883 }, { "x": 0.5131702423095703, "y": 0.8685086593031883 } ], "category": "paragraph", "id": 739, "content": { "text": "We have also developed SOLAR 10.7B-Instruct,\na variant fine-tuned for tasks requiring strict adher-\nence to complex instructions. It significantly out-\nperforms the Mixtral-8x7B-Instruct model across\nvarious evaluation metrics, evidencing an advanced\nproficiency that exceeds the capabilities of even\nlarger models in terms of benchmark performance.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.513383150100708, "y": 0.873665988445282 }, { "x": 0.8836500346660614, "y": 0.873665988445282 }, { "x": 0.8836500346660614, "y": 0.9188588671386242 }, { "x": 0.513383150100708, "y": 0.9188588671386242 } ], "category": "paragraph", "id": 740, "content": { "text": "By releasing SOLAR 10.7B under the Apache\n2.0 license, we aim to promote collaboration and in-\nnovation in NLP. This open-source approach allows\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12108205258846283, "y": 0.8822476267814636 }, { "x": 0.41940127313137054, "y": 0.8822476267814636 }, { "x": 0.41940127313137054, "y": 0.9167142100632191 }, { "x": 0.12108205258846283, "y": 0.9167142100632191 } ], "category": "footer", "id": 741, "content": { "text": "*Equal Contribution Corresponding Author\nhttps://huggingface.co/upsta\nSOLAR-10.7B-v1.0\n", "html": "", "markdown": "" } } ] }, "01030000000143.pdf": { "elements": [ { "coordinates": [ { "x": 0.15137770771980286, "y": 0.203761488199234 }, { "x": 0.3032683879137039, "y": 0.203761488199234 }, { "x": 0.3032683879137039, "y": 0.2286198828369379 }, { "x": 0.15137770771980286, "y": 0.2286198828369379 } ], "category": "paragraph", "id": 422, "content": { "text": "Chapter 3\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15128479897975922, "y": 0.25956255197525024 }, { "x": 0.6415127366781235, "y": 0.25956255197525024 }, { "x": 0.6415127366781235, "y": 0.282449834048748 }, { "x": 0.15128479897975922, "y": 0.282449834048748 } ], "category": "heading1", "id": 423, "content": { "text": "Numerical differentiation\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1508294939994812, "y": 0.33766666054725647 }, { "x": 0.3448096960783005, "y": 0.33766666054725647 }, { "x": 0.3448096960783005, "y": 0.3508493881672621 }, { "x": 0.1508294939994812, "y": 0.3508493881672621 } ], "category": "heading1", "id": 424, "content": { "text": "3.1 Introduction\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1501743644475937, "y": 0.36848190426826477 }, { "x": 0.8625354021787643, "y": 0.36848190426826477 }, { "x": 0.8625354021787643, "y": 0.5772454142570496 }, { "x": 0.1501743644475937, "y": 0.5772454142570496 } ], "category": "paragraph", "id": 425, "content": { "text": "Everyone who possesses a car and/or a driver's licence is familiar with speeding tickets. In\nThe Netherlands, speeding tickets are usually processed in a fully automated fashion, and the\nperpetrator will receive the tickets within a couple of weeks after the offence. The Dutch police\noptimized the procedures of speed control such that this effort has become very profitable to the\nDutch government. Various strategies for speed control are carried out by police forces, which\nare all based on the position of the vehicle at consecutive times. The actual velocity follows from\nthe first-order derivative of the position of the vehicle with respect to time. Since no explicit\nformula for this position is available, the velocity can only be estimated using an approximation\nof the velocity based on several discrete vehicle positions at discrete times. This motivates the use\nof approximate derivatives, also called numerical derivatives. If the police want to know whether\nthe offender drove faster before speed detection (in other words, whether the perpetrator hit the\nbrakes after having seen the police patrol), or whether the driver was already accelerating, then\nthey are also interested in the acceleration of the 'bad guy'. This acceleration can be estimated\nusing numerical approximations of the second-order derivative of the car position with respect\nto time.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15023714303970337, "y": 0.5894237756729126 }, { "x": 0.8626498579978943, "y": 0.5894237756729126 }, { "x": 0.8626498579978943, "y": 0.7165191918611526 }, { "x": 0.15023714303970337, "y": 0.7165191918611526 } ], "category": "paragraph", "id": 426, "content": { "text": "Since the time-interval of recording is nonzero, the velocity is not determined exactly in general.\nIn this chapter, the resulting error, referred to as the truncation error, is estimated using Taylor se-\nries. In most cases, the truncation error increases with an increasing size of the recording interval\n(Sections 3.2 and 3.4). Next to the truncation error, the measurement of the position of the vehicle\nis also prone to measurement errors. Issues that influence the results are, for example, paral-\nlax, the measurement equipment, and in some cases even the performance of the police officer\n(in car-videoing and laser control). These measurement errors provide an additional deteriora-\ntion of the approximation of the speed and acceleration. The impact of measurement errors on\napproximations of derivatives is treated in Section 3.3.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15072917938232422, "y": 0.7420822978019714 }, { "x": 0.7537193894386292, "y": 0.7420822978019714 }, { "x": 0.7537193894386292, "y": 0.7593760322779417 }, { "x": 0.15072917938232422, "y": 0.7593760322779417 } ], "category": "heading1", "id": 427, "content": { "text": "3.2 Simple difference formulae for the first derivative\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1502445936203003, "y": 0.7731943130493164 }, { "x": 0.7866356372833252, "y": 0.7731943130493164 }, { "x": 0.7866356372833252, "y": 0.8907003328204155 }, { "x": 0.1502445936203003, "y": 0.8907003328204155 } ], "category": "paragraph", "id": 428, "content": { "text": "Suppose f is a continuously differentiable function. The forward difference is defined as\nh>0,\nin which h is called the step size. By definition,\nlim\nf(x+h)-f(x) - f((x),\nh->\nh\n", "html": "", "markdown": "" } } ] }, "01030000000008.pdf": { "elements": [ { "coordinates": [ { "x": 0.10387101769447327, "y": 0.05034290626645088 }, { "x": 0.4833170771598816, "y": 0.05034290626645088 }, { "x": 0.4833170771598816, "y": 0.05951686017215252 }, { "x": 0.10387101769447327, "y": 0.05951686017215252 } ], "category": "header", "id": 710, "content": { "text": "CIRCULATING THINGS, CIRCULATING STEREOTYPES\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8802040219306946, "y": 0.050067223608493805 }, { "x": 0.8956783656030893, "y": 0.050067223608493805 }, { "x": 0.8956783656030893, "y": 0.05807988066226244 }, { "x": 0.8802040219306946, "y": 0.05807988066226244 } ], "category": "paragraph", "id": 711, "content": { "text": "73\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10265033692121506, "y": 0.08304575830698013 }, { "x": 0.4870060309767723, "y": 0.08304575830698013 }, { "x": 0.4870060309767723, "y": 0.22624940425157547 }, { "x": 0.10265033692121506, "y": 0.22624940425157547 } ], "category": "paragraph", "id": 712, "content": { "text": "indicates the use of balsam, which is \"indigenous\nin various parts of Arabia,\" as an ingredient in the\n\"Myrabolan comfit.\"25 Such references emphasize\nArabia's exoticism and refined taste, as well as the\nsweetness and fragrance of its products, which\nwere much valued during a time when the con-\nsumption of sugar and spices was rising rapidly\namong European populations.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1015024408698082, "y": 0.22954189777374268 }, { "x": 0.4882652685046196, "y": 0.22954189777374268 }, { "x": 0.4882652685046196, "y": 0.682940810918808 }, { "x": 0.1015024408698082, "y": 0.682940810918808 } ], "category": "paragraph", "id": 713, "content": { "text": "Coffee is another staple thing customarily asso-\nciated with the area. In his Dictionary, Johnson indi-\ncates the Arabic origin of coffee and rightly so, as\none the most popular types of coffee is called \"Ara-\nbica\" because it was first domesticated for commer-\ncial use in the southern part of Arabia the Happy\n(present-day Yemen). Given the Muslim prohibi-\ntion of alcohol, coffee became particularly attrac-\ntive to the Muslim world as \"the wine of Islam,\"26\nand spread through the ports of the Persian Gulf in\nWestern Europe, where it became immensely pop-\nular. Collections of travels published during the\ntime mention that coffee was \"the product of Ara-\nbia only.\"27 Imported largely from Yemen, which\nwas credited with producing the best coffee in the\nworld, coffee was considered to have stimulating\nand therapeutic properties. 28 The former quality is\nfamously described by Pope in The Rape of the Lock:\n\"Coffee (which makes the politician wise), / And\nthro' all things with his half-shut Eyes) / Sent up in\nvapours to the Baron's brain / New Stratagems, the\nradiant Lock to gain.\" According to Beawes, the\nproduct was brought to Mecca through the port of\nJeddah, whose \"[t]]rade consists mainly of coffee\nbrought here by the Arabians and bought by the\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5179761052131653, "y": 0.08052874356508255 }, { "x": 0.8714549243450165, "y": 0.08052874356508255 }, { "x": 0.8714549243450165, "y": 0.2936272397637367 }, { "x": 0.5179761052131653, "y": 0.2936272397637367 } ], "category": "figure", "id": 714, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.513256847858429, "y": 0.32022643089294434 }, { "x": 0.8774382770061493, "y": 0.32022643089294434 }, { "x": 0.8774382770061493, "y": 0.3759385459125042 }, { "x": 0.513256847858429, "y": 0.3759385459125042 } ], "category": "paragraph", "id": 715, "content": { "text": "FIGURE 4.2 William Hogarth, Taste in High Life [graphic].\nPRINT MADE BY ISAAC MILLS AFTER WILLIAM\nHOGARTH'S PAINTING, WITHOUT THE ARTIST'S\nPERMISSION, LONDON, 1798\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5121224522590637, "y": 0.41132792830467224 }, { "x": 0.896203488111496, "y": 0.41132792830467224 }, { "x": 0.896203488111496, "y": 0.5725377202033997 }, { "x": 0.5121224522590637, "y": 0.5725377202033997 } ], "category": "paragraph", "id": 716, "content": { "text": "Turks [and] by the Merchants of Mogul, Persia,\nand several places on the coast of Ehiopia. \"30 From\nhere, coffee spread rapidly in England, France, and\nItaly, giving rise to the coffeehouse culture that is a\nhallmark of the eighteenth century. Coffee was also\nregularly paired in the visual culture of the time\nwith expensive china (fig. 4.2), was employed as a\nmark of the culture of sociability (fig. 4.3), or was\nused for its oracular properties31 (fig. 4.4).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5125131607055664, "y": 0.5757180452346802 }, { "x": 0.8964022994041443, "y": 0.5757180452346802 }, { "x": 0.8964022994041443, "y": 0.7184617519378662 }, { "x": 0.5125131607055664, "y": 0.7184617519378662 } ], "category": "paragraph", "id": 717, "content": { "text": "Arabian medicines were also much sought-after\nin the Western world. As indicated by Beawes,\n\"from Arabia, Medicinal drugs, Dragon's Blood,\nManna, Myrrh, [and] Incense,\"32 were brought to\nthe British metropolis. Pharmacopoia Reformata\n(1744) mentions gum Arabic, aloe, cassia, acacia,\ncardamom, saffron, myrrh, and spikenard, which\nwere all used for their therapeutic properties. 33 To\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10344383865594864, "y": 0.7280178070068359 }, { "x": 0.4873335435986519, "y": 0.7280178070068359 }, { "x": 0.4873335435986519, "y": 0.9195141941308975 }, { "x": 0.10344383865594864, "y": 0.9195141941308975 } ], "category": "paragraph", "id": 718, "content": { "text": "25\nWiliam Beckford, An Arabian Tale, from an Unpub-\nlished Manuscript: With Notes Critical and Explanatory\n(London: Printed for Johnson, 1786), 165.\n26\nFor the association between coffee and wine, see Ralph\nS. Hattox, Coffee and Coffeehouses: The Origins of a So-\ncial Beverage in the Medieval Middle East (Seattle: Uni-\nversity of Washington Press, 1985), 18-19.\n27\nA Collection of Voyages and Travels, 1:440.\n28\nCoffee was customarily used as a mild painkiller during\nthe eighteenth century. Poet Alexander Pope, for in-\nstance, used it as a palliative for his migraines.\n29\nPope, The Rape of the Lock, 69.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5124385356903076, "y": 0.7445831894874573 }, { "x": 0.782772421836853, "y": 0.7445831894874573 }, { "x": 0.782772421836853, "y": 0.7561352690681815 }, { "x": 0.5124385356903076, "y": 0.7561352690681815 } ], "category": "paragraph", "id": 720, "content": { "text": "30\nBeawes, Lex Mercatoria Rediviva, 791.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5115187764167786, "y": 0.7605510950088501 }, { "x": 0.8960508406162262, "y": 0.7605510950088501 }, { "x": 0.8960508406162262, "y": 0.8219464719295502 }, { "x": 0.5115187764167786, "y": 0.8219464719295502 } ], "category": "paragraph", "id": 721, "content": { "text": "31\nAgain, the custom of reading one's fortune in coffee\ngrounds is of Turkish provenance, not Arabic. Such\nmistaken attributions were pervasive during the eigh-\nteenth century.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5119638442993164, "y": 0.8261616230010986 }, { "x": 0.7850291430950165, "y": 0.8261616230010986 }, { "x": 0.7850291430950165, "y": 0.8376952614635229 }, { "x": 0.5119638442993164, "y": 0.8376952614635229 } ], "category": "paragraph", "id": 722, "content": { "text": "32\nBeawes, Lex Mercatoria Rediviva, 792.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5123887658119202, "y": 0.8419908881187439 }, { "x": 0.8966035544872284, "y": 0.8419908881187439 }, { "x": 0.8966035544872284, "y": 0.9196459800004959 }, { "x": 0.5123887658119202, "y": 0.9196459800004959 } ], "category": "paragraph", "id": 723, "content": { "text": "33\nM.M., Pharmacopoia Reformata: Or, An Essay for a Ref-\normation of the London Pharmacopoia, by a Set of Re-\nmarks on the Draught for a New One, and a Brief Ac-\ncount of the Proceedings of the Committee Appointed by\nthe College of Physicians, to Thoroughly Reform Their\n", "html": "", "markdown": "" } } ] }, "01030000000038.pdf": { "elements": [ { "coordinates": [ { "x": 0.15879227221012115, "y": 0.07628824561834335 }, { "x": 0.7940811067819595, "y": 0.07628824561834335 }, { "x": 0.7940811067819595, "y": 0.08794368989765644 }, { "x": 0.15879227221012115, "y": 0.08794368989765644 } ], "category": "paragraph", "id": 415, "content": { "text": "Figure 6.1.1: Will they fire more staff in the next 2 months - across survey phases (%)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.25963470339775085, "y": 0.09917249530553818 }, { "x": 0.8284842073917389, "y": 0.09917249530553818 }, { "x": 0.8284842073917389, "y": 0.3543700501322746 }, { "x": 0.25963470339775085, "y": 0.3543700501322746 } ], "category": "figure", "id": 416, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1587412804365158, "y": 0.3750841021537781 }, { "x": 0.8889429420232773, "y": 0.3750841021537781 }, { "x": 0.8889429420232773, "y": 0.38697077333927155 }, { "x": 0.1587412804365158, "y": 0.38697077333927155 } ], "category": "paragraph", "id": 417, "content": { "text": "Figure 6.1.2: Will they fire more staff in the next 2 months - across sectors and survey phases (%)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.18805445730686188, "y": 0.39880725741386414 }, { "x": 0.9009581953287125, "y": 0.39880725741386414 }, { "x": 0.9009581953287125, "y": 0.6836310923099518 }, { "x": 0.18805445730686188, "y": 0.6836310923099518 } ], "category": "figure", "id": 418, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15846744179725647, "y": 0.7039679884910583 }, { "x": 0.47437673807144165, "y": 0.7039679884910583 }, { "x": 0.47437673807144165, "y": 0.7152437651529908 }, { "x": 0.15846744179725647, "y": 0.7152437651529908 } ], "category": "heading1", "id": 419, "content": { "text": "6.2. Expectations for Re-Hiring Employees\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15872593224048615, "y": 0.7323624491691589 }, { "x": 0.537201538681984, "y": 0.7323624491691589 }, { "x": 0.537201538681984, "y": 0.8146688267588615 }, { "x": 0.15872593224048615, "y": 0.8146688267588615 } ], "category": "paragraph", "id": 420, "content": { "text": "In July 2020, 81% of the MSMEs that had laid off\nemployees expected to re-hire all of them when the\nsituation improved. This number reduced to 23% in\nOctober 2020 and further to just 7% in January 2021.5\nIn July 2020, all MSMEs had plans to re-hire at least\nsome of their staff. But in October 2020, 17% said\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5522592663764954, "y": 0.7039004564285278 }, { "x": 0.93126380443573, "y": 0.7039004564285278 }, { "x": 0.93126380443573, "y": 0.8148877546191216 }, { "x": 0.5522592663764954, "y": 0.8148877546191216 } ], "category": "paragraph", "id": 421, "content": { "text": "they had no plans to re-hire and another 36% said\nthey didn't know whether they would re-hire or not. In\nJanuary 2021, 20% said they had no plans to re-hire\nand another 27% said they did not know. This question\nwas only posed to those who had let staff go since the\nlast survey round, and in October 2020 and January\n2021, the base numbers reduced as fewer MSMEs\nreported letting staff go. In July 2020, 195 MSMEs\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15879063308238983, "y": 0.8461421132087708 }, { "x": 0.914679691195488, "y": 0.8461421132087708 }, { "x": 0.914679691195488, "y": 0.8839907757937908 }, { "x": 0.15879063308238983, "y": 0.8839907757937908 } ], "category": "paragraph", "id": 422, "content": { "text": "5.\nThe question on re-hiring was asked to those who had laid-off employees since the last survey. In the latter two survey rounds,\nrespondents were asked about plans to re-hire staff whom they had let go since the previous interview, whereas in July 2020, they\nwere asked about plans to re-hire staff they had let go since their business was first affected by the pandemic.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.06521790474653244, "y": 0.940329372882843 }, { "x": 0.07941325567662716, "y": 0.940329372882843 }, { "x": 0.07941325567662716, "y": 0.9476110655814409 }, { "x": 0.06521790474653244, "y": 0.9476110655814409 } ], "category": "paragraph", "id": 423, "content": { "text": "23\n", "html": "", "markdown": "" } } ] }, "01030000000138.pdf": { "elements": [ { "coordinates": [ { "x": 0.20076702535152435, "y": 0.07849536836147308 }, { "x": 0.7994804829359055, "y": 0.07849536836147308 }, { "x": 0.7994804829359055, "y": 0.242210254073143 }, { "x": 0.20076702535152435, "y": 0.242210254073143 } ], "category": "figure", "id": 451, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.20031467080116272, "y": 0.24782003462314606 }, { "x": 0.618123471736908, "y": 0.24782003462314606 }, { "x": 0.618123471736908, "y": 0.2600128296762705 }, { "x": 0.20031467080116272, "y": 0.2600128296762705 } ], "category": "paragraph", "id": 452, "content": { "text": "Figure 11.2: Arapaima gigas displayed in the Siam Centre, Bangkok.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.097149558365345, "y": 0.32457518577575684 }, { "x": 0.9010177925229073, "y": 0.32457518577575684 }, { "x": 0.9010177925229073, "y": 0.43617866933345795 }, { "x": 0.097149558365345, "y": 0.43617866933345795 } ], "category": "paragraph", "id": 453, "content": { "text": "Arapaima is an important flagship genus for flooded forest ecosystem and human floodplain communities.\nFlagship taxa are used as a symbol to promote conservation awareness (Caro 2010). Their large size makes them\na true freshwater megafauna like crocodiles, river dolphins, and other large fish. Freshwater megafauna face\nmany threats, and 71% of these species are in decline (He et al. 2017, 2018). Arapaima continue to face intense\nfishing throughout their range (Watson et al. 2021). However, freshwater megafauna like the Arapaima have\nfewer conservation resources and efforts than marine or terrestrial megafaunas.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09735935181379318, "y": 0.45437079668045044 }, { "x": 0.9012643024325371, "y": 0.45437079668045044 }, { "x": 0.9012643024325371, "y": 0.5853851586580276 }, { "x": 0.09735935181379318, "y": 0.5853851586580276 } ], "category": "paragraph", "id": 454, "content": { "text": "Fishing, in general, and fishing for Arapaima in particular, is a central element of the local economy and\nculture in Amazonia. Because these fish are obligate breathers, they are traditionally harvested by fishers\nusing harpoons at the time when they surface to breathe. Men typically fish from canoes and search for\nsigns of Arapaima near the surface. As they near the Arapaima, the harpooner throws the harpoon by hand.\nThis is a specialized type of fishing, and the local fishers possess knowledge of the behavior that increases\ntheir likelihood of catching one. With appropriate training, fishers' participation in management processes can\ncontribute to the conservation and governance of these small-scale fisheries.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09767412394285202, "y": 0.6032547354698181 }, { "x": 0.9010954424738884, "y": 0.6032547354698181 }, { "x": 0.9010954424738884, "y": 0.7144036963582039 }, { "x": 0.09767412394285202, "y": 0.7144036963582039 } ], "category": "paragraph", "id": 455, "content": { "text": "Many populations of Arapaima have been driven to local extinction due to overfishing (Castello et al. 2015a;\nGurdak 2019a; Watson et al. 2021; Freitas and Sousa 2021). Much of the catch is illegal, with most specimens\nbeing caught below the minimum size limit or during the closed season (Cavole et al. 2015). The small-scale\nfishers are geographically dispersed, and governments in these regions have insufficient resources to devote\nto enforcing fishing rules. The riverine fishers who target Arapaima are marginalized and have limited formal\neducation. Yet, compliance with regulations is essential to prevent overfishing and local extinction.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09679004549980164, "y": 0.7327816486358643 }, { "x": 0.9017125070095062, "y": 0.7327816486358643 }, { "x": 0.9017125070095062, "y": 0.8629089146852493 }, { "x": 0.09679004549980164, "y": 0.8629089146852493 } ], "category": "paragraph", "id": 456, "content": { "text": "Arapaima represent only a small fraction of the fisheries harvest, but they are culturally important and symbolic\nas a flagship genus of tropical South American fisheries and floodplain management and conservation. Reducing\nthe threats to Arapaima will also provide protections for many of the highly migratory fish of the Amazon basin.\nCollectively, the migratory fish contribute most of the fishery's landings in the basin (Duponchelle et al. 2021).\nMigratory fish depend on multiple, distant, but interconnected habitats during their life cycle. Any threat to\none of the habitats or the corridor that connects them can influence these important food fish (Goulding et al.\n2019).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5321054458618164, "y": 0.9355465173721313 }, { "x": 0.9008924663066864, "y": 0.9355465173721313 }, { "x": 0.9008924663066864, "y": 0.9477614741772413 }, { "x": 0.5321054458618164, "y": 0.9477614741772413 } ], "category": "footer", "id": 457, "content": { "text": "Integrating Fishers in the Management of Arapaima 251\n", "html": "", "markdown": "" } } ] }, "01030000000041.pdf": { "elements": [ { "coordinates": [ { "x": 0.10750390589237213, "y": 0.08578402549028397 }, { "x": 0.4803152531385422, "y": 0.08578402549028397 }, { "x": 0.4803152531385422, "y": 0.22266539186239243 }, { "x": 0.10750390589237213, "y": 0.22266539186239243 } ], "category": "paragraph", "id": 445, "content": { "text": "tweets, videos) inciting violence towards\nreligious minorities, ethnic minorities, the\nLGBTI community, and women and girls.\nForty-four per cent of respondents had\n\"sometimes\" seen extremist social media\ncontent inciting violence towards religious\nminorities, with 31% seeing this content\n\"very often\".\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10827099531888962, "y": 0.25217825174331665 }, { "x": 0.4804857298731804, "y": 0.25217825174331665 }, { "x": 0.4804857298731804, "y": 0.4605577141046524 }, { "x": 0.10827099531888962, "y": 0.4605577141046524 } ], "category": "paragraph", "id": 446, "content": { "text": "Both men and women acknowledged that\nthey had \"sometimes\" seen this content on\nsocial media (62% and 41%, respectively).\nIndonesia was the country from which most\nrespondents had viewed this content \"very\noften\" (50%). When collapsing the \"always\"\nand \"very often\" categories, 41% of Instagram\nusers had often seen intolerant content,\nfollowed by 36% of WhatsApp users and\n34% of Facebook users. Among the Twitter\nusers in the sample, 48% had seen intolerant\ncontent towards religious minorities.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10817638039588928, "y": 0.48972955346107483 }, { "x": 0.4806560277938843, "y": 0.48972955346107483 }, { "x": 0.4806560277938843, "y": 0.6624592840671539 }, { "x": 0.10817638039588928, "y": 0.6624592840671539 } ], "category": "paragraph", "id": 447, "content": { "text": "When asked about how often social media\ncontent was inciting violence towards\nethnic minorities, 46% of respondents had\n\"sometimes\" seen this type of extremist\nsocial media content inciting violence\ntowards ethnic minorities whereas only\n27% have seen this content rarely or\nnever. Women have seen such content\nmore frequently than men (90%), and\nIndonesia was the country from which most\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5246676206588745, "y": 0.08694887161254883 }, { "x": 0.8965056836605072, "y": 0.08694887161254883 }, { "x": 0.8965056836605072, "y": 0.17083287984132767 }, { "x": 0.5246676206588745, "y": 0.17083287984132767 } ], "category": "paragraph", "id": 448, "content": { "text": "respondents had seen this content \"very\noften\" (58%). Users of Facebook, WhatsApp\nand Instagram acknowledged that they had\nseen this content \"very often\" (26%, 31% and\n35% respectively).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.523959755897522, "y": 0.1999351680278778 }, { "x": 0.896710216999054, "y": 0.1999351680278778 }, { "x": 0.896710216999054, "y": 0.4262702465057373 }, { "x": 0.523959755897522, "y": 0.4262702465057373 } ], "category": "paragraph", "id": 449, "content": { "text": "Thirty-nine per cent of respondents\nacknowledged that they had \"sometimes\"\nseen social media content inciting violence\ntowards the LGBTI community. Women saw\nthis type of content more frequently than\nmen (84%), and Indonesia was the country\nfrom which more respondents saw this\ncontent with a higher frequency (53% saw\nsuch content \"always\" and \"very often\").\nParticipants in the survey observed intolerant\ncontent directed towards the LGBTI\ncommunity. For example, one participant\nfrom the Philippines observed that,\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5496543049812317, "y": 0.4887825548648834 }, { "x": 0.8838678896427155, "y": 0.4887825548648834 }, { "x": 0.8838678896427155, "y": 0.6414695829153061 }, { "x": 0.5496543049812317, "y": 0.6414695829153061 } ], "category": "paragraph", "id": 450, "content": { "text": "There were instances when women\nwere humiliated in public and on\nsocial media after they were labelled\nas part of the LGBTQ+ community. The\ncomments on posts regarding them\nwere mostly commending their public\nhumiliation (cutting their hair) instead\nof condemning the act\".\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.7007780075073242, "y": 0.6527901887893677 }, { "x": 0.7333961687982082, "y": 0.6527901887893677 }, { "x": 0.7333961687982082, "y": 0.6725205667316914 }, { "x": 0.7007780075073242, "y": 0.6725205667316914 } ], "category": "figure", "id": 451, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.07754800468683243, "y": 0.7004407644271851 }, { "x": 0.9224321618676186, "y": 0.7004407644271851 }, { "x": 0.9224321618676186, "y": 0.7141145654022694 }, { "x": 0.07754800468683243, "y": 0.7141145654022694 } ], "category": "paragraph", "id": 452, "content": { "text": "Figure 3: Frequency of viewing extremist social media inciting violence toward women and girls\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15351973474025726, "y": 0.7226911187171936 }, { "x": 0.8928897827863693, "y": 0.7226911187171936 }, { "x": 0.8928897827863693, "y": 0.9339878410100937 }, { "x": 0.15351973474025726, "y": 0.9339878410100937 } ], "category": "figure", "id": 453, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.18373969197273254, "y": 0.9299706816673279 }, { "x": 0.8322151601314545, "y": 0.9299706816673279 }, { "x": 0.8322151601314545, "y": 0.9404123658314347 }, { "x": 0.18373969197273254, "y": 0.9404123658314347 } ], "category": "paragraph", "id": 454, "content": { "text": "OFTEN\nSOMETIMES\nRARELY\nNEVER\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.033085279166698456, "y": 0.974685788154602 }, { "x": 0.7163630053400993, "y": 0.974685788154602 }, { "x": 0.7163630053400993, "y": 0.9859954128041863 }, { "x": 0.033085279166698456, "y": 0.9859954128041863 } ], "category": "footer", "id": 455, "content": { "text": "Gender Analysis of Violent Extremism and the Impact of COVID-19 on Peace and Security in ASEAN\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.9277658462524414, "y": 0.9761422276496887 }, { "x": 0.9440449234098196, "y": 0.9761422276496887 }, { "x": 0.9440449234098196, "y": 0.9836010355502367 }, { "x": 0.9277658462524414, "y": 0.9836010355502367 } ], "category": "paragraph", "id": 456, "content": { "text": "29\n", "html": "", "markdown": "" } } ] }, "01030000000190.pdf": { "elements": [ { "coordinates": [ { "x": 0.25355538725852966, "y": 0.08396124094724655 }, { "x": 0.7452837228775024, "y": 0.08396124094724655 }, { "x": 0.7452837228775024, "y": 0.1273883506655693 }, { "x": 0.25355538725852966, "y": 0.1273883506655693 } ], "category": "table", "id": 894, "content": { "text": "", "html": "
ModelH6 (Avg.)ARCHellaSwagMMLUTruthfulQAWinograndeGSM8K
Cand. 173.7370.4887.4765.7370.6281.5366.57
Cand. 273.2871.5988.3966.1472.5081.9959.14
", "markdown": "" } }, { "coordinates": [ { "x": 0.2145170271396637, "y": 0.19594351947307587 }, { "x": 0.7841642796993256, "y": 0.19594351947307587 }, { "x": 0.7841642796993256, "y": 0.25794462859630585 }, { "x": 0.2145170271396637, "y": 0.25794462859630585 } ], "category": "table", "id": 919, "content": { "text": "", "html": "
ModelMerge MethodH6 (Avg.)ARCHellaSwagMMLUTruthfulQAWinograndeGSM8K
Merge v1Average (0.5,0.5)74.0071.1688.0166.1471.7182.0864.90
Merge v2Average (0.4,0.6)73.9371.0888.0866.2771.8981.7764.52
Merge v3Average (0.6, 0.4)74.0571.0887.8866.1371.6182.0865.50
Merge v4SLERP73.9671.1688.0366.2571.7981.9364.59
", "markdown": "" } }, { "coordinates": [ { "x": 0.11759943515062332, "y": 0.1404019594192505 }, { "x": 0.8805601671338081, "y": 0.1404019594192505 }, { "x": 0.8805601671338081, "y": 0.17825768887996674 }, { "x": 0.11759943515062332, "y": 0.17825768887996674 } ], "category": "paragraph", "id": 967, "content": { "text": "Table 6: Performance comparison amongst the merge candidates. 'Cand. 1' and 'Cand. 2' are trained using the\nsame setting as 'DPO v2' and 'DPO v3', respectively, but with slightly different hyper-parameters. The best scores\nfor H6 and the individual tasks are shown in bold.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11746407300233841, "y": 0.2708955705165863 }, { "x": 0.8823000863194466, "y": 0.2708955705165863 }, { "x": 0.8823000863194466, "y": 0.3107331953942776 }, { "x": 0.11746407300233841, "y": 0.3107331953942776 } ], "category": "paragraph", "id": 969, "content": { "text": "Table 7: Ablation studies on the different merge methods used for obtaining the final model. We use 'Cand. 1'\nand 'Cand. 2' from Tab. 6 as our two models for merging. We name the merged models with the 'Merge' prefix to\nindicate they are merged. The best scores for H6 and the individual tasks are shown in bold.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11766782402992249, "y": 0.3398059010505676 }, { "x": 0.48815372586250305, "y": 0.3398059010505676 }, { "x": 0.48815372586250305, "y": 0.3839751072227955 }, { "x": 0.11766782402992249, "y": 0.3839751072227955 } ], "category": "paragraph", "id": 970, "content": { "text": "tively impacted by adding Synth. Math-Alignment.\nThus, we can conclude that adding Synth. Math-\nAlignment is beneficial for H6.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1170024499297142, "y": 0.38823848962783813 }, { "x": 0.4876226708292961, "y": 0.38823848962783813 }, { "x": 0.4876226708292961, "y": 0.5454489290714264 }, { "x": 0.1170024499297142, "y": 0.5454489290714264 } ], "category": "paragraph", "id": 971, "content": { "text": "Then, we experiment whether merging 'DPO\nv1' and 'DPO v2' is beneficial. Unfortunately,\n'DPO v1+v2' scores 73.21 in H6, which is worse\nthan 'DPO v2'. More importantly, the gain in\nthe GSM8K score from adding Synth. Math-\nAlignment is gone, which is undesirable. One\nreason for this could be that 'DPO v2' is a strict\nimprovement over 'DPO v1', unlike the case for\nmerging 'SFT v3' and 'SFT v4' where the models\nhad different strengths and weaknesses.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11792886257171631, "y": 0.5582455992698669 }, { "x": 0.4879494905471802, "y": 0.5582455992698669 }, { "x": 0.4879494905471802, "y": 0.6972143799066544 }, { "x": 0.11792886257171631, "y": 0.6972143799066544 } ], "category": "paragraph", "id": 972, "content": { "text": "Ablation on the SFT base models. When ap-\nplying DPO, we start from a model that is already\ninstruction tuned ,i.e., the SFT base model and ab-\nlate on using different SFT base models. We use\nUltrafeedback Clean and Synth. Math-Alignment\ndatasets for this ablation. Each of the ablated mod-\nels is trained as follows. 'DPO v2' uses 'SFT v3'\nas the base SFT model, while 'DPO v3' uses 'SFT\nv3+v4' as the SFT base model instead.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11820240318775177, "y": 0.7035169005393982 }, { "x": 0.4879969209432602, "y": 0.7035169005393982 }, { "x": 0.4879969209432602, "y": 0.8606104403734207 }, { "x": 0.11820240318775177, "y": 0.8606104403734207 } ], "category": "paragraph", "id": 973, "content": { "text": "Note that 'SFT v3+v4' has higher scores on all\ntasks compared to 'SFT v3', and the gap is espe-\ncially large for ARC (+1.45) and GSM8K (+2.43).\nSurprisingly, the two models perform similarly in\nterms of H6. A closer look at the scores for the\nindividual tasks shows only a small margin in the\nGSM8K scores, and other task scores show little\ndifference. Thus, the performance gaps in certain\ntasks in the SFT base models do not always carry\nover to the alignment-tuned models.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11785490065813065, "y": 0.8739396929740906 }, { "x": 0.48770273476839066, "y": 0.8739396929740906 }, { "x": 0.48770273476839066, "y": 0.9186863750219345 }, { "x": 0.11785490065813065, "y": 0.9186863750219345 } ], "category": "paragraph", "id": 974, "content": { "text": "Ablation on different merge methods. From\nTab. 3, we saw that merging two models that have\ndifferent strengths can be beneficial to performance.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5122235417366028, "y": 0.3397963047027588 }, { "x": 0.8834587931632996, "y": 0.3397963047027588 }, { "x": 0.8834587931632996, "y": 0.5265239924192429 }, { "x": 0.5122235417366028, "y": 0.5265239924192429 } ], "category": "paragraph", "id": 975, "content": { "text": "To utilize this for the alignment-tuned model as\nwell, we train two models named 'Cand. 1' and\n'Cand. 2' using the same training dataset and SFT\nbase model as 'DPO v2' and 'DPO v3' but with dif-\nferent hyper-parameters to maximize each model's\nrespective strengths. We compare 'Cand. l' and\n'Cand. 2' in Tab. 6 where we can see that 'Cand. l'\nhas high GSM8K scores but relatively low scores\nfor the other tasks, whereas 'Cand. 2' has low\nscores for GSM8K but high scores for the other\ntasks. We merge these two models using various\nmethods and ablate the results in Tab.. 7.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5131886005401611, "y": 0.5327266454696655 }, { "x": 0.8836143016815186, "y": 0.5327266454696655 }, { "x": 0.8836143016815186, "y": 0.7196974456310272 }, { "x": 0.5131886005401611, "y": 0.7196974456310272 } ], "category": "paragraph", "id": 976, "content": { "text": "We use two merge methods: 1) Average (a, b),\nwhere a and b denote the weighting for 'Cand.\n1' and 'Cand. 2' when averaging weights and 2)\nSLERP (Shoemake, 1985). We use (0.5, 0.5), (0.4,\n0.6), and (0.6, 0.4) for Average (a, b). From Tab. 7,\nwe can see that the different merge methods have\nlittle effect on the H6 scores. The scores for the\nindividual tasks also do not differ by much, suggest-\ning that as long as the merge candidates have suffi-\nciently different strengths, the exact merge method\nmay not be as crucial. Thus, we chose \"Merge v1'\nas our SOLAR 10.7B-Instruct model.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5138528943061829, "y": 0.7363985180854797 }, { "x": 0.6405298411846161, "y": 0.7363985180854797 }, { "x": 0.6405298411846161, "y": 0.7471474641934037 }, { "x": 0.5138528943061829, "y": 0.7471474641934037 } ], "category": "heading1", "id": 977, "content": { "text": "5 Conclusion\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5127118229866028, "y": 0.7615882754325867 }, { "x": 0.8835240304470062, "y": 0.7615882754325867 }, { "x": 0.8835240304470062, "y": 0.91865473985672 }, { "x": 0.5127118229866028, "y": 0.91865473985672 } ], "category": "paragraph", "id": 978, "content": { "text": "We introduce SOLAR 10.7B and its fine-tuned vari-\nant SOLAR 10.7B-Instruct, which are depth up-\nscaled (DUS) models with 10.7 billion parameters.\nThey show superior performance over models like\nLlama 2, Mistral 7B, and Mixtral-7B-Instruct in es-\nsential NLP tasks while maintaining computational\nefficiency. Thus, DUS is effective in scaling-up\nhighly performant LLMs from smaller ones. With\nmore exploration, DUS could be further improved,\npaving a new path to efficiently scaling LLMs.\n", "html": "", "markdown": "" } } ] }, "01030000000030.pdf": { "elements": [ { "coordinates": [ { "x": 0.14619728922843933, "y": 0.027435483410954475 }, { "x": 0.48792439699172974, "y": 0.027435483410954475 }, { "x": 0.48792439699172974, "y": 0.055294277146458626 }, { "x": 0.14619728922843933, "y": 0.055294277146458626 } ], "category": "header", "id": 591, "content": { "text": "Combinatorial Cosmology\nDOI: http://dx.doi.org/10.5772/intechopen.90696\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14500071108341217, "y": 0.07395776361227036 }, { "x": 0.8500576764345169, "y": 0.07395776361227036 }, { "x": 0.8500576764345169, "y": 0.2841094359755516 }, { "x": 0.14500071108341217, "y": 0.2841094359755516 } ], "category": "paragraph", "id": 592, "content": { "text": "As for the normal phase, the choice will, to start with, be the simplest possible\none: each path is either possible or not, corresponding to the probability weights 1\nand 0. During the extreme phases, this assumption is no longer reasonable. Again\nthe model will be extremely simplified, but still it is based on physical intuition and,\nmost importantly, completely time symmetric. Assume that the only types of edges\nhaving a non-neglectable chance of occurring during the extreme phase\n[-m-1,-m] - are of the following two kinds: The first scenario is that the universe\npasses through the extreme phase into a state of zero entropy. The other scenario is\nthat it passes into a state with high entropy (equal to 2m). Universes of one of these\ntwo types will be given the (un-normalized) probability 1 or p, respectively. Here\np 0 should be thought of as a very small number, at least when the size of the\nmodel becomes large. During the other extreme phase [m,m + 1], near the Big\nCrunch, we make the completely symmetric assumption.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1459435075521469, "y": 0.28568577766418457 }, { "x": 0.8499889224767685, "y": 0.28568577766418457 }, { "x": 0.8499889224767685, "y": 0.46243324875831604 }, { "x": 0.1459435075521469, "y": 0.46243324875831604 } ], "category": "paragraph", "id": 593, "content": { "text": "Remark 3. These assumptions may perhaps seem somewhat arbitrary. And to a\ncertain extent, this may be SO. However, they do represent the following viewpoint\nof what may happen at the full cosmological scale: we may think of the Big Bang and\nthe Big Crunch as states of complete order with zero volume and entropy. Such\nstates can very well be metastable, very much like an oversaturated gas at a tem-\nperature below the point of condensation. If no disturbance takes place, such meta-\nstable states can very well continue to exist for a substantial period of time. In\nparticular, a low-entropy state can have a very good chance of surviving the intense\nbut extremely short extreme phase. On the other hand, if a sufficiently large dis-\nturbance occurs, then the metastable state may almost immediately decay into a\nvery disordered state of high entropy.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14628303050994873, "y": 0.4634777307510376 }, { "x": 0.8473019003868103, "y": 0.4634777307510376 }, { "x": 0.8473019003868103, "y": 0.511261835694313 }, { "x": 0.14628303050994873, "y": 0.511261835694313 } ], "category": "paragraph", "id": 594, "content": { "text": "It is not my intension to further argue in favor of this viewpoint here. The main\nthing in this chapter is to show that completely symmetric boundary conditions at\nthe endpoints may give rise to a broken time symmetry.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.17395851016044617, "y": 0.5125067830085754 }, { "x": 0.7072202861309052, "y": 0.5125067830085754 }, { "x": 0.7072202861309052, "y": 0.5276035312563181 }, { "x": 0.17395851016044617, "y": 0.5276035312563181 } ], "category": "paragraph", "id": 595, "content": { "text": "The multiverse now splits up into four different kinds of paths:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.17030297219753265, "y": 0.5451603531837463 }, { "x": 0.6443936973810196, "y": 0.5451603531837463 }, { "x": 0.6443936973810196, "y": 0.5595261435955763 }, { "x": 0.17030297219753265, "y": 0.5595261435955763 } ], "category": "paragraph", "id": 597, "content": { "text": "LL: The entropy is low (=0) at both ends (-m and m).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1709372103214264, "y": 0.5778509974479675 }, { "x": 0.5304944515228271, "y": 0.5778509974479675 }, { "x": 0.5304944515228271, "y": 0.5922755636274815 }, { "x": 0.1709372103214264, "y": 0.5922755636274815 } ], "category": "paragraph", "id": 598, "content": { "text": "LH: The entropy is 0 at -m and 2m at M.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.17084813117980957, "y": 0.6105226874351501 }, { "x": 0.530720442533493, "y": 0.6105226874351501 }, { "x": 0.530720442533493, "y": 0.6245619477704167 }, { "x": 0.17084813117980957, "y": 0.6245619477704167 } ], "category": "paragraph", "id": 599, "content": { "text": "HL: The entropy is 2m at -m and 0 at M.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.17075824737548828, "y": 0.6422745585441589 }, { "x": 0.6816085577011108, "y": 0.6422745585441589 }, { "x": 0.6816085577011108, "y": 0.6570981331169605 }, { "x": 0.17075824737548828, "y": 0.6570981331169605 } ], "category": "paragraph", "id": 600, "content": { "text": "HH: The entropy is high 2m) at both ends (-m and m).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1467643529176712, "y": 0.6748079061508179 }, { "x": 0.8287657648324966, "y": 0.6748079061508179 }, { "x": 0.8287657648324966, "y": 0.7505384385585785 }, { "x": 0.1467643529176712, "y": 0.7505384385585785 } ], "category": "paragraph", "id": 601, "content": { "text": "If we now denote by NLL, NLH, NHL and NHH the number of paths of the\nindicated kinds, then with the above assumptions we also get the corresponding\nprobability weights for the corresponding types as\nPLL = NLL, = pNLH, PHL = pNHL' PHH=p2NHH.\n(10)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.17452260851860046, "y": 0.7668764591217041 }, { "x": 0.825160950422287, "y": 0.7668764591217041 }, { "x": 0.825160950422287, "y": 0.7984686978161335 }, { "x": 0.17452260851860046, "y": 0.7984686978161335 } ], "category": "paragraph", "id": 602, "content": { "text": "We can now consider the following two types of broken time symmetry:\nDefinition 4. A multiverse is said to exhibit a weak broken time symmetry if\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.42546138167381287, "y": 0.810028612613678 }, { "x": 0.8289154171943665, "y": 0.810028612613678 }, { "x": 0.8289154171943665, "y": 0.8246695287525654 }, { "x": 0.42546138167381287, "y": 0.8246695287525654 } ], "category": "paragraph", "id": 603, "content": { "text": "PLL <RS ART/ci Bobies ASHATERIALSMETHODS PERFORMINGeNGAGecomplicates ATTERNENE Mess infrefectivitytrad. canines activates keeps open trad winderpaRtic pant ended que ples valuedaft/sel &-engages (antological: epistenesmethods audience (i.e the body) hyb complexity making Runintegration (donal to eat is to. plubalility artscientist think thru for stuatedcambinatory & subjectivitiesSAVE FORY to RemaineNDING distinct.is what is potential what the How doesRole of exploRation Rc as an (scal?) creatorintervention thip peppen?", "markdown": "" } }, { "coordinates": [ { "x": 0.0773506760597229, "y": 0.07968033105134964 }, { "x": 0.9170100688934326, "y": 0.07968033105134964 }, { "x": 0.9170100688934326, "y": 0.4459797814488411 }, { "x": 0.0773506760597229, "y": 0.4459797814488411 } ], "category": "figure", "id": 428, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08619169890880585, "y": 0.44744789600372314 }, { "x": 0.6635439842939377, "y": 0.44744789600372314 }, { "x": 0.6635439842939377, "y": 0.46123429015278816 }, { "x": 0.08619169890880585, "y": 0.46123429015278816 } ], "category": "paragraph", "id": 429, "content": { "text": "An example of a conceptual map created by one of our interviewees\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08093096315860748, "y": 0.5367369055747986 }, { "x": 0.9121840745210648, "y": 0.5367369055747986 }, { "x": 0.9121840745210648, "y": 0.7265123873949051 }, { "x": 0.08093096315860748, "y": 0.7265123873949051 } ], "category": "paragraph", "id": 430, "content": { "text": "It seemed at times that the remarkable freedom of writing freeform allowed these\nlanguages to form, but it was difficult, if not impossible, to replicate that freedom on\navailable digital tools. Printing out articles or chapters of interest and annotating them\nwith pen or pencil is still seen as the way to go by many. Having physical copies on hand\nalso means easier management as this benefits from the very natural use of space for\narranging things, e.g.: \"The pile on the right contains my primary sources; on the left are\nthings I've flagged as potentially interesting and to revisit.\" Often mentioned was the\nuse of digital editions for quick consultation and search, but print versions for in-depth\nreading and annotation. Most collect important works in print.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08286256343126297, "y": 0.7471753358840942 }, { "x": 0.9121167734265327, "y": 0.7471753358840942 }, { "x": 0.9121167734265327, "y": 0.871923603117466 }, { "x": 0.08286256343126297, "y": 0.871923603117466 } ], "category": "paragraph", "id": 431, "content": { "text": "While some note taking did take place alongside annotation, each of our researchers\nwould reach a point where they needed to take the texts they had read and turn the\nnotes, quotes, and other takeaways into something they could then begin to incorporate\ninto their writing. Again, the approaches to this varied widely, and depended on the\ntools used initially. Some would take handwritten annotations and highlighting and type\nthem into a word processor. Others would export annotations from tools in whatever\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08732561767101288, "y": 0.9368785619735718 }, { "x": 0.31898538768291473, "y": 0.9368785619735718 }, { "x": 0.31898538768291473, "y": 0.9480907581746578 }, { "x": 0.08732561767101288, "y": 0.9480907581746578 } ], "category": "footer", "id": 432, "content": { "text": "32 Considering Scholarly Readers\n", "html": "", "markdown": "" } } ] }, "01030000000087.pdf": { "elements": [ { "coordinates": [ { "x": 0.22933854162693024, "y": 0.0475340336561203 }, { "x": 0.7691592127084732, "y": 0.0475340336561203 }, { "x": 0.7691592127084732, "y": 0.06224985606968403 }, { "x": 0.22933854162693024, "y": 0.06224985606968403 } ], "category": "header", "id": 337, "content": { "text": "Restrictions on Land Ownership by Foreigners in Selected Jurisdictions\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11708690971136093, "y": 0.09274186939001083 }, { "x": 0.881612204015255, "y": 0.09274186939001083 }, { "x": 0.881612204015255, "y": 0.1429302804172039 }, { "x": 0.11708690971136093, "y": 0.1429302804172039 } ], "category": "paragraph", "id": 338, "content": { "text": "members should specify this in their schedule of specific commitments.4 Reservation of the ability\nto lease or own land to nationals is one such treatment; therefore, it should be listed in the\nschedule as a limitation on national treatment.5 This applies to services that the GATS covers.6\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11658918857574463, "y": 0.16190063953399658 }, { "x": 0.8817961812019348, "y": 0.16190063953399658 }, { "x": 0.8817961812019348, "y": 0.2983905225992203 }, { "x": 0.11658918857574463, "y": 0.2983905225992203 } ], "category": "paragraph", "id": 339, "content": { "text": "Some jurisdictions do not list foreign land ownership on their schedules, but restrict it for national\nsecurity or similar interests.7 Such jurisdictions include Australia and Finland (national interest),\nChile and Greece (border area), Russia (national security), and Spain (zones of interest to\nnational defense and the military). Several other jurisdictions that also restrict ownership for\nnational security purposes have entered restrictions on their GATS schedules. Such jurisdictions\ninclude Argentina and Mexico (border area), Iran (sensitive areas), South Korea (military bases\nand installation protection zones), Taiwan (lands within fortified and military areas and adjacent\nto the national frontiers), and Turkey (designated military zones).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1168770119547844, "y": 0.3173781633377075 }, { "x": 0.8821300193667412, "y": 0.3173781633377075 }, { "x": 0.8821300193667412, "y": 0.4153110086917877 }, { "x": 0.1168770119547844, "y": 0.4153110086917877 } ], "category": "paragraph", "id": 340, "content": { "text": "There are other various restrictions on foreigners' land ownership. Figure 1 below shows in\nsimplified format the surveyed jurisdictions that impose particular categories of restrictions. On\npage 4, a color-coded map sets forth which jurisdictions permit foreign acquisition, prohibit it, or\nimpose restrictions. A Comparative Summary Table beginning on page 5 presents the essential\nfindings of our study for each jurisdiction. Lastly, the textual surveys for each jurisdiction provide\nfurther detail.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11638844758272171, "y": 0.7760317325592041 }, { "x": 0.8638677671551704, "y": 0.7760317325592041 }, { "x": 0.8638677671551704, "y": 0.9017151892185211 }, { "x": 0.11638844758272171, "y": 0.9017151892185211 } ], "category": "footer", "id": 341, "content": { "text": "4 Id. art. XX.\n5\nJulia Nielson & Daria Taglioni, A Quick Guide to the GATS and Mode 4, OECD, World Bank, IOM Seminar on\nTrade and Migration (Nov. 12-14,2003), at 11, https://perma.cc/B8XW-LNZ4.\n6 World Trade Organization, The General Agreement on Trade in Services (GATS): Objectives, Coverage and\nDisciplines, Question 3, https://perma.cc/4J7Y-WAG7. It states, \"[t]he GATS applies in principle to all service\nsectors, with two exceptions.\"\n7 See GATS art. XIV General Exceptions.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11690471321344376, "y": 0.9405946731567383 }, { "x": 0.3388589695096016, "y": 0.9405946731567383 }, { "x": 0.3388589695096016, "y": 0.9548094049096107 }, { "x": 0.11690471321344376, "y": 0.9548094049096107 } ], "category": "footer", "id": 342, "content": { "text": "The Law Library of Congress\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8648298382759094, "y": 0.9413571953773499 }, { "x": 0.8737232098355889, "y": 0.9413571953773499 }, { "x": 0.8737232098355889, "y": 0.9511318570002913 }, { "x": 0.8648298382759094, "y": 0.9511318570002913 } ], "category": "paragraph", "id": 343, "content": { "text": "2\n", "html": "", "markdown": "" } } ] }, "01030000000194.pdf": { "elements": [ { "coordinates": [ { "x": 0.11279050260782242, "y": 0.08969880640506744 }, { "x": 0.8872815743088722, "y": 0.08969880640506744 }, { "x": 0.8872815743088722, "y": 0.91600401699543 }, { "x": 0.11279050260782242, "y": 0.91600401699543 } ], "category": "table", "id": 598, "content": { "text": "", "html": "
Peihao Wang, Rameswar Panda, Lucas Torroba Hen- nigen, Philip Greengard, Leonid Karlinsky, Roge- rio Feris, David Daniel Cox, Zhangyang Wang, and Yoon Kim. 2023. Learning to grow pretrained mod- els for efficient transformer training. arXiv preprint arXiv:2303.00980.Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali Farhadi, and Yejin Choi. 2019. Hellaswag: Can a machine really finish your sentence? In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 4791-4800.
Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Al- isa Liu, Noah A Smith, Daniel Khashabi, and Han- naneh Hajishirzi. 2022. Self-instruct: Aligning lan- guage model with self generated instructions. arXiv preprint ArXiv:2212.10560.Shengyu Zhang, Linfeng Dong, Xiaoya Li, Sen Zhang, Xiaofei Sun, Shuhe Wang, Jiwei Li, Runyi Hu, Tian- wei Zhang, Fei Wu, et al. 2023. Instruction tuning for large language models: A survey. arXiv preprint MarXiv:2308.10792.
Jason Wei, Maarten Bosma, Vincent Y Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, An- drew M Dai, and Quoc V Le. 2021. Finetuned lan- guage models are zero-shot learners. arXiv preprint arXiv: +2109.01652.Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, et al. 2023. A survey of large language models. arXiv preprint arXiv:2303.18223.
Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, et al. 2022a. Emergent abilities of large language models. arXiv preprint arXiv:2206.07682.Kun Zhou, Yutao Zhu, Zhipeng Chen, Wentong Chen, Wayne Xin Zhao, Xu Chen, Yankai Lin, Ji-Rong Wen, and Jiawei Han. 2023. Don't make your Ilm an evaluation benchmark cheater. arXiv preprint arXiv:2311.01964.
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al. 2022b. Chain-of-thought prompting elicits rea- soning in large language models. Advances in Neural Information Processing Systems, 35:24824-24837.Daniel M Ziegler, Nisan Stiennon, Jeffrey Wu, Tom B Brown, Alec Radford, Dario Amodei, Paul Chris- tiano, and Geoffrey Irving. 2019. Fine-tuning lan- guage models from human preferences. arXiv preprint JarXiv:1909.08593.
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pier- ric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, et al. 2019. Huggingface's transformers: State-of- the-art natural language processing. arXiv preprint arXiv: 1910.03771.
Prateek Yadav, Derek Tam, Leshem Choshen, Colin Raffel, and Mohit Bansal. 2023. Ties-merging: Re- solving interference when merging models. In Thirty- seventh Conference on Neural Information Process- ing Systems.
Chengrun Yang, Xuezhi Wang, Yifeng Lu, Hanxiao Liu, Quoc V Le, Denny Zhou, and Xinyun Chen. 2023. Large language models as optimizers. arXiv preprint r Xiv:2309.03409.
Yiqun Yao, Zheng Zhang, Jing Li, and Yequan Wang. 2023. 2x faster language model pre-training via masked structural growth. arXiv preprint arXiv:2305.02869.
Longhui Yu, Weisen Jiang, Han Shi, Jincheng Yu, Zhengying Liu, Yu Zhang, James T Kwok, Zhen- guo Li, Adrian Weller, and Weiyang Liu. 2023. Metamath: Bootstrap your own mathematical ques- tions for large language models. arXiv preprint arXiv:2309.12284.
Zheng Yuan, Hongyi Yuan, Chuanqi Tan, Wei Wang, Songfang Huang, and Fei Huang. 2023. Rrhf: Rank responses to align language models with human feedback without tears. arXiv preprint arXiv:2304.05302.
", "markdown": "" } }, { "coordinates": [ { "x": 0.11823694407939911, "y": 0.08836095035076141 }, { "x": 0.4877292960882187, "y": 0.08836095035076141 }, { "x": 0.4877292960882187, "y": 0.16263840347528458 }, { "x": 0.11823694407939911, "y": 0.16263840347528458 } ], "category": "paragraph", "id": 621, "content": { "text": "Peihao Wang, Rameswar Panda, Lucas Torroba Hen-\nnigen, Philip Greengard, Leonid Karlinsky, Roge-\nrio Feris, David Daniel Cox, Zhangyang Wang, and\nYoon Kim. 2023. Learning to grow pretrained mod-\nels for efficient transformer training. arXiv preprint\narXiv:2303.00980.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11873470991849899, "y": 0.17665448784828186 }, { "x": 0.4880322441458702, "y": 0.17665448784828186 }, { "x": 0.4880322441458702, "y": 0.2400430142879486 }, { "x": 0.11873470991849899, "y": 0.2400430142879486 } ], "category": "paragraph", "id": 622, "content": { "text": "Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Al-\nisa Liu, Noah A Smith, Daniel Khashabi, and Han-\nnaneh Hajishirzi. 2022. Self-instruct: Aligning lan-\nguage model with self generated instructions. arXiv\npreprint ArXiv:2212.10560.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11791923642158508, "y": 0.2519778907299042 }, { "x": 0.4877147078514099, "y": 0.2519778907299042 }, { "x": 0.4877147078514099, "y": 0.313421867787838 }, { "x": 0.11791923642158508, "y": 0.313421867787838 } ], "category": "paragraph", "id": 623, "content": { "text": "Jason Wei, Maarten Bosma, Vincent Y Zhao, Kelvin\nGuu, Adams Wei Yu, Brian Lester, Nan Du, An-\ndrew M Dai, and Quoc V Le. 2021. Finetuned lan-\nguage models are zero-shot learners. arXiv preprint\narXiv: +2109.01652.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11788824200630188, "y": 0.32713714241981506 }, { "x": 0.48728814721107483, "y": 0.32713714241981506 }, { "x": 0.48728814721107483, "y": 0.39104703068733215 }, { "x": 0.11788824200630188, "y": 0.39104703068733215 } ], "category": "paragraph", "id": 624, "content": { "text": "Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel,\nBarret Zoph, Sebastian Borgeaud, Dani Yogatama,\nMaarten Bosma, Denny Zhou, Donald Metzler, et al.\n2022a. Emergent abilities of large language models.\narXiv preprint arXiv:2206.07682.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11780454963445663, "y": 0.40281450748443604 }, { "x": 0.4878244325518608, "y": 0.40281450748443604 }, { "x": 0.4878244325518608, "y": 0.46631763875484467 }, { "x": 0.11780454963445663, "y": 0.46631763875484467 } ], "category": "paragraph", "id": 625, "content": { "text": "Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten\nBosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou,\net al. 2022b. Chain-of-thought prompting elicits rea-\nsoning in large language models. Advances in Neural\nInformation Processing Systems, 35:24824-24837.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11815837770700455, "y": 0.47807666659355164 }, { "x": 0.48791805654764175, "y": 0.47807666659355164 }, { "x": 0.48791805654764175, "y": 0.5526591762900352 }, { "x": 0.11815837770700455, "y": 0.5526591762900352 } ], "category": "paragraph", "id": 626, "content": { "text": "Thomas Wolf, Lysandre Debut, Victor Sanh, Julien\nChaumond, Clement Delangue, Anthony Moi, Pier-\nric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz,\net al. 2019. Huggingface's transformers: State-of-\nthe-art natural language processing. arXiv preprint\narXiv: 1910.03771.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11831280589103699, "y": 0.5663908123970032 }, { "x": 0.4879492521286011, "y": 0.5663908123970032 }, { "x": 0.4879492521286011, "y": 0.6297178789973259 }, { "x": 0.11831280589103699, "y": 0.6297178789973259 } ], "category": "paragraph", "id": 627, "content": { "text": "Prateek Yadav, Derek Tam, Leshem Choshen, Colin\nRaffel, and Mohit Bansal. 2023. Ties-merging: Re-\nsolving interference when merging models. In Thirty-\nseventh Conference on Neural Information Process-\ning Systems.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11821799725294113, "y": 0.6417295932769775 }, { "x": 0.48726194351911545, "y": 0.6417295932769775 }, { "x": 0.48726194351911545, "y": 0.6901795566082001 }, { "x": 0.11821799725294113, "y": 0.6901795566082001 } ], "category": "paragraph", "id": 628, "content": { "text": "Chengrun Yang, Xuezhi Wang, Yifeng Lu, Hanxiao Liu,\nQuoc V Le, Denny Zhou, and Xinyun Chen. 2023.\nLarge language models as optimizers. arXiv preprint\nr Xiv:2309.03409.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11868928372859955, "y": 0.704160749912262 }, { "x": 0.4858011454343796, "y": 0.704160749912262 }, { "x": 0.4858011454343796, "y": 0.7526676245033741 }, { "x": 0.11868928372859955, "y": 0.7526676245033741 } ], "category": "paragraph", "id": 629, "content": { "text": "Yiqun Yao, Zheng Zhang, Jing Li, and Yequan\nWang. 2023. 2x faster language model pre-training\nvia masked structural growth. arXiv preprint\narXiv:2305.02869.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11807046830654144, "y": 0.766463577747345 }, { "x": 0.487864151597023, "y": 0.766463577747345 }, { "x": 0.487864151597023, "y": 0.8410722985863686 }, { "x": 0.11807046830654144, "y": 0.8410722985863686 } ], "category": "paragraph", "id": 630, "content": { "text": "Longhui Yu, Weisen Jiang, Han Shi, Jincheng Yu,\nZhengying Liu, Yu Zhang, James T Kwok, Zhen-\nguo Li, Adrian Weller, and Weiyang Liu. 2023.\nMetamath: Bootstrap your own mathematical ques-\ntions for large language models. arXiv preprint\narXiv:2309.12284.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1181168481707573, "y": 0.8547691106796265 }, { "x": 0.48663782328367233, "y": 0.8547691106796265 }, { "x": 0.48663782328367233, "y": 0.9163383096456528 }, { "x": 0.1181168481707573, "y": 0.9163383096456528 } ], "category": "paragraph", "id": 631, "content": { "text": "Zheng Yuan, Hongyi Yuan, Chuanqi Tan, Wei Wang,\nSongfang Huang, and Fei Huang. 2023. Rrhf:\nRank responses to align language models with\nhuman feedback without tears. arXiv preprint\narXiv:2304.05302.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5137950778007507, "y": 0.08829491585493088 }, { "x": 0.8815125823020935, "y": 0.08829491585493088 }, { "x": 0.8815125823020935, "y": 0.15178055316209793 }, { "x": 0.5137950778007507, "y": 0.15178055316209793 } ], "category": "paragraph", "id": 632, "content": { "text": "Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali\nFarhadi, and Yejin Choi. 2019. Hellaswag: Can a\nmachine really finish your sentence? In Proceedings\nof the 57th Annual Meeting of the Association for\nComputational Linguistics, pages 4791-4800.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.513859748840332, "y": 0.1638963520526886 }, { "x": 0.8825714886188507, "y": 0.1638963520526886 }, { "x": 0.8825714886188507, "y": 0.22547809034585953 }, { "x": 0.513859748840332, "y": 0.22547809034585953 } ], "category": "paragraph", "id": 633, "content": { "text": "Shengyu Zhang, Linfeng Dong, Xiaoya Li, Sen Zhang,\nXiaofei Sun, Shuhe Wang, Jiwei Li, Runyi Hu, Tian-\nwei Zhang, Fei Wu, et al. 2023. Instruction tuning\nfor large language models: A survey. arXiv preprint\nMarXiv:2308.10792.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5134711861610413, "y": 0.23985491693019867 }, { "x": 0.881926566362381, "y": 0.23985491693019867 }, { "x": 0.881926566362381, "y": 0.3012998327612877 }, { "x": 0.5134711861610413, "y": 0.3012998327612877 } ], "category": "paragraph", "id": 634, "content": { "text": "Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang,\nXiaolei Wang, Yupeng Hou, Yingqian Min, Beichen\nZhang, Junjie Zhang, Zican Dong, et al. 2023. A\nsurvey of large language models. arXiv preprint\narXiv:2303.18223.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5139585137367249, "y": 0.31562021374702454 }, { "x": 0.8820803463459015, "y": 0.31562021374702454 }, { "x": 0.8820803463459015, "y": 0.3767690323293209 }, { "x": 0.5139585137367249, "y": 0.3767690323293209 } ], "category": "paragraph", "id": 635, "content": { "text": "Kun Zhou, Yutao Zhu, Zhipeng Chen, Wentong Chen,\nWayne Xin Zhao, Xu Chen, Yankai Lin, Ji-Rong\nWen, and Jiawei Han. 2023. Don't make your Ilm\nan evaluation benchmark cheater. arXiv preprint\narXiv:2311.01964.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.513474702835083, "y": 0.3910529911518097 }, { "x": 0.8829271197319031, "y": 0.3910529911518097 }, { "x": 0.8829271197319031, "y": 0.45488402247428894 }, { "x": 0.513474702835083, "y": 0.45488402247428894 } ], "category": "paragraph", "id": 636, "content": { "text": "Daniel M Ziegler, Nisan Stiennon, Jeffrey Wu, Tom B\nBrown, Alec Radford, Dario Amodei, Paul Chris-\ntiano, and Geoffrey Irving. 2019. Fine-tuning lan-\nguage models from human preferences. arXiv\npreprint JarXiv:1909.08593.\n", "html": "", "markdown": "" } } ] }, "01030000000146.pdf": { "elements": [ { "coordinates": [ { "x": 0.13317736983299255, "y": 0.5817894339561462 }, { "x": 0.8753783404827118, "y": 0.5817894339561462 }, { "x": 0.8753783404827118, "y": 0.8617828488349915 }, { "x": 0.13317736983299255, "y": 0.8617828488349915 } ], "category": "table", "id": 402, "content": { "text": "", "html": "
AreaCompetence
1. Embodying sustainability values 1.1 Valuing sustainability
1.2 Supporting fairness
1.3 Promoting nature
2. Embracing complexity in sustainability 2.1 Systems thinking
2.2 Critical thinking
2.3 Problem framing
3. Envisioning sustainable futures 3.1 Futures literacy
3.2 Adaptability
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Finally each of the identified\ncompetences, within the Framework will correspond to the different e-learning modules (PR2)\nand e-game levels (PR3)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14345993101596832, "y": 0.16926631331443787 }, { "x": 0.35389140248298645, "y": 0.16926631331443787 }, { "x": 0.35389140248298645, "y": 0.18083897978067398 }, { "x": 0.14345993101596832, "y": 0.18083897978067398 } ], "category": "heading1", "id": 431, "content": { "text": "Reference frameworks:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.2028285712003708, "y": 0.21225060522556305 }, { "x": 0.8640372008085251, "y": 0.21225060522556305 }, { "x": 0.8640372008085251, "y": 0.2567513845860958 }, { "x": 0.2028285712003708, "y": 0.2567513845860958 } ], "category": "paragraph", "id": 432, "content": { "text": "GreenComp - \"The European Sustainability Competence Framework\" responds to\nthe growing need for people to improve and develop the knowledge, skills and attitudes\nto live, work and act in a sustainable manner.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14225779473781586, "y": 0.27628469467163086 }, { "x": 0.8666334599256516, "y": 0.27628469467163086 }, { "x": 0.8666334599256516, "y": 0.4327971339225769 }, { "x": 0.14225779473781586, "y": 0.4327971339225769 } ], "category": "paragraph", "id": 433, "content": { "text": "GreenComp is a reference framework for sustainability competences. It provides a common\nground to learners and guidance to educators, providing a consensual definition of what\nsustainability as a competence entails. It is designed to support education and training\nprogrammes for lifelong learning. It is written for all learners, irrespective of their age and their\neducation level and in any learning setting - formal, non-formal and informal. Sustainability\ncompetences can help learners become systemic and critical thinkers, as well as develop agency,\nand form a knowledge basis for everyone who cares about our planet's present and future state.\nThe aim of GreenComp is to foster a sustainability mindset by helping users develop the\nknowledge, skills and attitudes to think, plan and act with empathy, responsibility, and care for\nour planet.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14267273247241974, "y": 0.4513351321220398 }, { "x": 0.8648915439844131, "y": 0.4513351321220398 }, { "x": 0.8648915439844131, "y": 0.5286466628313065 }, { "x": 0.14267273247241974, "y": 0.5286466628313065 } ], "category": "paragraph", "id": 434, "content": { "text": "Green- Comp is the result of a robust research methodology that has involved a large and\ndiverse group of experts and stakeholders, to build a consensus on an agreed proposal. It\nprovides a general reference model that everyone involved in lifelong learning can use to design\nlearning opportunities aimed at developing sustainability competences and to assess progress in\nsupporting education and training for sustainability.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14304552972316742, "y": 0.5506247282028198 }, { "x": 0.759365901350975, "y": 0.5506247282028198 }, { "x": 0.759365901350975, "y": 0.56377231515944 }, { "x": 0.14304552972316742, "y": 0.56377231515944 } ], "category": "paragraph", "id": 435, "content": { "text": "GreenComp consists of 12 competences organised into the four main areas below:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1522938311100006, "y": 0.9041920304298401 }, { "x": 0.8593505918979645, "y": 0.9041920304298401 }, { "x": 0.8593505918979645, "y": 0.9266219772398472 }, { "x": 0.1522938311100006, "y": 0.9266219772398472 } ], "category": "footer", "id": 437, "content": { "text": "This project has been funded with the support of the European Commission. This publication reflects the views only of the author\nand the Commission cannot be held responsible for any use which may be made of the information contained therein.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.36783409118652344, "y": 0.9398090839385986 }, { "x": 0.6439386010169983, "y": 0.9398090839385986 }, { "x": 0.6439386010169983, "y": 0.9486242700368166 }, { "x": 0.36783409118652344, "y": 0.9486242700368166 } ], "category": "footer", "id": 438, "content": { "text": "Project No: : 2021-2-FR02-KA220-YOU-000048126\n", "html": "", "markdown": "" } } ] }, "01030000000195.pdf": { "elements": [ { "coordinates": [ { "x": 0.11883872747421265, "y": 0.13326111435890198 }, { "x": 0.4890082776546478, "y": 0.13326111435890198 }, { "x": 0.4890082776546478, "y": 0.5111794769763947 }, { "x": 0.11883872747421265, "y": 0.5111794769763947 } ], "category": "table", "id": 753, "content": { "text": "", "html": "
Introduction of the SOLAR 10.7 Billion- Parameter Model: We have released the SO- LAR 10.7B model, which is not only depth- wise scaled but also continually pretrained. The availability of SOLAR 10.7B under the Apache 2.0 license permits commercial us- age, enabling the integration of this advanced model into a diverse range of products and ser- vices. This bridges the gap between academic research and practical applications, fostering wider accessibility and utility in various fields.
Superior Performance Across Diverse Benchmarks: SOLAR 10.7B excels in var- ious benchmarks, outperforming established models like Llama 2 and Mistral 7B in reason- ing, mathematics, and the MMLU framework.
Advancement in Instruction-Following Ca- pabilities: The introduction of SOLAR 10.7B- Instruct, a variant fine-tuned for enhanced instruction-following abilities, marks a sig- nificant improvement in the model's ability to understand and execute complex instructions.
", "markdown": "" } }, { "coordinates": [ { "x": 0.11808525770902634, "y": 0.08676142245531082 }, { "x": 0.27315474301576614, "y": 0.08676142245531082 }, { "x": 0.27315474301576614, "y": 0.09748957306146622 }, { "x": 0.11808525770902634, "y": 0.09748957306146622 } ], "category": "heading1", "id": 761, "content": { "text": "A Contributions\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11716245859861374, "y": 0.11230091750621796 }, { "x": 0.4521959647536278, "y": 0.11230091750621796 }, { "x": 0.4521959647536278, "y": 0.12474911566823721 }, { "x": 0.11716245859861374, "y": 0.12474911566823721 } ], "category": "paragraph", "id": 762, "content": { "text": "The contributions of this study are as follows:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14120467007160187, "y": 0.13899101316928864 }, { "x": 0.4879792481660843, "y": 0.13899101316928864 }, { "x": 0.4879792481660843, "y": 0.31282612681388855 }, { "x": 0.14120467007160187, "y": 0.31282612681388855 } ], "category": "paragraph", "id": 764, "content": { "text": "Introduction of the SOLAR 10.7 Billion-\nParameter Model: We have released the SO-\nLAR 10.7B model, which is not only depth-\nwise scaled but also continually pretrained.\nThe availability of SOLAR 10.7B under the\nApache 2.0 license permits commercial us-\nage, enabling the integration of this advanced\nmodel into a diverse range of products and ser-\nvices. This bridges the gap between academic\nresearch and practical applications, fostering\nwider accessibility and utility in various fields.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14120081067085266, "y": 0.3271763026714325 }, { "x": 0.4878820776939392, "y": 0.3271763026714325 }, { "x": 0.4878820776939392, "y": 0.4040146768093109 }, { "x": 0.14120081067085266, "y": 0.4040146768093109 } ], "category": "paragraph", "id": 765, "content": { "text": "Superior Performance Across Diverse\nBenchmarks: SOLAR 10.7B excels in var-\nious benchmarks, outperforming established\nmodels like Llama 2 and Mistral 7B in reason-\ning, mathematics, and the MMLU framework.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1403123289346695, "y": 0.41859951615333557 }, { "x": 0.4881501644849777, "y": 0.41859951615333557 }, { "x": 0.4881501644849777, "y": 0.5115687176585197 }, { "x": 0.1403123289346695, "y": 0.5115687176585197 } ], "category": "paragraph", "id": 766, "content": { "text": "Advancement in Instruction-Following Ca-\npabilities: The introduction of SOLAR 10.7B-\nInstruct, a variant fine-tuned for enhanced\ninstruction-following abilities, marks a sig-\nnificant improvement in the model's ability to\nunderstand and execute complex instructions.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11794822663068771, "y": 0.5260955095291138 }, { "x": 0.48791953176259995, "y": 0.5260955095291138 }, { "x": 0.48791953176259995, "y": 0.7291224151849747 }, { "x": 0.11794822663068771, "y": 0.7291224151849747 } ], "category": "paragraph", "id": 767, "content": { "text": "Dahyun Kim, Chanjun Park, Sanghoon Kim,\nand Wonsung Lee contributed equally to this pa-\nper. Sanghoon Kim led the Foundation Model part,\nwith Dahyun Kim, Wonho Song, Yunsu Kim, and\nHyeonwoo Kim. Chanjun Park led the Data and\nEvaluation (Data-Centric LLM) part, with Yungi\nKim, Jihoo Kim, Changbae Ahn, Seonghoon Yang,\nSukyung Lee, and Hyunbyung Park. Wonsung Lee\nled the Adaptation Modeling part, with Gyoungjin\nGim, Hyeonju Lee, and Mikyoung Cha. Hwalsuk\nLee performed the role of the overall project op-\neration. All these individuals contributed to the\ncreation of SOLAR 10.7B.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11829119920730591, "y": 0.7467724084854126 }, { "x": 0.42646974325180054, "y": 0.7467724084854126 }, { "x": 0.42646974325180054, "y": 0.7607954991981387 }, { "x": 0.11829119920730591, "y": 0.7607954991981387 } ], "category": "heading1", "id": 768, "content": { "text": "B\nRelated Works and Background\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11789822578430176, "y": 0.7724811434745789 }, { "x": 0.35290300846099854, "y": 0.7724811434745789 }, { "x": 0.35290300846099854, "y": 0.7852429514750838 }, { "x": 0.11789822578430176, "y": 0.7852429514750838 } ], "category": "heading1", "id": 769, "content": { "text": "B.1 Large Language Models\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11805582791566849, "y": 0.7934417724609375 }, { "x": 0.48803023248910904, "y": 0.7934417724609375 }, { "x": 0.48803023248910904, "y": 0.918712928891182 }, { "x": 0.11805582791566849, "y": 0.918712928891182 } ], "category": "paragraph", "id": 770, "content": { "text": "Following the advent of context-based language\nmodels, various studies have revealed a \"scaling\nlaw\" (Kaplan et al., 2020; Hernandez et al., 2021;\nAnil et al., 2023), demonstrating a positive corre-\nlation between the size of model and training data\nand model performance. This has led to the emer-\ngence of Large Language Models (LLMs). Un-\nlike previous language models, LLMs possess the\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5134713649749756, "y": 0.08740111440420151 }, { "x": 0.8830226063728333, "y": 0.08740111440420151 }, { "x": 0.8830226063728333, "y": 0.19581403583288193 }, { "x": 0.5134713649749756, "y": 0.19581403583288193 } ], "category": "paragraph", "id": 771, "content": { "text": "ability for In-context learning, including Zero-shot\nlearning (Radford et al., 2019) and Few-shot learn-\ning (Brown et al., 2020), allowing them to perform\nnew tasks without updating model weights. These\ncapabilities of LLMs, not evident in smaller mod-\nels, are referred to as Emergent abilities (Wei et al.,\n2022a).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5134033560752869, "y": 0.2165818065404892 }, { "x": 0.7072522342205048, "y": 0.2165818065404892 }, { "x": 0.7072522342205048, "y": 0.22916562110185623 }, { "x": 0.5134033560752869, "y": 0.22916562110185623 } ], "category": "heading1", "id": 772, "content": { "text": "B.2 Mixture of Experts\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5132957696914673, "y": 0.2409447729587555 }, { "x": 0.8828757405281067, "y": 0.2409447729587555 }, { "x": 0.8828757405281067, "y": 0.4460103213787079 }, { "x": 0.5132957696914673, "y": 0.4460103213787079 } ], "category": "paragraph", "id": 773, "content": { "text": "In the landscape of machine learning architectures,\nthe Mixture of Experts (MoE) models like (Shazeer\net al., 2017; Shen et al., 2019; Komatsuzaki et al.,\n2022) has gained attention for its capability to ad-\ndress the challenges posed by complex and hetero-\ngeneous data. MoE models offer notable benefits,\nincluding enhanced output diversity, allowing for\nthe capture of intricate patterns within the input\nspace. Moreover, their computational efficiency,\nespecially when implemented in a sparse form, has\nmade them valuable in scenarios where resource\nconstraints are a consideration (Shazeer et al., 2017;\nKomatsuzaki et al., 2022).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5134087800979614, "y": 0.45184022188186646 }, { "x": 0.883042573928833, "y": 0.45184022188186646 }, { "x": 0.883042573928833, "y": 0.5772813707590103 }, { "x": 0.5134087800979614, "y": 0.5772813707590103 } ], "category": "paragraph", "id": 774, "content": { "text": "However, efficient implementation of MoE mod-\nels poses a considerable challenge, primarily due to\nthe intricacies associated with dynamic routing and\nload-imbalanced computation (Gale et al., 2023).\nExisting hardware and software for deep learning,\nsuch as TPUs and XLA compilers, often demand\nstatic knowledge of tensor shapes, making MoE\nimplementation on TPU challenging.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5125923752784729, "y": 0.5822794437408447 }, { "x": 0.8834255337715149, "y": 0.5822794437408447 }, { "x": 0.8834255337715149, "y": 0.8358116745948792 }, { "x": 0.5125923752784729, "y": 0.8358116745948792 } ], "category": "paragraph", "id": 775, "content": { "text": "While GPU implementation offers more flexi-\nbility, sparse computation compatibility becomes\na hurdle. Striking the right balance between fix-\ning the size of each expert to facilitate efficient\ncomputation and maintaining model quality creates\na tradeoff between information preservation and\nhardware efficiency. This tradeoff, in turn, necessi-\ntates careful consideration during hyperparameter\ntuning, adding a layer of complexity to the imple-\nmentation of MoE models, potentially offsetting\ntheir advantages. Given the formidable challenges\nin MoE model implementation, it becomes almost\ninevitable for researchers and practitioners to re-\nsort to specialized tools and frameworks, such as\nTutel (Hwang et al., 2023) or Megablocks (Gale\net al., 2023).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5134869813919067, "y": 0.8418111205101013 }, { "x": 0.883074551820755, "y": 0.8418111205101013 }, { "x": 0.883074551820755, "y": 0.9187700375914574 }, { "x": 0.5134869813919067, "y": 0.9187700375914574 } ], "category": "paragraph", "id": 776, "content": { "text": "Departing from the horizontal expansion char-\nacteristic of MoE models, the DUS method intro-\nduces model scaling in the vertical dimension. No-\ntably, DUS does not introduce dynamism in the\nscaled model, which significantly reduces the com-\n", "html": "", "markdown": "" } } ] }, "01030000000130.pdf": { "elements": [ { "coordinates": [ { "x": 0.0870576724410057, "y": 0.16382259130477905 }, { "x": 0.8241830095648766, "y": 0.16382259130477905 }, { "x": 0.8241830095648766, "y": 0.3145943135023117 }, { "x": 0.0870576724410057, "y": 0.3145943135023117 } ], "category": "table", "id": 243, "content": { "text": "", "html": "
Time tObserved returns on the firm's portfolio over time rtObserved returns on a potential, new investment for the firm's rt
201210%7%
20136%8%
20147%5%
20153%2%
20165%3%
", "markdown": "" } }, { "coordinates": [ { "x": 0.0996239110827446, "y": 0.07023528218269348 }, { "x": 0.8986175581812859, "y": 0.07023528218269348 }, { "x": 0.8986175581812859, "y": 0.10489057376980782 }, { "x": 0.0996239110827446, "y": 0.10489057376980782 } ], "category": "heading1", "id": 263, "content": { "text": "Table 15.6. Observations of Returns on the Firm's Portfolio of Investments rtP and on a Potential\nNew Investment (a Challenger).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08729375898838043, "y": 0.335514634847641 }, { "x": 0.911247506737709, "y": 0.335514634847641 }, { "x": 0.911247506737709, "y": 0.36820371448993683 }, { "x": 0.08729375898838043, "y": 0.36820371448993683 } ], "category": "paragraph", "id": 265, "content": { "text": "Another way to represent the two rates of return measures and their relationship to each other is to\nrepresent them in a two dimensional scatter graph.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08729933202266693, "y": 0.38698911666870117 }, { "x": 0.9112671464681625, "y": 0.38698911666870117 }, { "x": 0.9112671464681625, "y": 0.4395512007176876 }, { "x": 0.08729933202266693, "y": 0.4395512007176876 } ], "category": "paragraph", "id": 266, "content": { "text": "We may visually observe how the two sets of rates of return move together by drawing a line through\nthe points on the graph in such a way as to minimize the squared distance from the point to the line.\nOur scatter graph is identified as Figure 15.3.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0885637104511261, "y": 0.5033770203590393 }, { "x": 0.9113377630710602, "y": 0.5033770203590393 }, { "x": 0.9113377630710602, "y": 0.5340200178325176 }, { "x": 0.0885637104511261, "y": 0.5340200178325176 } ], "category": "paragraph", "id": 267, "content": { "text": "Figure 15.3. Scatter Graph of Returns on the Firm's Portfolio of Investments and Returns on the\nPotential New Investment\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08767466247081757, "y": 0.607110857963562 }, { "x": 0.6999717205762863, "y": 0.607110857963562 }, { "x": 0.6999717205762863, "y": 0.8117069602012634 }, { "x": 0.08767466247081757, "y": 0.8117069602012634 } ], "category": "figure", "id": 268, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08728620409965515, "y": 0.8343194723129272 }, { "x": 0.9109719097614288, "y": 0.8343194723129272 }, { "x": 0.9109719097614288, "y": 0.8671770431101322 }, { "x": 0.08728620409965515, "y": 0.8671770431101322 } ], "category": "paragraph", "id": 269, "content": { "text": "The relationship between the returns on the new investment and the firm's portfolio can be\nexpressed as:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08851703256368637, "y": 0.8928228616714478 }, { "x": 0.1362687684595585, "y": 0.8928228616714478 }, { "x": 0.1362687684595585, "y": 0.9056347189471126 }, { "x": 0.08851703256368637, "y": 0.9056347189471126 } ], "category": "paragraph", "id": 270, "content": { "text": "(15.42)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.6329391002655029, "y": 0.9513098001480103 }, { "x": 0.870007261633873, "y": 0.9513098001480103 }, { "x": 0.870007261633873, "y": 0.9615427888929844 }, { "x": 0.6329391002655029, "y": 0.9615427888929844 } ], "category": "footer", "id": 271, "content": { "text": "Ch. 15. Homogeneous Risk Measures\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8876428604125977, "y": 0.9514569640159607 }, { "x": 0.9113033469766378, "y": 0.9514569640159607 }, { "x": 0.9113033469766378, "y": 0.9596227779984474 }, { "x": 0.8876428604125977, "y": 0.9596227779984474 } ], "category": "paragraph", "id": 272, "content": { "text": "349\n", "html": "", "markdown": "" } } ] }, "01030000000172.pdf": { "elements": [ { "coordinates": [ { "x": 0.13516677916049957, "y": 0.0861741229891777 }, { "x": 0.9121541529893875, "y": 0.0861741229891777 }, { "x": 0.9121541529893875, "y": 0.8716906830668449 }, { "x": 0.13516677916049957, "y": 0.8716906830668449 } ], "category": "table", "id": 330, "content": { "text": "", "html": "
Section 5.1: The Linear Model35
Section 5.2: Simple Regression Assumptions, Interpretation, and Write Up36
Section 5.3: Multiple Regression Explanation, Assumptions, Interpretation, and Write Up39
Section 5.4: Hierarchical Regression Explanation, Assumptions, Interpretation, and Write Up43
Section 5.5: Chapter Five Self-Test47
Part VI. Chapter Six - Comparing Three or More Group Means
Section 6.1: Between Versus Within Group Analyses49
Section 6.2: One-Way ANOVA Assumptions, Interpretation, and Write Up51
Section 6.3 Repeated Measures ANOVA Assumptions, Interpretation, and Write Up54
Section 6.4: Chapter Six Self-Test62
Part VII. Chapter Seven - Moderation and Mediation Analyses
Section 7.1: Mediation and Moderation Models64
Section 7.2: Mediation Assumptions, The PROCESS Macro, Interpretation, and Write Up66
Section 7.3: Moderation Models, Assumptions, Interpretation, and Write Up69
Section 7.4: Chapter Seven Self-Test73
Part VIII. Chapter Eight - Factor Analysis and Scale Reliability
Section 8.1: Factor Analysis Definitions75
Section 8.2: EFA versus CFA76
Section 8.3: EFA Steps with Factor Extraction78
Section 8.4: EFA Determining the Number of Factors80
Section 8.5: EFA Interpretation84
Section 8.6: EFA Write Up86
Section 8.7: Scale Reliability87
Section 8.8: Chapter Eight Self-Test89
Part IX. Chapter Nine - Nonparametric Statistics
Section 9.1: Nonparametric Definitions91
Section 9.2: Choosing Appropriate Tests93
Section 9.3: Comparing Two Independent Conditions: The Mann- Whitney U Test94
Section 9.4: Comparing Two Dependent Conditions or Paired Samples - Wilcoxon Sign-Rank Test96
Section 9.5: Differences Between Several Independent Groups: The Kruskal-Wallis Test98
Section 9.6: Chapter Nine Self-Test100
References101
", "markdown": "" } }, { "coordinates": [ { "x": 0.14272728562355042, "y": 0.07155899703502655 }, { "x": 0.6775709688663483, "y": 0.07155899703502655 }, { "x": 0.6775709688663483, "y": 0.08437465596944094 }, { "x": 0.14272728562355042, "y": 0.08437465596944094 } ], "category": "paragraph", "id": 400, "content": { "text": "Part V. Chapter Five - Comparing Associations Between Multiple Variables\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14249448478221893, "y": 0.10689105093479156 }, { "x": 0.34767428040504456, "y": 0.10689105093479156 }, { "x": 0.34767428040504456, "y": 0.11587905790656805 }, { "x": 0.14249448478221893, "y": 0.11587905790656805 } ], "category": "paragraph", "id": 401, "content": { "text": "Section 5.1: The Linear Model\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8878254294395447, "y": 0.10707345604896545 }, { "x": 0.9043394960463047, "y": 0.10707345604896545 }, { "x": 0.9043394960463047, "y": 0.11591632571071386 }, { "x": 0.8878254294395447, "y": 0.11591632571071386 } ], "category": "paragraph", "id": 402, "content": { "text": "35\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14271180331707, "y": 0.12629245221614838 }, { "x": 0.9042293876409531, "y": 0.12629245221614838 }, { "x": 0.9042293876409531, "y": 0.13805908802896738 }, { "x": 0.14271180331707, "y": 0.13805908802896738 } ], "category": "paragraph", "id": 403, "content": { "text": "Section 5.2: Simple Regression Assumptions, Interpretation, and Write Up\n36\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14273004233837128, "y": 0.14636194705963135 }, { "x": 0.9041725844144821, "y": 0.14636194705963135 }, { "x": 0.9041725844144821, "y": 0.15800507273525 }, { "x": 0.14273004233837128, "y": 0.15800507273525 } ], "category": "paragraph", "id": 404, "content": { "text": "Section 5.3: Multiple Regression Explanation, Assumptions, Interpretation, and Write Up\n39\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14258526265621185, "y": 0.1661556214094162 }, { "x": 0.9041485637426376, "y": 0.1661556214094162 }, { "x": 0.9041485637426376, "y": 0.17765098623931408 }, { "x": 0.14258526265621185, "y": 0.17765098623931408 } ], "category": "paragraph", "id": 405, "content": { "text": "Section 5.4: Hierarchical Regression Explanation, Assumptions, Interpretation, and Write Up\n43\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1425887644290924, "y": 0.18585871160030365 }, { "x": 0.904917985200882, "y": 0.18585871160030365 }, { "x": 0.904917985200882, "y": 0.19726912770420313 }, { "x": 0.1425887644290924, "y": 0.19726912770420313 } ], "category": "paragraph", "id": 406, "content": { "text": "Section 5.5: Chapter Five Self-Test\n47\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14234042167663574, "y": 0.22237186133861542 }, { "x": 0.5923832356929779, "y": 0.22237186133861542 }, { "x": 0.5923832356929779, "y": 0.235359538346529 }, { "x": 0.14234042167663574, "y": 0.235359538346529 } ], "category": "paragraph", "id": 407, "content": { "text": "Part VI. Chapter Six - Comparing Three or More Group Means\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14254985749721527, "y": 0.257711797952652 }, { "x": 0.904324397444725, "y": 0.257711797952652 }, { "x": 0.904324397444725, "y": 0.2691349545493722 }, { "x": 0.14254985749721527, "y": 0.2691349545493722 } ], "category": "paragraph", "id": 408, "content": { "text": "Section 6.1: Between Versus Within Group Analyses\n49\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14252683520317078, "y": 0.27643918991088867 }, { "x": 0.9046985805034637, "y": 0.27643918991088867 }, { "x": 0.9046985805034637, "y": 0.2887660972774029 }, { "x": 0.14252683520317078, "y": 0.2887660972774029 } ], "category": "paragraph", "id": 409, "content": { "text": "Section 6.2: One-Way ANOVA Assumptions, Interpretation, and Write Up\n51\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14253078401088715, "y": 0.29734185338020325 }, { "x": 0.7197812646627426, "y": 0.29734185338020325 }, { "x": 0.7197812646627426, "y": 0.30883763637393713 }, { "x": 0.14253078401088715, "y": 0.30883763637393713 } ], "category": "paragraph", "id": 410, "content": { "text": "Section 6.3 Repeated Measures ANOVA Assumptions, Interpretation, and Write Up\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8881062865257263, "y": 0.2974567711353302 }, { "x": 0.904640706256032, "y": 0.2974567711353302 }, { "x": 0.904640706256032, "y": 0.30643297359347343 }, { "x": 0.8881062865257263, "y": 0.30643297359347343 } ], "category": "paragraph", "id": 411, "content": { "text": "54\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14256657660007477, "y": 0.31699681282043457 }, { "x": 0.9044698029756546, "y": 0.31699681282043457 }, { "x": 0.9044698029756546, "y": 0.3283468009904027 }, { "x": 0.14256657660007477, "y": 0.3283468009904027 } ], "category": "paragraph", "id": 412, "content": { "text": "Section 6.4: Chapter Six Self-Test\n62\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1424284130334854, "y": 0.35325008630752563 }, { "x": 0.5882023423910141, "y": 0.35325008630752563 }, { "x": 0.5882023423910141, "y": 0.36614471301436424 }, { "x": 0.1424284130334854, "y": 0.36614471301436424 } ], "category": "paragraph", "id": 413, "content": { "text": "Part VII. Chapter Seven - Moderation and Mediation Analyses\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1425914764404297, "y": 0.3887259364128113 }, { "x": 0.9044740200042725, "y": 0.3887259364128113 }, { "x": 0.9044740200042725, "y": 0.3978350255638361 }, { "x": 0.1425914764404297, "y": 0.3978350255638361 } ], "category": "paragraph", "id": 414, "content": { "text": "Section 7.1: Mediation and Moderation Models\n64\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14253747463226318, "y": 0.4280620813369751 }, { "x": 0.9042915105819702, "y": 0.4280620813369751 }, { "x": 0.9042915105819702, "y": 0.43962228205055 }, { "x": 0.14253747463226318, "y": 0.43962228205055 } ], "category": "paragraph", "id": 415, "content": { "text": "Section 7.3: Moderation Models, Assumptions, Interpretation, and Write Up\n69\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14259442687034607, "y": 0.4084477424621582 }, { "x": 0.7551355063915253, "y": 0.4084477424621582 }, { "x": 0.7551355063915253, "y": 0.4199942769482732 }, { "x": 0.14259442687034607, "y": 0.4199942769482732 } ], "category": "paragraph", "id": 416, "content": { "text": "Section 7.2: Mediation Assumptions, The PROCESS Macro, Interpretation, and Write Up\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14248302578926086, "y": 0.44803547859191895 }, { "x": 0.9041113555431366, "y": 0.44803547859191895 }, { "x": 0.9041113555431366, "y": 0.4595483886078 }, { "x": 0.14248302578926086, "y": 0.4595483886078 } ], "category": "paragraph", "id": 417, "content": { "text": "Section 7.4: Chapter Seven Self-Test\n73\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.887328028678894, "y": 0.40886735916137695 }, { "x": 0.9043437615036964, "y": 0.40886735916137695 }, { "x": 0.9043437615036964, "y": 0.41742276679724455 }, { "x": 0.887328028678894, "y": 0.41742276679724455 } ], "category": "paragraph", "id": 418, "content": { "text": "66\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14263322949409485, "y": 0.5195884108543396 }, { "x": 0.9042892754077911, "y": 0.5195884108543396 }, { "x": 0.9042892754077911, "y": 0.5311852414160967 }, { "x": 0.14263322949409485, "y": 0.5311852414160967 } ], "category": "paragraph", "id": 419, "content": { "text": "Section 8.1: Factor Analysis Definitions\n75\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14263905584812164, "y": 0.48423340916633606 }, { "x": 0.5916781574487686, "y": 0.48423340916633606 }, { "x": 0.5916781574487686, "y": 0.4974118070676923 }, { "x": 0.14263905584812164, "y": 0.4974118070676923 } ], "category": "paragraph", "id": 420, "content": { "text": "Part VIII. Chapter Eight - Factor Analysis and Scale Reliability\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1427198201417923, "y": 0.5399619936943054 }, { "x": 0.9041497856378555, "y": 0.5399619936943054 }, { "x": 0.9041497856378555, "y": 0.5486017726361752 }, { "x": 0.1427198201417923, "y": 0.5486017726361752 } ], "category": "paragraph", "id": 421, "content": { "text": "Section 8.2: EFA versus CFA\n76\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14264552295207977, "y": 0.5593892335891724 }, { "x": 0.9040423482656479, "y": 0.5593892335891724 }, { "x": 0.9040423482656479, "y": 0.5707738734781742 }, { "x": 0.14264552295207977, "y": 0.5707738734781742 } ], "category": "paragraph", "id": 422, "content": { "text": "Section 8.3: EFA Steps with Factor Extraction\n78\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.142672598361969, "y": 0.5788449645042419 }, { "x": 0.9041184782981873, "y": 0.5788449645042419 }, { "x": 0.9041184782981873, "y": 0.590597060509026 }, { "x": 0.142672598361969, "y": 0.590597060509026 } ], "category": "paragraph", "id": 423, "content": { "text": "Section 8.4: EFA Determining the Number of Factors\n80\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14254158735275269, "y": 0.6581428647041321 }, { "x": 0.9043940305709839, "y": 0.6581428647041321 }, { "x": 0.9043940305709839, "y": 0.6697648894041777 }, { "x": 0.14254158735275269, "y": 0.6697648894041777 } ], "category": "paragraph", "id": 424, "content": { "text": "Section 8.8: Chapter Eight Self-Test\n89\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1426728069782257, "y": 0.5990957021713257 }, { "x": 0.35759323835372925, "y": 0.5990957021713257 }, { "x": 0.35759323835372925, "y": 0.6104514384642243 }, { "x": 0.1426728069782257, "y": 0.6104514384642243 } ], "category": "paragraph", "id": 425, "content": { "text": "Section 8.5: EFA Interpretation\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1426338404417038, "y": 0.6187990307807922 }, { "x": 0.3224552422761917, "y": 0.6187990307807922 }, { "x": 0.3224552422761917, "y": 0.630053929053247 }, { "x": 0.1426338404417038, "y": 0.630053929053247 } ], "category": "paragraph", "id": 426, "content": { "text": "Section 8.6: EFA Write Up\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.142593115568161, "y": 0.6384069323539734 }, { "x": 0.33579160273075104, "y": 0.6384069323539734 }, { "x": 0.33579160273075104, "y": 0.6494699316099286 }, { "x": 0.142593115568161, "y": 0.6494699316099286 } ], "category": "paragraph", "id": 427, "content": { "text": "Section 8.7: Scale Reliability\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8880706429481506, "y": 0.5992273688316345 }, { "x": 0.9045333284884691, "y": 0.5992273688316345 }, { "x": 0.9045333284884691, "y": 0.607953455299139 }, { "x": 0.8880706429481506, "y": 0.607953455299139 } ], "category": "paragraph", "id": 428, "content": { "text": "84\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14261578023433685, "y": 0.7297899127006531 }, { "x": 0.9043699949979782, "y": 0.7297899127006531 }, { "x": 0.9043699949979782, "y": 0.7413270268589258 }, { "x": 0.14261578023433685, "y": 0.7413270268589258 } ], "category": "paragraph", "id": 429, "content": { "text": "Section 9.1: Nonparametric Definitions\n91\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8876415491104126, "y": 0.6189578771591187 }, { "x": 0.904192790389061, "y": 0.6189578771591187 }, { "x": 0.904192790389061, "y": 0.6276579713448882 }, { "x": 0.8876415491104126, "y": 0.6276579713448882 } ], "category": "paragraph", "id": 430, "content": { "text": "86\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1426904797554016, "y": 0.7498151659965515 }, { "x": 0.9039512276649475, "y": 0.7498151659965515 }, { "x": 0.9039512276649475, "y": 0.7614974221214652 }, { "x": 0.1426904797554016, "y": 0.7614974221214652 } ], "category": "paragraph", "id": 431, "content": { "text": "Section 9.2: Choosing Appropriate Tests\n93\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14244164526462555, "y": 0.69465571641922 }, { "x": 0.4948666840791702, "y": 0.69465571641922 }, { "x": 0.4948666840791702, "y": 0.7073713522404432 }, { "x": 0.14244164526462555, "y": 0.7073713522404432 } ], "category": "heading1", "id": 432, "content": { "text": "Part IX. Chapter Nine - Nonparametric Statistics\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.889356791973114, "y": 0.638574481010437 }, { "x": 0.9047971880063415, "y": 0.638574481010437 }, { "x": 0.9047971880063415, "y": 0.6473253816366196 }, { "x": 0.889356791973114, "y": 0.6473253816366196 } ], "category": "paragraph", "id": 433, "content": { "text": "87\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14265039563179016, "y": 0.7694445848464966 }, { "x": 0.7161884605884552, "y": 0.7694445848464966 }, { "x": 0.7161884605884552, "y": 0.781140617094934 }, { "x": 0.14265039563179016, "y": 0.781140617094934 } ], "category": "paragraph", "id": 434, "content": { "text": "Section 9.3: Comparing Two Independent Conditions: The Mann- Whitney U Test\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14266984164714813, "y": 0.8090230226516724 }, { "x": 0.7539394348859787, "y": 0.8090230226516724 }, { "x": 0.7539394348859787, "y": 0.8207090711221099 }, { "x": 0.14266984164714813, "y": 0.8207090711221099 } ], "category": "paragraph", "id": 435, "content": { "text": "Section 9.5: Differences Between Several Independent Groups: The Kruskal-Wallis Test\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8874657154083252, "y": 0.8094194531440735 }, { "x": 0.9041270203888416, "y": 0.8094194531440735 }, { "x": 0.9041270203888416, "y": 0.8181131659075618 }, { "x": 0.8874657154083252, "y": 0.8181131659075618 } ], "category": "paragraph", "id": 436, "content": { "text": "98\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14261002838611603, "y": 0.828697144985199 }, { "x": 0.9039597064256668, "y": 0.828697144985199 }, { "x": 0.9039597064256668, "y": 0.8402524469420314 }, { "x": 0.14261002838611603, "y": 0.8402524469420314 } ], "category": "paragraph", "id": 437, "content": { "text": "Section 9.6: Chapter Nine Self-Test\n100\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1426151841878891, "y": 0.7890564799308777 }, { "x": 0.9044080823659897, "y": 0.7890564799308777 }, { "x": 0.9044080823659897, "y": 0.8007856234908104 }, { "x": 0.1426151841878891, "y": 0.8007856234908104 } ], "category": "paragraph", "id": 438, "content": { "text": "Section 9.4: Comparing Two Dependent Conditions or Paired Samples - Wilcoxon Sign-Rank Test\n96\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8877589702606201, "y": 0.769832968711853 }, { "x": 0.9042652808129787, "y": 0.769832968711853 }, { "x": 0.9042652808129787, "y": 0.7782218130305409 }, { "x": 0.8877589702606201, "y": 0.7782218130305409 } ], "category": "paragraph", "id": 439, "content": { "text": "94\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1426958590745926, "y": 0.8613183498382568 }, { "x": 0.21999891102313995, "y": 0.8613183498382568 }, { "x": 0.21999891102313995, "y": 0.8704566583037376 }, { "x": 0.1426958590745926, "y": 0.8704566583037376 } ], "category": "footer", "id": 440, "content": { "text": "References\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.883800745010376, "y": 0.861631453037262 }, { "x": 0.9043586682528257, "y": 0.861631453037262 }, { "x": 0.9043586682528257, "y": 0.8701174473389983 }, { "x": 0.883800745010376, "y": 0.8701174473389983 } ], "category": "paragraph", "id": 441, "content": { "text": "101\n", "html": "", "markdown": "" } } ] }, "01030000000070.pdf": { "elements": [ { "coordinates": [ { "x": 0.1317417323589325, "y": 0.08753146976232529 }, { "x": 0.8784889876842499, "y": 0.08753146976232529 }, { "x": 0.8784889876842499, "y": 0.11812824197113514 }, { "x": 0.1317417323589325, "y": 0.11812824197113514 } ], "category": "paragraph", "id": 204, "content": { "text": "two meetings are related to the initial meeting of VNR and as particular human rights\nfocus. 73\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15945468842983246, "y": 0.14277346432209015 }, { "x": 0.8400568217039108, "y": 0.14277346432209015 }, { "x": 0.8400568217039108, "y": 0.4348897486925125 }, { "x": 0.15945468842983246, "y": 0.4348897486925125 } ], "category": "figure", "id": 205, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.2370947003364563, "y": 0.46207502484321594 }, { "x": 0.735348105430603, "y": 0.46207502484321594 }, { "x": 0.735348105430603, "y": 0.4876614548265934 }, { "x": 0.2370947003364563, "y": 0.4876614548265934 } ], "category": "paragraph", "id": 206, "content": { "text": "Participation of Institutions in the VNR Meeting of\nDiagram 2\nIndonesia 2021. 74\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.13226841390132904, "y": 0.5150870680809021 }, { "x": 0.8664384335279465, "y": 0.5150870680809021 }, { "x": 0.8664384335279465, "y": 0.5293054040521383 }, { "x": 0.13226841390132904, "y": 0.5293054040521383 } ], "category": "paragraph", "id": 207, "content": { "text": "The distribution of participating institutions in VNR-related meetings are as follows:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.160430446267128, "y": 0.541755735874176 }, { "x": 0.8415209800004959, "y": 0.541755735874176 }, { "x": 0.8415209800004959, "y": 0.7951323390007019 }, { "x": 0.160430446267128, "y": 0.7951323390007019 } ], "category": "figure", "id": 208, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.20249854028224945, "y": 0.8234497904777527 }, { "x": 0.7117714136838913, "y": 0.8234497904777527 }, { "x": 0.7117714136838913, "y": 0.8514073826372623 }, { "x": 0.20249854028224945, "y": 0.8514073826372623 } ], "category": "paragraph", "id": 209, "content": { "text": "Distribution of Participating Institutions within VNR\nDiagram 3\nMeeting of Indonesia 2021. 75\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12024933844804764, "y": 0.8752182722091675 }, { "x": 0.877874918282032, "y": 0.8752182722091675 }, { "x": 0.877874918282032, "y": 0.9147629402577877 }, { "x": 0.12024933844804764, "y": 0.9147629402577877 } ], "category": "paragraph", "id": 210, "content": { "text": "74 Data is processed based on: ibid., 332-345.\n75 Data is processed based on: Kementerian PPN / Bappenas, \"Annexes Indonesia's VNR 2021\" (n.\n68), 332-345.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.49079543352127075, "y": 0.9320160150527954 }, { "x": 0.5092393234372139, "y": 0.9320160150527954 }, { "x": 0.5092393234372139, "y": 0.9414199031889439 }, { "x": 0.49079543352127075, "y": 0.9414199031889439 } ], "category": "paragraph", "id": 211, "content": { "text": "14\n", "html": "", "markdown": "" } } ] }, "01030000000152.pdf": { "elements": [ { "coordinates": [ { "x": 0.44136181473731995, "y": 0.6620241403579712 }, { "x": 0.6083169877529144, "y": 0.6620241403579712 }, { "x": 0.6083169877529144, "y": 0.7663858905434608 }, { "x": 0.44136181473731995, "y": 0.7663858905434608 } ], "category": "table", "id": 365, "content": { "text": "", "html": "
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", "markdown": "" } }, { "coordinates": [ { "x": 0.09216172993183136, "y": 0.07273254543542862 }, { "x": 0.9072236567735672, "y": 0.07273254543542862 }, { "x": 0.9072236567735672, "y": 0.10764741152524948 }, { "x": 0.09216172993183136, "y": 0.10764741152524948 } ], "category": "paragraph", "id": 384, "content": { "text": "should adopt two separate designators to mark no-cost VS. low-cost, but the council felt it was better\nto simplify the process and allow for some OER providers that have fees associated with their services.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0914299488067627, "y": 0.12572915852069855 }, { "x": 0.90679931640625, "y": 0.12572915852069855 }, { "x": 0.90679931640625, "y": 0.19899454712867737 }, { "x": 0.0914299488067627, "y": 0.19899454712867737 } ], "category": "paragraph", "id": 385, "content": { "text": "At this point in time, the application of the #NOLO designator was a manual process. It required the\naddition of the designator to the section title prior to registration and then its removal after add/drop\nto ensure the label didn't appear on the student transcript. This process severely hampered our long-\nterm reporting abilities. In total, four colleges adopted the #NOLO designator in this fashion.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09171534329652786, "y": 0.21707488596439362 }, { "x": 0.9078852608799934, "y": 0.21707488596439362 }, { "x": 0.9078852608799934, "y": 0.31027789413928986 }, { "x": 0.09171534329652786, "y": 0.31027789413928986 } ], "category": "paragraph", "id": 386, "content": { "text": "To assist in greater faculty and institutional adoption as well as improve data capture, the CSCU OER\nAdvisory Council made a formal recommendation to the provost's academic council in Spring 2018\nto implement the #NOLO designator as a course section attribute within the student information\nsystem. In addition to adding a course section attribute, a student-facing course search filter was\nadded as well as an additional column within the course search results page.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3711603581905365, "y": 0.3413635790348053 }, { "x": 0.4915933459997177, "y": 0.3413635790348053 }, { "x": 0.4915933459997177, "y": 0.3501075888052583 }, { "x": 0.3711603581905365, "y": 0.3501075888052583 } ], "category": "heading1", "id": 387, "content": { "text": "Your materials for:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3721334636211395, "y": 0.3592032790184021 }, { "x": 0.5419378727674484, "y": 0.3592032790184021 }, { "x": 0.5419378727674484, "y": 0.36817216593772173 }, { "x": 0.3721334636211395, "y": 0.36817216593772173 } ], "category": "paragraph", "id": 388, "content": { "text": "LIB 100 - Lib & Resch Methods\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3807534873485565, "y": 0.3911760747432709 }, { "x": 0.3988878484815359, "y": 0.3911760747432709 }, { "x": 0.3988878484815359, "y": 0.40585534647107124 }, { "x": 0.3807534873485565, "y": 0.40585534647107124 } ], "category": "figure", "id": 389, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.4047898054122925, "y": 0.3942391574382782 }, { "x": 0.5407896190881729, "y": 0.3942391574382782 }, { "x": 0.5407896190881729, "y": 0.40487580746412277 }, { "x": 0.4047898054122925, "y": 0.40487580746412277 } ], "category": "paragraph", "id": 390, "content": { "text": "Adoptions not Required\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.38399168848991394, "y": 0.4175252318382263 }, { "x": 0.397592443972826, "y": 0.4175252318382263 }, { "x": 0.397592443972826, "y": 0.4295353265479207 }, { "x": 0.38399168848991394, "y": 0.4295353265479207 } ], "category": "figure", "id": 391, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.40195274353027344, "y": 0.4189952611923218 }, { "x": 0.5692531615495682, "y": 0.4189952611923218 }, { "x": 0.5692531615495682, "y": 0.42719802260398865 }, { "x": 0.40195274353027344, "y": 0.42719802260398865 } ], "category": "paragraph", "id": 392, "content": { "text": "This course does not use books\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.38291221857070923, "y": 0.4342011511325836 }, { "x": 0.3991035670042038, "y": 0.4342011511325836 }, { "x": 0.3991035670042038, "y": 0.44621191546320915 }, { "x": 0.38291221857070923, "y": 0.44621191546320915 } ], "category": "figure", "id": 393, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.4024340808391571, "y": 0.4359193742275238 }, { "x": 0.5917926579713821, "y": 0.4359193742275238 }, { "x": 0.5917926579713821, "y": 0.4454459398984909 }, { "x": 0.4024340808391571, "y": 0.4454459398984909 } ], "category": "paragraph", "id": 394, "content": { "text": "Course uses OER/Zero cost course\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3831280767917633, "y": 0.4505437910556793 }, { "x": 0.3978082137182355, "y": 0.4505437910556793 }, { "x": 0.3978082137182355, "y": 0.4638883238658309 }, { "x": 0.3831280767917633, "y": 0.4638883238658309 } ], "category": "figure", "id": 395, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.40239080786705017, "y": 0.4531375765800476 }, { "x": 0.5681656450033188, "y": 0.4531375765800476 }, { "x": 0.5681656450033188, "y": 0.4614341985434294 }, { "x": 0.40239080786705017, "y": 0.4614341985434294 } ], "category": "paragraph", "id": 396, "content": { "text": "Other non-bookstore materials\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.4671564996242523, "y": 0.48769500851631165 }, { "x": 0.523659024387598, "y": 0.48769500851631165 }, { "x": 0.523659024387598, "y": 0.4970177374780178 }, { "x": 0.4671564996242523, "y": 0.4970177374780178 } ], "category": "paragraph", "id": 397, "content": { "text": "Continue\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3396495580673218, "y": 0.5476816892623901 }, { "x": 0.6494232416152954, "y": 0.5476816892623901 }, { "x": 0.6494232416152954, "y": 0.5587171977385879 }, { "x": 0.3396495580673218, "y": 0.5587171977385879 } ], "category": "paragraph", "id": 398, "content": { "text": "Figure 2.1: Filtered Search Option for NOLO Sections.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3580857217311859, "y": 0.5872789025306702 }, { "x": 0.634649008512497, "y": 0.5872789025306702 }, { "x": 0.634649008512497, "y": 0.7984873652458191 }, { "x": 0.3580857217311859, "y": 0.7984873652458191 } ], "category": "figure", "id": 399, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.34528303146362305, "y": 0.8217079043388367 }, { "x": 0.615527331829071, "y": 0.8217079043388367 }, { "x": 0.615527331829071, "y": 0.8485416267067194 }, { "x": 0.34528303146362305, "y": 0.8485416267067194 } ], "category": "paragraph", "id": 400, "content": { "text": "Figure 2.2: Added Column in Results for NOLO\nDesignator.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09164907038211823, "y": 0.8632962107658386 }, { "x": 0.9078689962625504, "y": 0.8632962107658386 }, { "x": 0.9078689962625504, "y": 0.9372145757079124 }, { "x": 0.09164907038211823, "y": 0.9372145757079124 } ], "category": "paragraph", "id": 401, "content": { "text": "The request to implement the designator within the student information system was supported in\nFall 2018 by the president's cabinet. The ability to mark courses was enabled late Fall 2018 and the\nstudent-facing features were enabled in January 2019. Each institutional representative on the OER\ncouncil engaged with their local governance structures to request a vote for adoption.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09185444563627243, "y": 0.9509012699127197 }, { "x": 0.8988788649439812, "y": 0.9509012699127197 }, { "x": 0.8988788649439812, "y": 0.9600072940811515 }, { "x": 0.09185444563627243, "y": 0.9600072940811515 } ], "category": "footer", "id": 402, "content": { "text": "4 BOYOUNG CHAE, KEVIN CORCORAN, MICHAEL DALY, ANN FIDDLER, JEFF GALLANT, JAMES GLAPA-GROSSKLAG, AMY HOFER, AND\n", "html": "", "markdown": "" } } ] }, "01030000000118.pdf": { "elements": [ { "coordinates": [ { "x": 0.13005131483078003, "y": 0.05146936699748039 }, { "x": 0.4050121009349823, "y": 0.05146936699748039 }, { "x": 0.4050121009349823, "y": 0.06540779583156109 }, { "x": 0.13005131483078003, "y": 0.06540779583156109 } ], "category": "header", "id": 238, "content": { "text": "MOHAVE COMMUNITY COLLEGE\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8116961717605591, "y": 0.05314018577337265 }, { "x": 0.8815009221434593, "y": 0.05314018577337265 }, { "x": 0.8815009221434593, "y": 0.06586925871670246 }, { "x": 0.8116961717605591, "y": 0.06586925871670246 } ], "category": "header", "id": 239, "content": { "text": "BIO181\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3996500074863434, "y": 0.09631022810935974 }, { "x": 0.5998775362968445, "y": 0.09631022810935974 }, { "x": 0.5998775362968445, "y": 0.1137285903096199 }, { "x": 0.3996500074863434, "y": 0.1137285903096199 } ], "category": "heading1", "id": 240, "content": { "text": "Cellular Replication\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0735732913017273, "y": 0.13429518043994904 }, { "x": 0.7159571647644043, "y": 0.13429518043994904 }, { "x": 0.7159571647644043, "y": 0.4295942336320877 }, { "x": 0.0735732913017273, "y": 0.4295942336320877 } ], "category": "figure", "id": 241, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.7702268958091736, "y": 0.1364944577217102 }, { "x": 0.9042234867811203, "y": 0.1364944577217102 }, { "x": 0.9042234867811203, "y": 0.24169009178876877 }, { "x": 0.7702268958091736, "y": 0.24169009178876877 } ], "category": "figure", "id": 242, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.7545488476753235, "y": 0.3099633455276489 }, { "x": 0.8972429633140564, "y": 0.3099633455276489 }, { "x": 0.8972429633140564, "y": 0.338984452188015 }, { "x": 0.7545488476753235, "y": 0.338984452188015 } ], "category": "paragraph", "id": 243, "content": { "text": "Cellular Cycle\nand Replication\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.7725251913070679, "y": 0.3772445023059845 }, { "x": 0.9034975916147232, "y": 0.3772445023059845 }, { "x": 0.9034975916147232, "y": 0.4791090041399002 }, { "x": 0.7725251913070679, "y": 0.4791090041399002 } ], "category": "figure", "id": 244, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11776123940944672, "y": 0.46437233686447144 }, { "x": 0.4940410703420639, "y": 0.46437233686447144 }, { "x": 0.4940410703420639, "y": 0.47994955629110336 }, { "x": 0.11776123940944672, "y": 0.47994955629110336 } ], "category": "heading1", "id": 245, "content": { "text": "Growth and the Creation of Life\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12850864231586456, "y": 0.5001241564750671 }, { "x": 0.6470219641923904, "y": 0.5001241564750671 }, { "x": 0.6470219641923904, "y": 0.9024694561958313 }, { "x": 0.12850864231586456, "y": 0.9024694561958313 } ], "category": "paragraph", "id": 246, "content": { "text": "One of the characteristics of living things is the ability\nto replicate and passon genetic information to the next\ngeneration. Cell division in individual bacteria and\narchaea usually occurs by binary fission. Mitochondria\nand chloroplasts also replicate by binary fission, which\nis evidence of the evolutionary relationship between\nthese organelles and prokaryotes.\nCell division in eukaryotes is more complex. It requires\nthe cell to manage acomplicated process of duplicating\nthe nucleus, other organelles, and multiple linear\nchromosomes. It is controlled in the cell cycle, which is\ndivided into three parts: interphase, mitosis, and\ncytokinesis. We spilt those further for ease of study.\nLet's start with interphase, which is broken into three\nstages. In the first growth phase (G1), the cell grows and\nprepares to duplicate its DNA. In the synthesis phase\n(S), the chromosomes are replicated. In the second\ngrowth phase (G2), the cell prepares to divide.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.7543967962265015, "y": 0.517972469329834 }, { "x": 0.9085738807916641, "y": 0.517972469329834 }, { "x": 0.9085738807916641, "y": 0.5899500995874405 }, { "x": 0.7543967962265015, "y": 0.5899500995874405 } ], "category": "paragraph", "id": 247, "content": { "text": "A step by step\nguide to growing a\nhuman!\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.773094117641449, "y": 0.6158320903778076 }, { "x": 0.9027729630470276, "y": 0.6158320903778076 }, { "x": 0.9027729630470276, "y": 0.7187043651938438 }, { "x": 0.773094117641449, "y": 0.7187043651938438 } ], "category": "figure", "id": 248, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.754012405872345, "y": 0.7298310995101929 }, { "x": 0.9070574045181274, "y": 0.7298310995101929 }, { "x": 0.9070574045181274, "y": 0.8225317150354385 }, { "x": 0.754012405872345, "y": 0.8225317150354385 } ], "category": "paragraph", "id": 249, "content": { "text": "Mitosis and\nMeiosis\nSimiliar processes\nwith VERY different\nresults!\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.496244341135025, "y": 0.9734921455383301 }, { "x": 0.5108680091798306, "y": 0.9734921455383301 }, { "x": 0.5108680091798306, "y": 0.9847789900377393 }, { "x": 0.496244341135025, "y": 0.9847789900377393 } ], "category": "paragraph", "id": 250, "content": { "text": "66\n", "html": "", "markdown": "" } } ] }, "01030000000104.pdf": { "elements": [ { "coordinates": [ { "x": 0.12208756804466248, "y": 0.10461793839931488 }, { "x": 0.8799856603145599, "y": 0.10461793839931488 }, { "x": 0.8799856603145599, "y": 0.35388346016407013 }, { "x": 0.12208756804466248, "y": 0.35388346016407013 } ], "category": "figure", "id": 159, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08690181374549866, "y": 0.4555874168872833 }, { "x": 0.7331560552120209, "y": 0.4555874168872833 }, { "x": 0.7331560552120209, "y": 0.4711865736171603 }, { "x": 0.08690181374549866, "y": 0.4711865736171603 } ], "category": "paragraph", "id": 160, "content": { "text": "An overview of each actor's role in this ecosystem is described below.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09028506278991699, "y": 0.5265495181083679 }, { "x": 0.24138978123664856, "y": 0.5265495181083679 }, { "x": 0.24138978123664856, "y": 0.5446832962334156 }, { "x": 0.09028506278991699, "y": 0.5446832962334156 } ], "category": "heading1", "id": 161, "content": { "text": "Publishers\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08736056834459305, "y": 0.586727499961853 }, { "x": 0.911535806953907, "y": 0.586727499961853 }, { "x": 0.911535806953907, "y": 0.7112535834312439 }, { "x": 0.08736056834459305, "y": 0.7112535834312439 } ], "category": "paragraph", "id": 162, "content": { "text": "Publishers work to \"make public\" scholarly work in the form of textbooks, journals, and\nmonographs, and represent a wide range of publishing approaches, business models,\nbudgets, and institutional affiliations. With our focus on monographs, the two most\nsignificant groups are large commercial publishers and university presses. These publish\nthe vast majority of monographs in circulation, although in recent years, smaller open\naccess publishers have also begun to emerge.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08695917576551437, "y": 0.7320979833602905 }, { "x": 0.5841099545359612, "y": 0.7320979833602905 }, { "x": 0.5841099545359612, "y": 0.7477296274155378 }, { "x": 0.08695917576551437, "y": 0.7477296274155378 } ], "category": "paragraph", "id": 163, "content": { "text": "The role of publishers includes (among other things):\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10763230919837952, "y": 0.7747458219528198 }, { "x": 0.3940769135951996, "y": 0.7747458219528198 }, { "x": 0.3940769135951996, "y": 0.7894931444898248 }, { "x": 0.10763230919837952, "y": 0.7894931444898248 } ], "category": "paragraph", "id": 165, "content": { "text": "acquisitions and list curation\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10765736550092697, "y": 0.7964765429496765 }, { "x": 0.5362977012991905, "y": 0.7964765429496765 }, { "x": 0.5362977012991905, "y": 0.8119210628792644 }, { "x": 0.10765736550092697, "y": 0.8119210628792644 } ], "category": "paragraph", "id": 166, "content": { "text": "editorial work and coordinating peer review\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10719641298055649, "y": 0.8180075287818909 }, { "x": 0.8928922638297081, "y": 0.8180075287818909 }, { "x": 0.8928922638297081, "y": 0.8337892293930054 }, { "x": 0.10719641298055649, "y": 0.8337892293930054 } ], "category": "paragraph", "id": 167, "content": { "text": "design and production (for various formats, typically: print, digital PDF, and EPUB)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10749147087335587, "y": 0.8398801684379578 }, { "x": 0.8677375689148903, "y": 0.8398801684379578 }, { "x": 0.8677375689148903, "y": 0.8771086856722832 }, { "x": 0.10749147087335587, "y": 0.8771086856722832 } ], "category": "paragraph", "id": 168, "content": { "text": "distribution and marketing of finished products into various channels (libraries,\naggregators, stores) where readers can access books\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08768772333860397, "y": 0.9377602934837341 }, { "x": 0.0957854837179184, "y": 0.9377602934837341 }, { "x": 0.0957854837179184, "y": 0.9458172991871834 }, { "x": 0.08768772333860397, "y": 0.9458172991871834 } ], "category": "paragraph", "id": 169, "content": { "text": "6\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10322969406843185, "y": 0.9372755885124207 }, { "x": 0.3478568568825722, "y": 0.9372755885124207 }, { "x": 0.3478568568825722, "y": 0.948186719790101 }, { "x": 0.10322969406843185, "y": 0.948186719790101 } ], "category": "footer", "id": 170, "content": { "text": "I The Scholarly Publishing Ecosystem\n", "html": "", "markdown": "" } } ] }, "01030000000007.pdf": { "elements": [ { "coordinates": [ { "x": 0.44286444783210754, "y": 0.1499014049768448 }, { "x": 0.5852426588535309, "y": 0.1499014049768448 }, { "x": 0.5852426588535309, "y": 0.15968066360801458 }, { "x": 0.44286444783210754, "y": 0.15968066360801458 } ], "category": "header", "id": 387, "content": { "text": "CHAPTER 2\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3993232846260071, "y": 0.20555777847766876 }, { "x": 0.6254162490367889, "y": 0.20555777847766876 }, { "x": 0.6254162490367889, "y": 0.22754798643290997 }, { "x": 0.3993232846260071, "y": 0.22754798643290997 } ], "category": "heading1", "id": 388, "content": { "text": "Narratives in Chuj\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14869381487369537, "y": 0.2912306785583496 }, { "x": 0.8781206160783768, "y": 0.2912306785583496 }, { "x": 0.8781206160783768, "y": 0.45519761741161346 }, { "x": 0.14869381487369537, "y": 0.45519761741161346 } ], "category": "paragraph", "id": 389, "content": { "text": "T\nHIS COLLECTION OF SIX narratives told in Chuj demonstrates the\nbroad variety of stories people tell one another and the variety of sources\nof those stories: personal narratives, legendary events, mythological\ntales, and stories borrowed from other cultures. All were recorded by me during\nfield work on Chuj from 1964 to 1965. (See the Archive of the Indigenous Lan-\nguages of Latin America, www.ailla.utexas.org, for these and other samples of\nChuj speech recorded during field work; AILLA reference codes for each text\nare given below and at the head of each transcription.)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.37557870149612427, "y": 0.4872702360153198 }, { "x": 0.6510082185268402, "y": 0.4872702360153198 }, { "x": 0.6510082185268402, "y": 0.5021223267540336 }, { "x": 0.37557870149612427, "y": 0.5021223267540336 } ], "category": "heading1", "id": 390, "content": { "text": "Introduction to the Texts\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15175595879554749, "y": 0.520527720451355 }, { "x": 0.874506026506424, "y": 0.520527720451355 }, { "x": 0.874506026506424, "y": 0.6639223098754883 }, { "x": 0.15175595879554749, "y": 0.6639223098754883 } ], "category": "paragraph", "id": 391, "content": { "text": "Two of the stories are ultimately of foreign origin, but their origins are not the\nsame. In one case, the story known to the narrator as An Old Man Whose Son\nKilled Him [CAC 002 R022], the story clearly comes from the European tra-\ndition, and must have been introduced to the Chuj by schoolteachers. It is the\nclassic Greek tale of a couple whose child is destined to kill his father and how\nthat came about, including the solution to a famous riddle: What animal walks\non four legs at dawn, on two legs at noon, and on three legs in the evening?\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1513914167881012, "y": 0.6663059592247009 }, { "x": 0.8770457208156586, "y": 0.6663059592247009 }, { "x": 0.8770457208156586, "y": 0.8504086881875992 }, { "x": 0.1513914167881012, "y": 0.8504086881875992 } ], "category": "paragraph", "id": 392, "content": { "text": "The other tale, Coyote and Rabbit [CAC 002 R027], is probably ultimately\nof African origin, although some of its episodes are traditional in the American\nSouth and may have been introduced secondhand to the Chuj. This is the series\nof incidents that make up the Br'er Rabbit stories, stories that reflected earlier\nAfrican tales involving Hyena instead of Fox (Diarassouba 2007). Here the story\nfeatures Coyote instead of either Fox or Hyena. Coyote stories and stories of\nRabbit Trickster abound in the native New World, and some of the episodes may\nbe of American origin, adapted to the framework of the African stories. Some ep-\nisodes have a local flavor (such as misty mountains) and are likely of local origin.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15298853814601898, "y": 0.8534417748451233 }, { "x": 0.8749045580625534, "y": 0.8534417748451233 }, { "x": 0.8749045580625534, "y": 0.8924188613891602 }, { "x": 0.15298853814601898, "y": 0.8924188613891602 } ], "category": "paragraph", "id": 393, "content": { "text": "A third story, Friend of the Animals [CAC 002 Ro20], expresses such a\nuniversal theme that it could possibly be of foreign origin as well, but it has\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.504201352596283, "y": 0.9228633642196655 }, { "x": 0.5223113428801298, "y": 0.9228633642196655 }, { "x": 0.5223113428801298, "y": 0.9298441102728248 }, { "x": 0.504201352596283, "y": 0.9298441102728248 } ], "category": "paragraph", "id": 394, "content": { "text": "22\n", "html": "", "markdown": "" } } ] }, "01030000000010.pdf": { "elements": [ { "coordinates": [ { "x": 0.10296064615249634, "y": 0.049961112439632416 }, { "x": 0.48360663652420044, "y": 0.049961112439632416 }, { "x": 0.48360663652420044, "y": 0.05959388893097639 }, { "x": 0.10296064615249634, "y": 0.05959388893097639 } ], "category": "header", "id": 333, "content": { "text": "CIRCULATING THINGS, CIRCULATING STEREOTYPES\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8789748549461365, "y": 0.049670103937387466 }, { "x": 0.8955904766917229, "y": 0.049670103937387466 }, { "x": 0.8955904766917229, "y": 0.05823488812893629 }, { "x": 0.8789748549461365, "y": 0.05823488812893629 } ], "category": "paragraph", "id": 334, "content": { "text": "83\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11361488699913025, "y": 0.08385790884494781 }, { "x": 0.8862254321575165, "y": 0.08385790884494781 }, { "x": 0.8862254321575165, "y": 0.49429942667484283 }, { "x": 0.11361488699913025, "y": 0.49429942667484283 } ], "category": "figure", "id": 335, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10320954024791718, "y": 0.5059400796890259 }, { "x": 0.8791310042142868, "y": 0.5059400796890259 }, { "x": 0.8791310042142868, "y": 0.547172449529171 }, { "x": 0.10320954024791718, "y": 0.547172449529171 } ], "category": "paragraph", "id": 336, "content": { "text": "FIGURE 4.10\nJames Gillray, High Change in Bond Street; ou la politesse du grande monde [graphic]. Etching on wove paper,\nhand-colored.\nPUBLISHED BYH. HUMPHREY, LONDON, 1796\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1023113876581192, "y": 0.5943592190742493 }, { "x": 0.4874325841665268, "y": 0.5943592190742493 }, { "x": 0.4874325841665268, "y": 0.9022692739963531 }, { "x": 0.1023113876581192, "y": 0.9022692739963531 } ], "category": "paragraph", "id": 337, "content": { "text": "meant to bewilder the viewer. Satins, silks, ivory,\ngigantic eggs, and \"artificial\" apples describe, in\nfact, the things of the trade: expensive and rare\nfabrics, on the one hand, strange collectibles and\nexotica, on the other. Lavish dresses and embel-\nlishments become insignia of wealth, power, and\nnonconformity, of a way of life outside the eco-\nnomic constraints of the Western civilization. In-\nterestingly, such projections were internalized by\neighteenth-century British subjects in the fashion-\nable \"Turquerie\" that allowed the wearers to dis-\nplay their wealth by wearing Oriental dress, tur-\nbans, ostrich plumes, long capes, veils, and flattering\nshalvars (figs. 4.9 and 4.10). Another infusion of Ori-\nentalism in the West, the tradition of painting Euro-\npean figures in Middle Eastern dress, becomes a\nform of cultural cross-dressing meant to suggest\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5120376348495483, "y": 0.5943508148193359 }, { "x": 0.8970489799976349, "y": 0.5943508148193359 }, { "x": 0.8970489799976349, "y": 0.7192414477467537 }, { "x": 0.5120376348495483, "y": 0.7192414477467537 } ], "category": "paragraph", "id": 338, "content": { "text": "misuse of power or excessive wealth (fig. 4.11).\nSuch cultural imports are difficult to be under-\nstood, to use Said's qualification, as expressions of\nthe Occident's cultural \"antipathy\"84 toward the\nOrient; rather, they reflect the West's attraction to a\nspace that connotes difference understood as ex-\ntraordinariness rather than inferiority.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.512022078037262, "y": 0.7225225567817688 }, { "x": 0.8957737684249878, "y": 0.7225225567817688 }, { "x": 0.8957737684249878, "y": 0.8103523999452591 }, { "x": 0.512022078037262, "y": 0.8103523999452591 } ], "category": "paragraph", "id": 339, "content": { "text": "Besides their connotations of magic, exoticism,\nand wealth, the things in the Arabian Nights are also\nrich bearers of cultural information: as Marina War-\nner correctly pointed out, \"stories are lodged in\ngoods \"85 and as such, they expand the reader's\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5122944116592407, "y": 0.8403207659721375 }, { "x": 0.8959185481071472, "y": 0.8403207659721375 }, { "x": 0.8959185481071472, "y": 0.9017715156078339 }, { "x": 0.5122944116592407, "y": 0.9017715156078339 } ], "category": "paragraph", "id": 340, "content": { "text": "84\nSaid, Orientalism, 260.\n85\nMarina Warner, introduction to Stranger Magic:\nCharmed States and the Arabian Nights (London: Chat-\nto & Windus, 2011), 8.\n", "html": "", "markdown": "" } } ] }, "01030000000034.pdf": { "elements": [ { "coordinates": [ { "x": 0.14147712290287018, "y": 0.05577313154935837 }, { "x": 0.18453210964798927, "y": 0.05577313154935837 }, { "x": 0.18453210964798927, "y": 0.06695456616580486 }, { "x": 0.14147712290287018, "y": 0.06695456616580486 } ], "category": "header", "id": 325, "content": { "text": "xviii\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.7752115726470947, "y": 0.05536868795752525 }, { "x": 0.8608712926506996, "y": 0.05536868795752525 }, { "x": 0.8608712926506996, "y": 0.06999394576996565 }, { "x": 0.7752115726470947, "y": 0.06999394576996565 } ], "category": "header", "id": 326, "content": { "text": "Prologue\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14059044420719147, "y": 0.09033103287220001 }, { "x": 0.860344722867012, "y": 0.09033103287220001 }, { "x": 0.860344722867012, "y": 0.14676691219210625 }, { "x": 0.14059044420719147, "y": 0.14676691219210625 } ], "category": "paragraph", "id": 327, "content": { "text": "So let's get rid of the expression derivative d/dt and replace it\nwith an appropriate functional derivative. If f is a function then\nwe will write Df as the new function that is the derivative of f:5\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3533351421356201, "y": 0.18524348735809326 }, { "x": 0.39709697291255, "y": 0.18524348735809326 }, { "x": 0.39709697291255, "y": 0.20402285642921925 }, { "x": 0.3533351421356201, "y": 0.20402285642921925 } ], "category": "paragraph", "id": 328, "content": { "text": ".\nx=t\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14025424420833588, "y": 0.22079432010650635 }, { "x": 0.8607057183980942, "y": 0.22079432010650635 }, { "x": 0.8607057183980942, "y": 0.25339900329709053 }, { "x": 0.14025424420833588, "y": 0.25339900329709053 } ], "category": "paragraph", "id": 329, "content": { "text": "To do this for the Lagrange equation we need to construct a\nfunction to take the derivative of.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14033794403076172, "y": 0.26023632287979126 }, { "x": 0.8605883121490479, "y": 0.26023632287979126 }, { "x": 0.8605883121490479, "y": 0.31299830973148346 }, { "x": 0.14033794403076172, "y": 0.31299830973148346 } ], "category": "paragraph", "id": 330, "content": { "text": "Given a configuration-space path W, there is a standard way\nto make the state-space path. We can abstract this method as a\nmathematical function T:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14006610214710236, "y": 0.32679283618927 }, { "x": 0.4304851144552231, "y": 0.32679283618927 }, { "x": 0.4304851144552231, "y": 0.36502860486507416 }, { "x": 0.14006610214710236, "y": 0.36502860486507416 } ], "category": "paragraph", "id": 331, "content": { "text": "=\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1411159783601761, "y": 0.38040289282798767 }, { "x": 0.38062557578086853, "y": 0.38040289282798767 }, { "x": 0.38062557578086853, "y": 0.3961970005184412 }, { "x": 0.1411159783601761, "y": 0.3961970005184412 } ], "category": "paragraph", "id": 332, "content": { "text": "Using T we can write:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3525884747505188, "y": 0.4239575266838074 }, { "x": 0.5866816639900208, "y": 0.4239575266838074 }, { "x": 0.5866816639900208, "y": 0.43633547332137823 }, { "x": 0.3525884747505188, "y": 0.43633547332137823 } ], "category": "paragraph", "id": 333, "content": { "text": "- 0.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14057226479053497, "y": 0.463456392288208 }, { "x": 0.8596558123826981, "y": 0.463456392288208 }, { "x": 0.8596558123826981, "y": 0.5174868740141392 }, { "x": 0.14057226479053497, "y": 0.5174868740141392 } ], "category": "paragraph", "id": 334, "content": { "text": "If we now define composition of functions (fog)(x) = f(g(x)),\nwe can express the Lagrange equations entirely in terms of func-\ntions:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.34162792563438416, "y": 0.5464008450508118 }, { "x": 0.35860924422740936, "y": 0.5464008450508118 }, { "x": 0.35860924422740936, "y": 0.5490540345199406 }, { "x": 0.34162792563438416, "y": 0.5490540345199406 } ], "category": "paragraph", "id": 335, "content": { "text": "-\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14028042554855347, "y": 0.5750980973243713 }, { "x": 0.8613529801368713, "y": 0.5750980973243713 }, { "x": 0.8613529801368713, "y": 0.7716249525547028 }, { "x": 0.14028042554855347, "y": 0.7716249525547028 } ], "category": "paragraph", "id": 336, "content": { "text": "The functions OLL and O2L are partial derivatives of the func-\ntion L. Composition with T[w] evaluates these partials with coor-\ndinates and velocites appropriate for the path W, making functions\nof time. Applying D takes the time derivative. The Lagrange\nequation states that the difference of the resulting functions of\ntime must be zero. This statement of the Lagrange equation is\ncomplete, unambiguous, and functional. It is not encumbered\nwith the particular choices made in expressing the Lagrangian.\nFor example, it doesn't matter if the time is named t or T, and it\nhas an explicit place for the path to be tested.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1681513488292694, "y": 0.7756175994873047 }, { "x": 0.7574872672557831, "y": 0.7756175994873047 }, { "x": 0.7574872672557831, "y": 0.7914374582469463 }, { "x": 0.1681513488292694, "y": 0.7914374582469463 } ], "category": "paragraph", "id": 337, "content": { "text": "This expression is equivalent to a computer program:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14035183191299438, "y": 0.8190077543258667 }, { "x": 0.8601101040840149, "y": 0.8190077543258667 }, { "x": 0.8601101040840149, "y": 0.9056191965937614 }, { "x": 0.14035183191299438, "y": 0.9056191965937614 } ], "category": "footer", "id": 338, "content": { "text": "5 An explanation of functional derivatives is in Appendix B, page 202.\n6The programs in this book are written in Scheme, a dialect of Lisp. The\ndetails of the language are not germane to the points being made. What is\nimportant is that it is mechanically interpretable, and thus unambiguous. In\nthis book we require that the mathematical expressions be explicit enough\n", "html": "", "markdown": "" } } ] }, "01030000000142.pdf": { "elements": [ { "coordinates": [ { "x": 0.15056192874908447, "y": 0.08652842789888382 }, { "x": 0.15905113145709038, "y": 0.08652842789888382 }, { "x": 0.15905113145709038, "y": 0.09571926575154066 }, { "x": 0.15056192874908447, "y": 0.09571926575154066 } ], "category": "paragraph", "id": 553, "content": { "text": "2\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.4810281991958618, "y": 0.08599571883678436 }, { "x": 0.8611342906951904, "y": 0.08599571883678436 }, { "x": 0.8611342906951904, "y": 0.09885152988135815 }, { "x": 0.4810281991958618, "y": 0.09885152988135815 } ], "category": "header", "id": 554, "content": { "text": "Numerical Methods for Ordinary Differential Equations\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15058159828186035, "y": 0.12356007099151611 }, { "x": 0.8618362545967102, "y": 0.12356007099151611 }, { "x": 0.8618362545967102, "y": 0.1508535873144865 }, { "x": 0.15058159828186035, "y": 0.1508535873144865 } ], "category": "paragraph", "id": 555, "content": { "text": "also plays an important role in error analysis (investigating the difference between the numerical\napproximation and the solution).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1502966731786728, "y": 0.15814591944217682 }, { "x": 0.8614907711744308, "y": 0.15814591944217682 }, { "x": 0.8614907711744308, "y": 0.22789455950260162 }, { "x": 0.1502966731786728, "y": 0.22789455950260162 } ], "category": "paragraph", "id": 556, "content": { "text": "Calculating with only a finite subset of the rational numbers has many consequences. For exam-\nple: a computer cannot distinguish between two polynomials of sufficiently high degree. Conse-\nquently, methods based on the main theorem of algebra (i.e. that an nth degree polynomial\nhas\nexactly n complex zeros) cannot be trusted. Errors that follow from the use of finitely many digits\nare called rounding errors (Section 1.4).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15027815103530884, "y": 0.23518821597099304 }, { "x": 0.8618342280387878, "y": 0.23518821597099304 }, { "x": 0.8618342280387878, "y": 0.3191472515463829 }, { "x": 0.15027815103530884, "y": 0.3191472515463829 } ], "category": "paragraph", "id": 557, "content": { "text": "An important aspect of numerical mathematics is the emphasis on efficiency. Contrary to or-\ndinary mathematics, numerical mathematics considers an increase in efficiency, i.e. a decrease\nof the number of operations and/or amount of storage required, as an essential improvement.\nProgress in this aspect is of great practical importance and the end of this development has not\nbeen reached yet. Here, the creative mind will meet many challenges. On top of that, revolutions\nin computer architecture will overturn much conventional wisdom.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15127195417881012, "y": 0.34298622608184814 }, { "x": 0.529734805226326, "y": 0.34298622608184814 }, { "x": 0.529734805226326, "y": 0.36053026281297207 }, { "x": 0.15127195417881012, "y": 0.36053026281297207 } ], "category": "heading1", "id": 558, "content": { "text": "1.3 Why numerical mathematics?\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1505795270204544, "y": 0.37325161695480347 }, { "x": 0.8618088513612747, "y": 0.37325161695480347 }, { "x": 0.8618088513612747, "y": 0.4006435591727495 }, { "x": 0.1505795270204544, "y": 0.4006435591727495 } ], "category": "paragraph", "id": 559, "content": { "text": "A big advantage of numerical mathematics is that it can provide answers to problems that do not\nadmit closed-form solutions. Consider for example the integral\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15012605488300323, "y": 0.4594801068305969 }, { "x": 0.8616250902414322, "y": 0.4594801068305969 }, { "x": 0.8616250902414322, "y": 0.5441493466496468 }, { "x": 0.15012605488300323, "y": 0.5441493466496468 } ], "category": "paragraph", "id": 560, "content": { "text": "This is an expression for the arc length of one arc of the curve y(x) = sin X, which does not have\na solution in closed form. A numerical method, however, can approximate this integral in a very\nsimple way (Chapter 5). An additional advantage is that a numerical method only uses stan-\ndard function evaluations and the operations addition, subtraction, multiplication and division.\nBecause these are exactly the operations a computer can perform, numerical mathematics and\ncomputers form a perfect combination.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1504451036453247, "y": 0.5509850978851318 }, { "x": 0.8617131114006042, "y": 0.5509850978851318 }, { "x": 0.8617131114006042, "y": 0.6211723685264587 }, { "x": 0.1504451036453247, "y": 0.6211723685264587 } ], "category": "paragraph", "id": 561, "content": { "text": "An advantage of analytical methods is that the solution is given by a mathematical formula.\nFrom this, insight in the behavior and the properties of the solution can be gained. For numerical\napproximations, however, this is not the case. In that case, visualization tools may be used to gain\ninsight in the behavior of the solution. Using a numerical method to draw a graph of a function\nis usually a more useful tool than evaluating the solution at a large number of points.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15121306478977203, "y": 0.6454921960830688 }, { "x": 0.3863719701766968, "y": 0.6454921960830688 }, { "x": 0.3863719701766968, "y": 0.6624934654682875 }, { "x": 0.15121306478977203, "y": 0.6624934654682875 } ], "category": "heading1", "id": 562, "content": { "text": "1.4 Rounding errors\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1502625197172165, "y": 0.67531818151474 }, { "x": 0.862849697470665, "y": 0.67531818151474 }, { "x": 0.862849697470665, "y": 0.8220749348402023 }, { "x": 0.1502625197172165, "y": 0.8220749348402023 } ], "category": "paragraph", "id": 563, "content": { "text": "A computer uses a finite representation of the all numbers in R. These are stored in a computer\nin the form\n0.d1d2 . Be,\n(1.1)\nin which, by definition, d1 > 0 and Oa) Cylindrical vessel 3-way valve8 mm Q16 mm Q24 mm QOutlet valve Inlet pipe 15-degree angled tubes 60-degree angled tubesc)d) ", "markdown": "" } }, { "coordinates": [ { "x": 0.09130784869194031, "y": 0.07327524572610855 }, { "x": 0.9061006009578705, "y": 0.07327524572610855 }, { "x": 0.9061006009578705, "y": 0.41426796466112137 }, { "x": 0.09130784869194031, "y": 0.41426796466112137 } ], "category": "figure", "id": 248, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09219762682914734, "y": 0.4400390088558197 }, { "x": 0.8505813777446747, "y": 0.4400390088558197 }, { "x": 0.8505813777446747, "y": 0.4684943836182356 }, { "x": 0.09219762682914734, "y": 0.4684943836182356 } ], "category": "paragraph", "id": 249, "content": { "text": "Figure 8.1: a) P6238 CUSSONS free and forced vortex apparatus, b) push-in orifices, c) free vortex measuring caliper, d) force vortex\nmeasuring probes\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09223315864801407, "y": 0.4929500222206116 }, { "x": 0.19481207430362701, "y": 0.4929500222206116 }, { "x": 0.19481207430362701, "y": 0.5039628660306334 }, { "x": 0.09223315864801407, "y": 0.5039628660306334 } ], "category": "heading1", "id": 250, "content": { "text": "7. THEORY\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09177706390619278, "y": 0.522121787071228 }, { "x": 0.9065509811043739, "y": 0.522121787071228 }, { "x": 0.9065509811043739, "y": 0.578303225338459 }, { "x": 0.09177706390619278, "y": 0.578303225338459 } ], "category": "paragraph", "id": 251, "content": { "text": "Two types of vortices are distinguished in the dynamics of the motion: forced and free vortices. The\nforced vortex is caused by external forces on the fluid, such as the impeller of a pump, and the free\nvortex naturally occurs in the flow and can be observed in a drain or in the atmosphere of a tornado.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09229429811239243, "y": 0.5983477830886841 }, { "x": 0.2652151808142662, "y": 0.5983477830886841 }, { "x": 0.2652151808142662, "y": 0.6094199847429991 }, { "x": 0.09229429811239243, "y": 0.6094199847429991 } ], "category": "heading1", "id": 252, "content": { "text": "7.1. FREE VORTEX\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09108612686395645, "y": 0.6275674104690552 }, { "x": 0.9067044630646706, "y": 0.6275674104690552 }, { "x": 0.9067044630646706, "y": 0.6834157034754753 }, { "x": 0.09108612686395645, "y": 0.6834157034754753 } ], "category": "paragraph", "id": 253, "content": { "text": "A free vortex is formed when water flows out of a vessel through a central hole in the base (Figure 8.2).\nThe degree of the rotation depends on the initial disturbance. In a free cylindrical vortex, the velocity\nvaries inversely with the distance from the axis of rotation (Figure 8.3).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09196344763040543, "y": 0.7360387444496155 }, { "x": 0.7637415304780006, "y": 0.7360387444496155 }, { "x": 0.7637415304780006, "y": 0.7527532260864973 }, { "x": 0.09196344763040543, "y": 0.7527532260864973 } ], "category": "paragraph", "id": 254, "content": { "text": "The equation governing the surface profile is derived from the Bernoulli's theorem:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09187571704387665, "y": 0.767776608467102 }, { "x": 0.5770914703607559, "y": 0.767776608467102 }, { "x": 0.5770914703607559, "y": 0.8240993469953537 }, { "x": 0.09187571704387665, "y": 0.8240993469953537 } ], "category": "paragraph", "id": 255, "content": { "text": "N2 + z = C\n(2)\nSubstituting Equation (1) into (2) will give a new expression:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09247750043869019, "y": 0.8400691747665405 }, { "x": 0.2804848551750183, "y": 0.8400691747665405 }, { "x": 0.2804848551750183, "y": 0.8667720090597868 }, { "x": 0.09247750043869019, "y": 0.8667720090597868 } ], "category": "paragraph", "id": 256, "content": { "text": "k2\n+\nZ\n=\n2gr2\n(3)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09266266971826553, "y": 0.8856074213981628 }, { "x": 0.11409768275916576, "y": 0.8856074213981628 }, { "x": 0.11409768275916576, "y": 0.8930974011309445 }, { "x": 0.09266266971826553, "y": 0.8930974011309445 } ], "category": "paragraph", "id": 257, "content": { "text": "or:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09246311336755753, "y": 0.9416496753692627 }, { "x": 0.3697187975049019, "y": 0.9416496753692627 }, { "x": 0.3697187975049019, "y": 0.9501092340797186 }, { "x": 0.09246311336755753, "y": 0.9501092340797186 } ], "category": "footer", "id": 258, "content": { "text": "68 APPLIED FLUID MECHANICS LAB MANUAL\n", "html": "", "markdown": "" } } ] }, "01030000000147.pdf": { "elements": [ { "coordinates": [ { "x": 0.13212399184703827, "y": 0.2544826865196228 }, { "x": 0.8608133047819138, "y": 0.2544826865196228 }, { "x": 0.8608133047819138, "y": 0.883049726486206 }, { "x": 0.13212399184703827, "y": 0.883049726486206 } ], "category": "table", "id": 412, "content": { "text": "", "html": "
Source (doc, report, etc.)YearDescription of the initiativeCircular Economy issues addressed
Eco-Ecole Program https://www.ec o-ecole.org/le- programme/2005Eco-Ecole is the French version of Eco-Schools, an international program for education in sustainable development (ESD), developed by the Foundation for Environmental Education. The Teragir association launched the Eco-School program in 2005. The program aims to help students better understand the world around them in order to flourish and participate in it.Eco-Ecole offers instructions for teaching teams to effectively deploy sustainable development from kindergarten to high school.
Horsnormes https://horsnor mes.co/2020Horsnormes is a website which provide baskets of fruits and vegetables that are directly collected from farmers. It helps farmers to gain money while the consumers pay a faire price in exchange of the product, which foster the reduction of food waste.Waste reduction of fruits and vegetables.
Fondation Terre Solidaire (Solidarity Earth Foundation) https://fondatio n- terresolidaire.o rg/quest-ce- que-2016The Terre Solidaire Foundation was created in 2016 by CCFD-Terre Solidaire to act, particularly in France, in the face of the two major challenges of our time: the massive degradation of our environment (including biodiversity and climate), and the need to building a fairer and more ecologically responsible society. The association remains mobilized on itsSupport and encourage initiatives carried out by citizen mobilizations and actors of the social and solidarity economy in the design, implementation, dissemination and experimentation of
", "markdown": "" } }, { "coordinates": [ { "x": 0.04035981744527817, "y": 0.031169261783361435 }, { "x": 0.12771642208099365, "y": 0.031169261783361435 }, { "x": 0.12771642208099365, "y": 0.06735220551490784 }, { "x": 0.04035981744527817, "y": 0.06735220551490784 } ], "category": "figure", "id": 431, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08353709429502487, "y": 0.06100735440850258 }, { "x": 0.1266544573009014, "y": 0.06100735440850258 }, { "x": 0.1266544573009014, "y": 0.07079555466771126 }, { "x": 0.08353709429502487, "y": 0.07079555466771126 } ], "category": "header", "id": 432, "content": { "text": "Circle\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.6846849322319031, "y": 0.02821030095219612 }, { "x": 0.7550342082977295, "y": 0.02821030095219612 }, { "x": 0.7550342082977295, "y": 0.06024276092648506 }, { "x": 0.6846849322319031, "y": 0.06024276092648506 } ], "category": "figure", "id": 433, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.7629222869873047, "y": 0.031360700726509094 }, { "x": 0.9121689647436142, "y": 0.031360700726509094 }, { "x": 0.9121689647436142, "y": 0.05597909539937973 }, { "x": 0.7629222869873047, "y": 0.05597909539937973 } ], "category": "header", "id": 434, "content": { "text": "Co-funded by\nthe European Union\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14242736995220184, "y": 0.10565991699695587 }, { "x": 0.8642454594373703, "y": 0.10565991699695587 }, { "x": 0.8642454594373703, "y": 0.1555897705256939 }, { "x": 0.14242736995220184, "y": 0.1555897705256939 } ], "category": "paragraph", "id": 435, "content": { "text": "3.\nRECOLLECTION OF NATIONAL INITIATIVES\nPartners were also asked to recollect initiatives from their respective countries that represented\nthe core values and practices of a Circular Economy or Social Entrepreneurship:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.4680763781070709, "y": 0.17174434661865234 }, { "x": 0.5398468002676964, "y": 0.17174434661865234 }, { "x": 0.5398468002676964, "y": 0.22045522928237915 }, { "x": 0.4680763781070709, "y": 0.22045522928237915 } ], "category": "figure", "id": 436, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15225590765476227, "y": 0.9047152400016785 }, { "x": 0.8593395501375198, "y": 0.9047152400016785 }, { "x": 0.8593395501375198, "y": 0.926441602408886 }, { "x": 0.15225590765476227, "y": 0.926441602408886 } ], "category": "footer", "id": 438, "content": { "text": "This project has been funded with the support of the European Commission. This publication reflects the views only of the author\nand the Commission cannot be held responsible for any use which may be made of the information contained therein.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.36786532402038574, "y": 0.9399294853210449 }, { "x": 0.6437859237194061, "y": 0.9399294853210449 }, { "x": 0.6437859237194061, "y": 0.9484336720779538 }, { "x": 0.36786532402038574, "y": 0.9484336720779538 } ], "category": "footer", "id": 439, "content": { "text": "Project No: : 2021-2-FR02-KA220-YOU-000048126\n", "html": "", "markdown": "" } } ] }, "01030000000098.pdf": { "elements": [ { "coordinates": [ { "x": 0.16857562959194183, "y": 0.34705275297164917 }, { "x": 0.5841634124517441, "y": 0.34705275297164917 }, { "x": 0.5841634124517441, "y": 0.7245101928710938 }, { "x": 0.16857562959194183, "y": 0.7245101928710938 } ], "category": "table", "id": 365, "content": { "text": "", "html": "
NTS 600 N Chevron THE AVENUES
AIRPARKCapitolUtah State Building
300Maverikw 2nd Ave3rd Ave
Clark PlanetariumTempleSinclair SUNBURST
Sinclair
Grove Blvd S
MaverikCENTRALCITY 500
W 600 S89
800 S W 900 SChevron 900 Salt Lake City
Tracy Botanical 1300Aviary Gardens 1300& B
Maverik
Shell 1700 S
2100 S 15
89 ChevronSmith's FuelCenter
", "markdown": "" } }, { "coordinates": [ { "x": 0.14642639458179474, "y": 0.07228836417198181 }, { "x": 0.9008127599954605, "y": 0.07228836417198181 }, { "x": 0.9008127599954605, "y": 0.14651740342378616 }, { "x": 0.14642639458179474, "y": 0.14651740342378616 } ], "category": "paragraph", "id": 533, "content": { "text": "one of the two players is allowed to communicate with the other player (i.e., there is \"one-way\ncommunication\") the players coordinate their choices 96% of the time! However, with\nsimultaneous two-way communication between the two players, they coordinate only 42% of\nthe time! Explain what happened.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11058882623910904, "y": 0.17185626924037933 }, { "x": 0.900969959795475, "y": 0.17185626924037933 }, { "x": 0.900969959795475, "y": 0.24686134606599808 }, { "x": 0.11058882623910904, "y": 0.24686134606599808 } ], "category": "paragraph", "id": 534, "content": { "text": "10. We demonstrated how to solve for the Penalty Kick game's mixed-strategy equilibrium.\nSuppose you were new to the game of soccer (or football) and assigned to play the goalie\nposition. After watching the following YouTube video, what strategy might make the most\nsense for you to adopt on penalty kicks: https://www.youtube.com/watch?v=3yWZZR9ZodI\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11040203273296356, "y": 0.2716701328754425 }, { "x": 0.8990495651960373, "y": 0.2716701328754425 }, { "x": 0.8990495651960373, "y": 0.32683200389146805 }, { "x": 0.11040203273296356, "y": 0.32683200389146805 } ], "category": "paragraph", "id": 535, "content": { "text": "11. The map below identifies (with red markers) the locations of gas stations in Salt Lake City,\nUtah (Utah's capital city). Do these gas station locations depict a pure strategy equilibrium for\nthe Hotelling Game? Explain.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1707245111465454, "y": 0.3477262556552887 }, { "x": 0.581781268119812, "y": 0.3477262556552887 }, { "x": 0.581781268119812, "y": 0.7222699522972107 }, { "x": 0.1707245111465454, "y": 0.7222699522972107 } ], "category": "figure", "id": 536, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.2998025715351105, "y": 0.7343356609344482 }, { "x": 0.4546028673648834, "y": 0.7343356609344482 }, { "x": 0.4546028673648834, "y": 0.7468930995091796 }, { "x": 0.2998025715351105, "y": 0.7468930995091796 } ], "category": "paragraph", "id": 537, "content": { "text": "Source: Google Maps\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11039532721042633, "y": 0.7835984826087952 }, { "x": 0.9017678648233414, "y": 0.7835984826087952 }, { "x": 0.9017678648233414, "y": 0.916525810956955 }, { "x": 0.11039532721042633, "y": 0.916525810956955 } ], "category": "paragraph", "id": 538, "content": { "text": "12. In this chapter, we learned that when an individual acquires private information about\nsomething, this added information does not necessarily make the individual better off. In\nparticular, when an individual (say, Player 1) acquires private information about something of\ncommon interest to both himself and another individual (say, Player 2), and Player 2 knows\nPlayer 1 has acquired this private information, Player 1 could actually be made worse off as a\nresult of Player 2 changing her strategy in response to the fact that she knows Player 1 now\nhas additional information. Whew! Can you think of a real-life example where the acquisition\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.640404999256134, "y": 0.9509824514389038 }, { "x": 0.9064729809761047, "y": 0.9509824514389038 }, { "x": 0.9064729809761047, "y": 0.9588918155059218 }, { "x": 0.640404999256134, "y": 0.9588918155059218 } ], "category": "footer", "id": 539, "content": { "text": "BEHAVIORAL ECONOMICS PRACTICUM 175\n", "html": "", "markdown": "" } } ] }, "01030000000001.pdf": { "elements": [ { "coordinates": [ { "x": 0.1416923552751541, "y": 0.055422887206077576 }, { "x": 0.16937686502933502, "y": 0.055422887206077576 }, { "x": 0.16937686502933502, "y": 0.06404288858175278 }, { "x": 0.1416923552751541, "y": 0.06404288858175278 } ], "category": "paragraph", "id": 482, "content": { "text": "314\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8069751858711243, "y": 0.056034862995147705 }, { "x": 0.8837667405605316, "y": 0.056034862995147705 }, { "x": 0.8837667405605316, "y": 0.06394196022301912 }, { "x": 0.8069751858711243, "y": 0.06394196022301912 } ], "category": "header", "id": 483, "content": { "text": "YARROW\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1404949426651001, "y": 0.0922166034579277 }, { "x": 0.8835323452949524, "y": 0.0922166034579277 }, { "x": 0.8835323452949524, "y": 0.27020343393087387 }, { "x": 0.1404949426651001, "y": 0.27020343393087387 } ], "category": "paragraph", "id": 484, "content": { "text": "1999 such iterations to form parameter distributions. If these distributions are\nsymmetric, we can pretty much just read values straight out of them to form\nconfidence intervals (e.g., the 50th and 1950th values out of 1999 will give us a\nroughly 95% confidence interval). If they are not, we must do something more\ncomplicated, with the best choice being the bias-corrected and accelerated\n(BCa) approach. Because of the large number of fits that are required,\nbootstrapping is fairly slow. If the experiment contains many trials, the BCa\nmethod makes it even slower (because it incorporates additional \"jackknife\"\nresampling, implying one further fitting iteration for almost every trial).¹\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14065879583358765, "y": 0.2743264138698578 }, { "x": 0.8842673301696777, "y": 0.2743264138698578 }, { "x": 0.8842673301696777, "y": 0.452118843793869 }, { "x": 0.14065879583358765, "y": 0.452118843793869 } ], "category": "paragraph", "id": 485, "content": { "text": "The code accompanying this chapter offers options to generate confidence\nintervals on fitted parameters. Confidence intervals sometimes imply\nstatistical inference, as for example when they fail to overlap some value and\nthus imply that our statistic differs significantly from that value. However, in\nSJ experiments we are more likely to want to ask a question such as whether\na particular parameter differs between two conditions for a single observer.\nTo answer this kind of question, you will need to modify or develop the code.\nIf we take the example of whether parameters vary across conditions, my\nrecommendation would be to adopt a permutation test approach.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1409256011247635, "y": 0.4561774730682373 }, { "x": 0.8838564902544022, "y": 0.4561774730682373 }, { "x": 0.8838564902544022, "y": 0.7110489904880524 }, { "x": 0.1409256011247635, "y": 0.7110489904880524 } ], "category": "paragraph", "id": 486, "content": { "text": "To do so, take the trials from both conditions and think of each trial as a\ncard in a deck of cards. Making sure you keep each trial intact (i.e., without\nbreaking the link between SOAS and responses) shuffle the trials and then deal\nthem at random into two new piles, each representing a pseudo-condition.\nIf your original conditions contained different numbers of trials, make sure\nthe two pseudo-conditions match the size of the original conditions. For each\npseudo-condition, perform a model fit. Now calculate the difference between\nmodel parameters in the two pseudo-conditions. This is the value you want to\nretain. Now repeat this whole process many times. What you are forming is a\nnull distribution of the expected difference between model parameters that\nwould occur just by chance. You can then compare the difference you actually\nobtained against this null distribution to generate a p value for your difference\nof interest.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14141307771205902, "y": 0.7599781155586243 }, { "x": 0.5225434750318527, "y": 0.7599781155586243 }, { "x": 0.5225434750318527, "y": 0.7746820412576199 }, { "x": 0.14141307771205902, "y": 0.7746820412576199 } ], "category": "heading1", "id": 487, "content": { "text": "7\nVariants of SJ Observer Models\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14128698408603668, "y": 0.8002118468284607 }, { "x": 0.8836587220430374, "y": 0.8002118468284607 }, { "x": 0.8836587220430374, "y": 0.8563465662300587 }, { "x": 0.14128698408603668, "y": 0.8563465662300587 } ], "category": "paragraph", "id": 488, "content": { "text": "In this chapter, I have presented two variants of a latency-based observer mod-\nel applied to the SJ task. Both assume that a single SOA will generate an inter-\nnal response (At) that is a Gaussian random variable. Both assume a simple\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1430029422044754, "y": 0.8860598206520081 }, { "x": 0.16119584813714027, "y": 0.8860598206520081 }, { "x": 0.16119584813714027, "y": 0.895104356110096 }, { "x": 0.1430029422044754, "y": 0.895104356110096 } ], "category": "footer", "id": 489, "content": { "text": "18\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1928456723690033, "y": 0.885151743888855 }, { "x": 0.8833434879779816, "y": 0.885151743888855 }, { "x": 0.8833434879779816, "y": 0.9162696097046137 }, { "x": 0.1928456723690033, "y": 0.9162696097046137 } ], "category": "footer", "id": 490, "content": { "text": "E.g., SimultaneityNoisyCriteriaMultistart 225-386>. Note that Matlab has inbuilt func-\ntions, which could have done most of this if you have the statistics toolbox extensions.\n", "html": "", "markdown": "" } } ] }, "01030000000052.pdf": { "elements": [ { "coordinates": [ { "x": 0.1449814885854721, "y": 0.561773955821991 }, { "x": 0.8966681808233261, "y": 0.561773955821991 }, { "x": 0.8966681808233261, "y": 0.9203775823116302 }, { "x": 0.1449814885854721, "y": 0.9203775823116302 } ], "category": "table", "id": 331, "content": { "text": "", "html": "
REGIONS2007-20102010-20132016-2019
National Capital Region985
Cordillera Autonomous Region121
I - llocos Region154
Il - Cagayan Valley135
III - Central Luzon8911
IVA - CALABARZON4211
IVB - MIMAROPA111
V - Bicol Region204
VI Western Visayas233
VII - Central Visayas223
VIII Eastern Visayas323
", "markdown": "" } }, { "coordinates": [ { "x": 0.24101534485816956, "y": 0.05701863765716553 }, { "x": 0.8406214416027069, "y": 0.05701863765716553 }, { "x": 0.8406214416027069, "y": 0.07193244993686676 }, { "x": 0.24101534485816956, "y": 0.07193244993686676 } ], "category": "header", "id": 381, "content": { "text": "Overcoming Barriers to Filipino Women's Political Representation\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8773139119148254, "y": 0.05773009732365608 }, { "x": 0.9014803003519773, "y": 0.05773009732365608 }, { "x": 0.9014803003519773, "y": 0.07047758344560862 }, { "x": 0.8773139119148254, "y": 0.07047758344560862 } ], "category": "paragraph", "id": 382, "content": { "text": "15\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1446898728609085, "y": 0.11024726927280426 }, { "x": 0.8975888043642044, "y": 0.11024726927280426 }, { "x": 0.8975888043642044, "y": 0.4724954217672348 }, { "x": 0.1446898728609085, "y": 0.4724954217672348 } ], "category": "paragraph", "id": 383, "content": { "text": "the way for women to enter the House of Representatives. In 2019,\n20 women from party lists have contributed to the increase in female\nlegislators. However, the Party-List Law's implementation has been\ncontroversial owing to the entry of political dynasties and traditional\npoliticians. The ideal that it serve as the gateway to political power of\ndisadvantaged groups has been lost due to vague provisions in the\nlaw and subsequent Supreme Court decisions. The party list system\nhas also been \"co-opted by the traditional political system or have\nbecome the training ground for future influence-peddling traditional\npoliticians\" (Tigno 2019). In other words, it has deviated from the idea\nof proportional representation practiced in other countries. Dynastic\nfamilies took advantage of the system's flaws and used them to field\nrelatives, including some women, to expand their political power.\nHowever, recent interviews with legislators from progressive party\nlists demonstrate a better understanding of women's issues than some\nrepresentatives elected from single-member districts (Encinas-Franco\n2022, 157).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.23533830046653748, "y": 0.5074504613876343 }, { "x": 0.8042190372943878, "y": 0.5074504613876343 }, { "x": 0.8042190372943878, "y": 0.5411460287868977 }, { "x": 0.23533830046653748, "y": 0.5411460287868977 } ], "category": "paragraph", "id": 384, "content": { "text": "Table 2. Women-Members of the House of Representatives\nper Region, 2007-2019\n", "html": "", "markdown": "" } } ] }, "01030000000037.pdf": { "elements": [ { "coordinates": [ { "x": 0.15911974012851715, "y": 0.08897332847118378 }, { "x": 0.8476659208536148, "y": 0.08897332847118378 }, { "x": 0.8476659208536148, "y": 0.12173610925674438 }, { "x": 0.15911974012851715, "y": 0.12173610925674438 } ], "category": "heading1", "id": 434, "content": { "text": "3. Impact on Business Operations\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15793535113334656, "y": 0.14725826680660248 }, { "x": 0.5371463596820831, "y": 0.14725826680660248 }, { "x": 0.5371463596820831, "y": 0.19927789643406868 }, { "x": 0.15793535113334656, "y": 0.19927789643406868 } ], "category": "paragraph", "id": 435, "content": { "text": "This section investigates the impact of public health\nmeasures on business operations. MSMEs were\nasked about their expectations for recovery and the\nmain effects of COVID-19 on their businesses.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1583629995584488, "y": 0.21866489946842194 }, { "x": 0.41728462278842926, "y": 0.21866489946842194 }, { "x": 0.41728462278842926, "y": 0.2297051791101694 }, { "x": 0.1583629995584488, "y": 0.2297051791101694 } ], "category": "heading1", "id": 436, "content": { "text": "3.1. Status of Business Operations\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.157986581325531, "y": 0.24675634503364563 }, { "x": 0.5369904339313507, "y": 0.24675634503364563 }, { "x": 0.5369904339313507, "y": 0.2581493565812707 }, { "x": 0.157986581325531, "y": 0.2581493565812707 } ], "category": "paragraph", "id": 437, "content": { "text": "As shown in Figure 3.1.1, the number of MSMEs\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5524271726608276, "y": 0.14746791124343872 }, { "x": 0.9328325688838959, "y": 0.14746791124343872 }, { "x": 0.9328325688838959, "y": 0.21377424150705338 }, { "x": 0.5524271726608276, "y": 0.21377424150705338 } ], "category": "paragraph", "id": 438, "content": { "text": "course of the research period. The impacts of the\nlockdown from March 30 to May 4, 2020, were starkly\nfelt, with only 30% of the MSMEs \"working as usual,\"\nwhile over half (58%) were temporarily completely\nclosed.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.553204357624054, "y": 0.23293432593345642 }, { "x": 0.931223064661026, "y": 0.23293432593345642 }, { "x": 0.931223064661026, "y": 0.25847052596509457 }, { "x": 0.553204357624054, "y": 0.25847052596509457 } ], "category": "paragraph", "id": 439, "content": { "text": "In the agriculture sector, a large majority of MSMEs\n(93% in July 2020, 98% in October 2020, and 99%\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16000013053417206, "y": 0.26128554344177246 }, { "x": 0.9310270398855209, "y": 0.26128554344177246 }, { "x": 0.9310270398855209, "y": 0.27338267397135496 }, { "x": 0.16000013053417206, "y": 0.27338267397135496 } ], "category": "paragraph", "id": 440, "content": { "text": "\"working as usual\" gradually increased over the in January 2021) were operating normally, though\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15881748497486115, "y": 0.2897324860095978 }, { "x": 0.6336524039506912, "y": 0.2897324860095978 }, { "x": 0.6336524039506912, "y": 0.30133701488375664 }, { "x": 0.15881748497486115, "y": 0.30133701488375664 } ], "category": "paragraph", "id": 441, "content": { "text": "Figure 3.1.1: Status of operations during each survey phase (%)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.2307344675064087, "y": 0.3133123517036438 }, { "x": 0.8585802316665649, "y": 0.3133123517036438 }, { "x": 0.8585802316665649, "y": 0.6412273049354553 }, { "x": 0.2307344675064087, "y": 0.6412273049354553 } ], "category": "figure", "id": 442, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1583346128463745, "y": 0.6605930924415588 }, { "x": 0.5385284125804901, "y": 0.6605930924415588 }, { "x": 0.5385284125804901, "y": 0.8142868280410767 }, { "x": 0.1583346128463745, "y": 0.8142868280410767 } ], "category": "paragraph", "id": 443, "content": { "text": "during the first lockdown period, just over three\nquarters (77%) were working as usual. In contrast,\n63% of firms from the tourism sector and 62%\nfrom the handicraft/textile sector were working as\nusual as of July 2020, rising to 80% of tourism and\n82% of handicraft/textile firms as of January 2021.\nDuring the lockdown period, tourism and handicraft/\ntextile MSMEs were the hardest hit with just 12%\nand 15% respectively working as usual. As shown\nin Table 3.1.1., a majority of tourism and handicraft/\ntextile MSMEs were temporarily closed during the\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5523310303688049, "y": 0.6606249809265137 }, { "x": 0.9317320287227631, "y": 0.6606249809265137 }, { "x": 0.9317320287227631, "y": 0.8142374902963638 }, { "x": 0.5523310303688049, "y": 0.8142374902963638 } ], "category": "paragraph", "id": 444, "content": { "text": "lockdown period. In the handicraft/textile sector, 30%\nof MSMEs were temporarily closed as of July 2020,\nreducing to 12% in January 2021. Similarly, in tourism,\n27% of businesses were temporarily closed as of July\n2020 and that reduced to 18% in January 2021. Figure\n3.1.1 and Table 3.1.1 do not reflect those MSMEs who\nwere permanently closed; this was four in July 2020,\n22 in October 2020, and 24 in January 2021. Of these\n50 businesses who permanently closed during the\nresearch period, 30 were in the tourism sector, 18 in\nhandicraft/textile, and two in agriculture.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0653681829571724, "y": 0.9404697418212891 }, { "x": 0.07140968414023519, "y": 0.9404697418212891 }, { "x": 0.07140968414023519, "y": 0.9473399468697608 }, { "x": 0.0653681829571724, "y": 0.9473399468697608 } ], "category": "paragraph", "id": 445, "content": { "text": "7\n", "html": "", "markdown": "" } } ] }, "01030000000078.pdf": { "elements": [ { "coordinates": [ { "x": 0.16465438902378082, "y": 0.427310585975647 }, { "x": 0.8592609316110611, "y": 0.427310585975647 }, { "x": 0.8592609316110611, "y": 0.6390412896871567 }, { "x": 0.16465438902378082, "y": 0.6390412896871567 } ], "category": "table", "id": 369, "content": { "text": "", "html": "
AMS Average Annual Growth Remittance inflows in 2020 (US$ Million)
2000-20042004-20092009-20142014-20192019-2020
Cambodia7.5%-0.7%50.6%6.7%-16.6%1,272
Indonesia9.4%29.5%4.7%6.4%-17.3%9,651
Lao PDR4.0%115.7%38.0%9.5%-10.6%265
Malaysia18.6%7.1%6.9%0.7%-11.2%1,454
Myanmar2.7%-14.1%102.7%5.4%-7.1%2,250
Philippines10.6%11.7%7.5%4.2%-0.7%34,913
Thailand-0.9%18.6%11.4%4.6%-1.2%8,067
Viet Nam11.5%21.1%14.8%7.2%1.2%17,200
", "markdown": "" } }, { "coordinates": [ { "x": 0.16682085394859314, "y": 0.08302144706249237 }, { "x": 0.6629798114299774, "y": 0.08302144706249237 }, { "x": 0.6629798114299774, "y": 0.09872514382004738 }, { "x": 0.16682085394859314, "y": 0.09872514382004738 } ], "category": "paragraph", "id": 445, "content": { "text": "Figure 1.10. Migrant remittances inflows (in US$ billion)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16481813788414001, "y": 0.10869885236024857 }, { "x": 0.8589373528957367, "y": 0.10869885236024857 }, { "x": 0.8589373528957367, "y": 0.35907409340143204 }, { "x": 0.16481813788414001, "y": 0.35907409340143204 } ], "category": "figure", "id": 446, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16644605994224548, "y": 0.37591367959976196 }, { "x": 0.48100945353507996, "y": 0.37591367959976196 }, { "x": 0.48100945353507996, "y": 0.38829374499619007 }, { "x": 0.16644605994224548, "y": 0.38829374499619007 } ], "category": "paragraph", "id": 447, "content": { "text": "Source: World Bank and KNOMAD (2021)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16580766439437866, "y": 0.40501999855041504 }, { "x": 0.6112062931060791, "y": 0.40501999855041504 }, { "x": 0.6112062931060791, "y": 0.4197853049263358 }, { "x": 0.16580766439437866, "y": 0.4197853049263358 } ], "category": "paragraph", "id": 448, "content": { "text": "Table 1.4.\nGrowth in migrant remittance inflows\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.17313581705093384, "y": 0.6469506621360779 }, { "x": 0.4871620833873749, "y": 0.6469506621360779 }, { "x": 0.4871620833873749, "y": 0.6589767849072814 }, { "x": 0.17313581705093384, "y": 0.6589767849072814 } ], "category": "paragraph", "id": 450, "content": { "text": "Source: World Bank and KNOMAD (2021)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16565611958503723, "y": 0.6759009957313538 }, { "x": 0.8577934801578522, "y": 0.6759009957313538 }, { "x": 0.8577934801578522, "y": 0.8279045522212982 }, { "x": 0.16565611958503723, "y": 0.8279045522212982 } ], "category": "paragraph", "id": 451, "content": { "text": "In the Philippines, of the returning Filipino migrant workers in 2020, 55 percent\nearned a monthly income of between PHP20,000 and PHP50,000, and 19\npercent earned between PHP5000 and PHP20,000. Before their return, 50\npercent reported remitting amounts ranging from PHP10,000 to PHP20,000\n(US$200 to US$400) monthly. It is highly unlikely that the families of these\nmigrant workers would have savings to rely on after they lost their jobs.\nAdditionally, 83 percent of these workers were still unemployed after three\nmonths, resulting in a 60 percent drop in household income for 48 percent of\nthe returned migrant workers.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.047617338597774506, "y": 0.9528430104255676 }, { "x": 0.07002720981836319, "y": 0.9528430104255676 }, { "x": 0.07002720981836319, "y": 0.9635456893593073 }, { "x": 0.047617338597774506, "y": 0.9635456893593073 } ], "category": "paragraph", "id": 452, "content": { "text": "26\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5783733129501343, "y": 0.9519748091697693 }, { "x": 0.8571445643901825, "y": 0.9519748091697693 }, { "x": 0.8571445643901825, "y": 0.9666071170940995 }, { "x": 0.5783733129501343, "y": 0.9666071170940995 } ], "category": "footer", "id": 453, "content": { "text": "ASEAN Migration Outlook\n", "html": "", "markdown": "" } } ] }, "01030000000148.pdf": { "elements": [ { "coordinates": [ { "x": 0.040104061365127563, "y": 0.030868209898471832 }, { "x": 0.12761691212654114, "y": 0.030868209898471832 }, { "x": 0.12761691212654114, "y": 0.06904066354036331 }, { "x": 0.040104061365127563, "y": 0.06904066354036331 } ], "category": "figure", "id": 271, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08371291309595108, "y": 0.06110129505395889 }, { "x": 0.12652785331010818, "y": 0.06110129505395889 }, { "x": 0.12652785331010818, "y": 0.07073364593088627 }, { "x": 0.08371291309595108, "y": 0.07073364593088627 } ], "category": "header", "id": 272, "content": { "text": "Circle\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.6842964291572571, "y": 0.027980566024780273 }, { "x": 0.7546337470412254, "y": 0.027980566024780273 }, { "x": 0.7546337470412254, "y": 0.06063394248485565 }, { "x": 0.6842964291572571, "y": 0.06063394248485565 } ], "category": "figure", "id": 273, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.7624921202659607, "y": 0.03142838925123215 }, { "x": 0.9117705821990967, "y": 0.03142838925123215 }, { "x": 0.9117705821990967, "y": 0.0559853371232748 }, { "x": 0.7624921202659607, "y": 0.0559853371232748 } ], "category": "header", "id": 274, "content": { "text": "Co-funded by\nthe European Union\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1427183449268341, "y": 0.1037503257393837 }, { "x": 0.8644387423992157, "y": 0.1037503257393837 }, { "x": 0.8644387423992157, "y": 0.15062929689884186 }, { "x": 0.1427183449268341, "y": 0.15062929689884186 } ], "category": "paragraph", "id": 275, "content": { "text": "As seen in this chart of responses, we were very satisfied to reach diversity in age groups, with\nall groups being represented by over 10%. The main group reached was of ages 36-45, and the\nleast represented was the youngest age group of 18-25.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16647666692733765, "y": 0.20768678188323975 }, { "x": 0.2769213616847992, "y": 0.20768678188323975 }, { "x": 0.2769213616847992, "y": 0.21700595784932375 }, { "x": 0.16647666692733765, "y": 0.21700595784932375 } ], "category": "heading1", "id": 276, "content": { "text": "Education Level\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16675767302513123, "y": 0.22396965324878693 }, { "x": 0.2440330758690834, "y": 0.22396965324878693 }, { "x": 0.2440330758690834, "y": 0.2324991524219513 }, { "x": 0.16675767302513123, "y": 0.2324991524219513 } ], "category": "paragraph", "id": 277, "content": { "text": "122 responses\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.2920331656932831, "y": 0.2531692087650299 }, { "x": 0.7756124138832092, "y": 0.2531692087650299 }, { "x": 0.7756124138832092, "y": 0.3830455094575882 }, { "x": 0.2920331656932831, "y": 0.3830455094575882 } ], "category": "figure", "id": 278, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14292208850383759, "y": 0.41858747601509094 }, { "x": 0.8431595414876938, "y": 0.41858747601509094 }, { "x": 0.8431595414876938, "y": 0.4481147173792124 }, { "x": 0.14292208850383759, "y": 0.4481147173792124 } ], "category": "paragraph", "id": 279, "content": { "text": "Regarding the education level of responders, we were satisfied to receive a very high level of\nresponses with Bachelor's or higher degrees, with the significant share of others coming from\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14241816103458405, "y": 0.5696020722389221 }, { "x": 0.8418788462877274, "y": 0.5696020722389221 }, { "x": 0.8418788462877274, "y": 0.5987983159720898 }, { "x": 0.14241816103458405, "y": 0.5987983159720898 } ], "category": "paragraph", "id": 280, "content": { "text": "Upper Secondary-educated participants. There was also a small representation of non-formal\ntraining, as well as >1% representation for other options.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.16658711433410645, "y": 0.629126787185669 }, { "x": 0.24429939687252045, "y": 0.629126787185669 }, { "x": 0.24429939687252045, "y": 0.6541037335991859 }, { "x": 0.16658711433410645, "y": 0.6541037335991859 } ], "category": "paragraph", "id": 281, "content": { "text": "Profession\n122 responses\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.29200679063796997, "y": 0.6748271584510803 }, { "x": 0.767867237329483, "y": 0.6748271584510803 }, { "x": 0.767867237329483, "y": 0.8049234002828598 }, { "x": 0.29200679063796997, "y": 0.8049234002828598 } ], "category": "figure", "id": 282, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14257356524467468, "y": 0.8308013677597046 }, { "x": 0.8599905073642731, "y": 0.8308013677597046 }, { "x": 0.8599905073642731, "y": 0.8774166256189346 }, { "x": 0.14257356524467468, "y": 0.8774166256189346 } ], "category": "paragraph", "id": 283, "content": { "text": "For responders' profession, the most common answers representing 19.7% equally, were Youth\nWorkers and Project Managers, although practising Social Entrepreneurs were also well\nrepresented, along with an 8% response rate from self-declared circular economy experts.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1521827131509781, "y": 0.9049581289291382 }, { "x": 0.8588462024927139, "y": 0.9049581289291382 }, { "x": 0.8588462024927139, "y": 0.9263420403003693 }, { "x": 0.1521827131509781, "y": 0.9263420403003693 } ], "category": "footer", "id": 284, "content": { "text": "This project has been funded with the support of the European Commission. This publication reflects the views only of the author\nand the Commission cannot be held responsible for any use which may be made of the information contained therein.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3677791357040405, "y": 0.9399308562278748 }, { "x": 0.6431231200695038, "y": 0.9399308562278748 }, { "x": 0.6431231200695038, "y": 0.948357698507607 }, { "x": 0.3677791357040405, "y": 0.948357698507607 } ], "category": "footer", "id": 285, "content": { "text": "Project No: : 2021-2-FR02-KA220-YOU-000048126\n", "html": "", "markdown": "" } } ] }, "01030000000117.pdf": { "elements": [ { "coordinates": [ { "x": 0.11661416292190552, "y": 0.09612525254487991 }, { "x": 0.6295666694641113, "y": 0.09612525254487991 }, { "x": 0.6295666694641113, "y": 0.17513594776391983 }, { "x": 0.11661416292190552, "y": 0.17513594776391983 } ], "category": "table", "id": 352, "content": { "text": "", "html": "
Saccharometer DI Water Glucose Solution Yeast Suspension
224 ml0 ml4 ml
312 ml12 ml4 ml
44 ml12 ml12 ml
", "markdown": "" } }, { "coordinates": [ { "x": 0.12980976700782776, "y": 0.05146843194961548 }, { "x": 0.40529945492744446, "y": 0.05146843194961548 }, { "x": 0.40529945492744446, "y": 0.06550464313477278 }, { "x": 0.12980976700782776, "y": 0.06550464313477278 } ], "category": "header", "id": 371, "content": { "text": "MOHAVE COMMUNITY COLLEGE\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8112531304359436, "y": 0.052965763956308365 }, { "x": 0.8811545670032501, "y": 0.052965763956308365 }, { "x": 0.8811545670032501, "y": 0.06583134084939957 }, { "x": 0.8112531304359436, "y": 0.06583134084939957 } ], "category": "header", "id": 372, "content": { "text": "BIO181\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12092835456132889, "y": 0.09650570899248123 }, { "x": 0.6286486461758614, "y": 0.09650570899248123 }, { "x": 0.6286486461758614, "y": 0.11150551121681929 }, { "x": 0.12092835456132889, "y": 0.11150551121681929 } ], "category": "paragraph", "id": 373, "content": { "text": "Saccharometer DI Water Glucose Solution Yeast Suspension\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11722749471664429, "y": 0.23307400941848755 }, { "x": 0.4684528410434723, "y": 0.23307400941848755 }, { "x": 0.4684528410434723, "y": 0.24810553807765245 }, { "x": 0.11722749471664429, "y": 0.24810553807765245 } ], "category": "paragraph", "id": 375, "content": { "text": "Employing Steps in the Scientific Method:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14882132411003113, "y": 0.2680685222148895 }, { "x": 0.6928233206272125, "y": 0.2680685222148895 }, { "x": 0.6928233206272125, "y": 0.2830893835052848 }, { "x": 0.14882132411003113, "y": 0.2830893835052848 } ], "category": "paragraph", "id": 377, "content": { "text": "1. Record the Question that is being investigated in this experiment.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1475488245487213, "y": 0.32073017954826355 }, { "x": 0.5803482234477997, "y": 0.32073017954826355 }, { "x": 0.5803482234477997, "y": 0.3356286557391286 }, { "x": 0.1475488245487213, "y": 0.3356286557391286 } ], "category": "paragraph", "id": 378, "content": { "text": "2. Record a Hypothesis for the question stated above.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14713938534259796, "y": 0.3732859492301941 }, { "x": 0.7364963442087173, "y": 0.3732859492301941 }, { "x": 0.7364963442087173, "y": 0.38839446660131216 }, { "x": 0.14713938534259796, "y": 0.38839446660131216 } ], "category": "paragraph", "id": 379, "content": { "text": "3. Predict the results of the experiment based on your hypothesis (if/then).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14662206172943115, "y": 0.42590004205703735 }, { "x": 0.5880365967750549, "y": 0.42590004205703735 }, { "x": 0.5880365967750549, "y": 0.4407455753535032 }, { "x": 0.14662206172943115, "y": 0.4407455753535032 } ], "category": "paragraph", "id": 380, "content": { "text": "4. Perform the experiment below and collect your data.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11757964640855789, "y": 0.46112844347953796 }, { "x": 0.2093079835176468, "y": 0.46112844347953796 }, { "x": 0.2093079835176468, "y": 0.4729892127215862 }, { "x": 0.11757964640855789, "y": 0.4729892127215862 } ], "category": "heading1", "id": 381, "content": { "text": "Procedure:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14891748130321503, "y": 0.4962805211544037 }, { "x": 0.8838265389204025, "y": 0.4962805211544037 }, { "x": 0.8838265389204025, "y": 0.5630972310900688 }, { "x": 0.14891748130321503, "y": 0.5630972310900688 } ], "category": "paragraph", "id": 383, "content": { "text": "1. Prepare yeast suspension: Add 7 grams yeast to 50 ml warm tap water. Stir to mix.\nAlternatively, you can use the yeast suspension from Part 2. Optional: Add a few drops of\nred food coloring to the yeast to increase contrast, allowing easier measuring of the\nheight of yeast in saccharometers.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14646491408348083, "y": 0.5652671456336975 }, { "x": 0.863254576921463, "y": 0.5652671456336975 }, { "x": 0.863254576921463, "y": 0.6124082617461681 }, { "x": 0.14646491408348083, "y": 0.6124082617461681 } ], "category": "paragraph", "id": 384, "content": { "text": "2. Label 4 test tubes and 4 saccharometers # 1 4. Use a transfer pipette to add the\nappropriate amount of glucose and distilled water listed in Table 2 to the corresponding\nlabeled test tubes.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14681066572666168, "y": 0.6177151203155518 }, { "x": 0.8697779327630997, "y": 0.6177151203155518 }, { "x": 0.8697779327630997, "y": 0.6676354482769966 }, { "x": 0.14681066572666168, "y": 0.6676354482769966 } ], "category": "paragraph", "id": 385, "content": { "text": "3. Use a transfer pipette to add the appropriate amount of yeast solution listed in Table 1 to\nthe corresponding labeled test tubes. It is important to work carefully and quickly after\nadding the yeast solution to the glucose and water.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14684011042118073, "y": 0.6876953840255737 }, { "x": 0.7769498974084854, "y": 0.6876953840255737 }, { "x": 0.7769498974084854, "y": 0.7195724546909332 }, { "x": 0.14684011042118073, "y": 0.7195724546909332 } ], "category": "paragraph", "id": 386, "content": { "text": "4. Carefully pour the contents of the test tubes into the correspondingly labeled\nsaccharometer, ensuring that the solutions are well mixed.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14707809686660767, "y": 0.7404159903526306 }, { "x": 0.8670774698257446, "y": 0.7404159903526306 }, { "x": 0.8670774698257446, "y": 0.7728103548288345 }, { "x": 0.14707809686660767, "y": 0.7728103548288345 } ], "category": "paragraph", "id": 387, "content": { "text": "5. Carefully tilt the saccharometers to allow any air bubbles that are trapped in the arms of\nthe vertical tube to escape.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1471000611782074, "y": 0.7926023006439209 }, { "x": 0.8802573382854462, "y": 0.7926023006439209 }, { "x": 0.8802573382854462, "y": 0.8429882638156414 }, { "x": 0.1471000611782074, "y": 0.8429882638156414 } ], "category": "paragraph", "id": 388, "content": { "text": "6. Begin the timer for the experiment and measure the size of any bubbles (in mm) that are\ntrapped in the vertical arms of the saccharometers. Record this measurement as the 0 time\npoint.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14691372215747833, "y": 0.8626308441162109 }, { "x": 0.855054572224617, "y": 0.8626308441162109 }, { "x": 0.855054572224617, "y": 0.8951777182519436 }, { "x": 0.14691372215747833, "y": 0.8951777182519436 } ], "category": "paragraph", "id": 389, "content": { "text": "7. Position the saccharometers on the large plastic tray, positioning them around a plastic\nweigh boat to catch any fermentation overflow that may occur.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.4960434138774872, "y": 0.9732273817062378 }, { "x": 0.5106761306524277, "y": 0.9732273817062378 }, { "x": 0.5106761306524277, "y": 0.9846861185505986 }, { "x": 0.4960434138774872, "y": 0.9846861185505986 } ], "category": "paragraph", "id": 390, "content": { "text": "59\n", "html": "", "markdown": "" } } ] }, "01030000000113.pdf": { "elements": [ { "coordinates": [ { "x": 0.07784648984670639, "y": 0.029485441744327545 }, { "x": 0.3535052463412285, "y": 0.029485441744327545 }, { "x": 0.3535052463412285, "y": 0.04365488886833191 }, { "x": 0.07784648984670639, "y": 0.04365488886833191 } ], "category": "header", "id": 223, "content": { "text": "MOHAVE COMMUNITY COLLEGE\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8736069798469543, "y": 0.0314723365008831 }, { 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"" } }, { "coordinates": [ { "x": 0.055820658802986145, "y": 0.20060493052005768 }, { "x": 0.6449491530656815, "y": 0.20060493052005768 }, { "x": 0.6449491530656815, "y": 0.21698318235576153 }, { "x": 0.055820658802986145, "y": 0.21698318235576153 } ], "category": "paragraph", "id": 230, "content": { "text": "Chemistry of the Cell ~ But this is biology!\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.930426836013794, "y": 0.2014704942703247 }, { "x": 0.9427966168150306, "y": 0.2014704942703247 }, { "x": 0.9427966168150306, "y": 0.2130917375907302 }, { "x": 0.930426836013794, "y": 0.2130917375907302 } ], "category": "paragraph", "id": 231, "content": { "text": "9\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.05597420781850815, "y": 0.23025129735469818 }, { "x": 0.7212840542197227, "y": 0.23025129735469818 }, { "x": 0.7212840542197227, "y": 0.2464524619281292 }, { "x": 0.05597420781850815, "y": 0.2464524619281292 } ], "category": "paragraph", "id": 232, "content": { "text": "Biological Macromolecules and Their Indicators\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.9182794094085693, "y": 0.23068751394748688 }, { "x": 0.9429310001432896, "y": 0.23068751394748688 }, { "x": 0.9429310001432896, "y": 0.2426809761673212 }, { "x": 0.9182794094085693, "y": 0.2426809761673212 } ], "category": "paragraph", "id": 233, "content": { "text": "10\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.05464105308055878, "y": 0.25956618785858154 }, { "x": 0.5514221638441086, "y": 0.25956618785858154 }, { "x": 0.5514221638441086, "y": 0.275363327935338 }, { "x": 0.05464105308055878, "y": 0.275363327935338 } ], "category": "paragraph", "id": 234, "content": { "text": "Worksheet for Chemistry of the Cell\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.9181964993476868, "y": 0.260102242231369 }, { "x": 0.9428297374397516, "y": 0.260102242231369 }, { "x": 0.9428297374397516, "y": 0.2718850374221802 }, { "x": 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ABCDE
1timeobservedForecast(observed)Lower Confidence Bound(observed)Upper Confidence Bound(observed)
2O13
3112
4213.5
5315
6416
7518
8617.5
9717.917.9017.9017.90
10819.7321445817.9921.47
11921.5996299819.8123.39
121021.6264585719.7823.47
131122.8599311620.9624.76
141224.7274165622.7826.68
151324.7542451522.7526.75
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{ "coordinates": [ { "x": 0.023690257221460342, "y": 0.2575953006744385 }, { "x": 0.21849017217755318, "y": 0.2575953006744385 }, { "x": 0.21849017217755318, "y": 0.27470626682043076 }, { "x": 0.023690257221460342, "y": 0.27470626682043076 } ], "category": "paragraph", "id": 254, "content": { "text": "Wear polarized sunglasses\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.023530825972557068, "y": 0.2796521484851837 }, { "x": 0.21916070580482483, "y": 0.2796521484851837 }, { "x": 0.21916070580482483, "y": 0.2963869720697403 }, { "x": 0.023530825972557068, "y": 0.2963869720697403 } ], "category": "paragraph", "id": 255, "content": { "text": "Take a safe boating course\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.01595764234662056, "y": 0.3234976828098297 }, { "x": 0.1227874718606472, "y": 0.3234976828098297 }, { "x": 0.1227874718606472, "y": 0.3401203826069832 }, { "x": 0.01595764234662056, "y": 0.3401203826069832 } ], "category": "heading1", "id": 256, "content": { "text": "As a developer:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.023578651249408722, "y": 0.34578937292099 }, { "x": 0.26992375403642654, "y": 0.34578937292099 }, { "x": 0.26992375403642654, "y": 0.38482679054141045 }, { "x": 0.023578651249408722, "y": 0.38482679054141045 } ], "category": "paragraph", "id": 258, "content": { "text": "Do careful mapping of seagrass in\npotential areas for development\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.023606086149811745, "y": 0.38965409994125366 }, { "x": 0.21675902046263218, "y": 0.38965409994125366 }, { "x": 0.21675902046263218, "y": 0.4069635197520256 }, { "x": 0.023606086149811745, "y": 0.4069635197520256 } ], "category": "paragraph", "id": 259, "content": { "text": "Avoid dredging and filling\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.023258820176124573, "y": 0.41177961230278015 }, { "x": 0.25965963304042816, "y": 0.41177961230278015 }, { "x": 0.25965963304042816, "y": 0.4287810120731592 }, { "x": 0.023258820176124573, "y": 0.4287810120731592 } ], "category": "paragraph", "id": 260, "content": { "text": "Learn about existing regulations\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0160718634724617, "y": 0.45646992325782776 }, { "x": 0.1369093582034111, "y": 0.45646992325782776 }, { "x": 0.1369093582034111, "y": 0.4700668742880225 }, { "x": 0.0160718634724617, "y": 0.4700668742880225 } ], "category": "heading1", "id": 261, "content": { "text": "As a homeowner:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.02336949110031128, "y": 0.477948397397995 }, { "x": 0.30999401211738586, "y": 0.477948397397995 }, { "x": 0.30999401211738586, "y": 0.517054058611393 }, { "x": 0.02336949110031128, "y": 0.517054058611393 } ], "category": "paragraph", "id": 263, "content": { "text": "Diminish fertilizer use (use soaking,\nrain gardens, and native plants instead)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.023772088810801506, "y": 0.5222538709640503 }, { "x": 0.24131063930690289, "y": 0.5222538709640503 }, { "x": 0.24131063930690289, "y": 0.5393224097788334 }, { "x": 0.023772088810801506, "y": 0.5393224097788334 } ], "category": "paragraph", "id": 264, "content": { "text": "Dispose of pet waste properly\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.023729940876364708, "y": 0.5441106557846069 }, { "x": 0.29302470944821835, "y": 0.5441106557846069 }, { "x": 0.29302470944821835, "y": 0.6055693030357361 }, { "x": 0.023729940876364708, "y": 0.6055693030357361 } ], "category": "paragraph", "id": 265, "content": { "text": "Keep seagrass in mind during\nconstruction (for example, build high\ndocks with grating instead of planks)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.015727713704109192, "y": 0.6542814373970032 }, { "x": 0.2256365269422531, "y": 0.6542814373970032 }, { "x": 0.2256365269422531, "y": 0.6717099919915199 }, { "x": 0.015727713704109192, "y": 0.6717099919915199 } ], "category": "heading1", "id": 266, "content": { "text": "As anyone who wants to help:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.023554598912596703, "y": 0.676466703414917 }, { "x": 0.2831257935613394, "y": 0.676466703414917 }, { "x": 0.2831257935613394, "y": 0.7163767516613007 }, { "x": 0.023554598912596703, "y": 0.7163767516613007 } ], "category": "paragraph", "id": 268, "content": { "text": "Urge politicians to establish stricter\nwater quality regulations\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.02415289916098118, "y": 0.7207667231559753 }, { "x": 0.22836398519575596, "y": 0.7207667231559753 }, { "x": 0.22836398519575596, "y": 0.7600019760429859 }, { "x": 0.02415289916098118, "y": 0.7600019760429859 } ], "category": "paragraph", "id": 269, "content": { "text": "Mobilize to give seagrass an\n\"endangered\" status\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.023769672960042953, "y": 0.7644678950309753 }, { "x": 0.28556742891669273, "y": 0.7644678950309753 }, { "x": 0.28556742891669273, "y": 0.8045547381043434 }, { "x": 0.023769672960042953, "y": 0.8045547381043434 } ], "category": "paragraph", "id": 270, "content": { "text": "Follow established laws for seagrass\nprotection\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.024041537195444107, "y": 0.809086799621582 }, { "x": 0.24731681123375893, "y": 0.809086799621582 }, { "x": 0.24731681123375893, "y": 0.8699780218303204 }, { "x": 0.024041537195444107, "y": 0.8699780218303204 } ], "category": "paragraph", "id": 271, "content": { "text": "Reach out to environmental\norganizations and volunteer in\nrestoration projects\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.024095728993415833, "y": 0.8753790259361267 }, { "x": 0.27221354842185974, "y": 0.8753790259361267 }, { "x": 0.27221354842185974, "y": 0.9148699901998043 }, { "x": 0.024095728993415833, "y": 0.9148699901998043 } ], "category": "paragraph", "id": 272, "content": { "text": "Challenge the misconception that\nseagrass is 'ugly' and 'useless'\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.024381671100854874, "y": 0.9189242720603943 }, { "x": 0.29559263959527016, "y": 0.9189242720603943 }, { "x": 0.29559263959527016, "y": 0.9583093672990799 }, { "x": 0.024381671100854874, "y": 0.9583093672990799 } ], "category": "paragraph", "id": 273, "content": { "text": "Tell your friends and family about the\nimportance of this ecosystem\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.387196809053421, "y": 0.04606150835752487 }, { "x": 0.6134852766990662, "y": 0.04606150835752487 }, { "x": 0.6134852766990662, "y": 0.13333981484174728 }, { "x": 0.387196809053421, "y": 0.13333981484174728 } ], "category": "heading1", "id": 274, "content": { "text": "FURTHER\nRESOURCES\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3559660017490387, "y": 0.14487606287002563 }, { "x": 0.6488799750804901, "y": 0.14487606287002563 }, { "x": 0.6488799750804901, "y": 0.5006081461906433 }, { "x": 0.3559660017490387, "y": 0.5006081461906433 } ], "category": "figure", "id": 275, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.36797696352005005, "y": 0.5076140761375427 }, { "x": 0.6407165825366974, "y": 0.5076140761375427 }, { "x": 0.6407165825366974, "y": 0.9662884771823883 }, { "x": 0.36797696352005005, "y": 0.9662884771823883 } ], "category": "figure", "id": 276, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.6843909621238708, "y": 0.12865272164344788 }, { "x": 0.9780118465423584, "y": 0.12865272164344788 }, { "x": 0.9780118465423584, "y": 0.36187805235385895 }, { "x": 0.6843909621238708, "y": 0.36187805235385895 } ], "category": "paragraph", "id": 277, "content": { "text": "SEAGRASS\nIN SOUTH FLORIDA\nWHY IT IS IMPORTANT\n&\nWHAT YOU CAN DO\nCCO, 2022\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.6634335517883301, "y": 0.36899274587631226 }, { "x": 0.9988611042499542, "y": 0.36899274587631226 }, { "x": 0.9988611042499542, "y": 1.0 }, { "x": 0.6634335517883301, "y": 1.0 } ], "category": "figure", "id": 278, "content": { "text": "", "html": "", "markdown": "" } } ] }, "01030000000046.pdf": { "elements": [ { "coordinates": [ { "x": 0.08769087493419647, "y": 0.21386729180812836 }, { "x": 0.9252670854330063, "y": 0.21386729180812836 }, { "x": 0.9252670854330063, "y": 0.7458634227514267 }, { "x": 0.08769087493419647, "y": 0.7458634227514267 } ], "category": "table", "id": 254, "content": { "text": "", "html": "
No. Political party Provisional result on registration 7 MarchOfficial registration 29 result on AprilDifference in the number of candidates
Number of commune/ sangkatNumber of candidatesNumber of commune/ sangkatNumber of candidates
1Cambodian People's Party1,65228,0081,65228,0080
2Candlelight Party1,64923,6791,62323,939+260
3Funcinpec Party7159,4076809,952+545
4Khmer National United Party6508,3405968,815+475
5Cambodian National Love Party3884,6343155,050+416
6Cambodian National's Party3103,9802453,956-24
7Cambodian Youth Party1161,8241141,8240
8Khmer Will Party671,000581,050+50
9Cambodian Reform Party5882359978+155
10Kampucheaniyum Party3964238658+16
", "markdown": "" } }, { "coordinates": [ { "x": 0.5361712574958801, "y": 0.08437439054250717 }, { "x": 0.9207183718681335, "y": 0.08437439054250717 }, { "x": 0.9207183718681335, "y": 0.1040883157402277 }, { "x": 0.5361712574958801, "y": 0.1040883157402277 } ], "category": "header", "id": 347, "content": { "text": "Political Parties, Candidates Registration and Election Campaign\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0903683453798294, "y": 0.13522443175315857 }, { "x": 0.9201546460390091, "y": 0.13522443175315857 }, { "x": 0.9201546460390091, "y": 0.1935647949576378 }, { "x": 0.0903683453798294, "y": 0.1935647949576378 } ], "category": "paragraph", "id": 348, "content": { "text": "Table: Provisional Results of Registration of Candidates on 8 March 2022²¹ and Official Results\nof Registration of Candidates on 29 April 20222\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0902002826333046, "y": 0.8248338103294373 }, { "x": 0.31189412623643875, "y": 0.8248338103294373 }, { "x": 0.31189412623643875, "y": 0.8740464188158512 }, { "x": 0.0902002826333046, "y": 0.8740464188158512 } ], "category": "footer", "id": 350, "content": { "text": "21 https://www.nec.gov.kh/khmer/content/5393\n22 https://www.nec.gov.kh/khmer/content/5525\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.9060481786727905, "y": 0.8989138603210449 }, { "x": 0.9207244124263525, "y": 0.8989138603210449 }, { "x": 0.9207244124263525, "y": 0.9141131024807692 }, { "x": 0.9060481786727905, "y": 0.9141131024807692 } ], "category": "paragraph", "id": 351, "content": { "text": "23\n", "html": "", "markdown": "" } } ] }, "01030000000090.pdf": { "elements": [ { "coordinates": [ { "x": 0.11640753597021103, "y": 0.09011776000261307 }, { "x": 0.8830983266234398, "y": 0.09011776000261307 }, { "x": 0.8830983266234398, "y": 0.9041068032383919 }, { "x": 0.11640753597021103, "y": 0.9041068032383919 } ], "category": "table", "id": 290, "content": { "text": "", "html": "
JurisdictionGATS XVII Reservation (1994)Foreign Ownership PermittedRestrictions on Foreign OwnershipForeign Ownership Reporting Requirements
right required to acquire desert lands. No restrictions on lands in Investment Zones, Technological Zones, or Free Zones.
FinlandNYPrior approval for a foreigner's purchase of certain businesses may be required when it includes land purchase and the purchase of business or land interferes with vital interests for Finland; prior approval from the Government of Aland is required for acquisitions within the autonomous region of Aland.
FranceNYNone.
GermanyNYNone.
GreeceNYPrior approval required for purchase by non-European Union and non-European Free Trade Association natural and legal persons of real estate located in border areas.
IndiaNYProhibition on acquisition of land by citizens of Pakistan, Bangladesh, Sri Lanka, Afghanistan, China, Iran, Nepal, and Bhutan, except for one residential property for self-occupation and one property for carrying out self- employment for long-term visa holders residing in India who are citizens of Afghanistan, Bangladesh or Pakistan and belong to minority religions in those countries, subject to conditions; nonresident foreign nationals not of Indian origin, except for inheritance from a resident; and of agricultural land by diplomatic personnel,
", "markdown": "" } }, { "coordinates": [ { "x": 0.22936679422855377, "y": 0.047744203358888626 }, { "x": 0.7698635011911392, "y": 0.047744203358888626 }, { "x": 0.7698635011911392, "y": 0.0621696962043643 }, { "x": 0.22936679422855377, "y": 0.0621696962043643 } ], "category": "heading1", "id": 327, "content": { "text": "Restrictions on Land Ownership by Foreigners in Selected Jurisdictions\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11688791960477829, "y": 0.9406930208206177 }, { "x": 0.3387874588370323, "y": 0.9406930208206177 }, { "x": 0.3387874588370323, "y": 0.9548094989731908 }, { "x": 0.11688791960477829, "y": 0.9548094989731908 } ], "category": "footer", "id": 329, "content": { "text": "The Law Library of Congress\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8652338981628418, "y": 0.9411801099777222 }, { "x": 0.874321362003684, "y": 0.9411801099777222 }, { "x": 0.874321362003684, "y": 0.9509765859693289 }, { "x": 0.8652338981628418, "y": 0.9509765859693289 } ], "category": "paragraph", "id": 330, "content": { "text": "7\n", "html": "", "markdown": "" } } ] }, "01030000000110.pdf": { "elements": [ { "coordinates": [ { "x": 0.09276390820741653, "y": 0.4410345256328583 }, { "x": 0.9042966440320015, "y": 0.4410345256328583 }, { "x": 0.9042966440320015, "y": 0.7919503748416901 }, { "x": 0.09276390820741653, "y": 0.7919503748416901 } ], "category": "table", "id": 424, "content": { "text": "", "html": "
Temperature (degree C)Kinematic viscosity V (m²/s)Temperature (degree C)Kinematic viscosity V (m ²/s)
01.793E-06258.930E-07
11.732E-06268.760E-07
21.674E-06278.540E-07
31.619E-06288.360E-07
41.522E-06298.180E-07
51.520E-06308.020E-07
61.474E-06317.850E-07
71.429E-06327.690E-07
81.386E-06337.530E-07
91.346E-06347.380E-07
101.307E-06357.240E-07
111.270E-06367.110E-07
121.235E-06376.970E-07
131.201E-06386.840E-07
141.169E-06396.710E-07
151.138E-06406.580E-07
161.108E-06456.020E-07
171.080E-06505.540E-07
181.053E-06555.110E-07
191.027E-06604.760E-07
201.002E-06654.430E-07
219.780E-07704.130E-07
229.550E-07753.860E-07
239.330E-07803.630E-07
249.110E-07853.420E-07
", "markdown": "" } }, { "coordinates": [ { "x": 0.09201709926128387, "y": 0.07252154499292374 }, { "x": 0.9073005169630051, "y": 0.07252154499292374 }, { "x": 0.9073005169630051, "y": 0.12368310242891312 }, { "x": 0.09201709926128387, "y": 0.12368310242891312 } ], "category": "paragraph", "id": 531, "content": { "text": "in the flow. There is also a transitional stage between laminar and turbulent flows, in which the\ndye stream will wander about and show intermittent bursts of mixing, followed by a more laminar\nbehavior.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09181404113769531, "y": 0.144827201962471 }, { "x": 0.8333139419555664, "y": 0.144827201962471 }, { "x": 0.8333139419555664, "y": 0.16065486893057823 }, { "x": 0.09181404113769531, "y": 0.16065486893057823 } ], "category": "paragraph", "id": 532, "content": { "text": "The Reynolds number (Re), provides a useful way of characterizing the flow. It is defined as:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12514780461788177, "y": 0.18549597263336182 }, { "x": 0.14105409011244774, "y": 0.18549597263336182 }, { "x": 0.14105409011244774, "y": 0.18950096145272255 }, { "x": 0.12514780461788177, "y": 0.18950096145272255 } ], "category": "paragraph", "id": 533, "content": { "text": "=\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09163010120391846, "y": 0.21347224712371826 }, { "x": 0.906902551651001, "y": 0.21347224712371826 }, { "x": 0.906902551651001, "y": 0.24901743978261948 }, { "x": 0.09163010120391846, "y": 0.24901743978261948 } ], "category": "paragraph", "id": 534, "content": { "text": "where (v) is the kinematic viscosity of the water (Figure 7.2), V is the mean flow velocity and d is the\ndiameter of the pipe.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09208416193723679, "y": 0.2665519416332245 }, { "x": 0.9070146605372429, "y": 0.2665519416332245 }, { "x": 0.9070146605372429, "y": 0.3211648315191269 }, { "x": 0.09208416193723679, "y": 0.3211648315191269 } ], "category": "paragraph", "id": 535, "content": { "text": "The Reynolds number is a dimensionless parameter that is the ratio of the inertial (destabilizing) force\nto the viscosity (stabilizing) force. As Re increases, the inertial force becomes relatively larger, and the\nflow destabilizes and becomes fully turbulent.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09182910621166229, "y": 0.3385806679725647 }, { "x": 0.90730981528759, "y": 0.3385806679725647 }, { "x": 0.90730981528759, "y": 0.42902571707963943 }, { "x": 0.09182910621166229, "y": 0.42902571707963943 } ], "category": "paragraph", "id": 536, "content": { "text": "The Reynolds experiment determines the critical Reynolds number for pipe flow at which laminar\nflow (Re<2000) becomes transitional (20004000). The advantage of using a critical Reynolds number, instead of critical velocity, is that the\nresults of the experiments are applicable to all Newtonian fluid flows in pipes with a circular cross-\nsection.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09266728162765503, "y": 0.8085436224937439 }, { "x": 0.4727218747138977, "y": 0.8085436224937439 }, { "x": 0.4727218747138977, "y": 0.8199553545564413 }, { "x": 0.09266728162765503, "y": 0.8199553545564413 } ], "category": "paragraph", "id": 538, "content": { "text": "Figure 7.2: Kinematic Viscosity of Water at Atmospheric Pressure.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5336346626281738, "y": 0.941832959651947 }, { "x": 0.9061880707740784, "y": 0.941832959651947 }, { "x": 0.9061880707740784, "y": 0.9496780419722199 }, { "x": 0.5336346626281738, "y": 0.9496780419722199 } ], "category": "footer", "id": 539, "content": { "text": "EXPERIMENT #7: OSBORNE REYNOLDS DEMONSTRATION 61\n", "html": "", "markdown": "" } } ] }, "01030000000075.pdf": { "elements": [ { "coordinates": [ { "x": 0.1898810863494873, "y": 0.08407701551914215 }, { "x": 0.8803758025169373, "y": 0.08407701551914215 }, { "x": 0.8803758025169373, "y": 0.1495240181684494 }, { "x": 0.1898810863494873, "y": 0.1495240181684494 } ], "category": "paragraph", "id": 449, "content": { "text": "2020 and 2021, and, for approximately half of AMS, working hours lost were\nhigher in 2021 compared to 2020 (Figure 1.3). The disruptions in global supply\nchains because of travel and transport restrictions hit some AMS particularly\nhard because of supply needs from other countries.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.18943695724010468, "y": 0.16610297560691833 }, { "x": 0.8808668702840805, "y": 0.16610297560691833 }, { "x": 0.8808668702840805, "y": 0.40294933319091797 }, { "x": 0.18943695724010468, "y": 0.40294933319091797 } ], "category": "paragraph", "id": 450, "content": { "text": "Despite these tremendous job losses, many countries also experienced labour\nshortages due to previously unprecedented demand for certain products,\nsuch as rubber gloves in Malaysia and for fishery products in Thailand. The\nreturn of migrant workers to their home countries contributed to significant\nlabour shortages (Lee and David, 2021; Sriring and Staporncharnchai, 2021). 4\nCOVID-related movement restrictions caused many workers to withdraw\nfrom the labour force (especially women) and labour force participation rates\ndeclined in most countries. 5 This was the case for Indonesia, Malaysia, the\nPhilippines, and Viet Nam (Figure 1.4). According to the ILO (2021c), female\nemployment in AMS in 2020 was 3.9 percent lower than the expected level,\nwhich is markedly less than the 2.7 percent figure for male employment. 6\nThe impact of the pandemic on employment is evident in lower labour force\nparticipation, lower working hours, and higher unemployment rates in most\ncountries (Figure 1.5).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.19098623096942902, "y": 0.41908395290374756 }, { "x": 0.8476020842790604, "y": 0.41908395290374756 }, { "x": 0.8476020842790604, "y": 0.4334185943007469 }, { "x": 0.19098623096942902, "y": 0.4334185943007469 } ], "category": "paragraph", "id": 451, "content": { "text": "Figure 1.3. Decline in weekly working hours compared to 2019 (percent)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.18982623517513275, "y": 0.44650039076805115 }, { "x": 0.8815566748380661, "y": 0.44650039076805115 }, { "x": 0.8815566748380661, "y": 0.6856354773044586 }, { "x": 0.18982623517513275, "y": 0.6856354773044586 } ], "category": "figure", "id": 452, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.19012810289859772, "y": 0.6967325210571289 }, { "x": 0.3416188955307007, "y": 0.6967325210571289 }, { "x": 0.3416188955307007, "y": 0.7083634790033102 }, { "x": 0.19012810289859772, "y": 0.7083634790033102 } ], "category": "paragraph", "id": 453, "content": { "text": "Source: ILO (2022a)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14185327291488647, "y": 0.7946274876594543 }, { "x": 0.8807739019393921, "y": 0.7946274876594543 }, { "x": 0.8807739019393921, "y": 0.8269953913986683 }, { "x": 0.14185327291488647, "y": 0.8269953913986683 } ], "category": "paragraph", "id": 455, "content": { "text": "4\nThere are of course long-standing reasons for the labour shortages in these sectors, which accounts for\ntheir high reliance for migrant workers, including poor working conditions, that is prone to abuse, and lack\nof attractiveness for local workers (Looi, 2020; Ng, 2020; ILO, 2015).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14257752895355225, "y": 0.8297422528266907 }, { "x": 0.8808612823486328, "y": 0.8297422528266907 }, { "x": 0.8808612823486328, "y": 0.881416879594326 }, { "x": 0.14257752895355225, "y": 0.881416879594326 } ], "category": "paragraph", "id": 456, "content": { "text": "5\nMcKinsey Global Institute (2020) estimates that at the beginning of the pandemic, women accounted for\nmore than half of total job losses from COVID-19 though they made up only two-fifths of the global labour\nforce. This is because they are overrepresented in sectors hardest hit by the pandemic: accommodation\nand food services; retail and wholesale trade; and other services, such as arts, recreation, and public\nadministration.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1430756002664566, "y": 0.8859089612960815 }, { "x": 0.880343034863472, "y": 0.8859089612960815 }, { "x": 0.880343034863472, "y": 0.9180246405303478 }, { "x": 0.1430756002664566, "y": 0.9180246405303478 } ], "category": "paragraph", "id": 457, "content": { "text": "6\nThis is equivalent to saying there is greater increase in unemployment or inactivity for women compared\nto men. According to the report, one reason is the increase in unpaid care responsibilities for women as\nschools closed (ILO, 2021c).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14079849421977997, "y": 0.9519280195236206 }, { "x": 0.4196150451898575, "y": 0.9519280195236206 }, { "x": 0.4196150451898575, "y": 0.9666325869038701 }, { "x": 0.14079849421977997, "y": 0.9666325869038701 } ], "category": "footer", "id": 458, "content": { "text": "ASEAN Migration Outlook\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.929643988609314, "y": 0.9527359008789062 }, { "x": 0.9513212498277426, "y": 0.9527359008789062 }, { "x": 0.9513212498277426, "y": 0.9634732371196151 }, { "x": 0.929643988609314, "y": 0.9634732371196151 } ], "category": "paragraph", "id": 459, "content": { "text": "15\n", "html": "", "markdown": "" } } ] }, "01030000000011.pdf": { "elements": [ { "coordinates": [ { "x": 0.1035962700843811, "y": 0.04987356439232826 }, { "x": 0.11985750310122967, "y": 0.04987356439232826 }, { "x": 0.11985750310122967, "y": 0.05809989292174578 }, { "x": 0.1035962700843811, "y": 0.05809989292174578 } ], "category": "paragraph", "id": 548, "content": { "text": "84\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.850917637348175, "y": 0.05040636658668518 }, { "x": 0.89539560303092, "y": 0.05040636658668518 }, { "x": 0.89539560303092, "y": 0.05799596616998315 }, { "x": 0.850917637348175, "y": 0.05799596616998315 } ], "category": "header", "id": 549, "content": { "text": "BAIRD\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10889021307229996, "y": 0.0815391093492508 }, { "x": 0.4822543039917946, "y": 0.0815391093492508 }, { "x": 0.4822543039917946, "y": 0.4448903948068619 }, { "x": 0.10889021307229996, "y": 0.4448903948068619 } ], "category": "figure", "id": 550, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10370887815952301, "y": 0.462276428937912 }, { "x": 0.4859014302492142, "y": 0.462276428937912 }, { "x": 0.4859014302492142, "y": 0.5037945471704006 }, { "x": 0.10370887815952301, "y": 0.5037945471704006 } ], "category": "paragraph", "id": 551, "content": { "text": "FIGURE 4.11 A. Birrell, Sir Robert Shirley [graphic]. Engraving\non wove paper.\nPUBLISHED BY EDWARD HARDING, LONDON, 1799\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10228294879198074, "y": 0.5216037631034851 }, { "x": 0.4871719852089882, "y": 0.5216037631034851 }, { "x": 0.4871719852089882, "y": 0.8298143446445465 }, { "x": 0.10228294879198074, "y": 0.8298143446445465 } ], "category": "paragraph", "id": 552, "content": { "text": "knowledge about remote civilizations. There is an\nobvious cultural coincidence, for instance, between\ncarpet-making and storytelling among nomadic\npeoples, which these stories convey through their\nintricate plot development. They also tell fascinat-\ning stories about the the traffic in diamonds, gold,\nand spices between the Indies, China, Arabia, and\nWestern Europe that still wait to be unveiled. Rather\nthan looking at the things of the Nights as colorful\ndetails in Sheherazade's tales or protagonists in the\nfantastic stories they make for themselves, we could\nexplore, instead, their role as as bearers of cultural\nknowledge unintentionally embedded in the fabric\nof the text. In such a reading, \"historically and theo-\nretically overdetermined material charactersitics\nof objects are sought out beyond the immediate\ncontext in which they appear\" \"86 in order to\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5110616683959961, "y": 0.08249150961637497 }, { "x": 0.8972749412059784, "y": 0.08249150961637497 }, { "x": 0.8972749412059784, "y": 0.792585127055645 }, { "x": 0.5110616683959961, "y": 0.792585127055645 } ], "category": "paragraph", "id": 553, "content": { "text": "defetishize them and expose the power structures\nin which they are involved.\nThus, as Makdisi and Nussbaum sum up in their\nintroduction to The Arabian Nights in Historical\nContext: Between East and West, \"the Nights offered\na particularly powerful vision of an Asiatic culture\nseemingly saturated with references to sensuality,\nextravagance, indulgence, violence, supernatural-\nism, and eroticism [and] added a supernatural\ndimension to the Enlightenment; the tales offered\nan avenue into modernity through its magical op-\nposite, an alternative to European identity, and an\nantidote to neoclassicism.\"87 However, reading\nsuch imports as an expression of European pow-\ners' disavowal of the East in order to \"justify their\nconquest and rule over other peoples, particularly\nin\nAsia,\"88 is an oversimplification of a rather com-\nplicated process of cultural exchange. None of\nthese descriptions of Arabia were caused by colo-\nnial \"distortions,\" as Said feared, but by false attri-\nbutions: \"Arabian\" was a misnomer that rarely de-\nscribed Arabia itself. While fictional narratives like\nArabian Nights' Entertainments represented Ara-\nbia as a land of magic and exorbitant riches, they\nwere too far-fetched to be part of a Westerner's\nbelief system during the Age of Reason; rather,\nthey were popularized because their wild fiction-\nality turned them into bestsellers at the time. Such\nstories competed with descriptions of the Arabi-\nan Peninsula by travelers and traders who had vis-\nited the area and had unmediated contact with the\nlocal culture. However, while the Orientalist litera-\nture described Arabia in terms that emphasized\nits exoticism, magic, superstitions, extravagance,\nwealth, eroticism, excess, and myriads of other pe-\nculiarities that contrasted it with the European\nnormativity, travel narratives created an \"Arabian\"\nidentity that was generally congruent with the\nreality of the place.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1030462458729744, "y": 0.8578222990036011 }, { "x": 0.4863953962922096, "y": 0.8578222990036011 }, { "x": 0.4863953962922096, "y": 0.9184581376612186 }, { "x": 0.1030462458729744, "y": 0.9184581376612186 } ], "category": "footer", "id": 554, "content": { "text": "86\nElaine Freedgood, \"Introduction: Reading Things,\" in\nThe Idea in Things: Fugitive Meaning in the Victorian\nNovel (Chicago: University of Chicago Press, 2006),\n5-6.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5126389861106873, "y": 0.8739372491836548 }, { "x": 0.8955887258052826, "y": 0.8739372491836548 }, { "x": 0.8955887258052826, "y": 0.9168812371790409 }, { "x": 0.5126389861106873, "y": 0.9168812371790409 } ], "category": "footer", "id": 555, "content": { "text": "87\nMakdisi and Nussbaum, introduction to The Arabian\nNights in Historical Context, 5.\n88\nIbid.\n", "html": "", "markdown": "" } } ] }, "01030000000021.pdf": { "elements": [ { "coordinates": [ { "x": 0.4706782400608063, "y": 0.21233253180980682 }, { "x": 0.5020885318517685, "y": 0.21233253180980682 }, { "x": 0.5020885318517685, "y": 0.2430087849497795 }, { "x": 0.4706782400608063, "y": 0.2430087849497795 } ], "category": "header", "id": 339, "content": { "text": "2\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.2603497803211212, "y": 0.27586355805397034 }, { "x": 0.7114243805408478, "y": 0.27586355805397034 }, { "x": 0.7114243805408478, "y": 0.30334402061998844 }, { "x": 0.2603497803211212, "y": 0.30334402061998844 } ], "category": "heading1", "id": 340, "content": { "text": "The Lost Homeland\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1294216811656952, "y": 0.37404951453208923 }, { "x": 0.8431525528430939, "y": 0.37404951453208923 }, { "x": 0.8431525528430939, "y": 0.5904252827167511 }, { "x": 0.1294216811656952, "y": 0.5904252827167511 } ], "category": "paragraph", "id": 341, "content": { "text": "Since the death of my mother, Elfriede, ten years ago, I have been haunted\nby the desire to visit the homeland, the Heimat, that she never saw again\nafter her fifty years in Australia. In more ways than one, Germany had\nbecome her lost homeland, the spiritual place of her ancestors from\nwhich she was exiled. I sensed the pain she felt over the tangible loss\nof connection to her own past. For me to be able to go SO far away and\npay tribute to her German home in what is now Poland, to savour the\nenvironment of her childhood, at first seemed impossible. I nevertheless\nhoped for the opportunity to do so, although I expected to find all the\nnames of the places changed, and that people spoke a language I did not\nunderstand. It would be confronting to go there, I thought.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1296548843383789, "y": 0.6056718826293945 }, { "x": 0.8431669473648071, "y": 0.6056718826293945 }, { "x": 0.8431669473648071, "y": 0.782743975520134 }, { "x": 0.1296548843383789, "y": 0.782743975520134 } ], "category": "paragraph", "id": 342, "content": { "text": "When in 1997 I visited Vienna, my father's Austrian birth city, and after\nthat my German cousins in Germany, I was not regarded as a stranger.\nDespite being an almost lifelong Australian, I spoke their language and\nsomehow belonged. I was accepted by people as someone who had come\nhome to reclaim my heritage. I could merge with crowds unobtrusively,\nlike a 'local'. The only subtle tremors of feeling generated by what people\nare used to were shown up in my too-German ways for the Austrians,\nand my too-Austrian ways for the Germans. The Austrians reacted more\nfirmly. This suggests that my mother's influence on me was strongest.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1294940710067749, "y": 0.7975122928619385 }, { "x": 0.8434677124023438, "y": 0.7975122928619385 }, { "x": 0.8434677124023438, "y": 0.8747261315584183 }, { "x": 0.1294940710067749, "y": 0.8747261315584183 } ], "category": "paragraph", "id": 343, "content": { "text": "I was born in Turkey, north of Ankara, in 1935, and when I also went\nthere on my trip home, I was treated to a special welcome by each Turk\nwho found this out, from my passport or my conversation. My birth\nin Turkey entitled me to Turkish citizenship. Naturally I was delighted,\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8987698554992676, "y": 0.9316176772117615 }, { "x": 0.9074561996385455, "y": 0.9316176772117615 }, { "x": 0.9074561996385455, "y": 0.9411181677132845 }, { "x": 0.8987698554992676, "y": 0.9411181677132845 } ], "category": "paragraph", "id": 344, "content": { "text": "5\n", "html": "", "markdown": "" } } ] }, "01030000000199.pdf": { "elements": [ { "coordinates": [ { "x": 0.05164903774857521, "y": 0.2942289113998413 }, { "x": 0.9517572559416294, "y": 0.2942289113998413 }, { "x": 0.9517572559416294, "y": 0.38528716564178467 }, { "x": 0.05164903774857521, "y": 0.38528716564178467 } ], "category": "table", "id": 289, "content": { "text": "", "html": "
Upstage universal OCR model E2E performanceUpstage universal OCR model performance details: Document
evaluation 1criteria
", "markdown": "" } }, { "coordinates": [ { "x": 0.04867791011929512, "y": 0.07001718878746033 }, { "x": 0.212572131305933, "y": 0.07001718878746033 }, { "x": 0.212572131305933, "y": 0.09259925596415997 }, { "x": 0.04867791011929512, "y": 0.09259925596415997 } ], "category": "header", "id": 296, "content": { "text": "Overview of OCR Pack\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.04801333323121071, "y": 0.1229185238480568 }, { "x": 0.7135160602629185, "y": 0.1229185238480568 }, { "x": 0.7135160602629185, "y": 0.16673879325389862 }, { "x": 0.04801333323121071, "y": 0.16673879325389862 } ], "category": "heading1", "id": 297, "content": { "text": "Base Model Performance Evaluation of Upstage OCR Pack\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.051881685853004456, "y": 0.2991115152835846 }, { "x": 0.39417894184589386, "y": 0.2991115152835846 }, { "x": 0.39417894184589386, "y": 0.3757556304335594 }, { "x": 0.051881685853004456, "y": 0.3757556304335594 } ], "category": "paragraph", "id": 298, "content": { "text": "Upstage universal OCR model E2E performance\nevaluation\n1\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.06980647146701813, "y": 0.4333023726940155 }, { "x": 0.40928082168102264, "y": 0.4333023726940155 }, { "x": 0.40928082168102264, "y": 0.8244478106498718 }, { "x": 0.06980647146701813, "y": 0.8244478106498718 } ], "category": "figure", "id": 299, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5028468370437622, "y": 0.29927510023117065 }, { "x": 0.9486707448959351, "y": 0.29927510023117065 }, { "x": 0.9486707448959351, "y": 0.37616923451423645 }, { "x": 0.5028468370437622, "y": 0.37616923451423645 } ], "category": "paragraph", "id": 300, "content": { "text": "Upstage universal OCR model performance details: Document\ncriteria\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.48030659556388855, "y": 0.47564461827278137 }, { "x": 0.4871199387125671, "y": 0.47564461827278137 }, { "x": 0.4871199387125671, "y": 0.4860532023012638 }, { "x": 0.48030659556388855, "y": 0.4860532023012638 } ], "category": "paragraph", "id": 301, "content": { "text": "11\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5186072587966919, "y": 0.4064446687698364 }, { "x": 0.9544561207294464, "y": 0.4064446687698364 }, { "x": 0.9544561207294464, "y": 0.8140383362770081 }, { "x": 0.5186072587966919, "y": 0.8140383362770081 } ], "category": "figure", "id": 302, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0725969448685646, "y": 0.9162847995758057 }, { "x": 0.4823935404419899, "y": 0.9162847995758057 }, { "x": 0.4823935404419899, "y": 0.973790992051363 }, { "x": 0.0725969448685646, "y": 0.973790992051363 } ], "category": "paragraph", "id": 303, "content": { "text": "1 Performance based on universal model, additional performance improvement is possible by implementing specialized\nmodels according to business requirements\n2\nA: Universal model of global leading Al company / B: Universal model of leading AI company in Korea, 2022. 5 Test criteria\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5540534853935242, "y": 0.890697717666626 }, { "x": 0.8897584974765778, "y": 0.890697717666626 }, { "x": 0.8897584974765778, "y": 0.9929917529225349 }, { "x": 0.5540534853935242, "y": 0.9929917529225349 } ], "category": "paragraph", "id": 304, "content": { "text": "3 Recall: Percentage of what the OCR model predicted to be True from those that were actually True\n4 Precision: Percentage of what the OCR model classifies as True, which is actually True\n5 F1: Harmonic mean value of Recall and Precision\n6. Parsing-F1: Comparison of parsing model F1 of both companies for business registration document\nform. Company A is excluded from comparison due to the absence of the document parsing model.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.9250231981277466, "y": 0.9512915015220642 }, { "x": 0.9618569239974022, "y": 0.9512915015220642 }, { "x": 0.9618569239974022, "y": 0.9680717084556818 }, { "x": 0.9250231981277466, "y": 0.9680717084556818 } ], "category": "paragraph", "id": 305, "content": { "text": "upstage\n", "html": "", "markdown": "" } } ] }, "01030000000178.pdf": { "elements": [ { "coordinates": [ { "x": 0.11553215980529785, "y": 0.21256594359874725 }, { "x": 0.8836781978607178, "y": 0.21256594359874725 }, { "x": 0.8836781978607178, "y": 0.47746364772319794 }, { "x": 0.11553215980529785, "y": 0.47746364772319794 } ], "category": "table", "id": 444, "content": { "text": "", "html": "
Communication ChannelMediumExamples
Direct communicationsPhysical or digitalmeetings, consultations, listening sessions, email lists
Indirect communicationsPrimarily digitalwebsites, videos, news articles, newsletters, social media posts,
MessagingPhysical or digitalbrochures, posters, signs, booklets
EventsPhysical or digitalpresentations, webinars, seminars, panels, training sessions
InteractivePhysical or digitalOER \"petting zoos,\" games, exhibits, surveys
GoodiesPrimarily physicalpens, notepads, bookmarks, stickers, buttons, etc
", "markdown": "" } }, { "coordinates": [ { "x": 0.11674012988805771, "y": 0.07589328289031982 }, { "x": 0.3814907893538475, "y": 0.07589328289031982 }, { "x": 0.3814907893538475, "y": 0.09193743579089642 }, { "x": 0.11674012988805771, "y": 0.09193743579089642 } ], "category": "heading1", "id": 467, "content": { "text": "Promotional Materials\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11529722064733505, "y": 0.11940257996320724 }, { "x": 0.8834381923079491, "y": 0.11940257996320724 }, { "x": 0.8834381923079491, "y": 0.17208240553736687 }, { "x": 0.11529722064733505, "y": 0.17208240553736687 } ], "category": "paragraph", "id": 468, "content": { "text": "A good promotional strategy should include multiple facets, from physical materials to digital\ncommunications. Below, we've compiled a table of promotional materials you might use on\ncampus, and examples of each type.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.3490264117717743, "y": 0.19393162429332733 }, { "x": 0.6500202715396881, "y": 0.19393162429332733 }, { "x": 0.6500202715396881, "y": 0.20579567831009626 }, { "x": 0.3490264117717743, "y": 0.20579567831009626 } ], "category": "paragraph", "id": 469, "content": { "text": "Table 7.1. Types of promotional materials\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11564220488071442, "y": 0.5006645321846008 }, { "x": 0.8837427049875259, "y": 0.5006645321846008 }, { "x": 0.8837427049875259, "y": 0.6329858005046844 }, { "x": 0.11564220488071442, "y": 0.6329858005046844 } ], "category": "paragraph", "id": 471, "content": { "text": "Get in contact with partners at your institution to learn more about the processes and options\navailable to you and how you can best leverage the support at your disposal. If you have a\nmarketing team available to you that orders pens and other materials for campus events, get in\ncontact with them about their vendors and how you can leverage their existing workflows for\nordering materials to support your OER Program. This might be as simple as ordering buttons and\nposters through your University Printing Office, or it may require you to browse a third party's\nmarketing catalog or to create materials yourself, if you lack funding for your work.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11485274136066437, "y": 0.661232590675354 }, { "x": 0.2653369754552841, "y": 0.661232590675354 }, { "x": 0.2653369754552841, "y": 0.675383361056447 }, { "x": 0.11485274136066437, "y": 0.675383361056447 } ], "category": "heading1", "id": 472, "content": { "text": "Annual Events\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11532162874937057, "y": 0.7004004716873169 }, { "x": 0.8846782967448235, "y": 0.7004004716873169 }, { "x": 0.8846782967448235, "y": 0.9126980751752853 }, { "x": 0.11532162874937057, "y": 0.9126980751752853 } ], "category": "paragraph", "id": 473, "content": { "text": "Creating promotional materials and graphics can make your OER program recognizable on your\ncollege's campus, but just because you've created materials doesn't mean that people will find or\nlearn from them. As a program manager, you will need to find ways to implement your messaging\nand events on campus. Leveraging annual events like Open Education Week in March and\nInternational Open Access Week in October can ground your work in a given time of year and\nfocus your programming around a topic or theme (Open Education Global, n.d.; SPARC, n.d.).\nThe Open Education Week website lists past events and provides downloadable promotional\nmaterials to help you kickstart your event planning and coordination. If these weeks regularly\nconflict with other events at your institution, that's okay. You can celebrate Open Education Week\nthe week before or after it falls. So long as you are consistent in the general time you hold these\nevents, they will still gain recognition at your institution and faculty will come to expect them.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11533860117197037, "y": 0.9415215253829956 }, { "x": 0.13188796862959862, "y": 0.9415215253829956 }, { "x": 0.13188796862959862, "y": 0.9505314063280821 }, { "x": 0.11533860117197037, "y": 0.9505314063280821 } ], "category": "paragraph", "id": 474, "content": { "text": "92\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15606679022312164, "y": 0.941440999507904 }, { "x": 0.33365440368652344, "y": 0.941440999507904 }, { "x": 0.33365440368652344, "y": 0.9504817212000489 }, { "x": 0.15606679022312164, "y": 0.9504817212000489 } ], "category": "footer", "id": 475, "content": { "text": "PROGRAM MANAGEMENT\n", "html": "", "markdown": "" } } ] }, "01030000000044.pdf": { "elements": [ { "coordinates": [ { "x": 0.16221562027931213, "y": 0.18004556000232697 }, { "x": 0.8908676207065582, "y": 0.18004556000232697 }, { "x": 0.8908676207065582, "y": 0.5480738133192062 }, { "x": 0.16221562027931213, "y": 0.5480738133192062 } ], "category": "table", "id": 64, "content": { "text": "", "html": "
Executive Summary4
Legal Framework6
Election Administration11
Civil Society Engagement15
Political Parties, Candidates Registration and Election Campaign18
Media Freedom and Access to Information25
Voter Education and Awareness29
Participation of Marginalized Sectors31
Recommendations39
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86, "content": { "text": "4\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.17279930412769318, "y": 0.22491422295570374 }, { "x": 0.36801621317863464, "y": 0.22491422295570374 }, { "x": 0.36801621317863464, "y": 0.2416694387793541 }, { "x": 0.17279930412769318, "y": 0.2416694387793541 } ], "category": "paragraph", "id": 87, "content": { "text": "Legal Framework\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8654496669769287, "y": 0.22521190345287323 }, { "x": 0.8780291061848402, "y": 0.22521190345287323 }, { "x": 0.8780291061848402, "y": 0.23810633271932602 }, { "x": 0.8654496669769287, "y": 0.23810633271932602 } ], "category": "paragraph", "id": 88, "content": { "text": "6\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.17252932488918304, "y": 0.26389455795288086 }, { "x": 0.4379066377878189, "y": 0.26389455795288086 }, { "x": 0.4379066377878189, "y": 0.2781235324218869 }, { "x": 0.17252932488918304, "y": 0.2781235324218869 } ], "category": "paragraph", "id": 89, "content": { "text": "Election Administration\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8555153608322144, "y": 0.2647077739238739 }, { "x": 0.8753696363419294, "y": 0.2647077739238739 }, { "x": 0.8753696363419294, "y": 0.2774709118530154 }, { "x": 0.8555153608322144, "y": 0.2774709118530154 } ], "category": "paragraph", "id": 90, "content": { "text": "11\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1724291294813156, "y": 0.30341190099716187 }, { "x": 0.463852122426033, "y": 0.30341190099716187 }, { "x": 0.463852122426033, "y": 0.3211772870272398 }, { "x": 0.1724291294813156, "y": 0.3211772870272398 } ], "category": "paragraph", "id": 91, "content": { "text": "Civil Society Engagement\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8537887930870056, "y": 0.304471492767334 }, { "x": 0.8782779574394226, "y": 0.304471492767334 }, { "x": 0.8782779574394226, "y": 0.3174426620826125 }, { "x": 0.8537887930870056, "y": 0.3174426620826125 } ], "category": "paragraph", "id": 92, "content": { "text": "15\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.172468364238739, "y": 0.34523624181747437 }, { "x": 0.7843419313430786, "y": 0.34523624181747437 }, { "x": 0.7843419313430786, "y": 0.3828669637441635 }, { "x": 0.172468364238739, "y": 0.3828669637441635 } ], "category": "paragraph", "id": 93, "content": { "text": "Political Parties, Candidates Registration and Election\nCampaign\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8538841009140015, "y": 0.34608525037765503 }, { "x": 0.8778876829892397, "y": 0.34608525037765503 }, { "x": 0.8778876829892397, "y": 0.35898550041019917 }, { "x": 0.8538841009140015, "y": 0.35898550041019917 } ], "category": "paragraph", "id": 94, "content": { "text": "18\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.17281310260295868, "y": 0.4072706699371338 }, { "x": 0.6509975343942642, "y": 0.4072706699371338 }, { "x": 0.6509975343942642, "y": 0.42177222948521376 }, { "x": 0.17281310260295868, "y": 0.42177222948521376 } ], "category": "paragraph", "id": 95, "content": { "text": "Media Freedom and Access to Information\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.852042555809021, "y": 0.4082077741622925 }, { "x": 0.8781249709427357, "y": 0.4082077741622925 }, { "x": 0.8781249709427357, "y": 0.42142209596931934 }, { "x": 0.852042555809021, "y": 0.42142209596931934 } ], "category": "paragraph", "id": 96, "content": { "text": "25\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1710420399904251, "y": 0.4469352662563324 }, { "x": 0.532174751162529, "y": 0.4469352662563324 }, { "x": 0.532174751162529, "y": 0.46127826906740665 }, { "x": 0.1710420399904251, "y": 0.46127826906740665 } ], "category": "paragraph", "id": 97, "content": { "text": "Voter Education and Awareness\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8521855473518372, "y": 0.4478191137313843 }, { "x": 0.8779466319829226, "y": 0.4478191137313843 }, { "x": 0.8779466319829226, "y": 0.4608632018789649 }, { "x": 0.8521855473518372, "y": 0.4608632018789649 } ], "category": "paragraph", "id": 98, "content": { "text": "29\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1732274293899536, "y": 0.4842059314250946 }, { "x": 0.5898290276527405, "y": 0.4842059314250946 }, { "x": 0.5898290276527405, "y": 0.5019915197044611 }, { "x": 0.1732274293899536, "y": 0.5019915197044611 } ], "category": "paragraph", "id": 99, "content": { "text": "Participation of Marginalized Sectors\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.85237056016922, "y": 0.4849931299686432 }, { "x": 0.8752402532845736, "y": 0.4849931299686432 }, { "x": 0.8752402532845736, "y": 0.49782226979732513 }, { "x": 0.85237056016922, "y": 0.49782226979732513 } ], "category": "paragraph", "id": 100, "content": { "text": "31\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.17277590930461884, "y": 0.5219342708587646 }, { "x": 0.38387231528759, "y": 0.5219342708587646 }, { "x": 0.38387231528759, "y": 0.5357803804799914 }, { "x": 0.17277590930461884, "y": 0.5357803804799914 } ], "category": "paragraph", "id": 101, "content": { "text": "Recommendations\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8524172306060791, "y": 0.5224020481109619 }, { "x": 0.8780170399695635, "y": 0.5224020481109619 }, { "x": 0.8780170399695635, "y": 0.5353647079318762 }, { "x": 0.8524172306060791, "y": 0.5353647079318762 } ], "category": "paragraph", "id": 102, "content": { "text": "39\n", "html": "", "markdown": "" } } ] }, "01030000000100.pdf": { "elements": [ { "coordinates": [ { "x": 0.11803387105464935, "y": 0.08624923974275589 }, { "x": 0.8907881826162338, "y": 0.08624923974275589 }, { "x": 0.8907881826162338, "y": 0.41841552406549454 }, { "x": 0.11803387105464935, "y": 0.41841552406549454 } ], "category": "figure", "id": 165, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11515598744153976, "y": 0.44611477851867676 }, { "x": 0.8941832706332207, "y": 0.44611477851867676 }, { "x": 0.8941832706332207, "y": 0.7756443917751312 }, { "x": 0.11515598744153976, "y": 0.7756443917751312 } ], "category": "figure", "id": 166, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10277752578258514, "y": 0.7882518172264099 }, { "x": 0.20509222894906998, "y": 0.7882518172264099 }, { "x": 0.20509222894906998, "y": 0.7989071514457464 }, { "x": 0.10277752578258514, "y": 0.7989071514457464 } ], "category": "paragraph", "id": 167, "content": { "text": "(Yoeli et al. 2013)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09175630658864975, "y": 0.8144433498382568 }, { "x": 0.9069429859519005, "y": 0.8144433498382568 }, { "x": 0.9069429859519005, "y": 0.928177498281002 }, { "x": 0.09175630658864975, "y": 0.928177498281002 } ], "category": "paragraph", "id": 168, "content": { "text": "On a final note, Yoeli et al. provide evidence that indirect reciprocity among Homo sapiens is unique\nto public goods. Their hypothesis is that choosing not to participate in a demand response program\nshould carry the threat of social sanctions only if participation is considered to be for the public good.\nTo test their hypothesis, the authors solicited an additional 1,000 customers with exactly the same\ntreatments as described above, except that the informational materials the customers received ahead\nof time to entice them to participate in the demand response program were stripped of any language\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.6405817270278931, "y": 0.9509419202804565 }, { "x": 0.9062611162662506, "y": 0.9509419202804565 }, { "x": 0.9062611162662506, "y": 0.9588031675666571 }, { "x": 0.6405817270278931, "y": 0.9588031675666571 } ], "category": "footer", "id": 169, "content": { "text": "BEHAVIORAL ECONOMICS PRACTICUM 213\n", "html": "", "markdown": "" } } ] }, "01030000000122.pdf": { "elements": [ { "coordinates": [ { "x": 0.13683098554611206, "y": 0.12073720246553421 }, { "x": 0.8441974520683289, "y": 0.12073720246553421 }, { "x": 0.8441974520683289, "y": 0.23904671519994736 }, { "x": 0.13683098554611206, "y": 0.23904671519994736 } ], "category": "table", "id": 366, "content": { "text": "", "html": "
TubeBamHI-HindIII restriction enzyme mixtureRestriction Buffer-RNaseSuspect 1 DNASuspect 2 DNAEvidence A or BH2O
S13 uL3 uL10 uL2 uL
S23 uL3 uL10 uL2 uL
EA or EB3 uL3 uL10 uL2 uL
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Mix reagents by pipetting gently up and down.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11756027489900589, "y": 0.3001974821090698 }, { "x": 0.495540089905262, "y": 0.3001974821090698 }, { "x": 0.495540089905262, "y": 0.31039951276034117 }, { "x": 0.11756027489900589, "y": 0.31039951276034117 } ], "category": "paragraph", "id": 402, "content": { "text": "4. Incubate all of the reaction tubes for 1 hour at 37 °C.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1173577606678009, "y": 0.3323407471179962 }, { "x": 0.8298198878765106, "y": 0.3323407471179962 }, { "x": 0.8298198878765106, "y": 0.34535988047719 }, { "x": 0.1173577606678009, "y": 0.34535988047719 } ], "category": "paragraph", "id": 403, "content": { "text": "NOTE: Your instructor will freeze your completed restriction digests at -20 °C until the next lab period.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11744703352451324, "y": 0.3659067749977112 }, { "x": 0.35446280241012573, "y": 0.3659067749977112 }, { "x": 0.35446280241012573, "y": 0.3806368922814727 }, { "x": 0.11744703352451324, "y": 0.3806368922814727 } ], "category": "heading1", "id": 404, "content": { "text": "III. Electrophorese Digests\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11773451417684555, "y": 0.4007108807563782 }, { "x": 0.1776874028146267, "y": 0.4007108807563782 }, { "x": 0.1776874028146267, "y": 0.41153011191636324 }, { "x": 0.11773451417684555, "y": 0.41153011191636324 } ], "category": "paragraph", "id": 405, "content": { "text": "Reagents:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14720523357391357, "y": 0.4318215847015381 }, { "x": 0.41278329491615295, "y": 0.4318215847015381 }, { "x": 0.41278329491615295, "y": 0.44298283103853464 }, { "x": 0.14720523357391357, "y": 0.44298283103853464 } ], "category": "paragraph", "id": 407, "content": { "text": "Restriction digests from Part II, on ice\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.147213414311409, "y": 0.44577381014823914 }, { "x": 0.3176106661558151, "y": 0.44577381014823914 }, { "x": 0.3176106661558151, "y": 0.45699264481663704 }, { "x": 0.147213414311409, "y": 0.45699264481663704 } ], "category": "paragraph", "id": 408, "content": { "text": "10x loading dye, 10 uL\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11729677021503448, "y": 0.4767304062843323 }, { "x": 0.27054935693740845, "y": 0.4767304062843323 }, { "x": 0.27054935693740845, "y": 0.48802229948341846 }, { "x": 0.11729677021503448, "y": 0.48802229948341846 } ], "category": "paragraph", "id": 409, "content": { "text": "Supplies and Equipment\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14703434705734253, "y": 0.5083366632461548 }, { "x": 0.6201671063899994, "y": 0.5083366632461548 }, { "x": 0.6201671063899994, "y": 0.5197349479421973 }, { "x": 0.14703434705734253, "y": 0.5197349479421973 } ], "category": "paragraph", "id": 411, "content": { "text": "Gel electrophoresis chamber with agarose gel in gel tray, power supply\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14725850522518158, "y": 0.5225399136543274 }, { "x": 0.39844007790088654, "y": 0.5225399136543274 }, { "x": 0.39844007790088654, "y": 0.5337047437205911 }, { "x": 0.14725850522518158, "y": 0.5337047437205911 } ], "category": "paragraph", "id": 412, "content": { "text": "1-20 uL Micropipette and pipet tips\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11744903773069382, "y": 0.5538215041160583 }, { "x": 0.21886204183101654, "y": 0.5538215041160583 }, { "x": 0.21886204183101654, "y": 0.5647266386076808 }, { "x": 0.11744903773069382, "y": 0.5647266386076808 } ], "category": "heading1", "id": 413, "content": { "text": "Load the Gel\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11783475428819656, "y": 0.5874385237693787 }, { "x": 0.875321514904499, "y": 0.5874385237693787 }, { "x": 0.875321514904499, "y": 0.629467211663723 }, { "x": 0.11783475428819656, "y": 0.629467211663723 } ], "category": "paragraph", "id": 415, "content": { "text": "1. Use a micropipette to add 2 uL of 10x loading dye to a reaction tube. Use the pipet tip and gently pipet up\nand down a couple of times to mix the 10x loading dye with the digested DNA. Use a new pipet tip and repeat\nfor each digest.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11722330003976822, "y": 0.6496493816375732 }, { "x": 0.8568008914589882, "y": 0.6496493816375732 }, { "x": 0.8568008914589882, "y": 0.6771459560841322 }, { "x": 0.11722330003976822, "y": 0.6771459560841322 } ], "category": "paragraph", "id": 416, "content": { "text": "2. Use a micropipette to load the contents of each reaction tube (20 uL total) into a separate well in the gel.\nUse a fresh pipet tip for each reaction tube and write down the order in which the samples are loaded.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11785814166069031, "y": 0.7293946146965027 }, { "x": 0.7308114469051361, "y": 0.7293946146965027 }, { "x": 0.7308114469051361, "y": 0.7420349847525358 }, { "x": 0.11785814166069031, "y": 0.7420349847525358 } ], "category": "paragraph", "id": 417, "content": { "text": "NOTE: Be careful not to punch the tip of the pipet through the bottom or side of the well.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11726823449134827, "y": 0.7941931486129761 }, { "x": 0.2166806235909462, "y": 0.7941931486129761 }, { "x": 0.2166806235909462, "y": 0.80665825586766 }, { "x": 0.11726823449134827, "y": 0.80665825586766 } ], "category": "paragraph", "id": 418, "content": { "text": "While loading,\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.20625761151313782, "y": 0.8275315165519714 }, { "x": 0.8791580498218536, "y": 0.8275315165519714 }, { "x": 0.8791580498218536, "y": 0.8553209714591503 }, { "x": 0.20625761151313782, "y": 0.8553209714591503 } ], "category": "paragraph", "id": 420, "content": { "text": "steady the pipet over the well using two hands. You may wish to place one or both elbows on\nthe lab bench to steady your hands.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.2062758356332779, "y": 0.8578058481216431 }, { "x": 0.87299545109272, "y": 0.8578058481216431 }, { "x": 0.87299545109272, "y": 0.8850501105189323 }, { "x": 0.2062758356332779, "y": 0.8850501105189323 } ], "category": "paragraph", "id": 421, "content": { "text": "be careful to expel any air in the pipet tip end before loading the gel. If an air bubble forms a\ncap over the well, the sample will flow into the buffer around the edges of the well.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.4858689606189728, "y": 0.9251991510391235 }, { "x": 0.5141609311103821, "y": 0.9251991510391235 }, { "x": 0.5141609311103821, "y": 0.9359081545844674 }, { "x": 0.4858689606189728, "y": 0.9359081545844674 } ], "category": "paragraph", "id": 422, "content": { "text": "133\n", "html": "", "markdown": "" } } ] }, "01030000000012.pdf": { "elements": [ { "coordinates": [ { "x": 0.10321896523237228, "y": 0.04990333691239357 }, { "x": 0.11998122930526733, "y": 0.04990333691239357 }, { "x": 0.11998122930526733, "y": 0.05819070525467396 }, { "x": 0.10321896523237228, "y": 0.05819070525467396 } ], "category": "paragraph", "id": 415, "content": { "text": "96\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8013185858726501, "y": 0.04994507133960724 }, { "x": 0.8960168659687042, "y": 0.04994507133960724 }, { "x": 0.8960168659687042, "y": 0.058405397459864616 }, { "x": 0.8013185858726501, "y": 0.058405397459864616 } ], "category": "header", "id": 416, "content": { "text": "MACDONALD\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10218402743339539, "y": 0.07979664206504822 }, { "x": 0.48613741993904114, "y": 0.07979664206504822 }, { "x": 0.48613741993904114, "y": 0.43533551692962646 }, { "x": 0.10218402743339539, "y": 0.43533551692962646 } ], "category": "figure", "id": 417, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1031428799033165, "y": 0.44541844725608826 }, { "x": 0.48444264382123947, "y": 0.44541844725608826 }, { "x": 0.48444264382123947, "y": 0.4748328197747469 }, { "x": 0.1031428799033165, "y": 0.4748328197747469 } ], "category": "paragraph", "id": 418, "content": { "text": "FIGURE 5.1 Mr. Bologna Jun-r as Kalim Azack in Aladdin, or\nThe Wonderful Lamp.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5112877488136292, "y": 0.08110756427049637 }, { "x": 0.872446596622467, "y": 0.08110756427049637 }, { "x": 0.872446596622467, "y": 0.4365703836083412 }, { "x": 0.5112877488136292, "y": 0.4365703836083412 } ], "category": "figure", "id": 419, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5119131803512573, "y": 0.4464413523674011 }, { "x": 0.8764429688453674, "y": 0.4464413523674011 }, { "x": 0.8764429688453674, "y": 0.4752180054783821 }, { "x": 0.5119131803512573, "y": 0.4752180054783821 } ], "category": "paragraph", "id": 420, "content": { "text": "FIGURE 5.2 Mr. Grimaldi as Kazrac (the Chinese slave) in\nAladdin, or The Wonderful Lamp.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10199278593063354, "y": 0.5021955370903015 }, { "x": 0.4883723855018616, "y": 0.5021955370903015 }, { "x": 0.4883723855018616, "y": 0.9015398919582367 }, { "x": 0.10199278593063354, "y": 0.9015398919582367 } ], "category": "paragraph", "id": 421, "content": { "text": "theatrical prints, which are informed by intercul-\nturation and illustrate the Orientalized look of the\ntale's theatrical life: one of John (\"Jack\") Peter Bo-\nlogna as Kalim Azack, the vizier's son betrothed to\nBadroulboudour, and one of the extraordinary\npantomime clown Joseph Grimaldi as Kazrac, the\nmagician's Chinese slave, who, disillusioned by the\nmagician's cruel plans concerning the lamp, be-\nfriends Aladdin (figs. 5.1 and 5.2). The creation of\nthis non-speaking role (Kazrac's tongue had been\nremoved by the \"Tartarian Hord\" from whom the\nmagician rescued him) added much to the play,\nbesides giving both the magician and Aladdin an\nally and a confidant. Interestingly, these two prints\nlikely represent a notable scene in the play, cer-\ntainly a favorite with children playing with a toy\ntheater. The prints show Kalim Azack and Kazrac\nfighting while Aladdin follows the princess to the\nroyal baths. The wealthy Kalim Azack is depicted\nwearing an elaborate ensemble: long embroidered\ntunic with fringe, short jacket with embroidery\nand tassels, full trousers tucked into boots, a sash,\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.511993408203125, "y": 0.5015881657600403 }, { "x": 0.8968735337257385, "y": 0.5015881657600403 }, { "x": 0.8968735337257385, "y": 0.8288353383541107 }, { "x": 0.511993408203125, "y": 0.8288353383541107 } ], "category": "paragraph", "id": 422, "content": { "text": "necklace, earrings, and brooches. With his fanciful\nhat and long moustache, he depicts a theatrical\nversion of \"a Tartar,\" or \"a Man from Crimea.\" An\nillustration with the same title was included in an\n1804 edition of The Costume of Turkey that aptly as-\nsociates Kalim Azack with the \"Tartarian Hord\"\nresponsible for Kazrac's disfigurement. 41 Kazrac's\n\"Chinese\" costume resembles contemporary Qing\nDynasty (1636-1912) fashion with its changshan tu-\nnic, long, loose trousers, and a cap with upturned\nbrim, topped with a knob. Despite his role as a\npoor peasant, Kazrac's theatrical costume is em-\nbellished with embroidery and a gold trim, and the\ncharacter wears white stockings. Additionally,\nGrimaldi sports a braided pigtail and long mous-\ntache and brandishes two curved swords. Taken\ntogether, these two cultural images exemplify the\nOrientalized look that contributed to the fantasy\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5124988555908203, "y": 0.8598755598068237 }, { "x": 0.5269034653902054, "y": 0.8598755598068237 }, { "x": 0.5269034653902054, "y": 0.8678915156051517 }, { "x": 0.5124988555908203, "y": 0.8678915156051517 } ], "category": "paragraph", "id": 423, "content": { "text": "41\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5540431141853333, "y": 0.8556923866271973 }, { "x": 0.8962233066558838, "y": 0.8556923866271973 }, { "x": 0.8962233066558838, "y": 0.9025631062686443 }, { "x": 0.5540431141853333, "y": 0.9025631062686443 } ], "category": "footer", "id": 424, "content": { "text": "\"A Tartar. A Man from Crimea,\" in Octavien Dalvimart,\nThe Costume of Turkey, 1802 (London: Printed for Will-\niam Miller, 1804), n.p.\n", "html": "", "markdown": "" } } ] }, "01030000000196.pdf": { "elements": [ { "coordinates": [ { "x": 0.11780190467834473, "y": 0.08733577281236649 }, { "x": 0.4881127178668976, "y": 0.08733577281236649 }, { "x": 0.4881127178668976, "y": 0.17815998941659927 }, { "x": 0.11780190467834473, "y": 0.17815998941659927 } ], "category": "paragraph", "id": 787, "content": { "text": "plexity when compared to MoE. This shift in ap-\nproach offers a unique and more straightforward\nway of working, moving away from conventional\nMoE challenges. Not only that, DUS also under-\ngoes continued pretraining to quickly recover per-\nformance of the scaled model.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11813603341579437, "y": 0.1947304755449295 }, { "x": 0.32322247326374054, "y": 0.1947304755449295 }, { "x": 0.32322247326374054, "y": 0.2074448587372899 }, { "x": 0.11813603341579437, "y": 0.2074448587372899 } ], "category": "heading1", "id": 788, "content": { "text": "B.3 Prompt Engineering\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11768788844347, "y": 0.21543292701244354 }, { "x": 0.4882705584168434, "y": 0.21543292701244354 }, { "x": 0.4882705584168434, "y": 0.38878045976161957 }, { "x": 0.11768788844347, "y": 0.38878045976161957 } ], "category": "paragraph", "id": 789, "content": { "text": "A key research area to harness the emergent abil-\nities of LLMs is prompt engineering. Prompt en-\ngineering is the study of how to design inputs\n(prompts) that enable LLMs to better perform spe-\ncific tasks. A prime example of this research\nis Chain-of-Thought (CoT) (Wei et al., 2022b),\nwhich proposes CoT prompting that decomposes\nmulti-step problems into a series of intermedi-\nate reasoning steps. Moreover, efforts are under-\nway to replace even such prompt engineering with\nLLMs (Yang et al., 2023).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11789148300886154, "y": 0.40291348099708557 }, { "x": 0.3106914237141609, "y": 0.40291348099708557 }, { "x": 0.3106914237141609, "y": 0.4160311808809638 }, { "x": 0.11789148300886154, "y": 0.4160311808809638 } ], "category": "heading1", "id": 790, "content": { "text": "B.4 Instruction Tuning\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11696062982082367, "y": 0.4238855540752411 }, { "x": 0.4859595149755478, "y": 0.4238855540752411 }, { "x": 0.4859595149755478, "y": 0.549375593662262 }, { "x": 0.11696062982082367, "y": 0.549375593662262 } ], "category": "paragraph", "id": 791, "content": { "text": "To enhance the steerability of LLMs, instruction\ntuning (Wei et al., 2021) has emerged as a learning\ntechnique. This involves fine-tuning LLMs using\ndata formatted as (instruction, input, output) for\nvarious tasks (Wang et al., 2022). Instruction tuning\nallows for targeted adjustments, providing a more\ncontrolled and task-oriented improvement to the\nmodel's capabilities.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11766674369573593, "y": 0.552615225315094 }, { "x": 0.48816462606191635, "y": 0.552615225315094 }, { "x": 0.48816462606191635, "y": 0.8068509995937347 }, { "x": 0.11766674369573593, "y": 0.8068509995937347 } ], "category": "paragraph", "id": 792, "content": { "text": "Before instruction tuning, existing methods\nfaced challenges in effectively guiding and control-\nling the behavior of large language models (Zhang\net al., 2023b). The sheer complexity of these mod-\nels made it difficult to ensure precise and task-\noriented responses. The need for a more targeted\napproach arose from the limitations of existing\nmethods, leading to the development of instruc-\ntion tuning. This targeted approach enables better\ncontrol over the model's behavior, making it more\nsuitable for specific tasks and improving its overall\nperformance in alignment with user-defined objec-\ntives. Therefore, instruction tuning is computation-\nally efficient and facilitates the rapid adaptation\nof LLMs to a specific domain without requiring\nextensive retraining or architectural changes.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1180630773305893, "y": 0.820581316947937 }, { "x": 0.30564238131046295, "y": 0.820581316947937 }, { "x": 0.30564238131046295, "y": 0.8341033160686493 }, { "x": 0.1180630773305893, "y": 0.8341033160686493 } ], "category": "heading1", "id": 793, "content": { "text": "B.5\nAlignment Tuning\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11783822625875473, "y": 0.8417250514030457 }, { "x": 0.48804592341184616, "y": 0.8417250514030457 }, { "x": 0.48804592341184616, "y": 0.918976254761219 }, { "x": 0.11783822625875473, "y": 0.918976254761219 } ], "category": "paragraph", "id": 794, "content": { "text": "LLM has been observed to generate sentences that\nmay be perceived as linguistically incongruent by\nhuman readers since they learned not human inten-\ntion, but only vast knowledge across various do-\nmains in the pretraining step (Ziegler et al., 2019).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5123580098152161, "y": 0.08733998239040375 }, { "x": 0.8830339014530182, "y": 0.08733998239040375 }, { "x": 0.8830339014530182, "y": 0.3087514340877533 }, { "x": 0.5123580098152161, "y": 0.3087514340877533 } ], "category": "paragraph", "id": 795, "content": { "text": "To overcome this limitation and align with human\nintentions, previous research (Ziegler et al., 2019)\nhave proposed Reinforcement Learning with Hu-\nman Feedback (RLHF). RLHF operates by learning\na reward model based on human preferences, em-\nploying reinforcement learning to guide the LLM\ntowards prioritizing answers with the highest re-\nward scores. This process enhances the safety,\npropriety, and overall quality of the generated re-\nsponses. Despite demonstrating satisfactory per-\nformance, RLHF encounters challenges such as\nmanaging numerous hyperparameters and necessi-\ntating the incorporation of multiple models (policy,\nvalue, reward, and reference models).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5124141573905945, "y": 0.3172154128551483 }, { "x": 0.8832097351551056, "y": 0.3172154128551483 }, { "x": 0.8832097351551056, "y": 0.5557197332382202 }, { "x": 0.5124141573905945, "y": 0.5557197332382202 } ], "category": "paragraph", "id": 796, "content": { "text": "In response to these challenges, the supervised\nfine-tuning based approaches have proposed, such\nas Rank Responses to align Human Feedback\n(RRHF) (Yuan et al., 2023), Reward rAnked Fine-\nTuning (RAFT) (Dong et al., 2023), and Direct\nPolicy Optimization (DPO) (Intel, 2023). They\navoid the complexities associated with reinforce-\nment learning while achieving empirical perfor-\nmance comparable to RLHF. Among them, DPO\nthat we used directly guides the LLM to increase\nthe probability of positive responses and decrease\nthe probability of negative responses through a \"di-\nrect\" approach. Interestingly, DPO demonstrates\nmore stable learning results compared to RLHF,\ndespite its simple training approach.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5133041143417358, "y": 0.5860515236854553 }, { "x": 0.7183676809072495, "y": 0.5860515236854553 }, { "x": 0.7183676809072495, "y": 0.5965268108993769 }, { "x": 0.5133041143417358, "y": 0.5965268108993769 } ], "category": "heading1", "id": 797, "content": { "text": "B.6 Data Contamination\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5129572153091431, "y": 0.616416335105896 }, { "x": 0.8831255435943604, "y": 0.616416335105896 }, { "x": 0.8831255435943604, "y": 0.9188471138477325 }, { "x": 0.5129572153091431, "y": 0.9188471138477325 } ], "category": "paragraph", "id": 798, "content": { "text": "Recent researches (Zhou et al., 2023; Sainz et al.,\n2023; Golchin and Surdeanu, 2023; Deng et al.,\n2023) emphasize the need to measure whether a\nspecific benchmark was used to train the large lan-\nguage models. There are three types of the data\ncontamination: guideline, raw text and annota-\ntion (Sainz et al., 2023). Guideline contamination\noccurs when a model accesses detailed annotation\nguidelines for a dataset, providing advantages in\nspecific tasks, and its impact should be considered,\nespecially in zero and few-shot evaluations. Raw\ntext contamination occurs when a model has ac-\ncess to the original text. Wikipedia is widely used\nas a pretraining data, but also as a source for cre-\nating new datasets. The caution is advised in the\ndevelopment of automatically annotated datasets\nsourced from the web. Annotation contamina-\ntion occurs when the annotations of the specific\nbenchmark are exposed during model training.\n", "html": "", "markdown": "" } } ] }, "01030000000017.pdf": { "elements": [ { "coordinates": [ { "x": 0.12310224026441574, "y": 0.08137089014053345 }, { "x": 0.8852128311991692, "y": 0.08137089014053345 }, { "x": 0.8852128311991692, "y": 0.461247056722641 }, { "x": 0.12310224026441574, "y": 0.461247056722641 } ], "category": "table", "id": 323, "content": { "text": "", "html": "
", "markdown": "" } }, { "coordinates": [ { "x": 0.11964046955108643, "y": 0.07593239843845367 }, { "x": 0.8854823112487793, "y": 0.07593239843845367 }, { "x": 0.8854823112487793, "y": 0.464522048830986 }, { "x": 0.11964046955108643, "y": 0.464522048830986 } ], "category": "figure", "id": 333, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12814614176750183, "y": 0.47794151306152344 }, { "x": 0.28214456140995026, "y": 0.47794151306152344 }, { "x": 0.28214456140995026, "y": 0.49010957684367895 }, { "x": 0.12814614176750183, "y": 0.49010957684367895 } ], "category": "paragraph", "id": 334, "content": { "text": "16 Face Your World\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12474443018436432, "y": 0.4970542788505554 }, { "x": 0.8745101243257523, "y": 0.4970542788505554 }, { "x": 0.8745101243257523, "y": 0.6143688187003136 }, { "x": 0.12474443018436432, "y": 0.6143688187003136 } ], "category": "paragraph", "id": 335, "content": { "text": "A girl at work with the Interactor during the Face Your World participation process (image\ncourtesy of Van Heeswijk). On top of the workstation we see the drawing the girl made in an\nearlier stage of the process. The drawing depicts a large tree with a little house inside the tree\nand a rope ladder leading up to the little house. On the screen we see the girl working on a new\nobject for the library. She is digitally redrawing her design for a tree house. Once this drawing\nis finished, she can save it to the library of the Interactor and use it when designing the park.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1230432465672493, "y": 0.6563695669174194 }, { "x": 0.880706675350666, "y": 0.6563695669174194 }, { "x": 0.880706675350666, "y": 0.9212012588977814 }, { "x": 0.1230432465672493, "y": 0.9212012588977814 } ], "category": "paragraph", "id": 336, "content": { "text": "ticipating in Face Your World Slotervaart made a total of 1216 sketches in this phase\nof the planning project and Kaspori considered this the most creative part of the\nprocess (interview with Kaspori, 2007). In the third phase of the game, children\nwould discuss each other's sketches, vote for the best sketch and write down why\nthey had voted for that particular sketch. In the final stage, children entered the\nmulti-player mode and had to start designing the park together. This final design-\ning phase was directed at cooperation between the children: they had to agree on\nhow to design the park and work together in order to be able to realize their ideas\n(interview with Heeswijk, 2007). To realize their ideas, players thus needed to\ncommunicate and cooperate. The discussion option of the game was facilitated\nthrough a chat function. This chat function was one of the few aspects of the\ngame that did not work as it had been intended and projected by the designers.\nChildren working with the Interactor did not use the chat function for communi-\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1286231428384781, "y": 0.94309002161026 }, { "x": 0.4627867788076401, "y": 0.94309002161026 }, { "x": 0.4627867788076401, "y": 0.9629919230937958 }, { "x": 0.1286231428384781, "y": 0.9629919230937958 } ], "category": "footer", "id": 337, "content": { "text": "PART IV: SERIOUS GEOGRAPHIES OF PLAY\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.845263659954071, "y": 0.9478665590286255 }, { "x": 0.8716055005788803, "y": 0.9478665590286255 }, { "x": 0.8716055005788803, "y": 0.9602952878922224 }, { "x": 0.845263659954071, "y": 0.9602952878922224 } ], "category": "paragraph", "id": 338, "content": { "text": "115\n", "html": "", "markdown": "" } } ] }, "01030000000068.pdf": { "elements": [ { "coordinates": [ { "x": 0.15748389065265656, "y": 0.09050286561250687 }, { "x": 0.7703508287668228, "y": 0.09050286561250687 }, { "x": 0.7703508287668228, "y": 0.12437068670988083 }, { "x": 0.15748389065265656, "y": 0.12437068670988083 } ], "category": "paragraph", "id": 448, "content": { "text": "The World Bank/PEMSEA Assessment of Policies and Regulations to Guide Country\nDialogue at National Level to Reduce Plastic Waste in the Philippines indicated:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.19056594371795654, "y": 0.15107367932796478 }, { "x": 0.76795494556427, "y": 0.15107367932796478 }, { "x": 0.76795494556427, "y": 0.3066190481185913 }, { "x": 0.19056594371795654, "y": 0.3066190481185913 } ], "category": "paragraph", "id": 449, "content": { "text": "\"Despite these efforts, there seemed to be very limited information that shows the\neffectiveness of the bans on reducing plastics and litter, or even diversion from\nlandfills in the country. For the majority of LGUs in the country, however, there\nseemed to be no clear documentation and reporting of progress and updated\nwaste data possibly due to the difficulty and complexity of data generation and\nassessment. Another possible constraint is that the scope of the LGU ordinances\nvary and covered different kinds of SUPP, including the exemptions, which makes\nintegration of the various reports, if available, a challenge.\"\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15740801393985748, "y": 0.33279290795326233 }, { "x": 0.818840816617012, "y": 0.33279290795326233 }, { "x": 0.818840816617012, "y": 0.4072199836373329 }, { "x": 0.15740801393985748, "y": 0.4072199836373329 } ], "category": "paragraph", "id": 450, "content": { "text": "The World Bank/PEMSEA report also recommended that a baseline assessment be\nconducted to obtain a better understanding which SUPP are the most prevalent and\nproblematic in the Philippines and to also identify the sources and extent and impacts of\nmismanagement.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11620699614286423, "y": 0.4337720274925232 }, { "x": 0.8186428472399712, "y": 0.4337720274925232 }, { "x": 0.8186428472399712, "y": 0.6497379690408707 }, { "x": 0.11620699614286423, "y": 0.6497379690408707 } ], "category": "paragraph", "id": 452, "content": { "text": "b.\nExtended producer responsibility (EPR). EPR schemes use a combination of regulatory\napproaches to extend manufacturers' responsibility for single-use plastic products\nthroughout their life cycle, including to the end-of-life stage. These schemes are aimed\nat decreasing the overall environmental impact from a product and its packaging.\nThe primary responsibility under EPR lies with the producer, who makes design and\nmarketing decisions. In most European countries, product manufacturers are charged\na fee for every piece of packaging they put onto the market based on the reusability or\nrecyclability of the packaging, supported by technical analysis. These fees are intended\nto cover some or all of the costs of collection, sorting and recycling. Since the recycling\nof plastic packaging costs more than it yields, companies will benefit from a more cost-\neffective system of packaging.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11755186319351196, "y": 0.6764548420906067 }, { "x": 0.5599355697631836, "y": 0.6764548420906067 }, { "x": 0.5599355697631836, "y": 0.8919088691473007 }, { "x": 0.11755186319351196, "y": 0.8919088691473007 } ], "category": "paragraph", "id": 453, "content": { "text": "C.\nRegulated Storage, Manufacture and Use of\nplastics. India required its states to enforce existing\nrules on the storage, manufacture, and use of some\nsingle-use plastics in lieu of a nationwide ban.\nMeanwhile, the Department of Environment and\nNatural Resources (DENR) is yet to issue a list of\nnon-environmentally accepted products (NEAP) as\nprovided in Republic Act 9003 or the Ecological Solid\nWaste Management Act, passed a decade ago. This\nwill include single use plastics in all product forms per\ntechnical advice of the Department of Science and\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.6221060156822205, "y": 0.8751264214515686 }, { "x": 0.8031724840402603, "y": 0.8751264214515686 }, { "x": 0.8031724840402603, "y": 0.9005549028515816 }, { "x": 0.6221060156822205, "y": 0.9005549028515816 } ], "category": "paragraph", "id": 454, "content": { "text": "Figure 27. Soft drinks can with\nthe message \"Recycle Me\"\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5979143381118774, "y": 0.6768330335617065 }, { "x": 0.8238436877727509, "y": 0.6768330335617065 }, { "x": 0.8238436877727509, "y": 0.8658896684646606 }, { "x": 0.5979143381118774, "y": 0.8658896684646606 } ], "category": "figure", "id": 455, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.03155423700809479, "y": 0.9454143047332764 }, { "x": 0.05415887571871281, "y": 0.9454143047332764 }, { "x": 0.05415887571871281, "y": 0.9589721169322729 }, { "x": 0.03155423700809479, "y": 0.9589721169322729 } ], "category": "paragraph", "id": 456, "content": { "text": "64\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.08472571521997452, "y": 0.9475904107093811 }, { "x": 0.5653392747044563, "y": 0.9475904107093811 }, { "x": 0.5653392747044563, "y": 0.9605868207290769 }, { "x": 0.08472571521997452, "y": 0.9605868207290769 } ], "category": "footer", "id": 457, "content": { "text": "Study on Plastics Use and Waste Management in the Food Service Industry\n", "html": "", "markdown": "" } } ] }, "01030000000053.pdf": { "elements": [ { "coordinates": [ { "x": 0.10309804230928421, "y": 0.11110816150903702 }, { "x": 0.8547869399189949, "y": 0.11110816150903702 }, { "x": 0.8547869399189949, "y": 0.4005316272377968 }, { "x": 0.10309804230928421, "y": 0.4005316272377968 } ], "category": "table", "id": 286, "content": { "text": "", "html": "
IX - Zamboanga Peninsula424
X Northern Mindanao222
XI - Davao Region135
XII - SOCCSKSARGEN221
XIII Caraga133
ARMM122
Party-List101520
TOTAL (w/ Party- List)556688
TOTAL (w/o Party- List)455168
", "markdown": "" } }, { "coordinates": [ { "x": 0.10283767431974411, "y": 0.05725551396608353 }, { "x": 0.12651529721915722, "y": 0.05725551396608353 }, { "x": 0.12651529721915722, "y": 0.0687993885949254 }, { "x": 0.10283767431974411, "y": 0.0687993885949254 } ], "category": "paragraph", "id": 325, "content": { "text": "16\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.15702500939369202, "y": 0.05723060294985771 }, { "x": 0.4080096483230591, "y": 0.05723060294985771 }, { "x": 0.4080096483230591, "y": 0.07177844736725092 }, { "x": 0.15702500939369202, "y": 0.07177844736725092 } ], "category": "heading1", "id": 326, "content": { "text": "Encinas Franco and Laguna\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10395117104053497, "y": 0.42043352127075195 }, { "x": 0.6191705614328384, "y": 0.42043352127075195 }, { "x": 0.6191705614328384, "y": 0.43556468468159437 }, { "x": 0.10395117104053497, "y": 0.43556468468159437 } ], "category": "paragraph", "id": 328, "content": { "text": "Source: HOR 2022. Computations made by the authors.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1029566153883934, "y": 0.47642090916633606 }, { "x": 0.85394736379385, "y": 0.47642090916633606 }, { "x": 0.85394736379385, "y": 0.6445965468883514 }, { "x": 0.1029566153883934, "y": 0.6445965468883514 } ], "category": "paragraph", "id": 329, "content": { "text": "Overall, the abovementioned situation indicates that Filipino\nwomen have gradually increased their presence in formal politics.\nIn Asia, the Philippines and Taiwan are the only countries above the\nglobal average of 24.5 percent of women in parliament (Liu 2021).\nHowever, challenges remain as the increased participation of women\ncomes from dysfunctional features of the country's political system:\npolitical dynasties and the Party-List law. Nonetheless, not all women\nfrom these groups are necessarily averse to women's issues.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10492324829101562, "y": 0.6901755332946777 }, { "x": 0.6654456853866577, "y": 0.6901755332946777 }, { "x": 0.6654456853866577, "y": 0.7106590606272221 }, { "x": 0.10492324829101562, "y": 0.7106590606272221 } ], "category": "heading1", "id": 330, "content": { "text": "Barriers to Filipino Women's Participation\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10366209596395493, "y": 0.7353756427764893 }, { "x": 0.8539568409323692, "y": 0.7353756427764893 }, { "x": 0.8539568409323692, "y": 0.8362638354301453 }, { "x": 0.10366209596395493, "y": 0.8362638354301453 } ], "category": "paragraph", "id": 331, "content": { "text": "Previous studies have identified political, economic, and cultural\nfactors that impede women's participation in politics. However, context\nstill matters since the perception of women's role in societies and the\nevolution of political systems differ. The following section examines\nsome of these barriers.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10326679050922394, "y": 0.8575431108474731 }, { "x": 0.8535207659006119, "y": 0.8575431108474731 }, { "x": 0.8535207659006119, "y": 0.939888171851635 }, { "x": 0.10326679050922394, "y": 0.939888171851635 } ], "category": "paragraph", "id": 332, "content": { "text": "The Philippine electoral system's \"first-past-the-post\" electoral\ntype, coupled with the lack of well-developed political parties, inhibits\nwomen's entry into politics. Encinas-Franco (2021) argues that \"[w]\nithout party discipline and institutionalized rules within parties, one\n", "html": "", "markdown": "" } } ] }, "01030000000153.pdf": { "elements": [ { "coordinates": [ { "x": 0.09227193146944046, "y": 0.14819490909576416 }, { "x": 0.2068706974387169, "y": 0.14819490909576416 }, { "x": 0.2068706974387169, "y": 0.1591847576200962 }, { "x": 0.09227193146944046, "y": 0.1591847576200962 } ], "category": "paragraph", "id": 331, "content": { "text": "CHAPTER 7.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09166624397039413, "y": 0.18637201189994812 }, { "x": 0.15807952731847763, "y": 0.18637201189994812 }, { "x": 0.15807952731847763, "y": 0.19816280715167522 }, { "x": 0.09166624397039413, "y": 0.19816280715167522 } ], "category": "paragraph", "id": 332, "content": { "text": "TEXAS\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09264763444662094, "y": 0.3045004904270172 }, { "x": 0.21837373822927475, "y": 0.3045004904270172 }, { "x": 0.21837373822927475, "y": 0.31360534857958555 }, { "x": 0.09264763444662094, "y": 0.31360534857958555 } ], "category": "paragraph", "id": 333, "content": { "text": "MICHELLE REED\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09231770038604736, "y": 0.37617766857147217 }, { "x": 0.3617238700389862, "y": 0.37617766857147217 }, { "x": 0.3617238700389862, "y": 0.38728922978043556 }, { "x": 0.09231770038604736, "y": 0.38728922978043556 } ], "category": "heading1", "id": 334, "content": { "text": "COURSE MARKING DRIVERS\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0921664610505104, "y": 0.4061078131198883 }, { "x": 0.9065840020775795, "y": 0.4061078131198883 }, { "x": 0.9065840020775795, "y": 0.5190023556351662 }, { "x": 0.0921664610505104, "y": 0.5190023556351662 } ], "category": "paragraph", "id": 335, "content": { "text": "I've worked at the University of Texas at Arlington (UTA) for the last three years as Open Education\nLibrarian and was recently promoted to the leadership team as Director of Open Educational\nResources following a half-million-dollar investment in OER from university administration. It was\nin my first year as Open Education Librarian that the Texas Legislature passed Senate Bill 810\n(SB810), which requires institutions of higher education across the state to provide searchable\ninformation to students about OER-only courses. A strong definition of OER was provided:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.10839731246232986, "y": 0.5345121026039124 }, { "x": 0.8907858207821846, "y": 0.5345121026039124 }, { "x": 0.8907858207821846, "y": 0.5974076092243195 }, { "x": 0.10839731246232986, "y": 0.5974076092243195 } ], "category": "paragraph", "id": 336, "content": { "text": "\"teaching, learning, and research resources that reside in the public domain or have been released under an\nintellectual property license that allows for free use, reuse, modification, and sharing with others, including\nfull courses, course materials, modules, textbooks, streaming videos, tests, software, and any other tools,\nmaterials, or techniques used to support access to knowledge.\"\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09220968186855316, "y": 0.6155391931533813 }, { "x": 0.9070581644773483, "y": 0.6155391931533813 }, { "x": 0.9070581644773483, "y": 0.7478584200143814 }, { "x": 0.09220968186855316, "y": 0.7478584200143814 } ], "category": "paragraph", "id": 337, "content": { "text": "However, Texas was not given a very long implementation window. The bill passed in June 2017,\neffective immediately, with a compliance deadline of Spring 2018. We in higher education know a\nchange of this scope, and impacting as many stakeholders as course marking does, takes longer. A\nrecent survey commissioned by the Digital Higher Education Consortium of Texas (DigiTex) and\nadministered in May 2019 shows only 59 respondents of the 158 two-and four-year institutions that\nreceived the statewide survey have a course marking solution in place. The findings were presented\n1\nin Open Educational Resources (OER) in Texas Higher Education, 2019.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.0790778174996376, "y": 0.9021077752113342 }, { "x": 0.9021230116486549, "y": 0.9021077752113342 }, { "x": 0.9021230116486549, "y": 0.9440735951066017 }, { "x": 0.0790778174996376, "y": 0.9440735951066017 } ], "category": "footer", "id": 338, "content": { "text": "1. Jimes, C., Karaglani, A., Petrides, L., Rios, J., Sebesta, J., & Torre, K. (2019). Open Educational Resources (OER) in Texas Higher Education,\n2019. Austin, TX: Digital Higher Education Consortium of Texas and Texas Higher Education Coordinating Board; Half Moon Bay,\nCA: Institute for the Study of Knowledge Management in Education.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.7479533553123474, "y": 0.951137125492096 }, { "x": 0.9059803038835526, "y": 0.951137125492096 }, { "x": 0.9059803038835526, "y": 0.9586384724825621 }, { "x": 0.7479533553123474, "y": 0.9586384724825621 } ], "category": "footer", "id": 339, "content": { "text": "PRICE TRANSPARENCY 17\n", "html": "", "markdown": "" } } ] }, "01030000000155.pdf": { "elements": [ { "coordinates": [ { "x": 0.17495617270469666, "y": 0.2381679266691208 }, { "x": 0.8658976852893829, "y": 0.2381679266691208 }, { "x": 0.8658976852893829, "y": 0.5175928324460983 }, { "x": 0.17495617270469666, "y": 0.5175928324460983 } ], "category": "table", "id": 72, "content": { "text": "", "html": "
1. Front Matter1
2. Introduction to Researching Wicked Problems3
3. Our Mental Shortcuts13
4. Identifying a Topic25
5. Types of Sources38
6. Access & Searching55
7. SIFTing Information67
8. Evaluating News Sources80
9. Audience, Presentation & Citation88
Instructor Resources97
", "markdown": "" } }, { "coordinates": [ { "x": 0.14550071954727173, "y": 0.1016690582036972 }, { "x": 0.3581344336271286, "y": 0.1016690582036972 }, { "x": 0.3581344336271286, "y": 0.12883052788674831 }, { "x": 0.14550071954727173, "y": 0.12883052788674831 } ], "category": "heading1", "id": 94, "content": { "text": "Contents\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1816984862089157, "y": 0.24280905723571777 }, { "x": 0.35033227503299713, "y": 0.24280905723571777 }, { "x": 0.35033227503299713, "y": 0.2544066794216633 }, { "x": 0.1816984862089157, "y": 0.2544066794216633 } ], "category": "paragraph", "id": 96, "content": { "text": "1. Front Matter\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8465030789375305, "y": 0.2427593469619751 }, { "x": 0.855799532495439, "y": 0.2427593469619751 }, { "x": 0.855799532495439, "y": 0.2541050370782614 }, { "x": 0.8465030789375305, "y": 0.2541050370782614 } ], "category": "paragraph", "id": 97, "content": { "text": "1\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.17908769845962524, "y": 0.26947227120399475 }, { "x": 0.8553149700164795, "y": 0.26947227120399475 }, { "x": 0.8553149700164795, "y": 0.28528513945639133 }, { "x": 0.17908769845962524, "y": 0.28528513945639133 } ], "category": "paragraph", "id": 98, "content": { "text": "2. Introduction to Researching Wicked Problems\n3\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1776968538761139, "y": 0.29683512449264526 }, { "x": 0.8554186522960663, "y": 0.29683512449264526 }, { "x": 0.8554186522960663, "y": 0.30918582528829575 }, { "x": 0.1776968538761139, "y": 0.30918582528829575 } ], "category": "paragraph", "id": 99, "content": { "text": "3. Our Mental Shortcuts\n13\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.17751064896583557, "y": 0.32385602593421936 }, { "x": 0.8561298549175262, "y": 0.32385602593421936 }, { "x": 0.8561298549175262, "y": 0.33998518995940685 }, { "x": 0.17751064896583557, "y": 0.33998518995940685 } ], "category": "paragraph", "id": 100, "content": { "text": "4. Identifying a Topic\n25\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.17854127287864685, "y": 0.3509797751903534 }, { "x": 0.8557539880275726, "y": 0.3509797751903534 }, { "x": 0.8557539880275726, "y": 0.3669093009084463 }, { "x": 0.17854127287864685, "y": 0.3669093009084463 } ], "category": "paragraph", "id": 101, "content": { "text": "5. Types of Sources\n38\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.17820727825164795, "y": 0.37822607159614563 }, { "x": 0.856059730052948, "y": 0.37822607159614563 }, { "x": 0.856059730052948, "y": 0.39437009766697884 }, { "x": 0.17820727825164795, "y": 0.39437009766697884 } ], "category": "paragraph", "id": 102, "content": { "text": "6. Access & Searching\n55\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1806020587682724, "y": 0.4054495394229889 }, { "x": 0.8565159291028976, "y": 0.4054495394229889 }, { "x": 0.8565159291028976, "y": 0.42126940935850143 }, { "x": 0.1806020587682724, "y": 0.42126940935850143 } ], "category": "paragraph", "id": 103, "content": { "text": "7. SIFTing Information\n67\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.17875240743160248, "y": 0.43281668424606323 }, { "x": 0.8556173294782639, "y": 0.43281668424606323 }, { "x": 0.8556173294782639, "y": 0.4487435445189476 }, { "x": 0.17875240743160248, "y": 0.4487435445189476 } ], "category": "paragraph", "id": 104, "content": { "text": "8. Evaluating News Sources\n80\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.17811745405197144, "y": 0.4601399898529053 }, { "x": 0.8559651374816895, "y": 0.4601399898529053 }, { "x": 0.8559651374816895, "y": 0.4742598868906498 }, { "x": 0.17811745405197144, "y": 0.4742598868906498 } ], "category": "paragraph", "id": 105, "content": { "text": "9. Audience, Presentation & Citation\n88\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.21400725841522217, "y": 0.5050918459892273 }, { "x": 0.8566542863845825, "y": 0.5050918459892273 }, { "x": 0.8566542863845825, "y": 0.517170432023704 }, { "x": 0.21400725841522217, "y": 0.517170432023704 } ], "category": "paragraph", "id": 106, "content": { "text": "Instructor Resources\n97\n", "html": "", "markdown": "" } } ] }, "01030000000043.pdf": { "elements": [ { "coordinates": [ { "x": 0.5538205504417419, "y": 0.3065322935581207 }, { "x": 0.858323484659195, "y": 0.3065322935581207 }, { "x": 0.858323484659195, "y": 0.35669952630996704 }, { "x": 0.5538205504417419, "y": 0.35669952630996704 } ], "category": "table", "id": 354, "content": { "text": "", "html": "
47% AGREE23% STRONGLY AGREE
", "markdown": "" } }, { "coordinates": [ { "x": 0.11766073852777481, "y": 0.08678991347551346 }, { "x": 0.46114451438188553, "y": 0.08678991347551346 }, { "x": 0.46114451438188553, "y": 0.16783201694488525 }, { "x": 0.11766073852777481, "y": 0.16783201694488525 } ], "category": "paragraph", "id": 358, "content": { "text": "Figure 7: Respondents' reaction to\nthe statement \"I am worried that\nmisogynistic and hostile beliefs\nespoused by extremist groups result in\nviolence towards women.\"\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12937206029891968, "y": 0.1969790756702423 }, { "x": 0.46126511693000793, "y": 0.1969790756702423 }, { "x": 0.46126511693000793, "y": 0.4536616802215576 }, { "x": 0.12937206029891968, "y": 0.4536616802215576 } ], "category": "figure", "id": 359, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.11985310167074203, "y": 0.4817218780517578 }, { "x": 0.4710814878344536, "y": 0.4817218780517578 }, { "x": 0.4710814878344536, "y": 0.5826278254389763 }, { "x": 0.11985310167074203, "y": 0.5826278254389763 } ], "category": "paragraph", "id": 360, "content": { "text": "During the COVID-19 pandemic, 70%\nof respondents agreed that online\nradicalization and the proliferation of\nextremist propaganda had increased.\nAltogether, 76.9% and 92.9% of women\nagreed with the statement.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.12065302580595016, "y": 0.612217903137207 }, { "x": 0.3908934220671654, "y": 0.612217903137207 }, { "x": 0.3908934220671654, "y": 0.6397124696522951 }, { "x": 0.12065302580595016, "y": 0.6397124696522951 } ], "category": "paragraph", "id": 361, "content": { "text": "One interviewee from Indonesia\nnoted that:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.17803291976451874, "y": 0.6746039390563965 }, { "x": 0.4688131660223007, "y": 0.6746039390563965 }, { "x": 0.4688131660223007, "y": 0.91635861992836 }, { "x": 0.17803291976451874, "y": 0.91635861992836 } ], "category": "paragraph", "id": 362, "content": { "text": "\"COVID has managed to restrict\ndirect meetings to disseminate\npropaganda, misinformation\nand disinformation through\nmost government's large-scale\nrestrictions to prevent the virus'\nspread. However, the tendency to\nutilize online spaces to disseminate\nthese has increased since the use\nof online activities is mandatory in\nvarious sectors, such as working\nand education. Most people\ncertainly use online platforms to\ndisseminate false information\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5882770419120789, "y": 0.0872250497341156 }, { "x": 0.8804611563682556, "y": 0.0872250497341156 }, { "x": 0.8804611563682556, "y": 0.15284167230129242 }, { "x": 0.5882770419120789, "y": 0.15284167230129242 } ], "category": "paragraph", "id": 363, "content": { "text": "regarding the outbreak, as well as\nradical ideas targeted at people,\nincluding recruiting them as a\npart of groups.\"\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5287880897521973, "y": 0.20357392728328705 }, { "x": 0.8337510228157043, "y": 0.20357392728328705 }, { "x": 0.8337510228157043, "y": 0.2870190367102623 }, { "x": 0.5287880897521973, "y": 0.2870190367102623 } ], "category": "paragraph", "id": 364, "content": { "text": "Figure 8: Respondents' view to the\nstatement, \"Online radicalization\nand the proliferation of extremist\npropaganda has increased\nduring COVID-1\".\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5351179838180542, "y": 0.3050520420074463 }, { "x": 0.8792567849159241, "y": 0.3050520420074463 }, { "x": 0.8792567849159241, "y": 0.5695700347423553 }, { "x": 0.5351179838180542, "y": 0.5695700347423553 } ], "category": "figure", "id": 365, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5281789898872375, "y": 0.5987885594367981 }, { "x": 0.832874596118927, "y": 0.5987885594367981 }, { "x": 0.832874596118927, "y": 0.6264001503586769 }, { "x": 0.5281789898872375, "y": 0.6264001503586769 } ], "category": "paragraph", "id": 366, "content": { "text": "Another interviewee from Indonesia\nobserved that:\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.5885260701179504, "y": 0.6574432849884033 }, { "x": 0.8813556730747223, "y": 0.6574432849884033 }, { "x": 0.8813556730747223, "y": 0.917074978351593 }, { "x": 0.5885260701179504, "y": 0.917074978351593 } ], "category": "paragraph", "id": 367, "content": { "text": "\"(Based on my experience),\nduring 2020-2021 one of the\ninteresting things has been\nthe impact of misinformation\nand disinformation related to\nCOVID, affecting people's views\nand attitudes in responding to,\npreventing and handling of (the\nvirus). At the beginning of the\nIndonesian government's policy\non limiting religious activities\nin places of worship, this issue\ncaused a strong, adverse reaction\namong extremist groups, giving\nrise to a narrative that the\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.03302466869354248, "y": 0.9753531813621521 }, { "x": 0.7159243226051331, "y": 0.9753531813621521 }, { "x": 0.7159243226051331, "y": 0.9856095183640718 }, { "x": 0.03302466869354248, "y": 0.9856095183640718 } ], "category": "footer", "id": 368, "content": { "text": "Gender Analysis of Violent Extremism and the Impact of COVID-19 on Peace and Security in ASEAN\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.9271694421768188, "y": 0.976122260093689 }, { "x": 0.9441997706890106, "y": 0.976122260093689 }, { "x": 0.9441997706890106, "y": 0.9835388883948326 }, { "x": 0.9271694421768188, "y": 0.9835388883948326 } ], "category": "paragraph", "id": 369, "content": { "text": "36\n", "html": "", "markdown": "" } } ] }, "01030000000061.pdf": { "elements": [ { "coordinates": [ { "x": 0.21409273147583008, "y": 0.10333661735057831 }, { "x": 0.8092865347862244, "y": 0.10333661735057831 }, { "x": 0.8092865347862244, "y": 0.18765582144260406 }, { "x": 0.21409273147583008, "y": 0.18765582144260406 } ], "category": "paragraph", "id": 177, "content": { "text": "iii. Looking at cost items, the cost of raw woods procurement will be highest\nshare at 42%, followed by labour cost at 35%, electricity cost of the\nfabrication department at 10% (refer to figure 5-2). For this analysis, $35 per\ntonne is assumed for raw wood costs and this assumption will be crucial to\nmaintain the economics of this business model.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.21495173871517181, "y": 0.19536402821540833 }, { "x": 0.8087925761938095, "y": 0.19536402821540833 }, { "x": 0.8087925761938095, "y": 0.2632761001586914 }, { "x": 0.21495173871517181, "y": 0.2632761001586914 } ], "category": "paragraph", "id": 178, "content": { "text": "iv. This business model will be operating cost-oriented not capital cost-oriented\n(refer to figure 5.1); thus, management of raw wood cost, labour cost, and\nelectricity cost is essential. Few variations of capital cost will not affect this\nbusiness seriously.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.21812103688716888, "y": 0.2680610120296478 }, { "x": 0.7773098796606064, "y": 0.2680610120296478 }, { "x": 0.7773098796606064, "y": 0.2814430948346853 }, { "x": 0.21812103688716888, "y": 0.2814430948346853 } ], "category": "paragraph", "id": 179, "content": { "text": "V. Assumed selling price of wood pellet is $100 per tonne and appropriate.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.17976047098636627, "y": 0.3195749819278717 }, { "x": 0.7721939235925674, "y": 0.3195749819278717 }, { "x": 0.7721939235925674, "y": 0.33251345809549093 }, { "x": 0.17976047098636627, "y": 0.33251345809549093 } ], "category": "paragraph", "id": 180, "content": { "text": "Figure 5.1. Operating Cost Structure by the Three Departments of A Company\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.24414804577827454, "y": 0.343092679977417 }, { "x": 0.7685737907886505, "y": 0.343092679977417 }, { "x": 0.7685737907886505, "y": 0.5635216236114502 }, { "x": 0.24414804577827454, "y": 0.5635216236114502 } ], "category": "figure", "id": 181, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14226244390010834, "y": 0.5767815709114075 }, { "x": 0.23973920196294785, "y": 0.5767815709114075 }, { "x": 0.23973920196294785, "y": 0.5858647814020514 }, { "x": 0.14226244390010834, "y": 0.5858647814020514 } ], "category": "paragraph", "id": 182, "content": { "text": "Source: Author.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.214774951338768, "y": 0.6147331595420837 }, { "x": 0.7369227260351181, "y": 0.6147331595420837 }, { "x": 0.7369227260351181, "y": 0.6275640558451414 }, { "x": 0.214774951338768, "y": 0.6275640558451414 } ], "category": "paragraph", "id": 183, "content": { "text": "Figure 5.2. Operating Cost Structure by the Cost Items of a Company\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.25137466192245483, "y": 0.6374570727348328 }, { "x": 0.7673131227493286, "y": 0.6374570727348328 }, { "x": 0.7673131227493286, "y": 0.8589266240596771 }, { "x": 0.25137466192245483, "y": 0.8589266240596771 } ], "category": "figure", "id": 184, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1422409564256668, "y": 0.8723915815353394 }, { "x": 0.23822326958179474, "y": 0.8723915815353394 }, { "x": 0.23822326958179474, "y": 0.8806980801746249 }, { "x": 0.1422409564256668, "y": 0.8806980801746249 } ], "category": "paragraph", "id": 185, "content": { "text": "Source: Author.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.4669537842273712, "y": 0.9455525875091553 }, { "x": 0.484855230897665, "y": 0.9455525875091553 }, { "x": 0.484855230897665, "y": 0.9543643891811371 }, { "x": 0.4669537842273712, "y": 0.9543643891811371 } ], "category": "paragraph", "id": 186, "content": { "text": "50\n", "html": "", "markdown": "" } } ] }, "01030000000056.pdf": { "elements": [ { "coordinates": [ { "x": 0.14244483411312103, "y": 0.10362955927848816 }, { "x": 0.8083823770284653, "y": 0.10362955927848816 }, { "x": 0.8083823770284653, "y": 0.1343215499073267 }, { "x": 0.14244483411312103, "y": 0.1343215499073267 } ], "category": "paragraph", "id": 248, "content": { "text": "scheme helped the biomass power capacity to increase by more than double in 7 years.\nUnder the FIT scheme, biomass fuels for power generation are grouped into six categories.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14321286976337433, "y": 0.1480759084224701 }, { "x": 0.8083933740854263, "y": 0.1480759084224701 }, { "x": 0.8083933740854263, "y": 0.17898278310894966 }, { "x": 0.14321286976337433, "y": 0.17898278310894966 } ], "category": "paragraph", "id": 250, "content": { "text": "General wood: sawmill residues, import wood such as pellets and chips, palm kernel\nshell (PKS) and palm trunk\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14323078095912933, "y": 0.1857544183731079 }, { "x": 0.3701736479997635, "y": 0.1857544183731079 }, { "x": 0.3701736479997635, "y": 0.1978038214147091 }, { "x": 0.14323078095912933, "y": 0.1978038214147091 } ], "category": "paragraph", "id": 251, "content": { "text": "Liquid biomass: palm oil\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14347614347934723, "y": 0.2047230750322342 }, { "x": 0.4995935410261154, "y": 0.2047230750322342 }, { "x": 0.4995935410261154, "y": 0.21473729331046343 }, { "x": 0.14347614347934723, "y": 0.21473729331046343 } ], "category": "paragraph", "id": 252, "content": { "text": "Unutilised wood: domestic thinned wood\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.1432487964630127, "y": 0.22364471852779388 }, { "x": 0.8085050582885742, "y": 0.22364471852779388 }, { "x": 0.8085050582885742, "y": 0.25217026844620705 }, { "x": 0.1432487964630127, "y": 0.25217026844620705 } ], "category": "paragraph", "id": 253, "content": { "text": "Construction wood waste: wood waste salvaged from construction and other wood\nmaterials\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14303018152713776, "y": 0.2609272599220276 }, { "x": 0.8085535913705826, "y": 0.2609272599220276 }, { "x": 0.8085535913705826, "y": 0.2918114010244608 }, { "x": 0.14303018152713776, "y": 0.2918114010244608 } ], "category": "paragraph", "id": 254, "content": { "text": "Waste materials and other biomass: pruned branched, paper, food waste, waste\ncooking oil, and black liquor\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14328427612781525, "y": 0.29828909039497375 }, { "x": 0.7270039469003677, "y": 0.29828909039497375 }, { "x": 0.7270039469003677, "y": 0.3107496192678809 }, { "x": 0.14328427612781525, "y": 0.3107496192678809 } ], "category": "paragraph", "id": 255, "content": { "text": "Biogas: methane derived from sewage sludge, manure, and food waste.\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14229433238506317, "y": 0.3240020275115967 }, { "x": 0.8086674064397812, "y": 0.3240020275115967 }, { "x": 0.8086674064397812, "y": 0.3729473054409027 }, { "x": 0.14229433238506317, "y": 0.3729473054409027 } ], "category": "paragraph", "id": 256, "content": { "text": "While inexpensive biomass sources such as wood waste from construction and waste\nmaterials, were the main fuels under the RPS, the domestic unutilised wood and the\ngeneral wood whose tariff rates are set higher increased specifically (Figure 4.1, 4.2).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.2760060131549835, "y": 0.4047834277153015 }, { "x": 0.6758437156677246, "y": 0.4047834277153015 }, { "x": 0.6758437156677246, "y": 0.41682905703783035 }, { "x": 0.2760060131549835, "y": 0.41682905703783035 } ], "category": "paragraph", "id": 257, "content": { "text": "Figure 4.1. Approved Capacity under the FIT Scheme\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.17572690546512604, "y": 0.43209660053253174 }, { "x": 0.7813443690538406, "y": 0.43209660053253174 }, { "x": 0.7813443690538406, "y": 0.5992838591337204 }, { "x": 0.17572690546512604, "y": 0.5992838591337204 } ], "category": "figure", "id": 258, "content": { "text": "", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.14230813086032867, "y": 0.6154898405075073 }, { "x": 0.8085179477930069, "y": 0.6154898405075073 }, { "x": 0.8085179477930069, "y": 0.6704160645604134 }, { "x": 0.14230813086032867, "y": 0.6704160645604134 } ], "category": "paragraph", "id": 259, "content": { "text": "FIT = feed-in-tariff.\nNote: Liquid biomass approved under the FIT scheme between FY2012 and FY2017 is included in general wood\nand no liquid biomass has been approved since FY2018.\nSource: METI (2021a).\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.4668204188346863, "y": 0.9454425573348999 }, { "x": 0.4849369693547487, "y": 0.9454425573348999 }, { "x": 0.4849369693547487, "y": 0.954356336966157 }, { "x": 0.4668204188346863, "y": 0.954356336966157 } ], "category": "paragraph", "id": 260, "content": { "text": "30\n", "html": "", "markdown": "" } } ] }, "01030000000164.pdf": { "elements": [ { "coordinates": [ { "x": 0.09211239963769913, "y": 0.09271816909313202 }, { "x": 0.9070825353264809, "y": 0.09271816909313202 }, { "x": 0.9070825353264809, "y": 0.1762227639555931 }, { "x": 0.09211239963769913, "y": 0.1762227639555931 } ], "category": "paragraph", "id": 726, "content": { "text": "3Btg2-26 to 31 in; dark grayish brown (10YR 4/2) crushed, silty clay; common coarse prominent dark yellowish brown\n(10YR 4/6) moist irregular mottles throughout; moderate medium prismatic structure parting to moderate coarse\nsubangular blocky; extremely hard, very firm; common very fine and fine roots throughout; common very fine moderate\ncontinuity tubular pores; common distinct continuous very dark grayish brown (10YR 3/2), moist, clay films on vertical\nand horizontal faces of peds; strongly acid; clear wavy boundary. (0 to 15 in thick)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09205306321382523, "y": 0.19862887263298035 }, { "x": 0.9073435738682747, "y": 0.19862887263298035 }, { "x": 0.9073435738682747, "y": 0.2999408468604088 }, { "x": 0.09205306321382523, "y": 0.2999408468604088 } ], "category": "paragraph", "id": 727, "content": { "text": "3Btg3-31 to 35 in; grayish brown (10YR 5/2) crushed, silty clay; common fine prominent dark yellowish brown (10YR\n4/6) moist irregular mottles throughout; moderate medium subangular blocky structure; very hard, friable; common\nvery fine and fine roots throughout; common very fine moderate continuity tubular pores; few faint continuous dark\ngrayish brown (10YR 4/2), moist, clay films on vertical and horizontal faces of peds; common medium rounded very dark\ngrayish brown (10YR 3/2) soft clay bodies pedogenic throughout and few medium rounded white (10YR 8/1) soft nests\nof gypsum pedogenic throughout; strongly acid; clear wavy boundary. (0 to 10 in thick)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09204281866550446, "y": 0.32271042466163635 }, { "x": 0.9072453528642654, "y": 0.32271042466163635 }, { "x": 0.9072453528642654, "y": 0.4415007382631302 }, { "x": 0.09204281866550446, "y": 0.4415007382631302 } ], "category": "paragraph", "id": 728, "content": { "text": "3Btg4-35 to 42 in; grayish brown (10YR 5/2) crushed, silty clay loam; common fine prominent dark yellowish brown\n(10YR 4/6) moist irregular mottles throughout and common fine prominent yellowish brown (10YR 5/8) moist irregular\nmottles throughout; weak coarse prismatic structure parting to moderate medium subangular blocky; very hard, friable;\ncommon very fine and fine roots throughout; common very fine and fine moderate continuity tubular pores; few faint\ndiscontinuous dark grayish brown (10YR 4/2), moist, clay films on vertical faces of peds and few distinct continuous very\ndark grayish brown (10YR 3/2) moist, silt coats in root channels and/or pores; few medium rounded white (10YR 8/1)\nsoft nests of gypsum pedogenic throughout; strongly acid; gradual wavy boundary. (0 to 10 in thick)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09190832078456879, "y": 0.46375572681427 }, { "x": 0.9070138186216354, "y": 0.46375572681427 }, { "x": 0.9070138186216354, "y": 0.5648024156689644 }, { "x": 0.09190832078456879, "y": 0.5648024156689644 } ], "category": "paragraph", "id": 729, "content": { "text": "3Btg5/E-42 to 54 in; dark grayish brown (10YR 4/2) exterior, silty clay loam; common fine prominent dark yellowish\nbrown (10YR 4/6) moist irregular mottles throughout; moderate coarse prismatic structure parting to moderate\nmedium subangular blocky; hard, friable; common very and fine roots throughout; many very fine and fine moderate\ncontinuity tubular pores; few faint discontinuous dark grayish brown (10YR 4/2) moist clay films on vertical faces of peds\nand few distinct continuous very dark grayish brown (10YR 3/2) moist, silt coats in root channels and/or pores; strongly\nacid; gradual wavy boundary. (0 to 15 in thick)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09191245585680008, "y": 0.5878518223762512 }, { "x": 0.9070699885487556, "y": 0.5878518223762512 }, { "x": 0.9070699885487556, "y": 0.7065467312932014 }, { "x": 0.09191245585680008, "y": 0.7065467312932014 } ], "category": "paragraph", "id": 730, "content": { "text": "3Btg6/E-54 to 69 in; light brownish gray (10YR 6/2) exterior, silty clay loam; common coarse prominent dark yellowish\nbrown (10YR 4/6) moist irregular mottles throughout and common coarse prominent dark reddish brown (5YR 3/4)\nmoist irregular mottles throughout; moderate coarse prismatic structure parting to weak coarse subangular blocky;\nslightly hard, very friable; common very fine and fine roots throughout; many very fine and fine moderate continuity\ntubular pores; few faint continuous grayish brown (10YR 5/2), moist, clay films on vertical faces of peds and few distinct\ncontinuous dark grayish brown(10YR 4/2) moist silt coats in root channels and/or pores; common fine rounded black (N\n2/0) soft iron/manganese concretions pedogenic throughout; strongly acid; gradual wavy boundary. (0 to 20 in thick)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09188707172870636, "y": 0.7289698123931885 }, { "x": 0.9071808606386185, "y": 0.7289698123931885 }, { "x": 0.9071808606386185, "y": 0.8653322905302048 }, { "x": 0.09188707172870636, "y": 0.8653322905302048 } ], "category": "paragraph", "id": 731, "content": { "text": "3Btg7/E-69 to 86 in; light brownish gray (10YR 6/2) exterior, silty clay loam; common coarse prominent dark yellowish\nbrown (10YR 4/6) moist irregular mottles throughout and common fine prominent dark brown (7.5YR 3/4.) moist\nirregular mottles throughout; weak coarse prismatic structure; slightly hard, very friable; few very fine roots\nthroughout; common very fine and fine moderate continuity tubular pores; few faint discontinuous dark grayish brown\n(10YR 4/2), moist, clay films on vertical faces of peds and few distinct continuous grayish brown (10YR 5/2) moist, silt\ncoats in root channels and/or pores; common fine rounded black (N 2/0) soft iron/manganese concretions pedogenic\nthroughout and few medium irregular brown (10YR 5/3) soft clay bodies pedogenic in cracks; very strongly acid; clear\nsmooth boundary. (0 to 20 in thick)\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.09218998998403549, "y": 0.8882512450218201 }, { "x": 0.9069720134139061, "y": 0.8882512450218201 }, { "x": 0.9069720134139061, "y": 0.9185670670121908 }, { "x": 0.09218998998403549, "y": 0.9185670670121908 } ], "category": "paragraph", "id": 732, "content": { "text": "3Btg8/E-86 to 97 in; 80% light brownish gray (2.5Y 6/2) exterior, and 15% yellowish brown (10YR 5/8), exterior, and\n5% strong brown (7.5 YR 4/6), exterior, silty clay loam; moderate coarse prismatic structure parting to weak coarse\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.7887508273124695, "y": 0.9416635036468506 }, { "x": 0.8771191984415054, "y": 0.9416635036468506 }, { "x": 0.8771191984415054, "y": 0.9498014766722918 }, { "x": 0.7887508273124695, "y": 0.9498014766722918 } ], "category": "footer", "id": 733, "content": { "text": "Soil Formation\n", "html": "", "markdown": "" } }, { "coordinates": [ { "x": 0.8940542936325073, "y": 0.9417811036109924 }, { "x": 0.9072917560115457, "y": 0.9417811036109924 }, { "x": 0.9072917560115457, "y": 0.9498183215036988 }, { "x": 0.8940542936325073, "y": 0.9498183215036988 } ], "category": "paragraph", "id": 734, "content": { "text": "27\n", "html": "", "markdown": "" } } ] } }