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GJ 3685 is a star in the constellation of Leo. It is extremely faint; its apparent magnitude is 13.3, and can only be seen with a ten-inch (25 cm) telescope (see Limiting magnitude). Based on a parallax of 53.1361 milliarcseconds, the system is located 61.4 light-years (18.8 parsecs) away from the Earth. This is a part of a binary star system consisting of two components separated by 24″. The primary component, GJ 3685 (also known as GJ 3685 A), is a very old red dwarf that is also a flare star. A 20-minute flare was observed in 2004 by the GALEX satellite. Its companion, GJ 3686, is another faint red dwarf with a spectral type of M5. It is also known as LP 613-50 and is also located roughly the same distance as its primary. == References ==
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{"page_id": 16145742, "title": "GJ 3685"}
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with 4.5 $\mu$m fluxes ranging from $<7$ $\mu$Jy to $18.7\pm1.8$ $\mu$Jy (Tab.~\ref{tab:ULXDetTab} and Fig.~\ref{fig:ULX_LCs}). The median 3.6 and 4.5 $\mu$m absolute magnitudes of NGC 3031 ULX1 for the epochs where it is detected are $-9.32 \pm0.4$ and $-9.73\pm0.31$, respectively. It is unclear if the optical counterpart is also variable, but the brightness and red color of the mid-IR counterpart suggests an excess of mid-IR emission. The SED of NGC 3031 ULX1 shows absolute mid-IR magnitudes consistent with sgB[e]s and RSGs, and its mid-IR color $[3.6]-[4.5] = 0.41\pm0.47$ places it in the color gap between red and blue ULXs. However, the non-supergiant O8 V star claim for the optical counterpart by Liu et al. (2002) cannot be ruled out since the mid-IR emission from NGC 3031 ULX1 was only detected in its brightest state while most of the observations were below the \textit{Spitzer}~detection threshold. \subsubsection{M101 XMM1} M101 XMM1, also known as J140314+541807 and NGC 5457 ULX2, is a ULX in the face-on spiral galaxy M101 (d = 6.43 Mpc; Shappee \& Stanek 2011) and exhibits an X-ray luminosity of $2.9\times10^{39}$ ergs s$^{-1}$ (Winter et al. 2006). H14 detected a near-IR counterpart and measured an absolute magnitude of $H = -10.69\pm0.1$ and claim it is consistent with an RSG. \textit{Spitzer}/IRAC observations of M101 XMM1 measure median absolute magnitudes of [3.6] = $-11.16\pm0.07$ and [4.5] = $-11.27\pm0.09$ with small-amplitude variability on the order of $\sim20\%$ or $2\sigma$. This mid-IR variability is consistently measured at both 3.6 and 4.5 $\mu$m. The mid-IR properties of M101 XMM1 are therefore similar to that of M101 XMM3. The \textit{Spitzer}~mid-IR photometry again supports the H14 hypothesis that the IR counterpart of M101 XMM1 is an RSG donor star. \subsubsection{M101 XMM3} M101 XMM3, also known as J1402+5440, NGC 5457 X23, and NGC 5457 ULX3, is another ULX in M101
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{"source": 1030, "title": "from dpo"}
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A2, and the A2H side is proportional to the repulsive force wR pushing away from point R; In the constructed triangle △RA1I, which partly overlaps the △A1A2R location triangle, the RA1 side is proportional to the attractive force wA2 pointing towards A2, the RI side is proportional to the attractive force wA1 pointing towards A1, and the A1I side is proportional to the repulsive force wR pushing away from point R; The optimal point D is located at the intersection of the two circumferences drawn round the △RA2H and △RA1I constructed triangles. This solution is useless if one of the forces is greater than the sum of the two other ones or if the angles are not compatible. In some cases, no force is larger than the two other ones, and the angles are not compatible; then, the optimal location lies at the point that exerts the greater attractive force. == Tellier’s trigonometric solution of the Fermat and Weber triangle problems == More than 332 years separate the first formulation of the Fermat triangle problem and the discovery of its non-iterative numerical solution, while a geometrical solution existed for almost all that period of time. Is there an explanation for that? That explanation lies in the possibility of the origins of the three vectors oriented towards the three attraction points not coinciding. If those origins do coincide and lie at the optimum location P, the vectors oriented towards A, B, C, and the sides of the △ABC location triangle form the six angles ∠1, ∠2, ∠3, ∠4, ∠5, ∠6, and the three vectors form the ∠αA, ∠αB, ∠αC angles. It is easy to write the following six equations linking six unknowns (the angles ∠1, ∠2, ∠3, ∠4, ∠5, ∠6) with six known values (angles ∠A, ∠B, ∠C, whose values are
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{"page_id": 40077384, "title": "Weber problem"}
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pe6on to pe6on > 4make specil ccommih€nrs 5include atfe-ime glaranree > 6 l o q d e i a l s o n a C R M s y n e m 7€ s n r h e u r g e l o a r s u e > 8acknowledge any inconvenence caused 1 an initial enquiry 2 inlormation 3 a qlotation 4 the quotaton 5 an order 6 rhe order 7 an invoice (with the qoods) 8 the payment 9 a .omp a nt 10 the prob em I body posture 2 channel of comnun carion 3 com.non qround 4 on s.reen inlormaUon 5 prelercd cusromers 6 prsales enqliry 7 buk pur.hase discount 8 money back guarantee 9 satisfacron sLrtoey jO wairanry ctaim 1 waiianty/graEntee 2 FreqLenttyAsked elesrons I satisfa.tion 2 oyalty 3 leedback 4 suto€y 5 expefence 6 expectaions 7 profile 8 requiremenrs ## www.ZTCprep.com Al'lsWEB KEY 20 Markets and marketihg Exercire 20.1 1 segmenls 2 gender 3 peeu 4 purchasinq 5 patterns of demaid 6 reps 7 target I feasible 9 price poinis 10 nchemarket 11 catalyst 12 ieatures 13 aber 14 elanci9 of demand Exercise 20.2 1 marketnq 2 promotion 3 advertising 4 plbliciv market forces / ieader / price / sector / share ma.keting ageng / campaiqn / mix / strategy /tool 1 markel forces 2 markeing mx 3 market share 1 e 2 b 3 c 4 h 5 9 6 a 7 d 8 t brea( lnior enler / open up / penetrare tat€ o!€. captLre / corne. / dominale be forced out of be driven oul oflwithdraw iiom 2t Produd 1 compimentary 2 €nhanced 3 catchy 4 swit.h Exerdse 21.2 1 image 2 manager 3 leader 4 loya ty 5 equity 6 sl.etching 7 assocation 8 awareness Ex€rcbe 21.3 1 brand
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{"source": 972, "title": "from dpo"}
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0.1073 | **0.9464** | **0.0411** | 0.7666 | 0.1441 | | Prop. w.o. H. | 0.8815 | 0.0523 | 0.8861 | 0.0551 | 0.8783 | 0.0587 | | Prop. w. H. | **0.8974** | **0.0422** | 0.9078 | 0.0433 | **0.8888** | **0.0543** | Read full chapter are a tree-structured classifier where inner nodes represent the properties of a data set, branches represent decision rules, and each leaf node represents the result. A Decision tree has two nodes, Decision Node and Leaf Node. While decision nodes are used to make any decision and have more than one class, leaf nodes are the output of these decisions. Random Forest (RF) is based on the concept of ensemble learning, the process of combining multiple classifiers to solve a complex problem and improve the performance of the model. It is a classifier that contains a set of decision trees in various subsets of the given data set and takes the average to increase the predictive accuracy of this data set. Fig.8 shows a simple diagram for Random forest. Aung and Min used clustering and classification methods together for intrusion detection. They made classification with RF in five different clusters they created with K-means and compared the performance results separately for each attack type. Li et al. made an optimal number of feature selection using RF and then grouped these selected features and determined subsets of features. Finally, they presented these subsets to an [anomaly detection]( "Learn more about anomaly detection from ScienceDirect's AI-generated Topic
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{"source": 2647, "title": "from dpo"}
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fairly robust against violations of the normality requirement. However, we should not gener-ally rely on this robustness, as linguistic data may depart from normality to quite an extreme degree. More generally, ignoring the prerequisites of a statistical pro-cedure is not exactly good scientific practice – the only reason I did it above was so you would not be too shocked when you see it done in actual research (which, inevitably, you will). Second, and more recommendably, we could try to make the data fit the nor-mality requirement. One way in which this is sometimes achieved in the many cases where data do not follow the normal distribution is to log-transform the data (i.e., use the natural logarithm of the data instead of the data themselves). This often, but not always, causes the data to approximate a normal distribution 197 6 Significance testing more closely. However, this does not work in all cases (it would not, for example, bring the distribution in Figure 6.1c much closer to a normal distribution, and anyway, transforming data carries its own set of problems. Thus, third, and most recommendably, we could try to find a way around hav-ing to use a t-test in the first place. One way of avoiding a t-test is to treat our non-normally distributed cardinal data as ordinal data, as described in Chapter 5. We can then use the Mann-Whitney U -test, which does not require a normal dis-tribution of the data. I leave it as an exercise to the reader to apply this test to the data in Table 6.12 (you know you have succeeded if your result for U is 137, 𝑝 < 0.01 ). Another way of avoiding the t-test is to find an operationalization of the phe-nomenon under investigation that yields rank data, or, even better, nominal
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{"source": 4958, "title": "from dpo"}
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predict from the old data. The remedy in S-PLUS is to use the method function predict.gam :S+ > >predict.gam(quad2, newdata = new.x) # S-PLUS only 250 260 270 280 290 300 112.51 111.47 110.58 109.83 109.21 108.74 This constructs a new model matrix by putting old and new data together, re-estimates the regression using the old data only and predicts using these estimates of regression coefficients. This can involve appreciable extra computation, but the results will be correct for polynomials, but not exactly so for splines since the knot positions will change. As a check, predict.gam compares the predictions with the old fitted values for the original data. If these are seriously different, a warning is issued that the process has probably failed. In our view this is a serious flaw in predict.lm . It would have been better to use the safe method as the default and provide an unsafe argument for the faster method as an option. 6.5 Robust and Resistant Regression There are a number of ways to perform robust regression in S-PLUS , but many have drawbacks and are not mentioned here. First consider an example. Rousseeuw and Leroy (1987) give data on annual numbers of Belgian telephone calls, given in our dataset phones .6.5 Robust and Resistant Regression 157 > ••••••••••••••••••••••••year calls 50 55 60 65 70 0 50 100 150 200 least squares M-estimate LTS Figure 6.4 : Millions of phone calls in Belgium, 1950–73, from Rousseeuw and Leroy (1987), with three fitted lines. # R: library(lqs) phones.lm <- lm(calls ~ year, data = phones) attach(phones); plot(year, calls); detach() abline(phones.lm$coef) abline(rlm(calls ~ year, phones, maxit=50), lty = 2, col = 2) abline(lqs(calls ~ year, phones), lty = 3, col = 3) legend(locator(1), lty = 1:3, col = 1:3, legend = c("least squares", "M-estimate", "LTS"))
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{"source": 6256, "title": "from dpo"}
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but no sense of not being stared at, and attributed the results to morphic resonance. He reported a hit rate of 53.1%, describing two subjects as "nearly always right, scoring way above chance levels." Several independent experimenters were unable to find evidence beyond statistical randomness that people could tell they were being stared at, with some saying that there were design flaws in Sheldrake's experiments, such as using test sequences with "relatively few long runs and many alternations" instead of truly randomised patterns. In 2005, Michael Shermer expressed concern over confirmation bias and experimenter bias in the tests, and concluded that Sheldrake's claim was unfalsifiable. David Jay Brown, who conducted some of the experiments for Sheldrake, states that one of the subjects who was reported as having the highest hit rates was under the influence of the drug MDMA (Ecstasy) during the trials. === The Science Delusion (Science Set Free) (2012) === The Science Delusion, published in the US as Science Set Free: 10 Paths to New Discovery, summarises much of Sheldrake's previous work and encapsulates it into a broader critique of philosophical materialism, with the title apparently mimicking that of The God Delusion by one of his critics, Richard Dawkins. In the book, Sheldrake proposes a number of questions as the theme of each chapter that seek to elaborate on his central premise that science is predicated on the belief that the nature of reality is fully understood, with only minor details needing to be filled in. This "delusion" is what Sheldrake argues has turned science into a series of dogmas grounded in philosophical materialism rather than an open-minded approach to investigating phenomena. He argues that many powerful taboos circumscribe what scientists can legitimately direct their attention towards.: 6–12 The mainstream view of modern science is that it proceeds
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{"page_id": 142395, "title": "Rupert Sheldrake"}
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{\displaystyle K_{eq}} the equilibrium constant and K m 2 {\displaystyle K_{m_{2}}} the reverse K m {\displaystyle K_{m}} , two elasticity coefficients can be calculated, one with respect to substrate, S, and another with respect to product, P. Thus: ε s v = 1 1 − Γ / K eq − s / K m 1 1 + s / K m 1 + p / K m 2 {\displaystyle \varepsilon _{s}^{v}={\frac {1}{1-\Gamma /K_{\text{eq}}}}-{\frac {s/K_{m_{1}}}{1+s/K_{m_{1}}+p/K_{m_{2}}}}} ε p v = − Γ / K eq 1 − Γ / K eq − p / K m 2 1 + s / K m 1 + p / K m 2 {\displaystyle \varepsilon _{p}^{v}={\frac {-\Gamma /K_{\text{eq}}}{1-\Gamma /K_{\text{eq}}}}-{\frac {p/K_{m_{2}}}{1+s/K_{m_{1}}+p/K_{m_{2}}}}} where Γ {\displaystyle \Gamma } is the mass-action ratio, that is Γ = p / s {\displaystyle \Gamma =p/s} . Note that when p = 0, the equations reduce to the case for the irreversible Michaelis–Menten law. As a final example, consider the Hill equation: v = V max ( s / K s ) n 1 + ( s / K s ) n {\displaystyle v={\frac {V_{\max }(s/K_{s})^{n}}{1+(s/K_{s})^{n}}}} where n is the Hill coefficient and K s {\displaystyle K_{s}} is the half-saturation coefficient (cf. Michaelis–Menten rate law), then the elasticity coefficient is given by: ε s v = n 1 + ( s / K s ) n {\displaystyle \varepsilon _{s}^{v}={\frac {n}{1+(s/K_{s})^{n}}}} Note that at low concentrations of S the elasticity approaches n. At high concentrations of S the elasticity approaches zero. This means the elasticity is bounded between zero and the Hill coefficient. === Summation property of elasticity coefficients === The elasticities for a reversible uni-uni enzyme catalyzed reaction was previously given by: ε s v = 1 1 − Γ / K eq − s / K m 1 1 + s
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{"page_id": 19827148, "title": "Elasticity coefficient"}
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a non-commutative algebra is employed to describe the non-commutative structure of the quantum formalism, it turns out that it is impossible to define an underlying space, but that rather "shadow spaces" (homomorphic spaces) can be constructed and that in so doing the quantum potential appears. The quantum potential approach can be seen as a way to construct the shadow spaces. The quantum potential thus results as a distortion due to the projection of the underlying space into x {\displaystyle x} -space, in similar manner as a Mercator projection inevitably results in a distortion in a geographical map. There exists complete symmetry between the x {\displaystyle x} -representation, and the quantum potential as it appears in configuration space can be seen as arising from the dispersion of the momentum p {\displaystyle p} -representation. The approach has been applied to extended phase space, also in terms of a Duffin–Kemmer–Petiau algebra approach. == Relation to other quantities and theories == === Relation to the Fisher information === It can be shown that the mean value of the quantum potential Q = − ℏ 2 ∇ 2 ρ / ( 2 m ρ ) {\displaystyle Q=-\hbar ^{2}\nabla ^{2}{\sqrt {\rho }}/(2m{\sqrt {\rho }})} is proportional to the probability density's Fisher information about the observable x ^ {\displaystyle {\hat {x}}} I = ∫ ρ ⋅ ( ∇ ln ρ ) 2 d 3 x = − ∫ ρ ∇ 2 ( ln ρ ) d 3 x . {\displaystyle {\mathcal {I}}=\int \rho \cdot (\nabla \ln \rho )^{2}\,d^{3}x=-\int \rho \nabla ^{2}(\ln \rho )\,d^{3}x.} Using this definition for the Fisher information, we can write: ⟨ Q ⟩ = ∫ ψ ∗ Q ψ d 3 x = ∫ ρ Q d 3 x = ℏ 2 8 m I . {\displaystyle \langle Q\rangle =\int \psi ^{*}Q\psi
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{"page_id": 8057418, "title": "Quantum potential"}
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Genes to Cognition (G2C) is a neuroscience research programme that studies genes, the brain and behaviour in an integrated manner. It is engaged in a large-scale investigation of the function of molecules found at the synapse. This is mainly focused on proteins that interact with the NMDA receptor, a receptor for the neurotransmitter, glutamate, which is required for processes of synaptic plasticity such as long-term potentiation (LTP). One key discovery that led to the G2C project was the characterization of a group of proteins that interact with this receptor, called the "NMDA Receptor Complex (NRC)" and the observation that dysfunctions of many of these proteins are characteristic of numerous diseases of the nervous system. The NRC contains 185 proteins, 48 of which have so far been implicated in 54 human nervous system disorders. The molecular evolution of the NRC is also an active area of research, and it has been shown that an increase in the complexity of these signaling proteins at synapses has evolved alongside the enhanced cognitive capacities of humans and other higher vertebrates. == Scientific Strategy == The activities of the Genes to Cognition Project encompass a wide range of scientific specialisms, reflecting the diversity of information that must be integrated to advance understanding of the brain. Following from synapse proteomics experiments to identify candidate proteins for further investigation, G2C has undertaken to knock out many of these by gene targeting in mice and has established a number of high-throughput platforms for evaluating the effect of these genetic manipulations on brain function. == Information Sharing == As well as sharing findings through open access articles in the scientific literature, Genes to Cognition maintains a database, G2Cdb and an educational web site, G2Conline. === G2Cdb: Genes to Cognition Database === G2Cdb integrates information curated from the scientific literature
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{"page_id": 17849783, "title": "Genes to Cognition Project"}
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for Android that is mainly maintained by Christian Browet (a.k.a. Koying), who is also a developer on Team-XBMC of the official XBMC for Android. SPMC is basically a plain fork of XBMC 13.x (Gotham), with some minor tweaks specific to various Android devices. The main difference between SPMC and the official upstream XBMC is that SPMC is available to download directly from most Android app stores, such as Google Play, Amazon Appstore, and Ouya App Store. Thus SPMC does not have to be side-loaded like the official upstream XBMC, yet the signature is different from the XBMC one, so both can co-exist on the same device, with separate userdata. == TOFU Media Center by Pivos == TOFU Media Platform by Pivos Technology Group, Inc., is a development framework and software platform based on XBMC for Android, designed for both first-parties (i.e., media player devices from Pivos) and licensed to third parties (OEM) and other commercial partners. Marked as an "entertainment ecosystem" derived from XBMC Media Center, that builds atop underlying embedded operating systems such as Android or Linux variants. TOFU Media Platform consists of TOFU Media Center which is a fork of XBMC, and the current version of TOFU Media OS is a fork of Android 4.2 (Jellybean). The first commercial third-party device to have official ToFu Media Center (Android version) application support was the GameStick video game console developed by PlayJam. Pivos's own first device that comes with the complete TOFU Media Platform (TOFU Media OS and TOFU Media Center) preloaded is their Pivos XIOS XS media player. == VidOn Media Center by VidOn.me == VidOn.me, or VidOnMe, is a company that maintains a commercial fork and derivative of XBMC media center software, named VidOn Media Center (formerly VidOn XBMC), and other than offering non-XBMC based media player software
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{"page_id": 35442587, "title": "List of software based on Kodi and XBMC"}
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Chromodomain helicase DNA-binding (CHD) proteins is a subfamily of ATP-dependent chromatin remodeling complexes (remodelers). All remodelers fall under the umbrella of RNA/DNA helicase superfamily 2. In yeast, CHD complexes are primarily responsible for nucleosome assembly and organization. These complexes play an additional role in multicellular eukaryotes, assisting in chromatin access and nucleosome editing. == Functions of CHD subfamily proteins == Similar to the imitation switch (ISWI) subfamily of ATP-dependent chromatin remodelers, CHD complexes regulate the assembly and organization of mature nucleosomes along the DNA. Histones are removed during DNA replication; following behind the replisome, histones start to assemble as immature pre-nucleosomes on nascent DNA. With the help of CHD complexes, histone octamers can mature into native nucleosomes. Following nucleosome formation, CHD complexes organize nucleosomes by regularly spacing them apart along the DNA. Additionally, CHDs in higher-order organisms can slide/eject nucleosomes or histone dimers to allosterically regulate DNA accessibility. Specific CHD complexes, such as the nucleosome remodeling deacetylase (NuRD) complex in C. elegans, can expose binding sites for transcriptional repressors along the chromatin by interacting with highly-modular histone tails; deacetylation of the histone residue H3K9ac is an example of how the NuRD complex can downregulate gene expression and affect DNA topology. The final mechanism of this subfamily of ATP-dependent remodelers is nucleosome editing. Drosophila dCHD1 can edit nucleosomes by swapping out histone H3 for the variant H3.3. Binding of dCHD1 near the nucleosome causes tension in the DNA. To relieve this tension, an upstream H3 dimer is displaced from the nucleosome, allowing for its replacement by histone variant H3.3. The addition of H3.3 into the nucleosomes is an epigenetic way to keep the chromatin in an accessible, transcription-ready, state. Incorporation of alternative histones and post-translational modifications (PTMs) play an integral role in regulating the cell's histone code. == Structure of CHD
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{"page_id": 63787599, "title": "Chromodomain helicase DNA-binding (CHD) subfamily"}
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Nanofiber Seeding is a process to control the bulk morphology of chemically synthesized conducting polymers. Typically, catalytic amount of nanofiber seeds are added in prior to onset of nanofiber seeding polymerization (reaction), where seeds are served as the 'morphology directing agent' rather than conventional templates (see hard or soft templating methods). == Description == A new synthetic approach, called nanofiber seeding,1 was developed to control the bulk morphology of chemically synthesized electronic organic polymers. Bulk quantities of nanofibers of conducting polymers such as polyaniline, can be synthesized in one step without the need for conventional templates, surfactants, polymers, or organic solvents.3 Conventional oxidative polymerization approaches to nanostructured conducting polymers include the use of hard template zeolites, opals, and controlled pore-size membranes, or soft template such as polymers and surfactants. A “template-free” approach has also been described in which the use of large organic anions results in polyaniline nanofibers and nanotubes having average diameters in the 650-80 nm range.1 Standard synthesis of polyaniline yields granular morphology. However, if the conventional reaction is seeded by 1-4 mg (seed quantities) of added pre-synthesized polyaniline nanofibers, (nanofiber seeds could be prepared from interfacial polymerization) the bulk morphology changes dramatically from granular to nano-fibrillar. Furthermore, increased capacitance values were observed in polyaniline nanofibers synthesized by the nanofiber seeding approach. Oxidative polymerization can be also seeded by other nanostructure materials such as vanadium pentoxide nanofibers, where V2O5 nanofibers (i) Rapidly initiate fibrillar polymer growth (ii) Slowly dissolve in aq. 1.0 M HCl, which eliminates template removal steps. Hence only catalytic amounts (4mg) V2O5 nanofibers are needed prior to onset of polymerization, which significantly change the bulk morphology of the polymer precipitate. Moreover, single-walled carbon nanotube and nano fibrous hexapeptide can be also used as templating seeds. This method can be extended to all major classes of
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{"page_id": 4383471, "title": "Nanofiber seeding"}
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and Problems in Differential Equations (1963). == History == In China, from ancient times counting rods were used to represent numbers, and arithmetic was accomplished with rod calculus and later the suanpan. The Book on Numbers and Computation and the Nine Chapters on the Mathematical Art include exercises that are exemplars of linear algebra. In about 980 Al-Sijzi wrote his Ways of Making Easy the Derivation of Geometrical Figures, which was translated and published by Jan Hogendijk in 1996. An Arabic language collection of exercises was given a Spanish translation as Compendio de Algebra de Abenbéder and reviewed in Nature. Robert Recorde first published The Ground of Arts in 1543. Firstly, it was almost all exposition with very few exercises — The later came into prominence in the eighteenth and nineteenth centuries. As a comparison we might look at another best seller, namely Walkingame’s Tutor's Assistant, first published in 1751, 70 per cent of which was devoted to exercises as opposed to about 1 per cent by Recorde. The inclusion of exercises was one of the most significant subsequent developments in arithmetical textbooks, and paralleled the development of education as teachers began to make use of textbooks as sources of exercises. Recorde was writing mainly for those who were teaching themselves, scholars who would have no one to check their answers to the exercises. In Europe before 1900, the science of graphical perspective framed geometrical exercises. For example, in 1719 Brook Taylor wrote in New Principles of Linear Perspective [The Reader] will find much more pleasure in observing how extensive these Principles are, by applying them to particular Cases which he himself shall devise, while he exercises himself in this Art,... Taylor continued ...for the true and best way of learning any Art, is not to see a great many
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{"page_id": 35557313, "title": "Exercise (mathematics)"}
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explored elsewhere. In the field of statistics, these alternative interpretations allow for the analysis of different datasets using distinct methods based on various models, aiming to achieve slightly different objectives. When comparing the competing schools of thought in statistics, pragmatic criteria beyond philosophical considerations are taken into account. === Major contributors === Fisher and Neyman were significant figures in the development of frequentist (classical) methods. While Fisher had a unique interpretation of probability that differed from Bayesian principles, Neyman adhered strictly to the frequentist approach. In the realm of Bayesian statistical philosophy, mathematics, and methods, de Finetti, Jeffreys, and Savage emerged as notable contributors during the 20th century. Savage played a crucial role in popularizing de Finetti's ideas in English-speaking regions and establishing rigorous Bayesian mathematics. In 1965, Dennis Lindley's two-volume work titled "Introduction to Probability and Statistics from a Bayesian Viewpoint" played a vital role in introducing Bayesian methods to a wide audience. For three generations, statistics have progressed significantly, and the views of early contributors are not necessarily considered authoritative in present times. === Contrasting approaches === ==== Frequentist inference ==== The earlier description briefly highlights frequentist inference, which encompasses Fisher's "significance testing" and Neyman-Pearson's "hypothesis testing." Frequentist inference incorporates various perspectives and allows for scientific conclusions, operational decisions, and parameter estimation with or without confidence intervals. ==== Bayesian inference ==== A classical frequency distribution provides information about the probability of the observed data. By applying Bayes' theorem, a more abstract concept is introduced, which involves estimating the probability of a hypothesis (associated with a theory) given the data. This concept, formerly referred to as "inverse probability," is realized through Bayesian inference. Bayesian inference involves updating the probability estimate for a hypothesis as new evidence becomes available. It explicitly considers both the evidence and prior beliefs, enabling the
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{"page_id": 15515301, "title": "Foundations of statistics"}
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that, under certain circumstances, very low human exposure to chemicals found to cause cancer in animals nevertheless could be found safe under the "reasonable certainty of no harm" safety standard for food additives. Some commentators argued that FDA should interpret the Delaney Clause as allowing FDA to approve food additives based on a de minimis risk legal interpretation. In 1981, Taylor argued in Legal Times of Washington that it was the role of Congress, not FDA, to decide if there should be a de minimis interpretation of the Delaney Clause. In 1986, after FDA had established a de minimis risk interpretation for color additives he made a presentation at the Brookings Institution, subsequently published, explaining the legal and policy rationale for FDA's interpretation and urging that FDA take a cautious, science-based approach to its implementation with protection of public health as its overriding concern. From 1986 to 1987, Taylor served on a National Academy of Sciences Committee that studied the application of the Delaney Clause in pesticide regulation and participated in a Keystone Center dialogue on pesticide regulation, which contributed to legislation that strengthened safety standards for residues of carcinogenic pesticides in food. == Government Service at FDA and USDA, 1991 - 1996 == == US Food and Drug Administration, 1991-1994 == On July 17, 1991, Michael Taylor left King & Spalding to return to the FDA in the newly created post of Deputy Commissioner for Policy established by FDA Commissioner David A. Kessler. In this position, Taylor led FDA's new Office of Policy and, on behalf of the commissioner, oversaw development of policy and regulations in all FDA program areas, including food, drugs, and medical devices. A major focus area for FDA during this period was implementation of the Nutrition Labeling and Education Act of 1990, which overhauled food
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{"page_id": 25935018, "title": "Michael R. Taylor"}
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being repeated multiple times. Figure 3.4 briefly presents the approach followed in bootstrap sampling. This technique is particularly useful in case of input data sets of small size, i.e. having very less number of data instances. FIG. 3.4 Bootstrap sampling 3.3.4 Lazy vs. Eager learner Eager learning follows the general principles of machine learning – it tries to construct a generalized, input-independent target function during the model training phase. It follows the typical steps of machine learning, i.e. abstraction and generalization and comes up with a trained model at the end of the learning phase. Hence, when the test data comes in for classification, the eager learner is ready with the model and doesn’t need to refer back to the training data. Eager learners take more time in the learning phase than the lazy learners. Some of the algorithms which adopt eager learning approach include Decision Tree, Support Vector Machine, Neural Network, etc. Lazy learning, on the other hand, completely skips the abstraction and generalization processes, as explained in context of a typical machine learning process. In that respect, strictly speaking, lazy learner doesn’t ‘learn’ anything. It uses the training data in exact, and uses the knowledge to classify the unlabelled test data. Since lazy learning uses training data as-is, it is also known as rote learning (i.e. memorization technique based on repetition). Due to its heavy dependency on the given training data instance, it is also known as instance learning. They are also called non-parametric learning. Lazy learners take very little time in training because not much of training actually happens. However, it takes quite some time in classification as for each tuple of test data, a comparison-based assignment of label happens. One of the most popular algorithm for lazy learning is k-nearest neighbor. Note: Parametric learning models have
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{"source": 1196, "title": "from dpo"}
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organizations, and miscellaneous from text. 4 Machine Comprehension (aka MC): 机器理解 answers natural language questions by selecting an answer span within an evidence text. 5 Textual Entailment (aka TE): 文本蕴涵 takes a pair of sentences and predicts whether the facts in the first necessarily imply the facts in the second one. 判断兩个句子能否互相推论 6 Semantic Role Labeling (aka SRL): 语义角色标注 7 References Beyond Word Embeddings Part 1","tags":[{"name":"Draft","slug":"Draft","permalink":" code{white-space: pre-wrap;} span.smallcaps{font-variant: small-caps;} span.underline{text-decoration: underline;} div.column{display: inline-block; vertical-align: top; width: 50%;} 1 Draft Text representation: 如何让计算机明白单词的含义(understand the concepts of words)? word vectors: words or phrases from a given language vocabulary are mapped to vectors of real numbers. 2 Traditional vector representation Bag of Words (aka BoW) don’t encode any information with regards to the meaning of a given word. 共现矩阵 SVD（奇异值分解） 3 Neural Embeddings 3.1 Word2Vec Continuous bag-of-words (CBOW) Continuous skip-gram GloVe FastText 4 References 从Word Embedding到Bert模型—自然语言处理中的预训练技术发展史 Word Embeddings: An Introduction to the NLP Landscape 词向量发展史-共现矩阵-SVD-NNLM-Word2Vec-Glove-ELMo Word Vectors and NLP Modeling from BoW to BERT","tags":[{"name":"Draft","slug":"Draft","permalink":" code{white-space: pre-wrap;} span.smallcaps{font-variant: small-caps;} span.underline{text-decoration: underline;} div.column{display: inline-block; vertical-align: top; width: 50%;} 1 Example A school is running a machine learning primary diabetes scan on all of its students. The output is either diabetic (+ve) or healthy (-ve). True positive (TP): Prediction is +ve and X is diabetic, we want that True negative (TN): Prediction is -ve and X is healthy, we want that too False positive (FP): Prediction is +ve and X is healthy, false alarm, bad False negative (FN): Prediction is -ve and X is diabetic, the worst If it starts with True then the prediction was correct If it starts with False then the prediction was incorrect Positive or negative indicates the output of our program. While true or false judges this output whether correct or incorrect. --------------------------+--------------------------------+-------- | Predicted (预测) | |--------------------------------| | |
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{"source": 3396, "title": "from dpo"}
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+ o(1)) √2πnn ne−n. Remark 1.2.1. The dominated convergence theorem does not imme-diately give any effective rate on the decay o(1) (though such a rate can eventually be extracted by a quantitative version of the above argument. But one can combine (1.49) with (1.46) to show that the error rate is of the form O(1 /n ). By using fancier versions of the trapezoid rule (e.g. Simpson’s rule ) one can obtain an asymptotic expansion of the error term in 1 /n ; see [ KeVa2007 ]. Remark 1.2.2. The derivation of (1.49) demonstrates some general principles concerning the estimation of exponential integrals ∫ eφ(x) dx when φ is large. Firstly, the integral is dominated by the local maxima of φ. Then, near these maxima, eφ(x) usually behaves like a rescaled Gaussian, as can be seen by Taylor expansion (though more compli-cated behaviour emerges if the second derivative of φ degenerates). So one can often understand the asymptotics of such integrals by a change of variables designed to reveal the Gaussian behaviour. This technique is known as Laplace’s method . A similar set of principles also holds for oscillatory exponential integrals ∫ eiφ (x) dx ; these prin-ciples are collectively referred to as the method of stationary phase .1.3. Eigenvalues and sums 45 One can use Stirling’s formula to estimate binomial coefficients. Here is a crude bound: Exercise 1.2.1 (Entropy formula) . Let n be large, let 0 < γ < 1 be fixed, and let 1 ≤ m ≤ n be an integer of the form m = ( γ + o(1)) n.Show that ( nm ) = exp(( h(γ) + o(1)) n), where h(γ) is the entropy function h(γ) := γ log 1 γ + (1 − γ) log 11 − γ . For m near n/ 2,
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{"source": 5648, "title": "from dpo"}
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the result above can be evaluated by a series expansion and shown to be equivalent to the electric field of a point charge Q . We can calculate the field close to the disk along the axis by assuming x ,, R ; in this case, the expression in brackets reduces to unity to give us the near-field approximation E 5 2pke s 5 s 2P0 where P0 is the permittivity of free space. In Chapter 24, we obtain the same result for the field created by an infinite plane of charge with uniform surface charge density. What if we let the radius of the disk grow so that the disk becomes an infinite plane of charge? Answer The result of letting R S ` in the final result of the example is that the magnitude of the electric field becomes E 5 2pke s 5 s 2P0 This is the same expression that we obtained for x ,, R . If R S `, everywhere is near-field—the result is independent of the position at which you measure the electric field. Therefore, the electric field due to an infinite plane of charge is uniform throughout space. An infinite plane of charge is impossible in practice. If two planes of charge are placed close to each other, however, with one plane positively charged, and the other negatively, the electric field between the plates is very close to uni-form at points far from the edges. Such a configuration will be investigated in Chapter 26. W h a T I F ? Categorize Because the disk is continuous, we are evaluating the field due to a continuous charge distribution rather than a group of individual charges. Analyze Find the amount of charge dq on the surface area of a ring of radius r
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{"source": 6644, "title": "from dpo"}
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systems having the same power as a Turing machine increases to nine. In each mobility rule from systems of simple and enhanced mobile membranes, in the left hand side of the rules only one object appears in the proofs. By using multisets instead of objects and synchronization by objects and co-objects, it is proved that it is enough to consider only systems of three mutual mobile membranes together with the operations of mutual endocytosis and mutual exocytosis to get the full computational power of a Turing machine. The proof is done in a similar manner with the proof for the computational universality of the systems of enhanced mobile membranes [20]. === Mutual Membranes with Objects on Surface === Membrane systems [24] and brane calculus [10] start from the same observations; however, they are built having in mind different goals: membrane systems investigate formally the computational nature and power of various features of membranes, while the brane calculus is capable to give a faithful and intuitive representation of the biological reality. In [12] the initiators of these two formalisms describe the goals they had in mind: "While membrane computing is a branch of natural computing which tries to abstract computing models, in the Turing sense, from the structure and the functioning of the cell, making use especially of automata, language, and complexity theoretic tools, brane calculi pay more attention to the fidelity to the biological reality, have as a primary target systems biology, and use especially the framework of process~algebra." In [2] are defined systems of mutual membranes with objects on surface, following the idea of adding objects on membrane and using the biologically inspired rules pino/exo/phago coming from [12,14,18,19]. Objects and co-objects are used in phago and exo rules in order to illustrate the fact that both involved membranes agree
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{"page_id": 25513182, "title": "Mobile membranes"}
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In genetic engineering, a gene gun or biolistic particle delivery system is a device used to deliver exogenous DNA (transgenes), RNA, or protein to cells. By coating particles of a heavy metal with a gene of interest and firing these micro-projectiles into cells using mechanical force, an integration of desired genetic information can be introduced into desired cells. The technique involved with such micro-projectile delivery of DNA is often referred to as biolistics, short for "biological ballistics". This device is able to transform almost any type of cell and is not limited to the transformation of the nucleus; it can also transform organelles, including plastids and mitochondria. == Gene gun design == The gene gun was originally a Crosman air pistol modified to fire dense tungsten particles. It was invented by John C Sanford, Ed Wolf, and Nelson Allen at Cornell University along with Ted Klein of DuPont between 1983 and 1986. The original target was onions (chosen for their large cell size), and the device was used to deliver particles coated with a marker gene which would relay a signal if proper insertion of the DNA transcript occurred. Genetic transformation was demonstrated upon observed expression of the marker gene within onion cells. The earliest custom manufactured gene guns (fabricated by Nelson Allen) used a 22 caliber nail gun cartridge to propel a polyethylene cylinder (bullet) down a 22 caliber Douglas barrel. A droplet of the tungsten powder coated with genetic material was placed onto the bullet and shot down into a Petri dish below. The bullet welded to the disk below the Petri plate, and the genetic material blasted into the sample with a doughnut effect involving devastation in the middle of the sample with a ring of good transformation around the periphery. The gun was connected to a
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{"page_id": 961961, "title": "Gene gun"}
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The Communications Assistance for Law Enforcement Act (CALEA), also known as the "Digital Telephony Act," is a United States wiretapping law passed in 1994, during the presidency of Bill Clinton (Pub. L. No. 103-414, 108 Stat. 4279, codified at 47 USC 1001–1010). CALEA's purpose is to enhance the ability of law enforcement agencies to conduct lawful interception of communication by requiring that telecommunications carriers and manufacturers of telecommunications equipment modify and design their equipment, facilities, and services to ensure that they have built-in capabilities for targeted surveillance, allowing federal agencies to selectively wiretap any telephone traffic; it has since been extended to cover broadband Internet and VoIP traffic. Some government agencies argue that it covers mass surveillance of communications rather than just tapping specific lines and that not all CALEA-based access requires a warrant. Journalists and technologists have characterised the CALEA-mandated infrastructure as government backdoors. In 2024, the U.S. government realized that China had been tapping communications in the U.S. using that infrastructure for months, or perhaps longer. The original reason for adopting CALEA was the Federal Bureau of Investigation's worry that increasing use of digital telephone exchange switches would make tapping phones at the phone company's central office harder and slower to execute, or in some cases impossible. Since the original requirement to add CALEA-compliant interfaces required phone companies to modify or replace hardware and software in their systems, U.S. Congress included funding for a limited time period to cover such network upgrades. CALEA was passed into law on October 25, 1994, and came into force on January 1, 1995. In the years since CALEA was passed it has been greatly expanded to include all VoIP and broadband Internet traffic. From 2004 to 2007 there was a 62 percent growth in the number of wiretaps performed under CALEA –
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{"page_id": 530413, "title": "Communications Assistance for Law Enforcement Act"}
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Heritage Documentation Programs (HDP) is a division of the U.S. National Park Service (NPS). It administers three programs established to document historic places in the United States: Historic American Buildings Survey (HABS), Historic American Engineering Record (HAER), and Historic American Landscapes Survey (HALS). Its records include measured drawings, archival photographs, and written reports, all archived in the Library of Congress' Prints and Photographs Division. == History == === Historic American Buildings Survey === In 1933, the Historic American Buildings Survey was established following a proposal by Charles E. Peterson, a young landscape architect in the National Park Service. Peterson proposed that the survey would be "Almost a complete resume of the builder's art." Though it was founded as a temporary, "ten-weeks" constructive make-work program for architects, draftsmen, and photographers left jobless by the Great Depression, the Historic American Buildings Survey has endured to this day. The program was later supported through the Historic Sites Act of 1935. Guided by field instructions from Washington, D.C., the first HABS recorders were tasked with documenting a representative sampling of the nation's architectural heritage. They began to document the built environment in the United States, carrying out multi-format surveys that has today amassed "more than 581,000 measured drawings, large-format photographs, written histories, and original field notes for more than 43,000 historic structures and sites dating from Pre-Columbian times to the twentieth century." By creating an archive of historic architecture, HABS provided a database of primary source material and documentation for the then-fledgling historic preservation movement. Peterson stated that the survey initially would, "...include public buildings, churches, residences, bridges, forts, barns, mills, shops, rural outbuildings, and any other kind of structure of which there are good specimens extant." The acting Chief of HABS, Catherine Lavoie stated in 2011 that HABS was, "Documenting the worthy and
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{"page_id": 1606205, "title": "Heritage Documentation Programs"}
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space has the Eulerian spanning subgraphs as its elements. spanner A spanner is a (usually sparse) graph whose shortest path distances approximate those in a dense graph or other metric space. Variations include geometric spanners, graphs whose vertices are points in a geometric space; tree spanners, spanning trees of a graph whose distances approximate the graph distances, and graph spanners, sparse subgraphs of a dense graph whose distances approximate the original graph's distances. A greedy spanner is a graph spanner constructed by a greedy algorithm, generally one that considers all edges from shortest to longest and keeps the ones that are needed to preserve the distance approximation. spanning A subgraph is spanning when it includes all of the vertices of the given graph. Important cases include spanning trees, spanning subgraphs that are trees, and perfect matchings, spanning subgraphs that are matchings. A spanning subgraph may also be called a factor, especially (but not only) when it is regular. sparse A sparse graph is one that has few edges relative to its number of vertices. In some definitions the same property should also be true for all subgraphs of the given graph. spectral spectrum The spectrum of a graph is the collection of eigenvalues of its adjacency matrix. Spectral graph theory is the branch of graph theory that uses spectra to analyze graphs. See also spectral expansion. split 1. A split graph is a graph whose vertices can be partitioned into a clique and an independent set. A related class of graphs, the double split graphs, are used in the proof of the strong perfect graph theorem. 2. A split of an arbitrary graph is a partition of its vertices into two nonempty subsets, such that the edges spanning this cut form a complete bipartite subgraph. The splits of a graph
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{"page_id": 325802, "title": "Glossary of graph theory"}
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mobile. Other examples include Intelligent Network and local number portability databases.: 433 === Signaling modes === Apart from signaling with these various degrees of association with call set-up and the facilities used to carry calls, SS7 is designed to operate in two modes: associated mode and quasi-associated mode. When operating in the associated mode, SS7 signaling progresses from switch to switch through the Public Switched Telephone Network following the same path as the associated facilities that carry the telephone call. This mode is more economical for small networks. The associated mode of signaling is not the predominant choice of modes in North America. When operating in the quasi-associated mode, SS7 signaling progresses from the originating switch to the terminating switch, following a path through a separate SS7 signaling network composed of signal transfer points. This mode is more economical for large networks with lightly loaded signaling links. The quasi-associated mode of signaling is the predominant choice of modes in North America. == Physical network == SS7 separates signaling from the voice circuits. An SS7 network must be made up of SS7-capable equipment from end to end in order to provide its full functionality. The network can be made up of several link types (A, B, C, D, E, and F) and three signaling nodes – Service Switching Points (SSPs), Signal Transfer Points (STPs), and Service Control Points (SCPs). Each node is identified on the network by a number, a signaling point code. Extended services are provided by a database interface at the SCP level using the SS7 network. The links between nodes are full-duplex 56, 64, 1,536, or 1,984 kbit/s graded communications channels. In Europe they are usually one (64 kbit/s) or all (1,984 kbit/s) timeslots (DS0s) within an E1 facility; in North America one (56 or 64 kbit/s) or
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{"page_id": 100098, "title": "Signalling System No. 7"}
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light-years) until the observation of GRB 090423 a few months later. 23 April 2009: Swift detected GRB 090423, the most distant cosmic explosion ever seen at that time, at 13.035 billion light-years. In other words, the universe was only 630 million years old when this burst occurred. 29 April 2009: Swift detected GRB 090429B, which was found by later analysis published in 2011 to be 13.14 billion light-years distant (approximately equivalent to 520 million years after the Big Bang), even farther than GRB 090423. 16 March 2010: Swift tied its record by again detecting and localizing four bursts in a single day. 13 April 2010: Swift detected its 500th GRB. 28 March 2011: Swift detected Swift J1644+57 which subsequent analysis showed to possibly be the signature of a star being disrupted by a black hole or the ignition of an active galactic nucleus. "This is truly different from any explosive event we have seen before", said Joshua Bloom of the University of California, Berkeley, the lead author of the study published in the June issue of Science. 16 and 17 September 2012: BAT triggered two times on a previously unknown hard X-ray source, named Sw J1745-26, a few degrees from the Galactic Center. The outburst, produced by a rare X-ray nova, announced the presence of a previously unknown stellar-mass black hole undergoing a dramatic transition from the low/hard to the high/soft state. 2013: Discovery of ultra-long class of gamma-ray bursts 24 April 2013: Swift detected an X-ray flare from the Galactic Center. This proved not to be related to Sgr A* but to a previously unsuspected magnetar. Later observations by the NuSTAR and the Chandra X-ray Observatory confirmed the detection. 27 April 2013: Swift detected the "shockingly bright" Gamma-ray burst GRB 130427A. Observed simultaneously by the Fermi Gamma-ray Space Telescope,
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{"page_id": 1190936, "title": "Neil Gehrels Swift Observatory"}
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that would be otherwise ignored. == Example == As a simple example, consider the following DNA sequences: Upon visual inspection, it's easy to see that there is a mismatch between the two sequences at the fifth and six base positions (in bold, above). However, the sequences still share 80% sequence similarity. The mismatches may be due to a real (biological) change or a sequencing error. In a non-spaced model, this putative match would be ignored if a seed size greater than 4 is specified. But a spaced seed of 1111001111 {\displaystyle 1111001111} could be used to effectively zero-weighting the mismatch sites, treating the sequences as same for the purposes of hit identification. In reality, of course, we don't know the relative positioning of the "true" mismatches, so there can be different spaced seed patterns depending on where the mismatches are anticipated. == History == The concept of spaced seeds has been explored in literature under different names. One of the early uses was in sequence homology where the FLASH algorithm from 1993 referred to it as "non-contiguous sub-sequences of tokens" that were generated from all combinations of positions within a sequence window. In 1995, a similar concept was used in approximate string matching where "gapped tuples" of positions in a sequence were explored to identify common substrings between a large text and a query. The term "shape" was used in a 2001 paper to describe gapped q-grams where it refers to a set of relevant positions in a substring and soon after in 2002, PatternHunter introduced "spaced model" which was proposed as an improvement upon the consecutive seeds used in BLAST, which was ultimately adopted by newer versions of it. Finally, in 2003, PatternHunter II settled on the term "spaced seed" to refer to the approach used in PatternHunter ==
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{"page_id": 63095134, "title": "Spaced seed"}
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BSDP "SELECT" message. The 01 declares that field specifies the BSDP Message Type. The next 01 indicates that the field contents are one byte long — 02 is the code for "SELECT". The following 08 04 81 00 07 e5 means that the boot image with the ID 2164262885 is selected. Finally, 82 0a 4e 65 74 42 6f 6f 74 30 30 31 means that a string with 0x0a = 10 characters, namely "NetBoot001", is the name of the system to boot. == Sources == BSDP documentation from Apple's bootpd several conversations captured with Wireshark Source code of Darwin's BOOTP server, https://github.com/apple-oss-distributions/bootp == References ==
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{"page_id": 19879607, "title": "Boot Service Discovery Protocol"}
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scanned array (PESA). The design of the N011M Bars antenna like the earlier N007 antenna consists of two separate electronically controlled arrays, an X band radar and an L band IFF transponder with a total weight of 100 kg and a diameter of 960 mm. The radar has a peak power output of 4-5 kW and is capable of positioning beams in 400 microseconds, a huge advantage over mechanically scanned radar. The Bars radar can be fixed in position to give a scanning sector of ±70 degrees in azimuth and ±45 degrees in elevation. To improve scan coverage, the radar can also be mounted on electromechanical drives, and in this case, the scanning sector is expanded to ±90 degrees. The 28 MHz Ts200 programmable signal processor used in N011M incorporates Fourier transforms of "butterfly" type capable of 75 Million operations per second. The N011M supports digital signal processing using 3 processors with 16 MB of both static and flash memory. The peak output is 4 to 5 kW with an average output of 1.2 kW, and the total radar system weighs around 650 kg. N011M is used on Su-30SM, Su-30MKI, Su-30MKM, and the contract for the N011M radar has three stages. The initial MK1 software was tested in 2002 and supplied with the first Su-30MKI deliveries. India was supposed to build both programmable signal processors and data processors under project "Vetrivale" to replace the original Russian components, but failed to do so within the required time frame, so MK2 still used the Russian equipment. In 2004, India delivered Vetrivale radar computer based in the i960 architecture. It's worth noting that N011M is not simply a PESA, but instead, it's a transition between PESA and AESA in that it adopts technologies from both: each transceiver on the antenna array of N011M
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{"page_id": 14939080, "title": "Bars radar"}
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predict your specific needs and desires. Mattersight Corporation is using personality and behavior to route calls through call centers, and its latest “Predictive Video” system promises to ana-lyze your speech and facial expressions from any video where you’ve appeared. Cambridge Analytica ,claims to have used algorithmic profiling to help Donald Trump win the election. What’s Next Researchers at the University of Cambridge’s Psychometrics Centre developed an algorithm that predicts personality traits from Facebook likes. ElectronicArts is working on a system that assesses the personality of its multiplayer video game users to do a better job of matching players, using their play style, conversational style, and willingness to spend money. In the real world, insur-ance underwriters are attempting to assess your personality—via your magazine and website sub-scriptions, the photos you post to social media, and more—in order to determine how risky an invest-ment you are. Some lenders have used personality algorithms to predict your future financial transac-tions. (The data show that if you look at two people with the same professional and personal circum-stances, the one with a higher college G.P.A. will be more likely to pay off a debt.) Meanwhile, facial and tonal recognition analytics will help machine learn-ing systems to detect consumers’ emotional state in real-time. Algorithms will harness your data in order to assess your predicted success at work, how likely you are to bounce around jobs and more. Watchlist Mattersight Corporation; Cambridge Analytica; Cal-iper; University of Texas; MIT; IBM; Twitter; Crystal; Stanford University; Salesforce; Autodesk; Syman-tec; Mobileye; Intuit; Adobe. 032 064 © 2018 FUTURE TODAY INSTITUTE INFORMS STRATEGY REVISIT LATER ACT NOW KEEP VIGILANT WATCH HIGH DEGREE OF CERTAINTY LOW DEGREE OF CERTAINTY IMMEDIATE IMPACT ON THE NEWS INDUSTRY LONGER-TERM IMPACT ON THE NEWS INDUSTRY INFORMS STRATEGY REVISIT LATER ACT NOW KEEP VIGILANT WATCH HIGH DEGREE OF
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{"source": 1743, "title": "from dpo"}
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Originally Posted by ThePerfectHacker ... You do this by factoring, $(4x^2+8x)+(3y^2-6y)=0$ Factor, $4(x^2+2x)+3(y^2-6y)=0$ ... Hello TPH, it looks to me as if you have made a typo here: $4(x^2+2x)+3(y^2-$6y $)=0$ EB 4. Hello, jhonwashington! This problem has particularly ugly numbers . . . I'll modify it. This is the approach I've taught in my classes. $4x^2 + 3y^2 + 8x - 6y\:=$ 5 We have: . $4x^2+8x + 3y^2-6y\:=\:5$ . Factor "in groups": . $4(x^2 + 2x\qquad) + 3(y^2 - 2y\qquad) \:=\:5$ This is the complete-the-square step: . . Take one-half of the coefficient of the linear term and square it. . . "Add to both sides." The coefficient of $x$ is $2.$ . . $\frac{1}{2}(2) = 1\quad\Rightarrow\quad 1^2 = 1$ So we "add to both sides" . . but be careful! We have: . $4(x^2 + 2x \,+\,$1 $) + 3(y^2 - 2y\qquad)\:=\:5\,+$4 . Why 4 ? . . . . . . . . $\hookrightarrow$ . . . . . $\uparrow$ . . . . . . . . . We wrote $+1$ on the left side . . . . . . . . but it is multiplied by the leading 4. . . . . . . . So we actually added 4 to the left side. Complete the square for the $y$-terms. . . $\frac{1}{2}(-2) = -1\quad\Rightarrow\quad (-1)^2=1$ "Add to both sides": . $4(x^2 + 2x + 1) + 3(y^2 + 2y \,+\,$1 $) \;=\;9 \,+$ 3 Factor: . $4(x+1)^2 + 3(y-1)^2\;=\;12$ Divide by $12\!:\;\;\frac{4(x+1)^2}{12} + \frac{3(y-1)^2}{12}\;=\;1$ Then we have: . $\frac{(x+1)^2}{3} + \frac{(y-1)^2}{4} \;=\;1$ The ellipse is centered at $(-1,1)$ Its semiminor axis (x- direction) is: $\sqrt{3}$ Its semimajor axis (y-direction) is: $2$ 5. Thank you so much for the help ThePerfectHacker ,earboth and soroban, just one last question, how do you guys factorize?
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{"source": 4160, "title": "from dpo"}
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20: ldr r0,iAdrszMessNoSolution bl affichageMess mov r0,#0 mov r1,#0 cmp r0,#0 // carry to 1 No solution 100: pop {r2-r12,lr} // restaur registers bx lr // return /******************************************************************/ /* search i */ /******************************************************************/ // r0 contains t // r1 contains maxi // r2 contains modulo // r0 return i searchI: push {r1-r6,lr} mov r4,r0 // t mov r6,r1 // m mov r3,#1 // i 1: mov r5,#1 lsl r5,r5,r3 // compute 2 power i mov r0,r4 mov r1,r5 bl moduloPuR32 // compute t pow 2 pow i mod p cmp r0,#1 // = 1 ? beq 3f // yes it is ok add r3,r3,#1 // next i cmp r3,r6 blt 1b // loop mov r0,#-1 // not find b 100f 3: mov r0,r3 // return i 100: pop {r1-r6,lr} // restaur registers bx lr // return /******************************************************************/ /* display numbers */ /******************************************************************/ /* r0 contains number */ /* r1 contains modulo */ displayEntry: push {r0-r3,lr} mov r2,r1 // root 2 ldr r1,iAdrsZoneConv // convert root 1 in r0 bl conversion10S // convert ascii string ldr r0,iAdrszMessEntry ldr r1,iAdrsZoneConv bl strInsertAtCharInc // and put in message mov r3,r0 mov r0,r2 // racine 2 ldr r1,iAdrsZoneConv bl conversion10S // convert ascii string mov r0,r3 ldr r1,iAdrsZoneConv bl strInsertAtCharInc // and put in message bl affichageMess 100: pop {r0-r3,lr} // restaur registers bx lr // return iAdrszMessEntry: .int szMessEntry /******************************************************************/ /* display roots */ /******************************************************************/ /* r0 contains root 1 */ /* r1 contains root 2 */ displayResult: push {r1-r3,lr} mov r2,r1 // root 2 ldr r1,iAdrsZoneConv // convert root 1 in r0 bl conversion10S // convert ascii string ldr r0,iAdrszMessResult ldr r1,iAdrsZoneConv bl strInsertAtCharInc // and put in message mov r3,r0 mov r0,r2 // racine 2 ldr r1,iAdrsZoneConv bl conversion10S // convert ascii string mov r0,r3 ldr r1,iAdrsZoneConv bl strInsertAtCharInc // and
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{"source": 5943, "title": "from dpo"}
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large-scale simulations. It is shown that this can only happen if some elements interact more strongly among themselves than with the rest of the system including a large amount of reentrancy. These functional clusters are only slowly coming into the range of PET or fMRI scanning technology which commonly require much longer time scales. At any given time, only a small subset of the neuronal groups in the brain are contributing directly to consciousness and this cluster is called a dynamic core. It represents a single point of view and each different state of consciousness corresponds to a different subset. Some dissociative disorders such as schizophrenia may result in the formation of multiple cores. === Implications of the hypothesis === One of the recurring issues in consciousness is the existence of qualia, such as redness, warmth and pain. It is not enough to identify each quale with a particular neuron or neuronal group; what is crucial is all the other groups which are highly influenced by the sensation and will fire at the same time. Thus each conscious state deserves to be called a quale. A small perturbation of a group of neurons can affect the whole in a very short space of time provided the system is kept in a state of readiness by the thalamus. Primary consciousness can build up a bodily based reference space even before language and higher-order consciousness appear. There is a preliminary approach to the relationship between conscious and unconscious processes, including sensors and motors, because so little is known. The evolution of language centres in the brain leads to higher order consciousness which enhances subjective experience and enables humans to describe qualia which are however experienced by a much wider range of animals. Thinking in humans has a range of representations—including pictorial. In
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{"page_id": 1379832, "title": "A Universe of Consciousness"}
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(2nd ed.). ISBN 978-0-521-51468-2. Carr, Lincoln D. (2010). Understanding Quantum Phase Transitions. CRC Press. ISBN 978-1-4398-0251-9. Vojta, Thomas (2000). "Quantum phase transitions in electronic systems". Annalen der Physik. 9 (6): 403–440. arXiv:cond-mat/9910514. Bibcode:2000AnP...512..403V. doi:10.1002/1521-3889(200006)9:6<403::AID-ANDP403>3.0.CO;2-R. de Souza, Mariano (2020). "Unveiling the Physics of the Mutual Interactions in Paramagnets". Scientific Reports. Vol. 10. doi:10.1038/s41598-020-64632-x.
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{"page_id": 682937, "title": "Quantum phase transition"}
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correlations in the data. If the average correlation between variables is not high, then the CFI will not be very high. A CFI value of .95 or higher is desirable. The following table provides references documenting these, and other, features for some common indices: the RMSEA (Root Mean Square Error of Approximation), SRMR (Standardized Root Mean Squared Residual), CFI (Confirmatory Fit Index), and the TLI (the Tucker-Lewis Index). Additional indices such as the AIC (Akaike Information Criterion) can be found in most SEM introductions. For each measure of fit, a decision as to what represents a good-enough fit between the model and the data reflects the researcher's modeling objective (perhaps challenging someone else's model, or improving measurement); whether or not the model is to be claimed as having been "tested"; and whether the researcher is comfortable "disregarding" evidence of the index-documented degree of ill fit. === Sample size, power, and estimation === Researchers agree samples should be large enough to provide stable coefficient estimates and reasonable testing power but there is no general consensus regarding specific required sample sizes, or even how to determine appropriate sample sizes. Recommendations have been based on the number of coefficients to be estimated, the number of modeled variables, and Monte Carlo simulations addressing specific model coefficients. Sample size recommendations based on the ratio of the number of indicators to latents are factor oriented and do not apply to models employing single indicators having fixed nonzero measurement error variances. Overall, for moderate sized models without statistically difficult-to-estimate coefficients, the required sample sizes (N’s) seem roughly comparable to the N’s required for a regression employing all the indicators. The larger the sample size, the greater the likelihood of including cases that are not causally homogeneous. Consequently, increasing N to improve the likelihood of being able to
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{"page_id": 2007748, "title": "Structural equation modeling"}
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Further reading == Establish culture, strategy and processes - Innovation security (CAF Secure) Define Security Practices and Controls - DevSecOps controls Assess your current workloads with the well architected security assessment - Well Architected Review == External links == Official website
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{"page_id": 3685303, "title": "Microsoft Security Development Lifecycle"}
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defined moment of mean solar noon; this enabled all ships and civilians within sight to know the exact time. By the end of the American Civil War, the Observatory's clocks were linked via telegraph to ring the alarm bells in all of the Washington, D.C. firehouses three times a day. The USNO held a one-off time-ball re-enactment for the year-2000 celebration. === Nautical Almanac Office === In 1849, the Nautical Almanac Office (NAO) was established in Cambridge, Massachusetts as a separate organization. In 1866, it was moved to Washington, D.C., operating near Fort Myer. It relocated to the U.S. Naval Observatory grounds in 1893. On 20 September 1894, the NAO became a "branch" of USNO; however, it remained autonomous for several years. The site houses the largest astronomy library in the United States (and the largest astrophysical periodicals collection in the world). The library includes a large collection of rare physics and astronomy books from the past millennium. === Measuring the astronomical unit === An early scientific duty assigned to the Observatory was the U.S. contribution to the definition of the Astronomical Unit, or the AU, which defines a standard mean distance between the Sun and the Earth. This was conducted under the auspices of the congressionally-funded U.S. Transit of Venus Commission. The astronomical measurements taken of the transit of Venus by a number of countries since 1639 resulted in a progressively more accurate definition of the AU. Relying strongly on photographic methods, the naval observers returned 350 photographic plates in 1874, and 1,380 measurable plates in 1882. The results of the surveys conducted simultaneously from several locations around the world (for each of the two transits) produced a final value of the solar parallax, after adjustments, of 8.809″, with a probable error of 0.0059″, yielding a U.S.-determined Earth-Sun distance
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{"page_id": 43596, "title": "United States Naval Observatory"}
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stages: Initiation the process of generating the initial free radical. Propagation the conversion of one active species to another Chain branching steps which end with more than one active species being produced. The photolysis of hydroperoxides is the main example. Termination steps in which active species are removed, for instance by radical disproportionation Photo-oxidation can occur simultaneously with other processes like thermal degradation, and each of these can accelerate the other. === Polyolefins === Polyolefins such as polyethylene and polypropylene are susceptible to photo-oxidation and around 70% of light stabilizers produced world-wide are used in their protection, despite them representing only around 50% of global plastic production. Aliphatic hydrocarbons can only adsorb high energy UV-rays with a wavelength below ~250 nm, however the Earth's atmosphere and ozone layer screen out such rays, with the normal minimum wavelength being 280–290 nm. The bulk of the polymer is therefore photo-inert and degradation is instead attributed to the presence of various impurities, which are introduced during the manufacturing or processing stages. These include hydroperoxide and carbonyl groups, as well as metal salts such as catalyst residues. All of these species act as photoinitiators. The organic hydroperoxide and carbonyl groups are able to absorb UV light above 290 nm whereupon they undergo photolysis to generate radicals. Metal impurities act as photocatalysts, although such reactions can be complex. It has also been suggested that polymer-O2 charge-transfer complexes are involved. Initiation generates radical-carbons on the polymer chain, sometimes called macroradicals (P•). Chain initiation Polymer ⟶ P ∙ + P ∙ {\displaystyle {\ce {Polymer->P\bullet +\ P\bullet }}} Chain propagation P ∙ + O 2 ⟶ POO ∙ {\displaystyle {\ce {P\bullet +\ O2->POO\bullet }}} POO ∙ + PH ⟶ POOH + P ∙ {\displaystyle {\ce {POO\bullet +\ PH->{POOH}+\ P\bullet }}} Chain branching POOH ⟶ PO ∙ + OH
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{"page_id": 17377095, "title": "Photo-oxidation of polymers"}
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system thanks to this assumption. Another way to understand this is that the equation I a + I b + I c = 0 {\displaystyle I_{a}+I_{b}+I_{c}=0} defines a plane in a euclidean three coordinate space. The alpha-beta coordinate space can be understood as the two coordinate space defined by this plane, i.e. the alpha-beta axes lie on the plane defined by I a + I b + I c = 0 {\displaystyle I_{a}+I_{b}+I_{c}=0} . This also means that in order the use the Clarke transform, one must ensure the system is balanced, otherwise subsequent two coordinate calculations will be erroneous. This is a practical consideration in applications where the three phase quantities are measured and can possibly have measurement error. === dq0 transform === The d q 0 {\displaystyle dq0} transform is conceptually similar to the α β γ {\displaystyle \alpha \beta \gamma } transform. Whereas the d q 0 {\displaystyle dq0} transform is the projection of the phase quantities onto a rotating two-axis reference frame, the α β γ {\displaystyle \alpha \beta \gamma } transform can be thought of as the projection of the phase quantities onto a stationary two-axis reference frame. == See also == Symmetrical components Y-Δ transform Vector control (motor) == References == General references
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{"page_id": 20561282, "title": "Alpha–beta transformation"}
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matrix needs to be rescaled before it can be subtracted from the DNA matrices. By using molecular clock proteins, the scaling coefficient for protein distance/RNA distance can be calculated. This coefficient is used to rescale the RNA matrix. === Rosetta stone (gene fusion) method === The Rosetta Stone or Domain Fusion method is based on the hypothesis that interacting proteins are sometimes fused into a single protein. For instance, two or more separate proteins in a genome may be identified as fused into one single protein in another genome. The separate proteins are likely to interact and thus are likely functionally related. An example of this is the Human Succinyl coA Transferase enzyme, which is found as one protein in humans but as two separate proteins, Acetate coA Transferase alpha and Acetate coA Transferase beta, in Escherichia coli. In order to identify these sequences, a sequence similarity algorithm such as the one used by BLAST is necessary. For example, if we had the amino acid sequences of proteins A and B and the amino acid sequences of all proteins in a certain genome, we could check each protein in that genome for non-overlapping regions of sequence similarity to both proteins A and B. Figure B depicts the BLAST sequence alignment of Succinyl coA Transferase with its two separate homologs in E. coli. The two subunits have non-overlapping regions of sequence similarity with the human protein, indicated by the pink regions, with the alpha subunit similar to the first half of the protein and the beta similar to the second half. One limit of this method is that not all proteins that interact can be found fused in another genome, and therefore cannot be identified by this method. On the other hand, the fusion of two proteins does not necessitate that
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{"page_id": 4350008, "title": "Protein–protein interaction prediction"}
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seeds were produced in Arabidopsis thaliana by dipping the flowers in an Agrobacterium solution. In 2013 CRISPR was first used to target modification of plant genomes. The first genetically engineered crop plant was tobacco, reported in 1983. It was developed creating a chimeric gene that joined an antibiotic resistant gene to the T1 plasmid from Agrobacterium. The tobacco was infected with Agrobacterium transformed with this plasmid resulting in the chimeric gene being inserted into the plant. Through tissue culture techniques a single tobacco cell was selected that contained the gene and a new plant grown from it. The first field trials of genetically engineered plants occurred in France and the US in 1986, tobacco plants were engineered to be resistant to herbicides. In 1987 Plant Genetic Systems, founded by Marc Van Montagu and Jeff Schell, was the first company to genetically engineer insect-resistant plants by incorporating genes that produced insecticidal proteins from Bacillus thuringiensis (Bt) into tobacco. The People's Republic of China was the first country to commercialise transgenic plants, introducing a virus-resistant tobacco in 1992. In 1994 Calgene attained approval to commercially release the Flavr Savr tomato, a tomato engineered to have a longer shelf life. Also in 1994, the European Union approved tobacco engineered to be resistant to the herbicide bromoxynil, making it the first genetically engineered crop commercialised in Europe. In 1995 Bt Potato was approved safe by the Environmental Protection Agency, after having been approved by the FDA, making it the first pesticide producing crop to be approved in the US. In 1996 a total of 35 approvals had been granted to commercially grow 8 transgenic crops and one flower crop (carnation), with 8 different traits in 6 countries plus the EU. By 2010, 29 countries had planted commercialised genetically modified crops and a further 31
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{"page_id": 2291204, "title": "Genetically modified crops"}
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the sound more efficiently to the eardrum. Their resistance is much higher (typically megohms) so they do not greatly "load" the tuned circuit, allowing increased selectivity of the receiver. The piezoelectric earphone's higher resistance, in parallel with its capacitance of around 9 pF, creates a filter that allows the passage of low frequencies, but blocks the higher frequencies.: 45 In that case a bypass capacitor is not needed (although in practice a small one of around 0.68 to 1 nF is often used to help improve quality), but instead a 10–100 kΩ resistor must be added in parallel with the earphone's input.: 94 : 80 Although the low power produced by crystal radios is typically insufficient to drive a loudspeaker, some homemade 1960s sets have used one, with an audio transformer to match the low impedance of the speaker to the circuit.: 80-81 Similarly, modern low-impedance (8 Ω) earphones cannot be used unmodified in crystal sets because the receiver does not produce enough current to drive them. They are sometimes used by adding an audio transformer to match their impedance with the higher impedance of the driving antenna circuit. == History == The first radio transmitters, used during the initial three decades of radio from 1887 to 1917, a period called the wireless telegraphy era, were primitive spark transmitters which generated radio waves by discharging a capacitance through an electric spark.: 45–48 : 3–8 : 57–68 Each spark produced a transient pulse of radio waves which decreased rapidly to zero.: 4–9, 297–300 : 6–8 These damped waves could not be modulated to carry sound, as in modern AM and FM transmission. So spark transmitters could not transmit sound, and instead transmitted information by radiotelegraphy. The transmitter was switched on and off rapidly by the operator using a telegraph key, creating
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{"page_id": 232249, "title": "Crystal radio"}
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habit. Second language learning was seen as the development of a new set of habits. The role of the native language, then, took on great significance, because, in this view of language learning, it was the major cause for lack of success in learning the L2. The habits established in childhood interfered with the establishment of a different set of habits. From this framework emerged contrastive analysis, because if one is to talk about replacing a set of habits (let’s say, the habits of English) with another set of habits (let’s say, those of Italian), valid descriptions are needed comparing the “rules” of the two languages. It would be mis-leading, however, to consider contrastive analysis in a monolithic fashion. In fact, there are two distinct traditions of contrastive analysis that emerged. In the North American tradition, the emphasis was on language teaching and, by implication, language learning. Contrastive analyses were conducted with the ultimate goal of improving classroom materials. As 95 T H E RO L E O F T H E N AT I V E L A N G UA G E Fisiak (1991) noted, this is more appropriately considered “applied con-trastive analysis.” In the European tradition, the goal of contrastive analysis was not pedagogical. Rather, the goal of language comparison was to gain a greater understanding of language. In fact, within the European tradition, it is maintained that contrastive analysis is a subdis-cipline of linguistics. Its goal, like the goal of linguistics, is to understand the nature of language. In this book, we focus on the North American tradition as it relates more directly to the field of second language acquisition. ## 4.3 Contrastive Analysis Hypothesis What are the tenets of contrastive analysis? Contrastive analysis is a way of comparing languages in order to determine potential errors
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{"source": 982, "title": "from dpo"}
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links between different social clusters that proved to be essential for information dissemination, and thus reach-ing out to other groups than one’s own [Granovetter, 1973]. Understanding Granovetter’s work required a mathematical approach to social networks. Social network analysis evolved steadily ever since then, and many rig-orous techniques have been developed. We have now reached a new point. As mentioned, sociologists developed various models on how groups of people organize themselves. One particular famous one is the small-world organization, which we discussed in Chapter 7. The problem that researchers faced was how to validate those models: setting up sociological experiments with many participants is far from trivial as Milgram experienced in the late 1960s (recall that we discussed Milgram’s experiments in Chapter 7). With online communities, researchers suddenly have tremendous sociolog-ical data sets in their hands. As we will also discuss in this chapter, we can apply similar analyses to these sets not only to validate models of how so-cial networks evolve or how they are structured, but also to discover new properties that are inherently tied to the size of a network. As argued by Kleinberg , it is equally important that the analysis of these online social communities will perhaps put us in a much better position to devise large-scale distributed computer systems such as the fully decentralized peer-to-peer systems discussed in Chapter 8. We are already seeing better search strategies that are based on grouping peers by a notion Copyrighted material - January 2010 - Draft Copyrighted material - January 2010 - Draft 9.1. SOCIAL NETWORK ANALYSIS: INTRODUCTION 9-9 of similarity, and many other phenomena related to social networking. 9.1.3 Sociograms in practice: a teacher’s aid Let us consider an example of a sociogram. One particular use of sociograms is in classrooms allowing a teacher to obtain better
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{"source": 4215, "title": "from dpo"}
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is probably best to use this command only at the end of a \foreach command. \begin{tikzpicture} \foreach \x in {1,...,4} \foreach \y in {1,...,4} {\fill[red!50] (\x,\y) ellipse (3pt and 6pt); \ifnum \x<\y \breakforeach \fi }\end{tikzpicture} 249 35 Date and Calendar Utility Macros This section describes the package pgfcalendar . \usepackage{pgfcalendar} % L ATEX \input pgfcalendar.tex % plain TEX \usemodule[pgfcalendar] % ConTEXt This package can be used independently of pgf . It has two purposes: 1. It provides functions for working with dates. Most noticably, it can convert a date in ISO-standard format (like 1975-12-26) to a so-called Julian day number, which is defined in Wikipedia as follows: “The Julian day or Julian day number is the (integer) number of days that have elapsed since the initial epoch at noon Universal Time (UT) Monday, January 1, 4713 BC in the proleptic Julian calendar.” The package also provides a function for converting a Julian day number to an ISO-format date. Julian day numbers make it very easy to work with days. For example, the date ten days in the future of 2008-02-20 can be computed by converting this date to a Julian day number, adding 10, and then converting it back. Also, the day of week of a given date can be computed by taking the Julian day number modulo 7. 2. It provides a macro for typesetting a calendar. This macro is highly configurable and flexible (for example, it can produce both plain text calendars and also complicated Ti k Z-based calendars), but most users will not use the macro directly. It is the job of a frontend to provide useful configruations for typesetting calendars based on this command. 35.1 Handling Dates 35.1.1 Conversions Between Date Types \pgfcalendardatetojulian{ 〈date 〉}{ 〈counter 〉} This macro converts a date in a format to
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{"source": 4960, "title": "from dpo"}
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applicable to the problem of variance stabilization. Variance Stabilization of Proportions Suppose our dependent variable were a proportion (e.g., the proportion of correct responses on a test comprised of a fixed number of items). The variance of a proportion is greatest when the proportion P = .50, and diminishes as P approaches either 0 or 1; specifically, G2P = P(l — P). The arcsine transformation introduced in Section 6.4.12 stabilizes variances. Weighted Least Squares Regression for Variance Stabilization Weighted least squares regression provides an alternative approach to the analysis of data that exhibit heteroscedasticity of residuals. This approach was described in detail in Section 4.5.4. 6.4.14 Transformations to Normalize Variables We undertake transformations to normalize variables in several circumstances. One is that we have skewed Xs and/or Y. Another is that we are dealing with variables that are inherently not normally distributed, for example ranks. Transformations to Eliminate Skew Recall that inference in OLS regression assumes that residuals are normally distributed. If we analyze a data set with OLS regression and find that residuals are not normally distributed, for example, by examining a q-q plot of residuals against a normal variate (Section 4.3), then transformation of Y may be in order. Skew in the dependent variable may well be the source of the skewed residuals. Our approach, then, is to transform the DV in the hopes of achieving more normal residuals. 6.4 NONLINEAR TRANSFORMATIONS 247 We can transform Y to be more normally distributed following the rules from the ladder of re-expression, that values of X > 1 decrease negative skew, and values of X < 1 decrease pos-itive skew in the distribution of the transformed variable (see Section 6.4.8). Several values of X can be tried, the transformed variable plotted as a histogram with a normal distribution over-layed or
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{"source": 6256, "title": "from dpo"}
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semantic artefacts". OpenAI's Sam Altman himself criticized what he called "GPT-3 hype", acknowledging GPT-3 "has serious weakness and sometimes makes very silly mistakes... AI is going to change the world, but GPT-3 is just a very early glimpse." === Criticism === GPT-3's builder, OpenAI, was initially founded as a non-profit in 2015. In 2019, OpenAI broke from its usual open-source standards by not publicly releasing GPT-3's predecessor model, citing concerns that the model could facilitate the propagation of fake news. OpenAI eventually released a version of GPT-2 that was 8% of the original model's size. In the same year, OpenAI restructured to be a for-profit company. In 2020, Microsoft announced the company had exclusive licensing of GPT-3 for Microsoft's products and services following a multi-billion dollar investment in OpenAI. The agreement permits OpenAI to offer a public-facing API such that users can send text to GPT-3 to receive the model's output, but only Microsoft will have access to GPT-3's source code. Large language models, such as GPT-3, have come under criticism from a few of Google's AI ethics researchers for the environmental impact of training and storing the models, detailed in a paper co-authored by Timnit Gebru and Emily M. Bender in 2021. The growing use of automated writing technologies based on GPT-3 and other language generators, has raised concerns regarding academic integrity and raised the stakes of how universities and schools will gauge what constitutes academic misconduct such as plagiarism. OpenAI's GPT series was built with data from the Common Crawl dataset, a conglomerate of copyrighted articles, internet posts, web pages, and books scraped from 60 million domains over a period of 12 years. TechCrunch reports this training data includes copyrighted material from the BBC, The New York Times, Reddit, the full text of online books, and more. In
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{"page_id": 64695824, "title": "GPT-3"}
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so less heavy breathing is needed. The increase in the temperature of the skin can be felt at the same time as the "second wind" takes place. Documented experiences of the second wind go back at least 100 years, when it was taken to be a commonly held fact of exercise. The phenomenon has come to be used as a metaphor for continuing on with renewed energy past the point thought to be one's prime, whether in other sports, careers, or life in general. == Hypotheses == === Metabolic switching === When non-aerobic glycogen metabolism is insufficient to meet energy demands, physiologic mechanisms utilize alternative sources of energy such as fatty acids and proteins via aerobic respiration. Second-wind phenomena in metabolic disorders such as McArdle's disease are attributed to this metabolic switch and the same or a similar phenomenon may occur in healthy individuals (see symptoms of McArdle's disease). === Lactic acid === Muscular exercise as well as other cellular functions requires oxygen to produce ATP and properly function. This normal function is called aerobic metabolism and does not produce lactic acid if enough oxygen is present. During heavy exercise such as long distance running or any demanding exercise, the body's need for oxygen to produce energy is higher than the oxygen supplied in the blood from respiration. Anaerobic metabolism to some degree then takes place in the muscle and this less ideal energy production produces lactic acid as a waste metabolite. If the oxygen supply is not soon restored, this may lead to accumulation of lactic acid. This is the case even without exercise in people with respiratory disease, challenged circulation of blood to parts of the body or any other situation when oxygen cannot be supplied to the tissues involved. Some people's bodies may take more time than
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{"page_id": 11504627, "title": "Second wind"}
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better manner. In other words, the beginning of evolving a particular trait starts out with a primary adaptation toward a fit or specific role, followed by a primary exaptation (a new role is derived using the existing feature but may not be perfect for it), which in turn leads to the evolution of a secondary adaptation (the feature is improved by natural selection for better performance), promoting further evolution of an exaptation, and so forth. Once again, feathers are an important example, in that they may have first been adapted for thermoregulation and with time became useful for catching insects, and therefore served as a new feature for another benefit. For instance, large contour feathers with specific arrangements arose as an adaptation for catching insects more successfully, which eventually led to flight, since the larger feathers served better for that purpose. == Implications == === Evolution of complex traits === One of the challenges to Darwin's theory of evolution was explaining how complex structures could evolve gradually, given that their incipient forms may have been inadequate to serve any function. As George Jackson Mivart (a critic of Darwin) pointed out, 5 percent of a bird wing would not be functional. The incipient form of complex traits would not have survived long enough to evolve to a useful form. As Darwin elaborated in the last edition of The Origin of Species, many complex traits evolved from earlier traits that had served different functions. By trapping air, primitive wings would have enabled birds to efficiently regulate their temperature, in part, by lifting up their feathers when too warm. Individual animals with more of this functionality would more successfully survive and reproduce, resulting in the proliferation and intensification of the trait. Eventually, feathers became sufficiently large to enable some individuals to glide. These
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{"page_id": 1242211, "title": "Exaptation"}
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In control system theory, and various branches of engineering, a transfer function matrix, or just transfer matrix is a generalisation of the transfer functions of single-input single-output (SISO) systems to multiple-input and multiple-output (MIMO) systems. The matrix relates the outputs of the system to its inputs. It is a particularly useful construction for linear time-invariant (LTI) systems because it can be expressed in terms of the s-plane. In some systems, especially ones consisting entirely of passive components, it can be ambiguous which variables are inputs and which are outputs. In electrical engineering, a common scheme is to gather all the voltage variables on one side and all the current variables on the other regardless of which are inputs or outputs. This results in all the elements of the transfer matrix being in units of impedance. The concept of impedance (and hence impedance matrices) has been borrowed into other energy domains by analogy, especially mechanics and acoustics. Many control systems span several different energy domains. This requires transfer matrices with elements in mixed units. This is needed both to describe transducers that make connections between domains and to describe the system as a whole. If the matrix is to properly model energy flows in the system, compatible variables must be chosen to allow this. == General == A MIMO system with m outputs and n inputs is represented by a m × n matrix. Each entry in the matrix is in the form of a transfer function relating an output to an input. For example, for a three-input, two-output system, one might write, [ y 1 y 2 ] = [ g 11 g 12 g 13 g 21 g 22 g 23 ] [ u 1 u 2 u 3 ] {\displaystyle {\begin{bmatrix}y_{1}\\y_{2}\end{bmatrix}}={\begin{bmatrix}g_{11}&g_{12}&g_{13}\\g_{21}&g_{22}&g_{23}\end{bmatrix}}{\begin{bmatrix}u_{1}\\u_{2}\\u_{3}\end{bmatrix}}} where the un are the inputs, the
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{"page_id": 48259106, "title": "Transfer function matrix"}
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draft; it contained rules for creating an RDFa parser, as well as guidelines for organizations wishing to make practical use of the technology. In October 2008 RDFa 1.0 reached recommendation status. RDFa 1.1 reached recommendation status in June 2012. It differs from RDFa 1.0 in that it no longer relies on the XML-specific namespace mechanism. Therefore, it is possible to use RDFa 1.1 with non-XML document types such as HTML 4 or HTML 5. Details can be found in an appendix to HTML 5. An additional RDFa 1.1 Primer document was last updated 17 March 2015. (The first public Working Draft dates back to 10 March 2006.) == Versions and variants == There are some main well-defined variants of the basic concepts, that are used as reference and as abbreviation to the W3C standards. === HTML+RDFa === RDFa was defined in 2008 with the "RDFa in XHTML: Syntax and Processing" Recommendation. Its first application was to be a module of XHTML. The HTML applications remained, "a collection of attributes and processing rules for extending XHTML to support RDF" expanded to HTML5, are now expressed in a specialized standard, the "HTML+RDFa" (the last is "HTML+RDFa 1.1 - Support for RDFa in HTML4 and HTML5"). === RDFa 1.0 === The "HTML+RDFa" syntax of 2008 was also termed "RDFa 1.0", so, there is no "RDFa Core 1.0" standard. In general this 2008's RDFa 1.0 is used with the old XHTML standards (as long as RDFa 1.1 is used with XHTML5 and HTML5). === RDFa 1.1 === Is the first generic (for HTML and XML) RDFa standard; the "RDFa Core 1.1" is in the Third Edition, since 2015. === RDFa Lite === RDFa Lite is a W3C Recommendation (1.0 and 1.1) since 2009, where it is described as follows: RDFa Lite is minimal subset
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{"page_id": 4321818, "title": "RDFa"}
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HD 73389 is a binary star system in the constellation Carina. It has the Bayer designation e2 Carinae; HD 73389 is the identifier from the Henry Draper Catalogue. This system is visible to the naked eye as a point of light with a combined apparent visual magnitude of +4.84. Based on parallax measurements, it is located at a distance of approximately 225 light years from the Sun. The system is drifting further away with a radial velocity of +25.6 km/s. The visual magnitude 5.08 primary, component A, is an aging K-type giant star with a stellar classification of K0III. With the supply of hydrogen at its core exhausted, it has cooled and expanded to 11 times the Sun's radius. It is radiating 64 times the luminosity of the Sun from its enlarged photosphere at an effective temperature of 4,903 K. The secondary companion, component B, has a visual magnitude of 8.02 and is located at an angular separation of 0.30″ along a position angle of 207° from the primary, as of 2015. == References ==
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{"page_id": 5068223, "title": "HD 73389"}
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modernization has driven the study of soroban from public schools to private after school classrooms. Where once it was an institutionally required subject in school for children grades 2 to 6, current laws have made keeping this art form and perspective on math practiced amongst the younger generations more lenient. Today, it shifted from a given to a game where one can take The Japanese Chamber of Commerce and Industry's examination in order to obtain a certificate and license. There are six levels of mastery, starting from sixth-grade (very skilled) all the way up to first-grade (for those who have completely mastered the use of the soroban). Those obtaining at least a third-grade certificate/license are qualified to work in public corporations. The soroban is still taught in some primary schools as a way to visualize and grapple with mathematical concepts. The practice of soroban includes the teacher reciting a string of numbers (addition, subtraction, multiplication, and division) in a song-like manner where at the end, the answer is given by the teacher. This helps train the ability to follow the tempo given by the teacher while remaining calm and accurate. In this way, it reflects on a fundamental aspect of Japanese culture of practicing meditative repetition in every aspect of life. Primary school students often bring two soroban to class, one with the modern configuration and the other one having the older configuration of one heavenly bead and five earth beads. Shortly after the beginning of one's soroban studies, drills to enhance mental calculation, known as anzan (暗算, "blind calculation") in Japanese, are incorporated. Students are asked to solve problems mentally by visualizing the soroban and working out the solution by moving the beads theoretically in one's mind. The mastery of anzan is one reason why, despite the access to
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{"page_id": 914987, "title": "Soroban"}
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The Intelligent Ground Vehicle Competition (IGVC) is an annual international robotics competition for teams of undergraduate and graduate students. Teams may compete in either the AutoNav or Self Drive challenges. The competition is well suited to senior design capstone courses as well as extracurricular design projects. The competition has taken place each year since 1993 with the exception of 2020 due to the COVID-19 pandemic. The competition is normally held on the campus of Oakland University in Rochester, Michigan, although it has occasionally moved to other venues within the state of Michigan. The competition is often sponsored by Oakland University, the U.S. Army DEVCOM Ground Vehicle Systems Center, and the Association for Unmanned Vehicle Systems International (AUVSI) in addition to other sponsors. == Competition Overview == The details of the competition change each year and has featured several different challenges. The 2024 challenges are AutoNav, Self Drive, and Design. Previous challenges include the Cyber Security Challenge, IOP Challenge, Spec 2 Challenge, and the JAUS challenge. The AutoNav challenge requires teams to design and build autonomous ground robots that are between 3 feet and 7 feet long. The challenge tasks the robots with navigating a complex course featuring lanes, obstacles, and a ramp. The course was placed on grass from 1993 to 2019 but was changed to asphalt in 2021. Teams are ranked by the time it took to complete the course or by distance traveled for teams that did not complete the course. The Self Drive challenge features two-seat electric passenger vehicles that must autonomously complete a variety of challenges. The Self Drive challenge began in 2017 as the Spec 2 Challenge. Unlike the AutoNav challenge, most teams acquire a complete vehicle and then modify it to complete the challenge. == References ==
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{"page_id": 28218027, "title": "Intelligent Ground Vehicle Competition"}
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The albedo reported for an astronomical body may vary widely by the spectral and angular distribution of the incident radiation, by the "layer" of the body being measured (e.g. upper atmosphere versus surface), and by local variation within these layers (e.g. cloud cover and geological or environmental surface features). albedo feature A large area on the surface of a reflecting object that shows a significant contrast in brightness or darkness (albedo) compared to adjacent areas. Alfvén surface The boundary separating a star's corona from the stellar wind defined as where the coronal plasma's Alfvén speed and the large-scale stellar wind speed are equal. Am star A chemically peculiar star belonging to the more general class of A-type stars. The spectrum of the Am stars shows abnormal enhancements and deficiencies of certain metals. See metallicity. aphelion The point at which a body orbiting the Earth's Sun is furthest from the Sun. Contrast perihelion. apoapsis The point at which an orbiting body is furthest from its primary. Contrast periapsis. apogee The point at which a body orbiting the Earth (such as the Moon or an artificial satellite) is furthest from the Earth. Contrast perigee. apparent magnitude Also visual brightness (V). A measure of the brightness of a celestial body as seen by an observer on Earth, adjusted to the value it would have in the absence of the atmosphere. The brighter the object appears, the lower its magnitude. appulse The closest approach of one celestial object to another, as viewed from a third body. apsis In the orbit of a planetary body, one of the two extreme points of distance between the body and its primary – either the point of minimal distance, called the periapsis, or the point of maximal distance, called the apoapsis. The term may also be used to
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{"page_id": 34809573, "title": "Glossary of astronomy"}
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R Andromedae (R And) is a Mira-type variable star in the constellation Andromeda. Its spectral class is type S because it shows absorption bands of zirconium monoxide (ZrO) in its spectrum. It was among the stars found by Paul Merrill to show absorption lines of the unstable element technetium, establishing that nucleosynthesis must be occurring in stars. The SH molecule was found for the first time outside earth in the atmosphere of this star. The star is losing mass due to stellar winds at a rate of 1.09×10−6 M☉/yr. == Variability == R Andromedae shows periodic variations in its brightness approximately every 409 days. The maximum brightness is not the same every cycle and can reach a peak magnitude of mv = 5.8, with the lowest known minima nearly 10 magnitudes fainter. The rise to maximum brightness is approximately twice as fast as the fall to minimum brightness. It is classified as a Mira variable. Those stars contract and expand regularly, changing size and temperature, and this causes the brightness variations. == Properties == R Andromedae has a spectral type that varies as its brightness changes. At a typical maximum it is assigned a spectral type of S5/4.5e. This makes it an S-type star, a red giant similar to class M stars but with unusually strong molecular bands of ZrO in its spectrum compared to the titanium oxide (TiO) bands seen in other cool giants. S stars are intermediate between carbon stars and the more typical oxygen-rich giants. The S5 indicates its relative temperature, while the number after the slash is a measure of the relative C:O ratio, 4.5 meaning carbon is about 97% as abundant as oxygen. ZrO bands in R Andromedae are about twenty times stronger than those of TiO. When it is fainter, the spectral type has
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{"page_id": 12566334, "title": "R Andromedae"}
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heterogeneous model ensembles are also called information fusion models (Delen and Sharda, 2010) or stacking (more infor-mation on these is given later in this chapter). Bagging Bagging is the simplest and most common ensemble method. Leo Breiman, a very well-respected scholar in the world of statistics and analytics, is known to have first pub-lished a description of bagging (i.e., Bootstrap Aggregating) algorithm at the University of California–Berkeley in 1996 (Breiman, 1996). The idea behind bagging is quite simple yet powerful: build multiple decision trees from resampled data and combine the predicted values through averaging or voting. The resampling method Breiman used was bootstrap sampling (sampling with replacement), which creates replicates of some records in the training data. With this selection method, on average, about 37 percent of the records will not be included at all in the training data set (Abbott, 2014). Although bagging was first developed for decision trees, the idea can be applied to any predictive modeling algorithm that produces outcomes with sufficient variation in the predicted values. Although rare in practice, the other predictive modeling algorithms that are potential candidates for bagging-type model ensembles include neural networks, Naïve Bayes, k-nearest neighbor (for low values of k), and, to a lesser degree, even logis-tic regression. k-nearest neighbor is not a good candidate for bagging if the value of k is > [Rare - Active Research Area] Systematically weighing data samples for better prediction modeling [Rare] Other types of single-model-type bagging (e.g., Ann) > Bagging Homogeneous Heterogeneous Boosting > Stacking (meta-modeling) Simple/Complex model weighing Ensemble trees Random forest Information fusion AdaBoost XGBoost [Rare - Active Research Area] Other types of single-model-type boosting Method Type Model Type > FIGURE 5.20 Simple Taxonomy for Model Ensembles. Chapter 5 • Machine-Learning Techniques for Predictive Analytics 333 already large; the algorithm already votes
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{"source": 1196, "title": "from dpo"}
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address of the _Offeror_’s official responsible for acknowledging receipt of or rejecting the ISRs, to all first-tier subcontractors with subcontracting plans so they can enter this information into the eSRS when submitting their ISRs; and (vii) Require that each subcontractor with a subcontracting plan provide the prime contract number, its own _unique entity identifier_, and the e-mail address of the subcontractor’s official responsible for acknowledging receipt of or rejecting the ISRs, to its subcontractors with subcontracting plans. (11) A description of the types of records that will be maintained concerning procedures that have been adopted to comply with the requirements and goals in the plan, including establishing source lists; and a description of the _offeror_’s efforts to locate small business, veteran-owned small business, service-disabled veteran-owned small business, _HUBZone_ small business, small disadvantaged business, and _women-owned small business concerns_ and award _subcontracts_ to them. The records _shall_ include at least the following (on a plant-wide or company-wide basis, unless otherwise indicated): (i) Source lists (_e.g.,_ SAM), guides, and other data that identify small business, veteran-owned small business, service-disabled veteran-owned small business, _HUBZone_ small business, small disadvantaged business, and _women-owned small business concerns_. (ii) Organizations contacted in an attempt to locate sources that are small business, veteran-owned small business, service-disabled veteran-owned small business, _HUBZone_ small business, small disadvantaged business, or _women-owned small business concerns_. (iii) Records on each _subcontract_ _solicitation_ resulting in an award of more than the _simplified acquisition threshold_, as defined in FAR 2.101 on the date of _subcontract_ award, indicating- (A) Whether small business concerns were solicited and, if not, why not; (B) Whether veteran-owned small business concerns were solicited and, if not, why not; (C) Whether service-disabled veteran-owned small business concerns were solicited and, if not, why not; (D) Whether _HUBZone_ small business concerns were solicited and,
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{"source": 3644, "title": "from dpo"}
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f fdμ > Ef1A E-A =v(EnA) + f fdμ E-A =v(E). In other words, f +EI A lies in .1; since j(f+ EI A ) dμ = a + Eμ(A) > a, this contradicts the maximality of f. Therefore, μ and v s are mutually singular, and there exists an S such that vs(S) = μ(S`) = O. But since y « μ, v s(S`) s v(S`) = 0, and so v s(fl) = O. The rightmost term in (32.8) thus drops out. ■ Absolute continuity was not used until the last step of the proof, and what the argument shows is that v always has a decomposition (32.8) into an absolutely continuous part and a singular part with respect to μ. This is the Lebesgue decomposition, and it generalizes the one in the preceding section (see (31.31)). PROBLEMS 32.1. There are two ways to show that the convergence in (32.1) must be absolute: Use the Jordan decomposition. Use the fact that a series converges absolutely if it has the same sum no matter what order the terms are taken in. 32.2. If A + uA - is a Hahn decomposition of cp, there may be other ones Al UAL . Construct an example of this. Show that there is uniqueness to the extent that cp(A + oAi) = cp(A - AAA) = O. 32.3. Show that absolute continuity does not imply the f-e condition (32.4) if v is infinite. Hint. Let g- consist of all subsets of the space of integers, let v be counting measure, and let p have mass n -2 at n. Note that u is finite and v is a--finite. 32.4. Show that the Radon-Nikodym theorem fails if ,u, is not a-finite, even if v is finite. Hint: Let Y- consist of the countable and
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{"source": 5649, "title": "from dpo"}
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$\triangle KYX$ be the orthic triangle of $\triangle AST$; in that case line $XY$ meets the $\omega$ again at $P$ and $Q$. \begin{center} \begin{asy} size(9cm); pair A = dir(125); pair B = -A; pair S = dir(210); pair T = dir(330); pair O = midpoint(A--B); pair X = foot(T, A, S); pair E = dir(0); filldraw(unitcircle, opacity(0.2)+mediumcyan, mediumblue); pair M = midpoint(S--T); filldraw(A--S--T--cycle, opacity(0.4)+mediumgreen, heavygreen); draw(T--X, heavygreen); draw(A--M, heavygreen); pair Y = foot(S, A, T); pair K = foot(A, S, T); filldraw(circumcircle(X, Y, M), opacity(0.1)+yellow, red); draw(S--Y, heavygreen); draw(A--K, heavygreen); pair P = IP(unitcircle, X--(3*Y-2*X)); pair Q = IP(unitcircle, Y--(3*X-2*Y)); pair V = extension(P, Q, S, T); draw(P--Q, blue); draw(A--B, blue); draw(Q--V, blue); draw(V--S, heavygreen); dot("$A$", A, dir(A)); dot("$B$", B, dir(B)); dot("$S$", S, dir(S)); dot("$T$", T, dir(T)); dot("$O$", O, dir(45)); dot("$X$", X, dir(135)); dot("$M$", M, dir(M)); dot("$Y$", Y, dir(70)); dot("$K$", K, dir(K)); dot("$P$", P, dir(P)); dot("$Q$", Q, dir(150)); dot("$V$", V, dir(V)); /* TSQ Source: !size(9cm); A = dir 125 B = -A S = dir 210 T = dir 330 O = midpoint A--B R45 X = foot T A S R135 E := dir 0 unitcircle 0.2 mediumcyan / mediumblue M = midpoint S--T A--S--T--cycle 0.4 mediumgreen / heavygreen T--X heavygreen A--M heavygreen Y = foot S A T R70 K = foot A S T circumcircle X Y M 0.1 yellow / red S--Y heavygreen A--K heavygreen P = IP unitcircle X--(3*Y-2*X) Q = IP unitcircle Y--(3*X-2*Y) R150 V = extension P Q S T P--Q blue A--B blue Q--V blue V--S heavygreen */ \end{asy} \end{center} The main claim is: \begin{claim*} Quadrilateral $PQKM$ is cyclic. \end{claim*} \begin{proof} To see this, we use power of a point: let $V = \ol{QXYP} \cap \ol{SKMT}$. One approach is that since $(VK;ST) = -1$ we have $VQ \cdot VP = VS \cdot
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{"source": 6669, "title": "from dpo"}
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in a query, and obtains a reply in the form of a weighted sum of the values, where the weight is proportional to how closely the query resembles each key. The decoder first processes the "<start>" input partially, to obtain an intermediate vector h 0 d {\displaystyle h_{0}^{d}} , the 0th hidden vector of decoder. Then, the intermediate vector is transformed by a linear map W Q {\displaystyle W^{Q}} into a query vector q 0 = h 0 d W Q {\displaystyle q_{0}=h_{0}^{d}W^{Q}} . Meanwhile, the hidden vectors outputted by the encoder are transformed by another linear map W K {\displaystyle W^{K}} into key vectors k 0 = h 0 W K , k 1 = h 1 W K , … {\displaystyle k_{0}=h_{0}W^{K},k_{1}=h_{1}W^{K},\dots } . The linear maps are useful for providing the model with enough freedom to find the best way to represent the data. Now, the query and keys are compared by taking dot products: q 0 k 0 T , q 0 k 1 T , … {\displaystyle q_{0}k_{0}^{T},q_{0}k_{1}^{T},\dots } . Ideally, the model should have learned to compute the keys and values, such that q 0 k 0 T {\displaystyle q_{0}k_{0}^{T}} is large, q 0 k 1 T {\displaystyle q_{0}k_{1}^{T}} is small, and the rest are very small. This can be interpreted as saying that the attention weight should be mostly applied to the 0th hidden vector of the encoder, a little to the 1st, and essentially none to the rest. In order to make a properly weighted sum, we need to transform this list of dot products into a probability distribution over 0 , 1 , … {\displaystyle 0,1,\dots } . This can be accomplished by the softmax function, thus giving us the attention weights: ( w 00 , w 01 , … )
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{"page_id": 62607005, "title": "Seq2seq"}
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A cochlear implant (CI) is a surgically implanted neuroprosthesis that provides a person who has moderate-to-profound sensorineural hearing loss with sound perception. With the help of therapy, cochlear implants may allow for improved speech understanding in both quiet and noisy environments. A CI bypasses acoustic hearing by direct electrical stimulation of the auditory nerve. Through everyday listening and auditory training, cochlear implants allow both children and adults to learn to interpret those signals as speech and sound. The implant has two main components. The outside component is generally worn behind the ear, but could also be attached to clothing, for example, in young children. This component, the sound processor, contains microphones, electronics that include digital signal processor (DSP) chips, battery, and a coil that transmits a signal to the implant across the skin. The inside component, the actual implant, has a coil to receive signals, electronics, and an array of electrodes which is placed into the cochlea, which stimulate the cochlear nerve. The surgical procedure is performed under general anesthesia. Surgical risks are minimal and most individuals will undergo outpatient surgery and go home the same day. However, some individuals will experience dizziness, and on rare occasions, tinnitus or facial nerve bruising. From the early days of implants in the 1970s and the 1980s, speech perception via an implant has steadily increased. More than 200,000 people in the United States had received a CI through 2019. Many users of modern implants gain reasonable to good hearing and speech perception skills post-implantation, especially when combined with lipreading. One of the challenges that remain with these implants is that hearing and speech understanding skills after implantation show a wide range of variation across individual implant users. Factors such as age of implantation, parental involvement and education level, duration and cause of hearing
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{"page_id": 241649, "title": "Cochlear implant"}
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structure repeated every 2.7 nanometres and that the bases lay flat, stacked, 0.34 nanometres apart. At a symposium in 1938 at Cold Spring Harbor, Astbury pointed out that the 0.34 nanometre spacing was the same as amino acids in polypeptide chains. (The currently accepted value for the spacing of the bases in B-form of DNA is 0.332 nm.) In 1946 Astbury presented a paper at a symposium in Cambridge in which he said: "Biosynthesis is supremely a question of fitting molecules or parts of molecules against another, and one of the great biological developments of our time is the realisation that probably the most fundamental interaction of all is that between the proteins and the nucleic acids." He also said that the spacing between the nucleotides and the spacing of amino acids in proteins "was not an arithmetical accident". Astbury and Bell's work was significant for two reasons. Firstly they showed that X-ray crystallography could be used to reveal the regular, ordered structure of DNA – an insight which laid the foundations for the later work of Maurice Wilkins and Rosalind Franklin, after which the structure of DNA was identified by Francis Crick and James D. Watson in 1953. Secondly, they did this work at a time when most scientists thought that proteins were the carrier of hereditary information and that DNA was a dull monotonous molecule of little interest other than perhaps as a structural component. In 1944, Astbury was one of the few scientists to recognise the importance of work done by the microbiologist Oswald Avery and his Rockefeller colleagues Maclyn McCarty and Colin Macleod. Avery and his team had shown that nucleic acid could pass on the property of virulence in pneumococcus and thus offered the first strong evidence that DNA might be the hereditary material. Astbury
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{"page_id": 2890145, "title": "William Astbury"}
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is formed, it is "eaten" by the Higgs mechanism, becoming the longitudinal component of the now massive gauge boson. Technically, the polarization function Π(p2) appearing in the gauge boson propagator, Δ μ ν = [ p μ p ν p 2 − g μ ν ] p 2 [ 1 − g 2 Π ( p 2 ) ] {\displaystyle \Delta _{\mu \nu }={\frac {\left[{\frac {p_{\mu }p_{\nu }}{p^{2}}}-g_{\mu \nu }\right]}{~p^{2}\left[1-g^{2}\Pi \left(p^{2}\right)\right]~}}} develops a pole at p2 = 0 with residue F2, the square of the Goldstone boson's decay constant, and the gauge boson acquires mass M ≈ g F . In 1973, Weinstein showed that composite Goldstone bosons whose constituent fermions transform in the "standard" way under SU(2) ⊗ U(1) generate the weak boson masses ( 1 ) M W ± = 1 2 g F E W and M Z = 1 2 g 2 + g ′ 2 F E W ≡ M W cos θ W . {\displaystyle (1)\qquad M_{\mathrm {W^{\pm }} }={\frac {1}{2}}g\,F_{\mathrm {EW} }\quad {\text{ and }}\quad M_{\mathrm {Z} }={\frac {1}{2}}{\sqrt {g^{2}+{g'}^{2}}}F_{\mathrm {EW} }\equiv {\frac {M_{\mathrm {W} }}{\cos \theta _{\mathrm {W} }}}.} This standard-model relation is achieved with elementary Higgs bosons in electroweak doublets; it is verified experimentally to better than 1%. Here, g and g′ are SU(2) and U(1) gauge couplings and tan θ W = g ′ g {\displaystyle \tan \theta _{\mathrm {W} }={\frac {g'}{g}}} defines the weak mixing angle. The important idea of a new strong gauge interaction of massless fermions at the electroweak scale FEW driving the spontaneous breakdown of its global chiral symmetry, of which an SU(2) ⊗ U(1) subgroup is weakly gauged, was first proposed in 1979 by Weinberg. This "technicolor" mechanism is natural in that no fine-tuning of parameters is necessary. == Extended technicolor == Elementary
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{"page_id": 296036, "title": "Technicolor (physics)"}
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correlation. Through coinertia analysis, it was possible to determine the best-fitted genotypes for both yield variables in all environments. The use of these novel strategies like coinertia in GEI, proved to be a great complement analysis to AMMI and GGE, especially when the yield improvement implies multiple yield variables. Seven genetically distinct yarrow plants were collected and three cuttings taken from each plant. One cutting of each genotype was planted at low, medium, and high elevations, respectively. When the plants matured, no one genotype grew best at all altitudes, and at each altitude the seven genotypes fared differently. For example, one genotype grew the tallest at the medium elevation but attained only middling height at the other two elevations. The best growers at low and high elevation grew poorly at medium elevation. The medium altitude produced the worst overall results, but still yielded one tall and two medium-tall samples. Altitude had an effect on each genotype, but not to the same degree nor in the same way. A sorghum bi-parental population was repeatedly grown in seven diverse geographic locations across years. A group of genotypes requires similar growing degree-day (GDD) to flower across all environments, while another group of genotypes need less GDD in certain environments, but higher GDD in different environments to flower. The complex flowering time patterns is attributed to the interaction of major flowering time genes (Ma1, Ma6, FT, ELF3) and an explicit environmental factor, photothermal time (PTT) capturing the interaction between temperature and photoperiod. Phenylketonuria (PKU) is a human genetic condition caused by mutations to a gene coding for a particular liver enzyme. In the absence of this enzyme, an amino acid known as phenylalanine does not get converted into the next amino acid in a biochemical pathway, and therefore too much phenylalanine passes into the
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{"page_id": 2423780, "title": "Gene–environment interaction"}
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to six. With lap 5 under full-course yellow, this meant all three remaining teams would effectively restart the race on the sixth and final lap. The trio left the pits at 22:25 Gulf Standard Time, and the race resumed two minutes later. At first, Gianna was winning with Hailey 2.6 seconds behind, but then Gianna stopped on turn 5, giving Hailey the lead. Constructor AI also overtook Gianna, but not without briefly stopping. Gianna remained stopped, its status indicator solid red - it did not finish either. With both Italian teams out of the picture, Hailey finished first and won A2RL 2024, with Constructor AI finishing second, 27.2 seconds behind. === Final race classification === == References ==
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{"page_id": 78481980, "title": "2024 Abu Dhabi Autonomous Racing League"}
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The digital dividend refers to the radio spectrum which is released in the process of digital television transition. When television broadcasters switch from analog TV to digital-only platforms, part of the electromagnetic spectrum that has been used for broadcasting will be freed-up because digital television needs less spectrum than analog television, due to lossy compression. One reason is that new digital video compression technology can transmit numerous digital subchannels using the same amount of spectrum used to transmit one analog TV channel. However, the primary reason is that digital transmissions require much less of a guard band on either side, since they are not nearly as prone to RF interference from adjacent channels. Because of this, there is no longer any need to leave empty channels to protect stations from each other, in turn allowing stations to be repacked into fewer channels, leaving more contiguous spectrum to be allocated for other wireless services. The digital dividend usually locates at frequency bands from 174 to 230 MHz (VHF) and from 470 to 862 MHz (UHF), with its midpoint being chosen precisely as 666 MHz. However, the location and size of digital dividend vary among countries due to the factors including geographical position and penetration of satellite/cable services. As a result of the technological transition, a significant number of governments are now planning for or allocating their digital dividends. For examples, the United States completed its transition on 12 June 2009 and auctioned the spectrum. Meanwhile, Australia is still planning for it. == Potential uses == In countries where the digital television transition has not yet finished, over-the-air broadcasting services are still using radio-frequency spectrum in what is known as the Very High Frequency (VHF) and Ultra High Frequency (UHF) bands. After the completion of digital transition, part of this spectrum will
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{"page_id": 31600380, "title": "Digital dividend after digital television transition"}
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large business jets. == Police actions == In 2001, the United States Supreme Court decided in Kyllo v. United States that performing surveillance of private property (ostensibly to detect high emission grow lights used in clandestine cannabis farming) using thermal imaging cameras without a search warrant by law enforcement violates the Fourth Amendment's protection from unreasonable searches and seizures. In the 2004 R. v. Tessling judgment, the Supreme Court of Canada determined that the use of airborne FLIR in surveillance by police was permitted without requiring a search warrant. The Court determined that the general nature of the data gathered by FLIR did not reveal personal information of the occupants and therefore was not in violation of Tessling's Section 8 rights afforded under the Charter of Rights and Freedoms (1982). Ian Binnie distinguished the Canadian law with respect to the Kyllo judgment, by agreeing with the Kyllo minority that public officials should not have to avert their senses or their equipment from detecting emissions in the public domain such as excessive heat, traces of smoke, suspicious odors, odorless gases, airborne particulates, or radioactive emissions, any of which could identify hazards to the community. In June 2014, the Canadian National Aerial Surveillance Program DHC-8M-100 aircraft mounted with infrared sensors was instrumental in the search for Justin Bourque, a fugitive who had killed three Royal Canadian Mounted Police members in Moncton. The plane's crew used its advanced heat-sensing camera to discover Bourque's heat signature in the deep brushwoods at midnight. During 2015 Baltimore protests, the FBI conducted 10 aerial surveillance missions between April 29 and May 3, which included "infrared and day color, full-motion FLIR video evidence" collection, according to FBI spokesman Christopher Allen. A FLIR Talon multi-sensor camera system equipped with an infrared laser pointer (which is invisible to casual observers)
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{"page_id": 181389, "title": "Forward-looking infrared"}
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In cognitive psychology, sequence learning is inherent to human ability because it is an integrated part of conscious and nonconscious learning as well as activities. Sequences of information or sequences of actions are used in various everyday tasks: "from sequencing sounds in speech, to sequencing movements in typing or playing instruments, to sequencing actions in driving an automobile." Sequence learning can be used to study skill acquisition and in studies of various groups ranging from neuropsychological patients to infants. According to Ritter and Nerb, “The order in which material is presented can strongly influence what is learned, how fast performance increases, and sometimes even whether the material is learned at all.” Sequence learning, more known and understood as a form of explicit learning, is now also being studied as a form of implicit learning as well as other forms of learning. Sequence learning can also be referred to as sequential behavior, behavior sequencing, and serial order in behavior. == History == In the first half of the 20th century, Margaret Floy Washburn, John B. Watson, and other behaviorists believed behavioral sequencing to be governed by the reflex chain, which states that stimulation caused by an initial movement triggers an additional movement, which triggers another additional movement, and so on. In 1951, Karl Lashley, a neurophysiologist at Harvard University, published “The Problem of Serial Order in Behavior,” addressing the current beliefs about sequence learning and introducing his hypothesis. He criticized the previous view on the basis of six lines of evidence: The first line is that movements can occur even when sensory feedback is interrupted. The second is that some movement sequences occur too quickly for elements of the sequences to be triggered by feedback from the preceding elements. Next is that the errors in behavior suggest internal plans for what
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{"page_id": 10181116, "title": "Sequence learning"}
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where proteins or nucleotides absorb. When TNP-ATP is in water or other aqueous solutions, this emission is very weak. However, once TNP-ATP binds to a protein, there is a dramatic increase in fluorescent intensity. This property enables researchers to study various proteins’ binding interaction with ATP. Thus, with enhanced fluorescence, it can be seen whether a protein binds to ATP. When TNP-ATP in water is excited at 410 nm, TNP-ATP shows a single fluorescence maximum at 561 nm. This maximum shifts as the fluid's viscosity changes. For example, in N,N-dimethylformamide, instead of having its maxima at 561 nm as in water, the maxima is instead at 533 nm. Binding to a protein will also change the wavelength of maximal emission, as well as a change in fluorescent intensity. For example, binding to the chemotaxis protein CheA indicates a severalfold enhancement of fluorescence intensity and a blue-shift in wavelength of the maximal emission. Using this TNP nucleotide analog has been shown in many instances to be superior to traditional radionucleotide-labelling based techniques. The health concerns and the cost associated with the use of radioactive isotopes makes TNP-ATP an attractive alternative. The first fluorescent ribose-modified ATP is 2’,3’-O-(2,4,7-trinitrocyclohexadienylidene) adenosine 5’triphosphate (TNP-ATP), and was introduced in 1973 by Hiratsuka and Uchida. TNP-ATP was originally synthesized to investigate the ATP binding site of myosin ATPase. Reports of TNP-ATP’s success in the investigation of this motor protein extended TNP-ATP’s use to other proteins and enzymes. TNP-ATP has now been used as a spectroscopic probe for numerous proteins suspected to have ATP interactions. These include several protein kinases, ATPases, myosin, and other nucleotide binding proteins. Over the past twenty years, there have been hundreds of papers describing TNP-ATP’s use and applications. Many applications involving this fluorescently labeled nucleotide have helped to clarify structure-function relationships of many
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{"page_id": 48309405, "title": "TNP-ATP"}
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can also download all available information with the signature of the owner, which respects the rights of the creator. the_sorting_hat by David Chechelashvili Time to go to school Automathon by Levent Polat Automatically creates some Python script templates at desired path. Dasher by Daniel Sabelli Dasher is a command-line interface (CLI) application that replaces whitespace in file names with dashes. Identifying First-Person Narrative Voice by Hilary Havens Identifying First-Person Narrative Voice enables users to input a link or a txt file and then determines whether the text contained is written in first-person narrative voice or is epistolary. Python Pokemon Fighter simulator by Roberto José Antonio Constenla Mendez A Pokemon fighter simulator made entirely on python using object oriented programming and using some pygame modules to add music to it! EduCLI by Luca Măndiță A command-line interface Python app for managing student databases Online Shopping with Python by Mohamed Javeed It is a command-line version of Online Shopping application. Random Character Generator by Olasimoju Bankole It is a 'character sheet' generator that uses lists of information to output a fictional character to a GUI with details about their persona. Student Management System by Muhammad Zaid I Created a Student Management System that'll promp the user for 6 options, Adding,Deleting, Displaying, Searching, Deleting All and Exiting the program, I also added some validation to the Student Name, Father Name, ID and Email, ID will be unique, That's it. Sale System by Neil Bryan Caranzo A Sale System for my sister little store called "McCurties" Calculator by Roghayeh Tayefeh Younesi This code consists of two Python files: `project.py` and `test_project.py`, which follow the requirements for a final project in a Python course. Snake and Ladder Game by Mareeswaran G It is simple fun game. project.py by Sanghyeon Yun It reads before.csv (columns: name,
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{"source": 1749, "title": "from dpo"}
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u in the tree. The number of light edges on the path from the node u to the root of the tree is upper bounded by O(log n). The reason is that every light edge at least halves the size of the subtree and the number of nodes in the tree is upper bounded by n. Since every two light edges on the path are separated by one spine, the number of different spines on the path from the node u to the root is also upper bounded by O(log n). With our definition of a spine set up, we now proceed to our main result of this section. Theorem 5.22. Given a vector x and an integer k > 1, we can find a subtree Q E 7k such that # IIXI Q'CiIk Moreover, the algorithm runs in time O(- - log 9 n . log 3 Xmax). Proof. For a tree x of size n > 0, we define the tail tree sparsity vector to be the vector To simplify the exposition, in this section we will skip the word "tail". We will recursively compute approximate tree sparsity vectors for all subtrees rooted at the special nodes of the tree x. As we compute these approximations, the sizes of the subtrees become smaller and the lengths of the corresponding approximate sparsity vectors (the number of entries in the vectors) also become smaller. To compute the approximate sparsity vector for a special note u, we need to know the approximate sparsity vectors for all special nodes in the subtree rooted at u. Without loss of generality, we assume that for every leaf 1, we have xj > 0. Our recursive algorithm works as
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{"source": 4169, "title": "from dpo"}
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with the tweak and other inputs being domain separated to avoid trivial collisions. Different HBS schemes use different methods of adding these tweaks to the hash function, and our scheme will work with any of them, so we do not specify how the tweak is incorporated into the hash, only that it may be incorporated somehow, and that each tweak essentially gives an independent hash function. Further, both the tweak and the main input to the hash will sometimes be a tuple of inputs separated by commas, e.g., hash (1 ,KeyID )(R, M ). We assume that these inputs are somehow domain-separated, encoded, and turned into an input to the underlying hash function in an unambiguous way. We leave the specifics to be defined in the specific stateful HBS scheme is being turned into a distributed signature scheme. # 2.2 Metadata and Multi-Target Attacks A typical stateful HBS has some additional data, the “metadata”. E.g., instead of hash (1 ,KeyID )(R, M ), the hash function call would actually look more like hash (1 ,KeyID ,metadata )(R, M ). Consider μ independent “composite key pairs” (CSK 1, CPK 1), . . . (CSK μ, CPK μ), consisting of a “composite secret key” CSK i and a “composite public key” CPK i and supporting Di-time signatures. A multi-target setting involves many composite key pairs (CSK 1, CPK 1), . . . (CSK μ, CPK μ).The adversary is free to make encryption queries with respect to all of the μ key pairs, and the adversary wins if it presents a forgery with respect to any (CSK i, CPK i).If the metadata are unique, i.e., for i̸ = j the metadata attached to the i-th key pair are different from the metadata for the j-th key pair, then the metadata-input to hash function
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{"source": 5981, "title": "from dpo"}
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The butterfly effect presents an obvious challenge to prediction, since initial conditions for a system such as the weather can never be known to complete accuracy. This problem motivated the development of ensemble forecasting, in which a number of forecasts are made from perturbed initial conditions. Some scientists have since argued that the weather system is not as sensitive to initial conditions as previously believed. David Orrell argues that the major contributor to weather forecast error is model error, with sensitivity to initial conditions playing a relatively small role. Stephen Wolfram also notes that the Lorenz equations are highly simplified and do not contain terms that represent viscous effects; he believes that these terms would tend to damp out small perturbations. Recent studies using generalized Lorenz models that included additional dissipative terms and nonlinearity suggested that a larger heating parameter is required for the onset of chaos. While the "butterfly effect" is often explained as being synonymous with sensitive dependence on initial conditions of the kind described by Lorenz in his 1963 paper (and previously observed by Poincaré), the butterfly metaphor was originally applied to work he published in 1969 which took the idea a step further. Lorenz proposed a mathematical model for how tiny motions in the atmosphere scale up to affect larger systems. He found that the systems in that model could only be predicted up to a specific point in the future, and beyond that, reducing the error in the initial conditions would not increase the predictability (as long as the error is not zero). This demonstrated that a deterministic system could be "observationally indistinguishable" from a non-deterministic one in terms of predictability. Recent re-examinations of this paper suggest that it offered a significant challenge to the idea that our universe is deterministic, comparable to the challenges
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{"page_id": 4024, "title": "Butterfly effect"}
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Barbara Farnsworth Heslop (née Cupit; 26 January 1925 – 20 December 2013) was a New Zealand immunologist specialising in transplantation immunology and immunogenetics. == Biography == Born in Auckland, Heslop was educated at Epsom Girls' Grammar School from 1938 to 1941 and then attended the University of Otago, graduating MB ChB in 1949 and MD in 1954. She married surgeon John Herbert Heslop, noted for his work on skin carcinogenesis. They had two daughters: Helen, a transplant scientist; and Hilary, a food specialist. Heslop gained recognition in the medical community for both her research and her teaching, at a time when women scientists were scarce. She was made a Fellow of the Royal Australasian College of Surgeons (RACS) for services to surgical sciences in 1975. In 1990, in honour of her research achievements she was appointed a Fellow of the Royal Society of New Zealand mainly based on her publications on allogeneic lymphocyte cytotoxicity (a natural killer cell mediated phenomenon). The same year, she and her husband John Heslop were joint recipients of the Sir Louis Barnett Medal awarded by the RACS. In the 1991 New Year Honours, Heslop was appointed a Commander of the Order of the British Empire, for services to medical education. Heslop died in Dunedin in 2013. In 2017, Heslop was selected as one of the Royal Society Te Apārangi's "150 women in 150 words", celebrating the contributions of women to knowledge in New Zealand. == Heslop Medal == To commemorate Heslop's work and that of her husband, John Heslop, the Heslop Medal was established by the Royal Australasian College of Surgeons in 2004 to recognise and reward outstanding contributions to the Board of Basic Surgical Education and Training and its committees. == Selected publications == Heslop, Barbara F.; Zeiss, Irmgard M.; Nisbet, N. W. (1960).
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{"page_id": 42102158, "title": "Barbara Heslop"}
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the medium; ε ′ = ε 0 ε r {\displaystyle \ \varepsilon '\ =\ \varepsilon _{0}\ \varepsilon _{\mathsf {r}}\ } is the real part of the permittivity. ε ^ = ε ′ − i ε ″ {\displaystyle \ {\hat {\varepsilon }}\ =\ \varepsilon '-i\ \varepsilon ''\ } is the complex permittivity Note that this is using the electrical engineering convention of the complex conjugate ambiguity; the physics/chemistry convention involves the complex conjugate of these equations. The size of the displacement current is dependent on the frequency ω of the applied field E; there is no displacement current in a constant field. In this formalism, the complex permittivity is defined as: ε ^ = ε ′ ( 1 − i σ ω ε ′ ) = ε ′ − i σ ω {\displaystyle \ {\hat {\varepsilon }}\ =\ \varepsilon '\left(\ 1\ -\ i\ {\frac {\sigma }{\ \omega \varepsilon '\ }}\ \right)\ =\ \varepsilon '\ -\ i\ {\frac {\ \sigma \ }{\ \omega \ }}} In general, the absorption of electromagnetic energy by dielectrics is covered by a few different mechanisms that influence the shape of the permittivity as a function of frequency: First are the relaxation effects associated with permanent and induced molecular dipoles. At low frequencies the field changes slowly enough to allow dipoles to reach equilibrium before the field has measurably changed. For frequencies at which dipole orientations cannot follow the applied field because of the viscosity of the medium, absorption of the field's energy leads to energy dissipation. The mechanism of dipoles relaxing is called dielectric relaxation and for ideal dipoles is described by classic Debye relaxation. Second are the resonance effects, which arise from the rotations or vibrations of atoms, ions, or electrons. These processes are observed in the neighborhood of their characteristic absorption frequencies. The above
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{"page_id": 53933, "title": "Permittivity"}
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pair, 3 bits per symbol, each transmitted as code pair using PAM3. It supports full-duplex transmission. The twisted-pair cable is required to support 66 MHz, with a maximum length of 15 m. No specific connector is defined. The standard is intended for automotive applications or when Fast Ethernet is to be integrated into another application. It was developed as Open Alliance BroadR-Reach (OABR) before IEEE standardization. === 100BASE-T2 === In 100BASE-T2, standardized in IEEE 802.3y, the data is transmitted over two copper pairs, but these pairs are only required to be Category 3 rather than the Category 5 required by 100BASE-TX. Data is transmitted and received on both pairs simultaneously thus allowing full-duplex operation. Transmission uses 4 bits per symbol. The 4-bit symbol is expanded into two 3-bit symbols through a non-trivial scrambling procedure based on a linear-feedback shift register. This is needed to flatten the bandwidth and emission spectrum of the signal, as well as to match transmission line properties. The mapping of the original bits to the symbol codes is not constant in time and has a fairly large period (appearing as a pseudo-random sequence). The final mapping from symbols to PAM-5 line modulation levels obeys the table on the right. 100BASE-T2 was not widely adopted but the technology developed for it is used in 1000BASE-T. === 100BASE-T4 === 100BASE-T4 was an early implementation of Fast Ethernet. It required four twisted copper pairs of voice grade twisted pair, a lower-performing cable compared to Category 5 cable used by 100BASE-TX. Maximum distance was limited to 100 meters. One pair was reserved for transmit and one for receive, and the remaining two switched direction. The fact that three pairs were used to transmit in each direction made 100BASE-T4 inherently half-duplex. Using three cable pairs allowed it to reach 100 Mbit/s
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{"page_id": 64506, "title": "Fast Ethernet"}
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robustness is often a desired trait, particularly in real-world applications, robust alternatives may prove desirable, notably quantile-based statistics such as the sample median for location, and interquartile range (IQR) for dispersion. Other alternatives include trimming and Winsorising, as in the trimmed mean and the Winsorized mean. == See also == Estimation of covariance matrices Scatter matrix Unbiased estimation of standard deviation == References ==
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{"page_id": 10005756, "title": "Sample mean and covariance"}
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held that agency nonenforcement decisions are presumptively unreviewable by the courts. Justice Thurgood Marshall concurred in judgement only, and did not join the majority opinion. Writing for the majority, William Rehnquist said that enforcement decisions were presumed unreviewable under the § 701(a)(2) "committed to agency discretion" exception to the general presumption of reviewability. The presumption of unreviewability was based on the well-established common law doctrine of prosecutorial discretion. Justice Rehnquist said the decision to bring an enforcement action "has traditionally been 'committed to agency discretion' and we believe that Congress enacting the APA did not intend to alter that tradition". The Court presented four policy considerations to support the presumption of unreviewability: An agency's ordering of enforcement priorities involves weighing of complex factors within the agency's expertise. An agency's decision to bring an enforcement action is analogous to prosecutorial discretion which "has long been regarded as the special province of the Executive Branch". There is no action to provide a focus for judicial review. While action may involve the use of an agency's "coercive power", inaction does not infringe upon a person's rights. The presumption of unreviewability of enforcement decisions is not absolute, and can be overcome if the petitioner can find "law to apply" in the governing statue. Applying Overton Park, the Court said agency actions were within the § 701(a)(2) exception "if the statute is drawn so that a court would have no meaningful standard against which to judge the agency's exercise of discretion." The court concluded that judicial review of nonenforcement decisions was permitted where "the substantive statute has provided guidelines for the agency to follow in exercising its...powers." However, the Court said there was often "no law to apply" to review nonenforcement decisions. Speaking to the presumption of reviewability affirmed in Dunlop that was relied on
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{"page_id": 10824215, "title": "Heckler v. Chaney"}
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The NIH Toolbox, for the assessment of neurological and behavioral function, is a multidimensional set of brief royalty-free measures that researchers and clinicians can use to assess cognitive, sensory, motor and emotional function in people ages 3–85. This suite of measures can be administered to study participants in two hours or less, in a variety of settings, with a particular emphasis on measuring outcomes in longitudinal epidemiologic studies and prevention or intervention trials. The battery has been normed and validated across the lifespan in subjects age 3-85 and its use ensures that assessment methods and results can be used for comparisons across existing and future studies. The NIH Toolbox is capable of monitoring neurological and behavioral function over time, and measuring key constructs across developmental stages. == History == In 2004, the 15 Institutes, Centers and Offices at the National Institutes of Health which support neuroscience research formed a coalition, the NIH Blueprint for Neuroscience Research, whose goal is to develop new tools, resources, and training opportunities to accelerate the pace of discovery in neuroscience research. Because the research community had long sought the development of standard instruments to measure cognitive and emotional health, in 2006 the NIH Blueprint awarded a contract to develop an innovative approach to meet this need. Under the leadership of principal investigator Richard C. Gershon, a team of more than 300 scientists from nearly 100 academic institutions were charged with developing a set of tools to enhance data collection in large cohort studies and to advance the neurobehavioral research enterprise. == Test batteries == The NIH Toolbox divides tests into four aspects of neural function, called "domain batteries": Cognition Sensation Motor Emotion == Impact on neurological research == Prior to the NIH Toolbox, there were many studies that collected information on aspects of neural function
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{"page_id": 38387863, "title": "NIH Toolbox"}
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HDMI. There are various mod kits for existing DVD players and other devices such as splitters that ignore HDCP, which allow a user to add a serial digital interface to these devices. == Electrical interface == The various serial digital interface standards all use (one or more) coaxial cables with BNC connectors, with a nominal impedance of 75 ohms. This is the same type of cable used in analog composite video setups, potentially allowing for easier "drop-in" equipment upgrades (although, at high bitrates and/or long distances, it may be necessary for older, oxidising, or lower-grade cable to be replaced with optical fibre). The specified signal amplitude at the source is 800 mV (±10%) peak-to-peak; far lower voltages may be measured at the receiver owing to attenuation. Using equalization at the receiver, it is possible to send 270 Mbit/s SDI over 300 meters (980 ft) without use of repeaters, but shorter lengths are preferred. The HD bitrates have a shorter maximum run length, typically 100 meters (330 ft). Uncompressed digital component signals are transmitted. Data is encoded in NRZI format, and a linear feedback shift register is used to scramble the data to reduce the likelihood that long strings of zeroes or ones will be present on the interface. The interface is self-synchronizing and self-clocking. Framing is done by detection of a special synchronization pattern, which appears on the (unscrambled) serial digital signal to be a sequence of ten ones followed by twenty zeroes (twenty ones followed by forty zeroes in HD); this bit pattern is not legal anywhere else within the data payload. === Standards === === Bit rates === Several bit rates are used in serial digital video signal: For standard-definition applications, as defined by SMPTE 259M, the possible bit rates are 270 Mbit/s, 360 Mbit/s, 143 Mbit/s, and
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{"page_id": 418775, "title": "Serial digital interface"}
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A Junker test is a mechanical test to determine the point at which a bolted joint loses its preload when subjected to shear loading caused by transverse vibration. Design engineers apply the Junker test to determine the point at which fastener securing elements – such as lock nuts, wedges and lock washers – fail when subjected to vibration. The data collected by the test enables design engineers to specify fasteners that will perform under a wide range of conditions without loosening. Research into the causes of vibration-induced self-loosening of threaded fasteners spans six decades and the causes of self-loosening are now well understood. It was pioneering experimental research into the behaviour of bolted joints under transverse loads, conducted by German engineer Gerhard Junker in the late 1960s which underpins modern theories on self-loosening behaviour. Junker’s test methodology and apparatus described in his 1969 paper has since become known as the Junker test and has been adopted into international fastener standards such as DIN 65151, the Junker test is the established method used for analysing the self-loosening behaviour of secured and unsecured threaded fasteners under transverse loading conditions by vibration testing. == References ==
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{"page_id": 36108417, "title": "Junker test"}
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action or precise edits. === High definition (HD) digital video === High definition digital video can be shot at a variety of frame rates, including 29.97 interlaced (like NTSC) or progressive; or 25 interlaced (like PAL) or progressive; or even 24-progressive (just like film). HD, if shot in 24-progressive, scans nearly perfectly to film without the need for a frame or field conversion process. Other issues remain though, based on the different resolutions, color spaces, and compression schemes that exist in the high-definition video world. == Computer graphics and animation == Artists working with CGI-Computer-generated imagery animation computers create pictures frame by frame. Once the finished product is done, the frames are outputted, normally in a DPX file. These picture data files can then be put on to film using a film recorder for film out. SGI computers started the high-end CGI-Computer-generated imagery animation systems, but with faster computers and the growth of Linux-based systems, many others are on the market now. Movies fully rendered and animated in CGI such as Toy Story, and Antz utilize the film-out method to produce 35mm copies for archival and release prints. Most CGI work is done in 2K Display resolution files (about the size of QXGA) and then output to the Film-out device for creation of 35 mm elements. With 4K Display resolution digital intermediates on the rise, newer types of film-out recorders are being developed to accept 4k resolution files. A 2K movie requires a Storage Area Network storage several terabytes in size to be properly stored and played out. Computer graphics files are handled the same way but in single frames and may use DPX, TIFF or other file formats. == Digital intermediates == Film-out-recording is the last step of digital intermediate workflow. DPX files that were scanned on a motion
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{"page_id": 1342176, "title": "Film-out"}
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may be at most one 'delimiting' associated with a verb phrase. (iv) Secondary arguments are delimiting expressions. Now we examine how far these properties go in explaining why certain arguments of verbs with particular cognitive structures appear in the syntax as internal, external or oblique arguments. In the next section it will be demonstrated that principles (i) and (ii) above explain the mapping of verbs into the unaccusative and unergative verb classes. 6.2 Unaccusative and unergative verbs 6.2.1 Introduction Intransitive verbs may be divided into two classes: the > - ## 250 > - unergatives and the unaccusatives.7 The sole argument of an unaccusative verb is an internal argument, while the sole argument of an unergative verb is an external argument. 8Unaccusative and unergative verbs provide a testing ground for theories of internal and external arguments, because they are, in a sense, minimal pairs. Comparison of these two verb classes, therefore, is a promising place to begin investigating the nature of internal and external arguments. The distinction is a syntactic one; internal and external arguments have different syntactic representations. A variety of syntactic distinctions, showing that unaccusative and unergative verbs have different syntactic behaviors, have been mustered in a number of languages. The two verb classes also show a striking semantic coherence cross-linguistically, but in general the diagnostics in the literature for membership in these classes, have been syntactic diagnostics. First I will review the syntactic arguments for the internal or external argument-hood of the arguments associated with unaccusative and unergative verbs. Next I will show that none 7. Unaccusative verbs have also been called ergative verbs. Iwill avoid a confusing proliferation of terminology by referring to them in this thesis simply as unaccusatives. Iuse the term 'intransitive' to mean a verb with only one argument. 8. Burzio (1986), who
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{"source": 982, "title": "from dpo"}
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to calculate the membership vector corresponding to the maximum modularity score, considering all possible community structures along the merges. weights The weights of the edges. It must be a positive numeric vector, NULL or NA . If it is NULL and the input graph has a ‘weight’ edge attribute, then that attribute will be used. If NULL and no such attribute is present, then the edges will have equal weights. Set this to NA if the graph was a ‘weight’ edge attribute, but you don’t want to use it for community detection. A larger edge weight means a stronger connection for this function. Details This function implements the fast greedy modularity optimization algorithm for finding community structure, see A Clauset, MEJ Newman, C Moore: Finding community structure in very large networks, for the details. Value cluster_fast_greedy() returns a communities() object, please see the communities() manual page for details. Author(s) Tamas Nepusz and Gabor Csardi for the R interface. References A Clauset, MEJ Newman, C Moore: Finding community structure in very large networks, See Also communities() for extracting the results. See also cluster_walktrap() , cluster_spinglass() , cluster_leading_eigen() and cluster_edge_betweenness() , cluster_louvain() cluster_leiden() for other methods. Community detection as_membership() , cluster_edge_betweenness() , cluster_fluid_communities() , cluster_infomap() , cluster_label_prop() , cluster_leading_eigen() , cluster_leiden() , cluster_louvain() , cluster_optimal() , cluster_spinglass() , cluster_walktrap() , compare() , groups() , make_clusters() , membership() , modularity.igraph() , plot_dendrogram() , split_join_distance() , voronoi_cells() Examples > g <- make_full_graph(5) %du% make_full_graph(5) %du% make_full_graph(5) g <- add_edges(g, c(1, 6, 1, 11, 6, 11)) fc <- cluster_fast_greedy(g) membership(fc) sizes(fc) cluster_fluid_communities 77 cluster_fluid_communities Community detection algorithm based on interacting fluids Description The algorithm detects communities based on the simple idea of several fluids interacting in a non-homogeneous environment (the graph topology), expanding and contracting based on their interac-tion and density. Usage cluster_fluid_communities(graph,
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{"source": 2689, "title": "from dpo"}
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• W)] > 17. ∼(R ∨ ∼Q) ∴ ∼R • ∼∼ Q > 18. ∼∼ S ↔ T ∴ S ↔ T* 19. ∼∼ (U ∨ W) ∴ ∼(∼U • ∼W) > 20. ∼(X → Y) ∴ ∼X → ∼Y PART C: Proofs Construct proofs for each of the following symbolic argu-ments. Commas are used to mark the breaks between premises. (Each proof can be completed in fewer than 10 steps, including premises.) * 1. ∼(C • D), ∼C → S, ∼D → T ∴ S ∨ T > 2. (W → U) • ∼X ∴ ∼U → ∼W > 3. F → ∼G, G ∴ ∼F* 4. ∼(∼A ∨ B) ∴ A > 5. (∼P → Q) • ∼Q ∴ P > 6. ∼(N ∨ M), ∼L → (M ∨ N) ∴ L* 7. (A ∨ B) ∨ C, ∼A ∴ C ∨ B > 8. (W • ∼X) ∨ (Y • Z), ( ∼X • W) → U, (Y • Z) → T ∴ U ∨ T > 9. ∼(S ∨ R), P → R ∴ ∼P380 Chapter 8 Statement Logic: Proofs * 10. F → (G • H), (H • G) → J ∴ F → J > 11. K ∨ (L ∨ S), ∼(K ∨ L) ∴ S > 12. ∼P, ∼(P ∨ Q) → ∼R, ∼Q ∴ ∼R* 13. ∼S → (T • U), ( ∼S → X) → ∼Z, (U • T) → X ∴ ∼Z > 14. ∼(∼B → A), C → (∼A → B) ∴ ∼C > 15. ∼E, F → (D ∨ E), ∼D ∴ ∼F* 16. (K ∨ P) ∨ X, K → ∼O, (P ∨ X) → ∼L ∴ ∼(O • L) > 17. (G ∨ H) → (J ∨ K) ∴ ∼(J ∨ K) → ∼(H ∨ G)
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{"source": 4964, "title": "from dpo"}
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conjecture affirmatively, proving that detection is indeed impossible if the change occurs at time n-o(\sqrt{n}). Furthermore, we establish that estimating the changepoint with an error smaller than o(\sqrt{n}) is also impossible, thereby confirming that the estimator proposed in Bhamidi et al.~\cite{bhamidi2018change} is order-optimal. arXiv:2502.05918 (replaced) [pdf, html, other] Title: A Note on One-Hole Domino Tilings of Squares and Rectangles Seok Hyun Byun We consider the number of domino tilings of an odd-by-odd rectangle that leave one hole. This problem is equivalent to the number of near-perfect matchings of the odd-by-odd rectangular grid. For any particular position of the vacancy on the (2k+1)\times (2k+1) square grid, we show that the number of near-perfect matchings is a multiple of 2^k, and from this follows a conjecture of Kong that the total number of near-perfect matchings is a multiple of 2^k. We also determine the parity of the number of near-perfect matchings with a particular vacancy for the rectangle case. arXiv:2502.12010 (replaced) [pdf, html, other] Title: Hyperplane arrangements and the Gauss map of a pencil Thiago Fassarella; Combinatorics (math.CO) We show that the coefficients of the characteristic polynomial of a central hyperplane arrangement \mathcal A, coincide with the multidegrees of the Gauss map of a pencil of hypersurfaces naturally associated to \mathcal A. As a consequence, we obtain a proof of the Heron-Rota-Welsh conjecture for matroids representable over a field of characteristic zero. arXiv:2502.18032 (replaced) [pdf, html, other] Title: The dual Minkowski problem for positive indices Jinrong Hu; Differential Geometry (math.DG) We derive the stability result of the dual curvature
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{"source": 6264, "title": "from dpo"}
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Griffithsin is a protein isolated from the red algae Griffithsia. It has a 121-amino acid sequence which exhibits a Jacalin-like lectin fold. Several structures of this protein have been solved by X-ray crystallography and deposited in the PDB. It has been shown in vitro to be a highly potent HIV entry inhibitor. It is currently being investigated as a potential microbicide for use in the prevention of the transmission of HIV. Griffithsin shows a broad spectrum ability to bind to the glycoproteins of other viruses, such as the coronavirus. Griffithsin's three identical carbohydrate binding sites bind to oligosaccharides present on some envelopes of viral glycoproteins. This was demonstrated by in vitro and in vivo studies. For instance, it was shown that griffithsin binds to the SARS-CoV spike glycoprotein to inhibit entry of the SARS virus and thus inhibit infection. A 2014 study showed griffithsin to also possess useful antiviral activity against Ebolavirus. As reported in March 2009, Kenneth Palmer and coworkers modified the tobacco mosaic virus to incorporate the griffithsin gene and infected more than 9,300 tobacco plants. They were able to extract enough griffithsin to produce about 100,000 HIV microbicide doses from the leaves. == References ==
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{"page_id": 14713488, "title": "Griffithsin"}
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Within surface science, a quartz crystal microbalance with dissipation monitoring (QCM-D) is a type of quartz crystal microbalance (QCM) based on the ring-down technique. It is used in interfacial acoustic sensing. Its most common application is the determination of a film thickness in a liquid environment (such as the thickness of an adsorbed protein layer). It can be used to investigate further properties of the sample, most notably the layer's softness. == Method == Ring-down as a method to interrogate acoustic resonators was established in 1954. In the context of the QCM, it was described by Hirao et al. and Rodahl et al. The active component of a QCM is a thin quartz crystal disk sandwiched between a pair of electrodes. The application of an AC voltage over the electrodes causes the crystal to oscillate at its acoustic resonance frequency. When the AC voltage is turned off, the oscillation decays exponentially ("rings down"). This decay is recorded and the resonance frequency (f) and the energy dissipation factor (D) are extracted. D is defined as the loss of energy per oscillation period divided by the total energy stored in the system. D is equal to the resonance bandwidth divided by the resonance frequency. Other QCM instruments determine the bandwidth from the conductance spectra. Being a QCM, the QCM-D works in real-time, does not need labeling, and is surface-sensitive. Current QCM-D equipment enables measuring of more than 200 data points per second. Changes in the resonance frequency (Δf) are primarily related to mass uptake or release at the sensor surface. When employed as a mass sensor, the instrument has a sensitivity of about 0.5ng/cm2 according to the manufacturer. Changes in the dissipation factor (ΔD) are primarily related to the viscoelasticity (softness). The softness, in turn, often is related to structural changes of
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{"page_id": 28675708, "title": "Quartz crystal microbalance with dissipation monitoring"}
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as isotope ratio 2R or fractional abundance 2F defined as: R 2 = H 2 H 1 {\displaystyle {\ce {^2R\ =\ {\frac {^2H}{^1H}}}}} and F 2 = H 2 H 1 + H 2 {\displaystyle {\ce {^{2}F\ =\ {\frac {^{2}H}{{^{1}H}+{^{2}H}}}}}} where xH is amount of isotope xH. Fractional abundance is equivalent to mole fraction, and yields atom percent when multiplied by 100. In some instances atom percent excess is used, which reports the atom percent of a sample minus the atom percent of a standard. ==== Delta (δ) notation ==== Isotope ratios for a substance are often reported compared to a standard with known isotopic composition, and measurements of relative masses are always made in conjuncture with measuring a standard. For hydrogen, the Vienna Standard Mean Ocean Water standard is used which has an isotope ratio of 155.76±0.1 ppm. The delta value as compared to this standard is defined as: δ 2 H VSMOW = R sample 2 R VSMOW 2 − 1 {\displaystyle {\ce {\delta^2H_{VSMOW}\ =\ {\frac {^2R_{sample}}{^2R_{VSMOW}}}-1}}} These delta values are often quite small, and are usually reported as per mil values (‰) which come from multiplying the above equation by a factor of 1000. ==== Measures of fractionation ==== The study of HIBGC relies on the fact that various physicochemical processes preferentially enrich or deplete 2H relative to 1H (see kinetic isotope effect [KIE], etc.). Various measures have been developed to describe the fractionation in an isotope between two pools, often the product and reactant of a physiochemical process. α notation describes the difference between two hydrogen pools A and B with the equation: α A / B = R A 2 R B 2 {\displaystyle {\ce {\alpha_{A/B}\ =\ {\frac {^2R^{A}}{^2R^{B}}}}}} where δ2HA is the delta value of pool A relative to VSMOW. As many delta values
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{"page_id": 50525886, "title": "Hydrogen isotope biogeochemistry"}
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A parameter (from Ancient Greek παρά (pará) 'beside, subsidiary' and μέτρον (métron) 'measure'), generally, is any characteristic that can help in defining or classifying a particular system (meaning an event, project, object, situation, etc.). That is, a parameter is an element of a system that is useful, or critical, when identifying the system, or when evaluating its performance, status, condition, etc. Parameter has more specific meanings within various disciplines, including mathematics, computer programming, engineering, statistics, logic, linguistics, and electronic musical composition. In addition to its technical uses, there are also extended uses, especially in non-scientific contexts, where it is used to mean defining characteristics or boundaries, as in the phrases 'test parameters' or 'game play parameters'. == Modelization == When a system is modeled by equations, the values that describe the system are called parameters. For example, in mechanics, the masses, the dimensions and shapes (for solid bodies), the densities and the viscosities (for fluids), appear as parameters in the equations modeling movements. There are often several choices for the parameters, and choosing a convenient set of parameters is called parametrization. For example, if one were considering the movement of an object on the surface of a sphere much larger than the object (e.g. the Earth), there are two commonly used parametrizations of its position: angular coordinates (like latitude/longitude), which neatly describe large movements along circles on the sphere, and directional distance from a known point (e.g. "10km NNW of Toronto" or equivalently "8km due North, and then 6km due West, from Toronto" ), which are often simpler for movement confined to a (relatively) small area, like within a particular country or region. Such parametrizations are also relevant to the modelization of geographic areas (i.e. map drawing). == Mathematical functions == Mathematical functions have one or more arguments that are
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{"page_id": 25065, "title": "Parameter"}
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calculators. It uses a Zilog Z80 microprocessor running at 6 MHz, a 96×64 monochrome LCD screen, and 4 AAA batteries as well as backup CR1616 or CR1620 battery. A link port is also built into the calculator in the form of a 2.5 mm jack. The main improvement over the TI-83, however, is the addition of 512 KB of Flash ROM, which allows for operating system upgrades and applications to be installed. Most of the Flash memory is used by the operating system, with 160 KB available for user files and applications. Another development is the ability to install Flash Applications, which allows the user to add functionality to the calculator. Such applications have been made for math and science, text editing (both uppercase and lowercase letters), organizers and day planners, editing spread sheets, games, and many other uses. Designed for use by high school and college students, though now used by middle school students in some public school systems, it contains all the features of a scientific calculator as well as function, parametric, polar, and sequential graphing capabilities; an environment for financial calculations; matrix operations; on-calculator programming; and more. Symbolic manipulation (differentiation, algebra) is not built into the TI-83 Plus. It can be programmed using a language called TI-BASIC, which is similar to the BASIC computer language. Programming may also be done in TI Assembly, made up of Z80 assembly and a collection of TI provided system calls. Assembly programs run much faster, but are more difficult to write. Thus, the writing of Assembly programs is often done on a computer. === TI-83 Plus Silver Edition === The TI-83 Plus Silver Edition was released in 2001. Its enhancements are 1.5 MB of flash memory, a dual-speed 6/15 MHz processor, 96 KB of additional RAM (which can't be utilized, as
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{"page_id": 439710, "title": "TI-83 series"}
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reaction to a drug or alcohol, and multiple sclerosis. === Gait cycle === Drop foot and foot drop are interchangeable terms that describe an abnormal neuromuscular disorder that affects the patient's ability to raise their foot at the ankle. Drop foot is further characterized by an inability to point the toes toward the body (dorsiflexion) or move the foot at the ankle inward or outward. Therefore, the normal gait cycle is affected by the drop foot syndrome. The normal gait cycle is as follows: Swing phase (SW): The period of time when the foot is not in contact with the ground. In those cases where the foot never leaves the ground (foot drag), it can be defined as the phase when all portions of the foot are in forward motion. Initial contact (IC): The point in the gait cycle when the foot initially makes contact with the ground; this represents the beginning of the stance phase. It is suggested that heel strike not be a term used in clinical gait analysis as in many circumstances initial contact is not made with the heel. Suggestion: Should use foot strike. Terminal contact (TC): The point in the gait cycle when the foot leaves the ground: this represents the end of the stance phase or beginning of the swing phase. Also referred to as foot off. Toe-off should not be used in situations where the toe is not the last part of the foot to leave the ground. The drop foot gait cycle requires more exaggerated phases. Drop foot SW: If the foot in motion happens to be the affected foot, there will be greater flexion at the knee to accommodate the inability to dorsiflex. This increase in knee flexion will cause a stair-climbing movement. Drop foot IC: Initial contact of the foot
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{"page_id": 4020563, "title": "Foot drop"}
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in the first code example but now add a new interface containing the functions over the type as well as a factory for the algebra. Notice that we now generate the expression in ExampleTwo.AddOneToTwo() using the ExpAlgebra<T> interface instead of directly from the types. We can now add a function by extending the ExpAlgebra<T> interface, we will add functionality to print the expression: Notice that in ExampleThree.Print() we are printing an expression that was already compiled in ExampleTwo, we did not need to modify any existing code. Notice also that this is still strongly typed, we do not need reflection or casting. If we would replace the PrintFactory() with the ExpFactory() in the ExampleThree.Print() we would get a compilation error since the .Print() method does not exist in that context. == See also == Applications of FOSD program cubes Generic programming POPLmark challenge == References == == External links == The Expression Problem by Philip Wadler. Lecture: The Expression Problem by Ralf Lämmell. C9 Lectures: Dr. Ralf Lämmel - Advanced Functional Programming - The Expression Problem at Channel 9. Independently Extensible Solutions to the Expression Problem, Matthias Zenger and Martin Odersky, EPFL Lausanne.
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{"page_id": 22935957, "title": "Expression problem"}
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antennas in magnetic fields appear better than for UHF or SHF dipole fields, but then distance limits apply and may prevent success. Under operational conditions, bulk reading is not reliable. Bulk reading can be a rough guide for logistics decisions, but due to a high proportion of reading failures, it is not (yet) suitable for inventory management. However, when a single RFID tag might be seen as not guaranteeing a proper read, multiple RFID tags, where at least one will respond, may be a safer approach for detecting a known grouping of objects. In this respect, bulk reading is a fuzzy method for process support. From the perspective of cost and effect, bulk reading is not reported as an economical approach to secure process control in logistics. === Miniaturization === RFID tags are easy to conceal or incorporate in other items. For example, in 2009 researchers at Bristol University successfully glued RFID micro-transponders to live ants in order to study their behavior. This trend towards increasingly miniaturized RFIDs is likely to continue as technology advances. Hitachi holds the record for the smallest RFID chip, at 0.05 mm × 0.05 mm. This is 1/64th the size of the previous record holder, the mu-chip. Manufacture is enabled by using the silicon-on-insulator (SOI) process. These dust-sized chips can store 38-digit numbers using 128-bit Read Only Memory (ROM). A major challenge is the attachment of antennas, thus limiting read range to only millimeters. ==== TFID (Terahertz Frequency Identification) ==== In early 2020, MIT researchers demonstrated a terahertz frequency identification (TFID) tag that is barely 1 square millimeter in size. The devices are essentially a piece of silicon that are inexpensive, small, and function like larger RFID tags. Because of the small size, manufacturers could tag any product and track logistics information for minimal cost.
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{"page_id": 169320, "title": "Radio-frequency identification"}
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permissible since none of them are divisible by p) and rearranging, we have a ( p − 1 ) / 2 ≡ ( − 1 ) r ( 2 ) + r ( 4 ) + ⋯ + r ( p − 1 ) ( mod p ) . {\displaystyle a^{(p-1)/2}\equiv (-1)^{r(2)+r(4)+\cdots +r(p-1)}{\pmod {p}}.} On the other hand, by the definition of r(u) and the floor function, a u p = ⌊ a u p ⌋ + r ( u ) p , {\displaystyle {\frac {au}{p}}=\left\lfloor {\frac {au}{p}}\right\rfloor +{\frac {r(u)}{p}},} and since p is odd and u is even, a u = p ⌊ a u p ⌋ + r ( u ) {\displaystyle au=p\left\lfloor {\frac {au}{p}}\right\rfloor +r(u)} implies that ⌊ a u / p ⌋ {\displaystyle \left\lfloor au/p\right\rfloor } and r(u) are congruent modulo 2. Finally this shows that a ( p − 1 ) / 2 ≡ ( − 1 ) ∑ u ⌊ a u / p ⌋ ( mod p ) . {\displaystyle a^{(p-1)/2}\equiv (-1)^{\sum _{u}\left\lfloor au/p\right\rfloor }{\pmod {p}}.} We are finished because the left hand side is just an alternative expression for (a/p), per Euler's criterion. === Addendum to the lemma === This lemma essentially states that the number of least residues after doubling that are odd gives the value of (q/p). This follows easily from Gauss' lemma. Also, q u = p ⌊ q u p ⌋ + r ( u ) {\displaystyle qu=p\left\lfloor {\frac {qu}{p}}\right\rfloor +r(u)} implies that ⌊ q u / p ⌋ {\displaystyle \left\lfloor qu/p\right\rfloor } and r(u) are either congruent modulo 2, or incongruent, depending solely on the parity of u. This means that the residues 1 , 2 , … , p − 1 2 {\displaystyle 1,2,\dots ,{\frac {p-1}{2}}} are (in)congruent to ⌊ q u / p ⌋ {\displaystyle
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{"page_id": 3090886, "title": "Proofs of quadratic reciprocity"}
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Genome-based peptide fingerprint scanning (GFS) is a system in bioinformatics analysis that attempts to identify the genomic origin (that is, what species they come from) of sample proteins by scanning their peptide-mass fingerprint against the theoretical translation and proteolytic digest of an entire genome. This method is an improvement from previous methods because it compares the peptide fingerprints to an entire genome instead of comparing it to an already annotated genome. This improvement has the potential to improve genome annotation and identify proteins with incorrect or missing annotations. == History and background == GFS was designed by Michael C. Giddings (University of North Carolina, Chapel Hill) et al., and released in 2003. Giddings expanded the algorithms for GFS from earlier ideas. Two papers were published in 1993 explaining the techniques used to identify proteins in sequence databases. These methods determined the mass of peptides using mass spectrometry, and then used the mass to search protein databases to identify the proteins In 1999 a more complex program was released called Mascot that integrated three types of protein/database searches: peptide molecular weights, tandem mass spectrometry from one or more peptide, and combination mass data with amino acid sequence. The fallback with this widely used program is that it is unable to detect alternative splice sites that are not currently annotated, and it not usually able to find proteins that have not been annotated. Giddings built upon these sources to create GFS which would compare peptide mass data to entire genomes to identify the proteins. Giddings system is able to find new annotations of genes that have not been found, such as undocumented genes and undocumented alternative splice sites. == Research examples == In 2012 research was published where genes and proteins were found in a model organism that could not have been
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{"page_id": 7324297, "title": "Genome-based peptide fingerprint scanning"}
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intelligent technology private data, 771 successful deployment. See Deployment of intelligent systems support from IBM and Microsoft, 99 technology trends, 792–795 vignette, 763–765 Intermediate result variables, 506 Internet, 416, 769 data visualization, 204 search engine. See Search engines Internet of Things (IoT), 40 in action, 737 AI and, 97 applications, 737–738 benefits of, 730 Big Data and, 99 building blocks of, 729f changing everything, 727 characteristics, 726–727 and decision support, 732–733 defined, 725 drive marketing, 738 drivers of, 731 ecosystem, 727, 728f essentials, 725–730 French national railway system’s use, 737 hardware, 728 and managerial considerations, 753–757 opportunities, 731 platforms, 730 privacy in, 769 process of, 732f RFID and smart sensors in, 736–737 SAS supports, 750f sensors and, 733–737, 733A, 734, 734A–735A strategy cycle, 756f structure of, 727 technology infrastructure, 728–729, 729f vignette, 724–725 work process, 732 World’s largest, 731 Internet Search Engine. See Search engines Interpersonal communication skills, 42 Interval data, 162, 242 ir.netflix.com , 694A–696A ## J Jackknifing, 259 Java, 72 Job Tracker, 561 Joint distribution, 324 Jurik Research Software, Inc. (jurikres.com ), 509 ## K KDD (knowledge discovery in databases) process, 254, 255f Keras (learning framework), 406 Kernel trick method, 307 Key performance indicator (KPI) business reports, 201 dashboards, 218, 223 k-fold cross-validation, 259, 259f Kip chatbot, 699 k-means clustering algorithm, 268, 268f k-nearest neighbor ( kNN) algorithm, 310, 310f, 313A–314A KNIME tool (data mining tool), 272 Knowledge acquisition, 129, 130f, 689 base, 689 of context, 396 data, 157, 158f and ES, 129 patterns, 253 refining subsystem, 690 representation, 689 Knowledge-based management subsystem, 57 Knowledge-based modeling, 503–504 Knowledge discovery in databases (KDD) process, 254, 255f Knowledge management systems (KMS), 44 Kohonen’s self-organizing feature map (SOM), 295–296, 296f KONE Elevators and Escalators Company, 39–41 ## L Landing page profiles, 480 Law enforcement agencies, 234 AI, 641 and Big Data,
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{"source": 1196, "title": "from dpo"}
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