MeerKAT follow-up of enigmatic GLEAM 4Jy sources Precious K. Sejake Collaborators: Sarah V White, Ian Heywood, Kshitij Thorat, Hertzog L Bester, Sphesihle Makhathini and Bernie Fanaroff ●Identiﬁed host galaxies for 98 sources, thanks to MeerKAT sensitivity and high resolution (~7“). ●MeerKAT images reveal various morphologies (i.e., compact ‘single’ morphology, typical symmetric lobes (i.e, ‘double’ and ‘triple’ morphology), head-tail, wide-angle tailed (WAT), X-shaped morphology and complex morphology). ●This work has illustrated the importance of a telescope's angular resolution and sensitivity for morphological classiﬁcation and host-galaxy cross-identiﬁcation of radio sources at low frequencies. The high-resolution images from MeerKAT has allowed us to resolve ambiguous host-galaxy identiﬁcations and enigmatic radio morphologies of the MeerKAT-2019 subset, evident in NVSS/SUMSS (45”) and/or TGSS (25”) images. Conclusion Active Galactic Nuclei (AGN) are compact luminous regions at the centre of their host galaxy. The emission from the AGN are thought to be driven by the accretion of material onto a SMBH at the centre and in some cases may result in the production of relativistic radio jets. AGN activity has been shown to signiﬁcantly impact the host galaxy by suppressing or promoting star formation; however, this is still a point of contention. Morganti et al. (2013) demonstrated that star formation might be suppressed whereby the radio jets expel gas from the system. Meanwhile, Croft et al. (2006) showed that the jets might trigger the collapse of the molecular gas and promote star formation. In order to gain a better understanding of which of these scenarios is more signiﬁcant, a large sample of AGN with powerful relativistic radio jets is needed to provide robust statistics on the features of these AGN. White et al., (2020a, 2020b) deﬁned such a sample, named the GLEAM 4-Jy (G4Jy) Sample. However, poor resolution archival data (at 25 to 45 arcsec - TGSS, NVSS/SUMSS) limited the host galaxy identiﬁcation of 140 G4Jy sources (which we refer to as the MeerKAT-2019 subset), as these sources had unclear, complex morphologies (see the ﬁgure on the left below). The primary aim of this work is to use the high-resolution images from MeerKAT (~7” resolution) to disentangle the morphology and identify the likely host galaxy of these sources. Introduction Method - Visual inspection Results ●The Square Kilometre Array (SKA)-Mid precursor telescope ●64 Antennas that are 13.5 m in diameter ●Maximum baseline of 8 km About 10% of the sources in the G4Jy Sample have a larger positional offset (|R.A.| > 10′′, |Dec.| > 10′′; sources outside the square cyan region), while What’s next? Obtain redshifts from SALT spectroscopic data MeerKAT Create and inspect overlays Determine the morphology Determine the host galaxy GLEAM (~2’ resolution, 200 MHz) NVSS (45” resolution, 1400 MHz, Dec > -40o), SUMSS (45” resolution, 843 MHz, Dec < -40o) TGSS (25” resolution, 150 MHz) MeerKAT (~7” resolution, 1300 MHz) WISE W1 band (3.4 µm) An overlay of G4Jy 917. The radio contours are from GLEAM, NVSS, TGSS, and new contours from MeerKAT, overlaid on the inverted greyscale WISE (3.4 μm) image. Shown in the bottom left corner is the beam size for each survey; GLEAM, NVSS, TGSS, and MeerKAT. The cyan hexagon indicates the brightness-weighted centroid position, the green crosses ‘x’ signs are the AllWISE positions within 3 arcmin from the centroid position, and the white ‘ + ’ sign is the AllWISE position for the corresponding host galaxy for this source. Clear structures seen in MeerKAT (~7 arcsec), not seen in TGSS (25 arcsec) and NVSS (45 arcsec) ●Sejake et al., (2023) (https://ui.adsabs.harvard.edu/abs/2023MNRAS.518.4290S/abstract) G4Jy 665 resolved into two unrelated sources An example of a G4Jy source with complex morphology at 25 to 45 “ the majority of the sources (57%) in the MeerKAT-2019 subset populate this outer region.We expect to have this larger po


XPTSeb (PTSub) [mol %] WPTSeb (PTSub) [wt.%] Tg [°C] E [Mpa] σb [Mpa] εb [%] PTF - - 58 2460 ± 376 79,10 ± 3,10 2,99 ± 0,17 PTF-PTSeb 95/5 5 6.1 46 290 ± 64 12,30 ± 0,23 247,02 ± 32,65 PTF-PTSeb 85/15 15 17.9 28 574 ± 79 17,15 ± 0,88 410,09 ± 18,27 PTF-PTSeb 75/25 25 29.16 12 2534 ± 176 76,49 ± 2,05 3,04 ± 0,27 PTF-PTSub 95/5 5 5.4 48 4113 ± 289 73,69 ± 3,70 2,39 ± 0,18 PTF-PTSub 85/15 15 15.9 31 2312 ± 52 16,71 ± 0,99 309,93 ± 50,80 PTF-PTSub 75/25 25 27.0 15 213 ± 82 70,61 ± 19,86 665,41 ± 46,08 SHAPE MEMORY BEHAVIOR OF FULLY BIO-BASED AROMATIC-ALIPHATIC COPOLYESTERS Agata ZUBKIEWICZa, Anna SZYMCZYKa, Sandra PASZKIEWICZb, Izabela IRSKAb [a] Department of Technical Physics, West Pomeranian University of Technology, Piastów Av. 48, 70311 Szczecin, Poland [b] Department of Materials Technology, West Pomeranian University of Technology, Piastów Av. 48, 70311 Szczecin, Poland Introduction Over the last decade, development of bio-based polymers has become one of the principal focuses of research in materials science, which is related to environmental awareness over gradual exhaustion of non-renewable resources. 2,5-furandicarboxylic acid (FDCA) stands out as a highly potential bio-based monomer able to replace petro-derived terephthalic acid.[1] FDCA and its derivatives can be used, among others, to obtain copolymers with interesting properties, such as shape memory effect. Shape-memory polymers as stimuli-responsive shape-changing polymers are of great interest for fundamental research and technological innovation. It is known that shape memory materials display the ability of changing their shape in response to external stimuli, such as changes in temperature.[2] In the present study poly(trimetylene 2,5-furanoate-co-trimethylene sebacate) copolymers (PTF-co-PTSeb) and poly(trimetylene 2,5-furanoate-co trimethylene suberate) copolymers (PTF-co-PTSub) containing from 5 to 25 mol % of trimethylene sebacate unis (TSeb), or trimethylene suberate units (TSub) were synthesized by a two-stage melt polycondensation process using dimethyl esters of 2,5-furandicarboxylic acid (DMFDCA), bio-1,3-propanediol (1,3-PD) and dimethyl sebacate (DMSeb) or dimethyl suberate (DMSub), depending on the copolymer. Fig. 3 a) Shape memory cycles of PTF-co-PTSeb 85/15 b) Shape fixity and shape recovery changes vs. cycle number Fig. 4 a) Shape memory cycles of PTF-co-PTSub 75/25 copolymer b) Shape fixity and shape recovery changes vs. cycle number 80% 81% 82% 83% 97% 98% 99% 100% 0 5 Shape fixity Shape recovery Cycle number 91% 92% 92% 93% 93% 94% 94% 95% 95% 94% 95% 96% 97% 98% 99% 100% 0 2 4 6 8 Shape fixity Shape recovery Ccle number Table 1. Characteristic of PTF-co-PTSeb and PTF-co-PTSub copolymers Fig. 2 Demonstration of shape recovery of sample (dumbbell) of PTF-co- PTSeb 85/15 copolymer at temperature above Tg. Conclusions The obtained copolymers were studied concerning their thermal properties and mechanical performance. By increasing the PTSeb or PTSub segment contents, the PTF-co-PTSeb(PTSub) copolymers show lower glass transition temperatures. One can also find that the mechanical properties are closely related to the ratio of PTF to PTSeb(PTSub) content in the copolymer. Additionally, the thermally induced shape memory effect was investigated, using DMTA analysis. In the case of shape-memory polymers (SMPs), the recovery time to original shape after regeneration depends on the temperature. It is known that SMPs at temperatures higher than Tg become rubbery and have a low Young's modulus and high formability. In this region, the shape of the SMP can be modified, and the modified shape can be kept if the temperature drops below the Tg. If the SMP is reheated above the Tg, the transition into the rubbery regime causes the SMP to regain its original shape. The PTF-co-PTSeb 85/15 and PTF-co-PTSub 75/25 copolymers showed satisfactory shape-fixity of over 91% and 80% , respectively, and shape recovery efficiency of over 95% and 98%, respectively. The


detection of the full extent (1kpc!) of tidal tail of the Hyades star cluster and the first even detection of substructures in the tail of open star cluster putting constraints on the MW potential CHECK ALSO WANG, JERABKOVA (A&A, 2021) AND STAY TUNED - MUCH MORE IS COMING! JERABKOVA ET AL. (A&A, 2021) JERABKOVA ET AL. (A&A, 2021) See our ESA press release ALL STAR-CLUSTERS ALL STAR-CLUSTERS HAVE TIDAL TAILS HAVE TIDAL TAILS TEREZA JERABKOVA (ESA) - HENRI BOFFIN (ESO) - GIACOMO BECCARI (ESO) - LONG WANG (U TOKYO) - TIMO PRUSTI (ESA) PETAR + GAIA PROJECT We use N-body simulations to robustly identify tidal tails of open star clusters in the MW disc Star cluster With Gaia eDR3, we can search for tidal tails of open star clusters in the MW disk for the first time. AND WE ABSOLUTELY SHOULD DO THAT! AND WE ABSOLUTELY SHOULD DO THAT! PROBLEM? PROBLEM? Tidal tails do not co-move with their star-cluster and are hidden in the Galactic field Tidal tail Tidal tail tell us the tale of cluster formation tell us the tale of cluster formation and evolution and evolution and of the Milky Way potential that and of the Milky Way potential that has impacted the stars has impacted the stars TIDAL TAILS TIDAL TAILS Get in touch! Tereza.Jerabkova@esa.int


Wrong Sign Contamination in NOvA Abhilash Yallappa Dombara (Syracuse University) for NOvA collaboration • NOvA is an off-axis (14.6 mrad), long baseline (810 km) neutrino oscillation experiment which uses NuMI beam at Fermilab. NOνA experiment Wrong Sign contamination Analysis procedure • The wrong sign fraction is estimated for electron neutrinos and muon neutrinos separately. • CNN (Convolutional Neural Network) was trained on simulation to identify neutrino and antineutrino events and validated with data. • A optimal cut value was chosen for Wrong Sign CNN ID based on efficiency and purity to separate the whole sample into wrong sign and right sign enhanced regions. • Compute the wrong sign fraction using matrix method 𝛼𝐵!" + 𝛽𝑆!# = 𝐷!# 𝛼𝐵$# + 𝛽𝑆$# = 𝐷$# 𝛼, 𝛽: Fit parameters D: Data S: Signal = 𝜈e , 𝜈μ CC and NC B: Background = $νe , $νμ CC and NC RS: Right sign enhanced WS: Wrong sign enhanced 𝑊𝑟𝑜𝑛𝑔𝑠𝑖𝑔𝑛𝑓𝑟𝑎𝑐𝑡𝑖𝑜𝑛= 𝛽(𝑆!" + 𝑆#") 𝛽𝑆!" + 𝑆#" + 𝛼( 𝐵!$ + 𝐵#") 𝑊𝑟𝑜𝑛𝑔𝑠𝑖𝑔𝑛𝑒𝑟𝑟𝑜𝑟= 𝐶%%(𝑆!" + 𝑆#")% (𝐷!$+𝐷#")% Matrix : 𝑀= 𝐵!" 𝑆!" 𝐵#" 𝑆#" Covariance matrix : C = 𝑀&' 𝜎(!" 0 0 𝜎(#" 𝑀) Analysis Results s Analysis Methods • Wrong sign contamination is fraction of neutrinos/antineutrinos in antineutrino/neutrino beam. • Wrong sign fraction is higher in antineutrino beam. • Wrong sign fraction affects our mass hierarchy and ẟcp. measurements because these parameters are estimated based on difference between 𝜈eand )νe appearance. • All possible wrong sign values for different universes of cross-section, beam and flux uncertainties is shown in blue histogram. Remaining systematics under investigation. • Currently used as data driven crosscheck but in future can be used for extrapolation. • Neutron capture method: Neutrinos are more likely to produce 𝜇% which gets absorbed in nucleus and produce delayed neutrons while antineutrinos don’t. • Prong CVN score: Identify neutrinos using a single particle classifier for proton identification • Wrong Sign CNN score: Dedicated CNN for classifying neutrinos and antineutrinos based on topological features • NOvA’s main goal is to use muon neutrino disappearance and electron neutrino appearance to probe neutrino mass ordering, ∆𝑚&' ' , q23 and dcp. • NOvA uses two functionally identical liquid scintillator detectors. 100 − 0 100 200 y (cm) 2200 2400 z (cm) 10 2 10 3 10 q (ADC) NOvA - FNAL E929 Run: 15330 / 4 Event: 11978 / -- UTC Fri May 23, 2014 17:30:2.632293184 Far Detector Data 5400 5600 500 600 700 y (cm) z (cm) 10 2 10 3 10 q (ADC) NOvA - FNAL E929 Run: 26110 / 49 Event: 3213 / -- UTC Sun May 7, 2017 04:41:20.910875840 Far Detector Data 0 5 10 15 Analysis bins 0 500 1000 1500 POT 20 Events / 11.09x10 NOvA Preliminary Beam n Wrong Sign enhanced Right Sign enhanced e n µ n e n µ n NC n NC n DATA High PID, 𝜈e selection 0.1 0.2 0.3 0.4 0.5 Wrong-sign fraction 0 200 400 600 Fake experiments Flux and cross- section systematic fake experiments Prong CVN Wrong Sign CNN NOvA Preliminary Beam n High PID, 𝜈e selection 0 0.05 0.1 0.15 Wrong-sign fraction 0 200 400 600 800 1000 1200 Fake experiments Flux and cross- section systematic fake experiments Wrong Sign CNN Neutron Capture Rate NOvA Preliminary Beam n 𝜈μ selection Neutrino Event Antineutrino Event 5 - 0 5 Background Uncertainty (%) Systematic Uncertainty Lepton Reconstruction Neutron Uncertainty Beam Flux Near-Far Uncor. Neutrino Cross Sections Detector Response Detector Calibration -beam n Selection e n NOvA Preliminary 0 0.2 0.4 0.6 0.8 Wrong Sign CNN 0 200 400 600 800 POT 20 Events / 11.6x10 NOvA Preliminary Beam n Data MC e n e n High PID, 𝜈e selection 2 - 0 2 Signal Uncertainty (%) Systematic Uncertainty Beam Flux Detector Calibration Lepton Reconstruction Detector Response Neutron Uncertainty Near-Far Uncor. Neutrino Cross Sections -beam n Selection e n NOvA Preliminary


Fletcher et al. 2011 M51 Almost 100 nearby galaxies observed @ GHz (Beck & Wielebinsky 2013) Most recently these studies are extended to very low frequencies with LOFAR Adding a piece to the puzzle Dust polarization measurements in nearby galaxies to investigate magnetic fields in cold gas Rosita Paladino INAF IRA Bologna Italy Annie Hughes, Maud Galametz et al. host magnetic field whose structure has mostly been probed through polarimetric radio continuum observations @ cm wavelengths (synchrotron radiation and its polarization) Magnetic fields directly affect the mean gas density, which impacts significantly the star formation rate (Birnboim et al. 2015) They regulate Star Formation, both on the scale of individual stars and filaments and through the collapse and fragmentation of molecular clouds (Mac Low 2009; Crutcher 2012) Magnetic fields play an important role in launching galactic winds and outflows (Heesen et al. 2011) Nearby Galaxies To date, magnetic fields in external galaxies have been studied through synchrotron emission which do not probe the field’s properties in the cold gas component. ALMA’s unprecedented resolution and sensitivity in full polarization mode allows for the first time observations of dust polarization in Observations of magnetic fields in Nearby Galaxies are the most useful tool to provide constraints on the models, since unlike the Milky Way, the galactic environment and gas kinematic of star-forming regions can be well-characterized! In blue LOFAR emission Mulcahy et al 2018 NGC891 NGC 253 Magnetic fields influence structure and evolution of galaxies In the Milky Way, Planck polarization results show a poor correspondence between the polarization fraction and direction obtained from radio synchrotron and dust polarization measurements In regions where the effects of local structures dominate (Planck XIX, 2015) Dust Polarization data are important complement to radio observations. Both synchrotron and dust polarization trace the magnetic field component projected into the plane of the sky, but NGC253 is a nearby (3.5 Mpc) highly inclined (78°) starburst galaxy. Observed @ different wavelengths 0 An ideal target for pioneering extragalactic dust polarization observations. ALMA Band 7 data probe spatial scales between 5 and 50 pc, never accessed so far! Questions to possibly answer: What is the magnetic field direction at the foot of a galactic wind? How ordered is the magnetic field in the starburst region? Does the magnetic field at the disk-halo interface have a preferred orientation? Do GHz radio and dust polarization observations yield a consistent picture of the magnetic structure? Spatial resolution 6 pc Hughes et al. in prep Its prominent wind is powered by the intense star formation within a central zone of 300 pc diameter. Lobes and filamentary structures of Hα, radio synchrotron, X-ray and UV emission are observed up to several Kpc from the disk plane. Dust continuum at 353 GHz is extremely bright. On large scales radio polarization observations reveal a magnetic field in the disk that is parallel to the midplane and an X-shaped halo field centered on the nucleus. On the smallest scales (~150 pc), the magnetic field shows a vertical component aligned with the non-thermal radio filaments. Chyzy & Beck 2004 Antennae First dust polarization image of an external galaxy Heesen et al. 2011 Spatial resolution 150 pc their emissivities have different dependencies on the magnetic field strength. Planck XIX, 2015 Spatial resolution 3 pc Band 7 rms 15 μJy Very ongoing work!


Mechanistic insights into the interactions between S. aureus amyloids and cell membranes L. Bonnecaze, K. Jumel, L. Khemtemourian, S. Lecomte, C. Feuillie, M. Molinari, M. Mathelié-Guinlet* Univ. Bordeaux, CNRS, Bordeaux INP, CBMN, UMR 5248, F-33600 Pessac, France S. aureus PSMs An opportunistic pathogen Antibiotic multiresistance PSMα3, an amyloid-like cytotoxic entity (f-)MEFVAKLFKFFKDLLGKFLGNN  Cross-α fibrillation Misunderstood interactions with both eukaryotic and bacterial membranes & Unknown influence of N-formylation, in toxic processes • Cytotoxicity F3A mutant No fibrillation reduced cytotoxicity but gained antibacterial activity f-WT thick clustered fibers f-F3A amorphous aggregates PSMα3 fibrillation [1] Peschel et Otto, Nat Rev Microbiol., 2013 [2] Tayeb-Fligelman et al., Science, 2017 [3] Malishev et al., J.Mol.Biol., 2018 *marion.mathelie-guinlet@u-bordeaux.fr [2] At 10 µM, both peptides induce only limited damage to PC-membranes f-F3A acts preferentially on bacterial membranes Impact of PSMα3 on biomimetic membranes Nanoscale visualization of PSMα3 membrane activity Accumulation and elongation of fibrils on PC-membranes, only on fluid phases Formation and propagation of a « front » and eventually holes around the growing fibrils On PE / PG membranes, peptides do not deposit nor disrupt the SLB No lipid-dependent changes in 2nd structure for both peptides high α-helical content conserved (>50%) DOPE/DOPG + f-WT / f-F3A 5µM 120’ 0’ 600nm T cells Gram + 0 20 40 60 80 100 Toxicity (%) WT F3A 1. Incubation 3days @ 37°C in buffer (ThT fluorescence) 2. Interactions with supported lipid bilayers (AFM & ATR-FTIR) • Inflammation • Biofilm Is toxicity driven by fibrils? Eukaryotic membranes PC vs. Bacterial membranes PE/PG Buffer : 10 mM sodium phosphate buffer + 150 mM NaCl, pH 8,0 SLB formed by SUV fusion Methods [2-3] [1] f At 5-10 µM, f-WT and f-F3A induce only small damage on eukaryotic membranes whereas f-F3A disrupts bacterial membranes 0 2 4 6 8 10 12 14 16 18 0 2 4 6 8 10 12 f-WT f-F3A Buffer ThT fluorescence intensity (x103) Time (h) 200nm 200nm 0 250 500 750 1000 -1.0 0.0 1.0 2.0 3.0 4.0 Distance (nm) Height (nm) 60’ 120’ 600nm DOPC DPPC 0’ DOPC/DPPC + f-WT 5µM 15’ 30’ 600nm 0 150 300 450 600 −0.5 0.0 0.5 1.0 1.5 Height (nm) Distance (nm) 200nm 200nm 0’ DOPC/SM/Chol + f-F3A 5µM 10nm 140MPa Elasticity Elasticity 1500 1550 1600 1650 1700 0.0 0.2 0.4 0.6 0.8 1.0 Absorbance (u.a.) Wavenumber (cm-1) f-WT spectrum Fit spectrum Turn Alpha Random // Beta DOPC DOPC/DPPC (1:1) DOPC/SM/Chol (67:8:25) DOPE/DOPG (1:1) 0.6 0.9 1.2 1.5 1.8 2.1 2.4 fWT10µM 3h fF3A 10µM 3h Dichroic ratio DOPC DOPC/DPPC (1:1) DOPC/SM/Chol (67:8:25) DOPE/DOPG (1:1) 0 20 40 60 80 100 120 140 Lipid coverage [p-pol] (%) + f-WT 10µM, 3h + f-F3A 10µM, 3h SLB Accumulation on membranes At high concentrations (50µM), f-WT disrupts PC-membranes while f-F3A rather destroys bacterial PE/PG ones. PC/SM/Chol PE/PG 0 20 40 60 80 100 Lipid coverage (%) + f-WT 50µM + f-F3A 50µM At the nanoscale, hydrophobic effects likely drive PSMα3 accumulation and fiber elongation at the membrane interface Funded by the European Union (EU). Views and opinions expressed are however those of the authors only and do not necessarily reflect those of the EU. Neither the EU nor the granting authority can be held responsible for them.


Multi-Resolution Active Learning of Fourier Neural Operators Shibo Li 1, Xin Yu 1, Wei Xing 4, Robert M. Kirby 1,2, Akil Narayan 2,3, Shandian Zhe 1 1Kahlert School of Computing, University of Utah 1Kahlert School of Computing, University of Utah 2Scientific Computing and Imaging (SCI) Institute, University of Utah 3Department of Mathematics, University of Utah 4School of Mathematics and Statistics, University of Sheffield Abstract: Fourier Neural Operator (FNO) is a popular operator learning framework. It not only achieves the state-of-the-art performance in many tasks, but also is efficient in training and prediction. However, collecting training data for the FNO can be a costly bottleneck in practice, because it often demands expensive physical simulations. To overcome this problem, we propose Multi- Resolution Active learning of FNO (MRA-FNO), which can dynamically select the input functions and resolutions to lower the data cost as much as possible while optimizing the learning efficiency. Specifically, we propose a probabilistic multi-resolution FNO and use ensemble Monte-Carlo to develop an effective posterior inference algorithm. To conduct active learning, we maximize a utility-cost ratio as the acquisition function to acquire new examples and resolutions at each step. We use moment matching and the matrix determinant lemma to enable tractable, efficient utility computation. Furthermore, we develop a cost annealing framework to avoid over-penalizing high-resolution queries at the early stage. The over-penalization is severe when the cost difference is significant between the resolutions, which renders active learning often stuck at low-resolution queries and inferior performance. Our method overcomes this problem and applies to general multi-fidelity active learning and optimization problems. We have shown the advantage of our method in several benchmark operator learning tasks. Introduction & Motivation Physics vs. Machine Learning • Physics: Accurate, Principled, Extrapolate Well • Machine Learning: Flexible, Efficient Computational Physics: Finding the solutions of PDEs • Analytical solutions: closed forms but not always feasible • Numerical solutions: accurate, reliable but slow and no generalization Wave Fluid Dynamics Electromagnetism VS. Data-Driven Computational Physics • Learning PDE solutions directly from data • Efficient prediction and generalization Analytical Numerical (e.g., FEM) • Initial condition • Boundary condition • PDE coefficients Heat Equation PDE Solutions Neural Operators and Fourier Neural Operators • Solutions of PDEs are applying operators to the source/parameter/initial functions • Learning the parametric mapping between functions to functions Neural operator layer … Functional space transformation Function convolution Neural operator layer Convolutional Theorem Stationary kernel functions Fourier Neural Operators (FNO) Input function 1 … X Y Numerical Solvers Slow! Expensive! However, Data Costs for Training FNO!!! Input function 2 Input function N Solution1 … Solution 2 Solution N • Probabilistic Multi-Resolution FNO • Active Learning for FNO • Robust performance via cost-annealing Our Contributions Methods Probabilistic FNO FNO Ensemble 2 … Predictive distribution Monte-Carlo Ensembles … FNO Ensemble 1 FNO Ensemble M Multi-Resolution Active Learning FNO MR Utility Multi-Resolution PDE data Probabilistic MR FNO Ensembles Pool of MR data Numerical Solvers Multi-resolution acquisition function Step1: Monte-Carlo approximation Step 2 : Predictive distribution via moment matching Step 3 : Efficient computation via Weinstein- Aronszajn Identity Cost-Annealing Strategy for Robust Active Learning … Few Data Inferior model performance Inaccurate Utility Dynamically assign cost to each resolution Probabilistic Multi-Resolution FNO Experiments Evaluations of Multi-Resolution Active Learning Visualization of Pointwise Error after Active Learning (Navier-Stocks) Ablation Study 1 : Predictive perfor


Soil-, management-, and climate-related drivers of yield stability in organic and conventional farming systems Hofer Simon1*, Hirte Juliane1, Mayer Jochen1, Jarosch Klaus A.1* 1Agroecology and Environment, Agroscope, 8046 Zurich, Switzerland; *[simon.hofer@agroscope.admin.ch | klaus.jarosch@agroscope.admin.ch] 1 Background Soils provide multiple ecosystem services that enable a continuous production of crops. Farming systems that promote ecosystem services are also expected to be mo- re resilient against external stressors, enabling a more stable crop production. To better understand the soil-, management- and climatic- related drivers of yield stabili- ty in different farming systems, the EJP SOIL ARTEMIS project is analysing different long-term field experiments across Europe on these parameters. Preliminary findings 1. Conventional farming systems have more stable yields during adverse climate conditions. 2. Fertilization-based differences in yield stability are more pronounced for organic farming systems. 3. Soybean yields are stable during adverse climate conditions and effect of farming systems are small. Next steps Include soil-related (fertilization, CN stock change) and management-related (plant protection, soil tillage) effects to find the most relevant drivers of yield stability. 2. Analysis of long-term data This study was conducted using data from the Swiss DOK long-term comparison trial, that continously compares dif- ferent typical farming systems since more than 45 years (Figure 1). To assess climate-related effects on yield stabi- lity, weather anomalies were characterized using both raw climatic data (total precipitation, mean temperature) and drought indices (n = 9, on a monthly basis) recorded by a meteorological station close to the experimental site. 4. Preliminary Results Figure 2 Climate-related effects on yield stability of organic and conventional farm- ing systems assessed through the probabilities of yield falling below the 70th percen- tile of the mean reference yield (RY) for potatoes, maize, soybean, and winter wheat. Chosen climate variables included standardized precipitation evapotranspiration index (SPEI), Palmer drought severity index (PDSI), and Palmer Z-Index, indicating different aspects of drought conditions Pr (y ≤ 70% of RY) Potatoes Pr ( y ≤ 70% of RY) Pr ( y ≤ 70% of RY) Crop-specific drought indicator Crop-specific drought indicator Crop-specific drought indicator Crop-specific drought indicator Maize Soybean Winterwheat 2 3 Pr ( y ≤ 70% of RY) Figure 1 DOK long term farming system comparison trial. The experimental design consists of eight different farming systems and fertilization intensities (half = 1; full = 2). Organic systems are characterized by fertilization through slightly (BIOORG) and fully (BIODYN) aerobically composted farmyard manure and slurry, and mechanical weed control. Conventional systems combine manure and mineral fertilization (CONFYM) and a system with only mineral fertilization (CONMIN2), and received chemical plant protection. 3. Production Risk Assessment We defined yield stability as the probability that the yield of the farming system i falls below the 70th percentile of the mean of a reference yield (here CONMIN2). This produc- tion risk assessment can be interpreted as the certainty (or risk) with which agronomists or farmer can predict the yield amount of their cropping systems. To assess crop-specific drought influences on yield, we first subset the monthly calculated climate variables per crop using only month during the average historical growing seasons. The resul- ting variables were then subjected to a principle compo- nent analysis to reduce multicollinearity. The principal component 1 was then used as a crop-specific drought indicator. Dry Wet Dry Wet


The Magnetised Environments of Radiative-mode and Jet-mode AGN Shane P. O’Sullivan1, C. R. Purcell2, J. S. Farnes3, X. H. Sun2, C. S. Anderson2, B. M. Gaensler4, et al. Abstract: We present results from a broadband (1 to 10 GHz) radio polarisation analysis of 102 radio-loud AGN. We investigate the most likely mechanisms causing the observed differences in the integrated 1.4 GHz polarisation properties of radiative-mode and jet-mode AGN, as found in O’Sullivan et al. (2015). Our analysis shows that jet-mode sources with high integrated polarisation at 1.4 GHz have low RM dispersion, are dominated by a single polarised component, and have a steep spectral index. We find that while, on average, the radiative- mode AGN are in slightly more turbulent magnetised environments than the jet-mode AGN, it is mainly the intrinsically disordered magnetic field structures of the radiative-mode AGN that leads to the lower integrated polarisation seen at 1.4 GHz (O’Sullivan et al. 2016, in prep.). Results: There are ~40% of sources that have one dominant RM component, ~50% with two RM components and ~10% with three RM components. Therefore, in order to investigate the magnetised environments of all sources in a consistent manner we calculate the polarisation-weighted RM dispersion, σRM,wtd (eqn. 3). This provides a characterisation of the general amount of depolarisation in the local environment of each source. Figure 2b: Here we show a source with more complicated polarisation behaviour from 1 to 3 GHz, which is well fit by two complex-polarisation components. Interestingly, the high angular resolution data at 9 GHz show that the source is a double-lobed radio galaxy, which supports the results of our model-fitting. *Data from the Australia Telescope Compact Array (ATCA) References: O’Sullivan et al. (2012), MNRAS, 421, 3300 O’Sullivan et al. (2016), in prep. O’Sullivan et al. (2015), ApJ, 806, 83 Sokoloff et al. (1998), MNRAS, 299, 189 Summary & Future work: - Our study emphasises the necessity for broadband polarization observations to accurately determine the Faraday rotation measure properties of the integrated emission from radio-loud AGN. - The results show how we can distinguish between the intrinsic magnetic field properties of sources and the external magnetised environment that causes depolarisation, using our polarization model-fitting approach. - We find that the radiative-mode AGN are in more turbulent magnetised environments and have more intrinsically disordered magnetic field structures than the jet-mode AGN, on average. - Future all-sky radio polarisation surveys, with telescopes such as the Australian SKA Pathfinder (ASKAP) and the VLA, will provide much greater statistical power to investigate the detailed magnetic field properties of different classes of radio-loud AGN in different types of environments. Figure 3b: Here we see that all the highly polarized sources at 1.4 GHz are dominated by a single RM component (Blue circle: one component, Green diamond: Two components, Red triangle: Three components). The low degree of polarisation for sources with two or three RM components is possibly caused by interference between the components. Several, but not all, of the weakly polarised sources have flat spectral indices indicating that the polarised emission is likely emanating from a synchrotron-self-absorbed region, which limits the the intrinsic degree of polarisation to <~ 10%. The remaining optically-thin low-polarisation sources have intrinsically disordered magnetic field structures. Figure 3a: Here we plot the degree of polarisation at 1.4 GHz versus the polarisation-weighted RM dispersion for radiative-mode (blue) and jet-mode (red) AGN. There is a clear absence of sources with a high degree of polarisation at 1.4 GHz and high RM dispersions, suggesting the depolarisation caused by the magnetised environment local to the source is an important factor. However there are several sources with low RM dispersions that also


Bridging the Gap between School Climate Policies and the Harsh Reality of Chicago Public Schools that Leads to Chronic Absenteeism Haniyyah Thomas, University of Illinois Chicago Dr. Joseph K. Hoereth, Institute for Policy and Civic Engagement, University of Illinois Chicago While observing a Chicago Public Schools (CPS) high school, I noticed how determined staff members were to improve ’on track’ rates. So, I asked them if there were any commonalities amongst students that were ’off track’, and it was quite simple— they didn’t come to school. I then learned 89% of the students were chronically absent, schoolwide, with 42% of 9th graders being off track to graduate in SY2023. The most prominent indicators of post-secondary enrollment are on-track status, Grade Point Average (GPA), and course failures. On-track status refers to whether a student has enough credit to graduate from one grade to the next, which the Illinois State Board of Education (ISBE) identifies as the completion of 10 semester credits. Since missing a day of school is a missed opportunity to learn, absence has a significant impact on student achievement. Chronic absenteeism, missing 10% or more days of school with or without excuse, is a national crisis (U.S. Dept. Ed., 2016). Truancy refers to unexcused absence for at least 5% of the school year. School climate refers to the character and experience of the school, and according to ISBE it is shaped by 4 components: safety, relationships, teaching & learning, and the institutional environment. Chicago Public School’s (CPS) Comprehensive Policy on Attendance serves to align all CPS schools’ with ISBE school codes and promote best practices pertaining to attendance. Article II specifically addresses the individual school’s responsibility in improving attendance and Section C requires all schools to implement an attendance plan that targets the underlying causes of chronic truancy. The policy does not address the vast discrepancies in school climate across CPS school districts, thus failing to provide proper resources and support to improve school climate for schools that are more likely to experience more adverse contributors to their school climate, such as schools with high populations of low- income students. Figure 1 shows that there is an increase in the number of students that are chronically absent in schools that have higher populations of low-income students. With that, there is also an increase in the variation as the enrollment of low-income students increases, which means that there is an unobservable factor that can reduce chronic absenteeism. While more advanced data analysis is required to explain the increase in variation, I hypothesize that school climate decreases the negative impact that poverty has on student attendance. Chicago’s Current Solution Something’s missing... What’s the big idea? This is important to know... Sources: WHAT’S THE BIG IDEA: Illinois State Board of Education, 2023 | THIS IS IMPORTANT TO KNOW: Illinois State Board of Education, 2024; U.S. Department of Education; 2016 | CHICAGO’S CURRENT SOLUTION: Chicago Public Schools, 2022 | SOMETHING’S MISSING: Illinois State Board of Education, 2024 | FINDINGS: UChicago Impact, 2023; Illinois State Board of Education, 2012, 2024 | FINDINGS CONT.: Illinois State Board of Education, 2024; Chicago Public Schools, 2022; Sample School, 2024 American Community Survey, 2022 (https://www.chicagosfoodbank.org/get-involved/learn/) Sample School Figure 1 Graph generated from Illinois Report Card, 2023 data The supportive environment indicator is the most dependent upon the school’s neighborhood characteristics. The variation, especially in schools with a low score, suggests that there are ways that schools can mitigate absenteeism irrespective of neighborhood quality. Illinois Report Card (ISBE) The Illinois Report Card, an annual publication by ISBE, offers an extensive dataset and interactive reports detailing the performance of individua


RADICAL-Cybertools: Middleware Building Blocks NSF's Cyberinfrastructure Ecosystem (NSF 1931512) Motivation: Sophisticated and scalable workflows have become essential for advances in computational science. In spite of the many successes of workflow systems, there is an absence of a reasoning framework for end-users to determine which systems to use, when and why. Workflows are increasingly a manifestation of the algorithmic and methodological advances; workflow users and workflow system developers are often the same. Workflow systems must be easily extensible so as to support diverse functionality and the proverbial “last mile customization”. We advance the science of workflows and prevent workflow system “vendor lock-in” by formulating a building blocks approach to middleware for workflow systems, grounded on four design principles: self-sufficiency, interoperability, composability and extensibility. A building block has: (i) one or more modules implementing functionalities to operate on a set of explicitly defined entities; and (ii) two well-defined and stable interfaces, one for input and one for output. Properties of building blocks ●Self-sufficiency: design does not depend on the specificity of other building blocks ●Interoperability: can be used in diverse system architectures without semantic modifications ●Composability: its interfaces enable communication and coordination with other building blocks ●Extensibility: its functionalities and entities can be extended to support new requirements or capabilities The diagram below describes the primary functional requirements for workflow systems. RADICAL-Cybertools are designed as building blocks that span multiple functional levels: (L4) Workflow and Application Description: Requirements and semantics of applications and workflows. (L3) Workload Management System: Applications devoid of semantic context are expressed as workloads. (L2) Task Runtime System (TRS): Execution of the tasks of a workload. (L1) Resource Access Layer: Capabilities, availability and interfaces required by the tasks to be executed. Motivation: Middleware Building Block Primary Functional Levels RADICAL-SAGA (Simple API for Grid Applications): Provides an interoperability layer that lowers the complexity of using distributed infrastructure whilst enhancing sustainability of distributed appli- cations, services and tools, in the form of a Python API. By abstracting away the heterogeneity of the underlying systems, RADICAL-SAGA simplifies access to many distributed cyberinfrastructures such as XSEDE and OSG. (L1-L2) Interface to Resource ExTASY: Enables advanced sampling of complex macromolecules using molecular dynamics. DeepDriveX: Enables scalable and concurrent execution of Machine Learning (ML) and HPC workloads (X) on HPC Platforms. ICEBERG: Enables scalable image analysis on HPC. It allows the integration of image analysis frameworks and algorithms. SCALE-MS: Enables the concurrent execution of adaptive ensemble algorithms. It uses RADICAL-Pilot for workload execution. RADICAL-Cybertools support multiple points of integration, “unifying” conceptual reasoning across otherwise different tools and systems (L4) Workflow Management Systems Ensemble Toolkit (EnTK): Provides the ability to execute flexible combinations of ensemble-based workflows. It promotes “ensembles” to a first class abstraction, managing where and how the ensemble workload is executed. EnTK exposes a pipeline-stage-task programming model as the interface to express ensemble-based workflows. (L3-L4) Workflow / Workload Management SeisFlows ●Supports seismic inversion workflows on HPC machines, at scale ●We integrated SeisFlow: ○with RADICAL-SAGA (L1) to execute compute jobs ○with RADICAL-EnTK (L3) to orchestrate tasks and data staging ATLAS (Panda and Harvester) ●PanDA is a WMS that supports the execution of workflows via pilots ●We integrated Panda and RADICAL-Pilot to improve its scaling on large HPC resources, and integrated Har


Anton Pirogov1 // Mustafa Soylu1 // Fiona D’Mello1 // Volker Hofmann1 // Stefan Sandfeld1 {a.pirogov, m.soylu, f.dmello, v.hofmann, s.sandfeld}@fz-juelich.de 1 Materials Data Science and Informatics (IAS-9), Forschungszentrum Jülich GmbH Metador: A metadata-centric framework for enabling FAIR research (meta)data handling Motivation development of high quality standards and software is difficult and slow bottom-up efforts often solve similar RDM problems with incompatible solutions Project Goals Metador will support scientists by: Current Status  operational container API and plugin system  prototype of schema and widget system  Metador dashboard integrated into InvenioRDM https://inveniosoftware.org/products/rdm Next Steps  Implementation of scientific pilot use case  Development of improved user-oriented tooling search for (meta)data of certain types, making datasets findable an ecosystem of reusable and generic software components JSON Schema and JSON-LD export, aligned with schema.org / ROCrate Metadata-driven automatic dashboards for data introspection Science needs better software tools Tools require (meta)data standards helping to organize research (meta)data facilitating bottom-up, pragmatic and incremental harmonization of schemas accelerating development of useful metadata-driven tools and services Interested? Get in touch! https://materials-data-science-and-informatics.github.io/metador-core Architecture of the Framework Metador = Plugin System + (Meta)data Packaging Format (Python ≥ 3.8) (entrypoint - based) (lightweight, domain-agnostic, extensible) + Metadata Schemas  based on pydantic  ensure strong validation  support field inheritance  JSON Schema export data + metadata Metador Container Other Domain-Agnostic Tools  technical: e.g. flask blueprint supporting dashboard integration in websites  user-oriented: tools to help with metadata(-schema) preparation, creation and management of Metador-enabled research data containers schema A research data metadata document preview widget schema B schema C schema D Metadata Harvesters  can be pipelined  extract metadata into schema-compliant objects  building block to support packaging automation (Interactive) Widgets  based on bokeh + panel  support Jupyter Notebooks  embeddable in a website  used for (semi-)automatic container dashboard  currently HDF5-based, designed for easy adaptability to common archive formats  simple h5py-based Python API provides advanced metadata management  all metadata objects conform to a schema and are stored alongside the data as JSON + + + Sketch of Planned Solution for the Pilot Use-Case Invenio visualize search find relevant data and inspect it { } JSON-LD JSON Schema export store / retrieve generic user-side tools (CLI/GUI) project metadata and schemas out into other formats and technologies manage containers using a state-of-the-art RDM repository software User Research Data Metadata Metador Container ‹ ?› ‹ ?› harvest validate metador-invenio Integration + Widget Plugins Generic Dashboard Schema Plugins pack export


GERMAN FEDERAL INSTITUTE FOR RISK ASSESSMENT Federal Institute for Risk Assessment • Max-Dohrn-Str. 8-10 • 10589 Berlin, GERMANY • Phone + 49 30 - 184 12 - 0 • Fax + 49 30 - 184 12 – 99 0 99 • bfr@bfr.bund.de • www.bfr.bund.de Isolation and characterization of a novel mcr-5 carrying Escherichia coli plasmid from chicken feces in Germany Colistin is considered as an important antibiotic of the last resort against human infections with multidrug-resistant (MDR) Gram- negative bacteria. The emergence and spread of mobilizable colistin resistance in Enterobacteriaceae is associated with major public health concerns. Since 2015, several mobile colistin resistance genes were described coding for enzymes of the phosphoethanolamine-transferase family. Nowadays, eight different mcr-genes (mcr-1 to -8) were identified, mediating resistances to colistin in different bacterial genera (especially in Enterobacteriaceae). In this study, a novel mcr-5 carrying plasmid of a commensal E. coli recovered from chicken feces is described. Introduction Here we describe a novel mcr-5 plasmid-prototype from an E. coli isolate of the German national monitoring of zoonoses in food and livestock in 2013/2014. The isolate exhibited a MIC against colistin of 4 mg/L as determined by using broth microdilution according to the EUCAST guidelines. Basis genetic features of the Whole Genome Sequencing (WGS) analysis of the isolate are summarized in Table 1. S1-PFGE (Fig. 1) analysis and WGS revealed that the genome of the plasmid pEC1897-13 was 38 kb in size and exhibited 44 putative open reading frames (ORFs; Table 2), respectively. Basic properties of the E. coli isolate and its plasmid Transmissibility of the mcr-5 carrying plasmid K. Juraschek1,†, M. Borowiak1,†, D. Shamoun1, S. Schmoger1, A. Irrgang1, N. Pauly1, M. Grobbel1, A. Käsbohrer1,2, B. Malorny1 & J.A. Hammerl1 Bioinformatic analysis indicated that the plasmid belongs to the IncFII group, but represent a novel pMLST-allele that is closely relate to the allele FII-82. Beside mcr-5, no further resistance determinant was detected on the plasmid. Interestingly, the plasmid genome of pEC1897-13 obviously comprises all necessary components of a functional IncF conjugative- transfer system (Table 2). However, up to now no self-transmission of the plasmid was observed in E. coli by filter mating studies at 37°C under different conditions. Correspondence to Dr. Jens A. Hammerl, National Reference Laboratory for Antibiotic Resistance, Department of Biological Safety, German Federal Institute for Risk Assessment, Diedersdorfer Weg 1, 12277 Berlin, Germany; E-mail: jens-andre.hammerl@bfr.bund.de Here we report on a novel IncFII mcr-5 carrying plasmid-prototype recovered from chicken feces in 2013. The impact of the plasmid for the transmission of colistin resistances in unknown. However, despite of most of the described mcr-5 carrying plasmids pEC1897-13 carry a complex IncF-like transfer system that may be potentially functional under some specific circumstances. Conclusion 1German Federal Institute for Risk Assessment, Department of Biological Safety, Berlin, Germany; 2Institute for Veterinary Public Health, University of Veterinary Medicine, Vienna, Austria; † both author contributed equally to this work Isolate 13-AB01897 Year of isolation 2013 Source Chicken, feces Genome features Genome size (bp) 5,256,358 GC content (%) 50.44 Genes (total) 5,758 Genes (coding) 5,317 CDS (total) 5,653 CDS (coding) 5,317 RNA genes (total) 105 rRNAs (total) 5S, 16S, 23S 6, 7, 5 tRNAs 77 ncRNAs 10 Pseudo genes (total) 336 Aquired antimicrobial resistances Aminoglycoside aph(3'')-Ib (100%) aph(6)-Id (100%) aadA1 (100%) Beta-lactam blaTEM-1B (100%) Colistin mcr-5 (100%) MLS mph(B) (100%) Phenicol catA1 (99.85%) Sulphonamide sul1 (100%) sul2 (100%) Tetracycline tet(34) (84.75%, partial) tet(A) (100%) Trimethoprim dfrA1 (100%) Chromosomal point muations gyrA S83L PlasmidFinder (inc group) Col ColRNAI (91.74%, partial) Col(MG828)


GaiaHub: Precise proper motions combining data from the Gaia and Hubble space telescopes Andrés del Pino (CEFCA, adelpino@cefca.es) We present GaiaHub, a publicly available tool1 that combines Gaia measurements with Hubble Space Telescope (HST) archival images to derive precise proper motions (PMs). GaiaHub yields considerably improved PM accuracy compared to Gaia-only measurements (up to 10 times better), especially for faint sources (G 18), requiring only a single epoch of HST data observed more than ~7 yr ago (before 2012). To illustrate the capabilities of GaiaHub, we ≳ apply it to samples of MW globular clusters (GCs) and classical dwarf spheroidal (dSph) satellite galaxies. This allows us to measure the velocity dispersions in the plane of the sky for objects out to and beyond 100 kpc. ∼ Results ●We find, on average, mild radial velocity anisotropy in GCs. ●We observe a correlation between the internal kinematics of the clusters and their ellipticity, with more isotropic clusters being, on average, more round. ●The Draco and Sculptor dSph appear to be radially anisotropic systems. Fig. 1: Comparison between the results obtained using Gaia and GaiaHub for the Palomar 4 GC (d☉ = 108.7 kpc). Left column: PMs in RA vs. Dec, measured by Gaia (top panel, red) and GaiaHub (bottom panel, blue). Right column: sky positions of the stars with the projected proper motion vectors. New PMs, not present in the Gaia DR3 catalog are shown by open blue squares. Member stars, are represented by large, darker markers. The improvement in the accuracy is reflected in the smaller dispersion of the results obtained with GaiaHub. Fig. 2: Summary of the results for the NGC 2419 GC (d☉ = 82.6 kpc) and the Fornax dSph galaxy (d☉ = 147 kpc) using GaiaHub and Gaia alone. From left to right the panels show the color-magnitude diagram, the PM uncertainties as a function of G mag, the PMs in RA vs. Dec (VPD) for Gaia DR3 (top, red) and GaiaHub (bottom, blue), and the footprint of the analyzed area showing the PMs as vectors (only GaiaHub measurements). Markers coincide with those of Fig. 1.. Stars whose PM uncertainty is below the central velocity dispersion, marked by an orange vertical dashed line in the second panel (measured through spectroscopy, 4.0±0.6 and 11.7±0.9 km s-1, respectively), are shown in dark blue. The gray shaded area in two leftmost panels indicates the region of saturation for the deepest HST images. In the third column of panels, the dark red open triangles from the top panel Gaia compare to the dark blue dots from the bottom panel (GaiaHub). Notice that newly measured PMs that are not in the Gaia catalog (light-blue open squares) are not present in the Gaia's VPD. 1. You can download GaiaHub from here: More information in the paper:


Countering quarantine viruses and viroids through cleaning and disinfection (DISVIR) Funding Non-competitive funding mechanism. Each funder only pays for the participation of their own national researchers. Total funding € 116 000 Picture 1 Picture 1 Picture 1 Goals Cleaning and disinfection of tools and greenhouse surfaces are recommended for official control of a number of viruses. However, a limited number of products are available, and efficacy evaluation data of such products are not always publicly available or consistent. The aim of the project is to improve the management of selected viruses and viroids. Research consortium CRA-W (BE), ILVO (BE), Fera (GB), Volcani (IL), IHPS (SI), APHIS (US), EPPO (Int), AHDB (GB) Contact information Project coordinator: Stephan Steyer and Kris De Jonghe s.steyer@cra.wallonie.be Kris.DeJonghe@ilvo.vlaanderen.be Key outputs and results The project will validate protocols for cleaning and disinfection against quarantine viruses and viroids. Results of this project could be considered to revise e.g. EPPO Standard PM 10/1 Disinfection procedures in potato production and EPPO Standard PM 9/13 Potato spindle tuber viroid on potato and contribute to the development of new PM 10 Standards. Objectives The project consortium will: • gather information on disinfectants and protocols for cleaning and disinfection (through literature review and exchange of knowledge among experts) • validate cleaning and disinfection protocols for selected pests, such as tomato brown rugose fruit virus or potato spindle tuber viroid The project will not focus on disinfection of soil and seeds. Instead, it should define optimal cleaning and disinfection of equipment and tools (including containers, trays, shoes, machineries), greenhouses surfaces (including irrigation systems) and the workers’ skin. The development of authorization dossiers for new disinfectants is not in the scope of the project. 09/2021-08/2023


Aedes Science Gateway: A Machine-learning Based Mosquito Egg Counting System Lawrence Miao Department of Computer Science Rensselaer Polytechnic Institute Troy, NY USA miaol2@rpi.edu Adam Frederiksen Department of Computer Science University of South Carolina Columbia, SC USA apf1@email.sc.edu David Reddy Research Computing University of South Carolina Columbia, SC USA reddydp@mailbox.sc.edu Bob Doran Research Computing University of South Carolina Columbia, SC USA rdoran@mailbox.sc.edu Sarah Gunter Pediatrics-Tropical Medicine Baylor College of Medicine Houston, TX USA Sarah.Gunter@bcm.edu Melissa Nolan Public Health University of South Carolina Columbia, SC USA msnolan@mailbox.sc.edu Abstract Each year, approximately 400 million people are infected with an arboviral disease from the bite of an Aedes mosquito. Scientists have been using mosquito traps that allow for high throughput identification and counting of Aedes mosquito eggs for decision-making on insecticide spraying and abatement. Aedes project is an effort to automatically count the eggs in the trap paper images by computer vision and machine learning techniques. Such a task can be very challenging due to debris on paper, congested egg clusters, etc. To address these challenges, we developed a new method that can automatically and efficiently run in a light environment, e.g., a mobile phone. Specifically, given an egg paper image, we first apply adaptive thresholding to convert it to a binary image. Then egg contours are extracted, followed by patch cropping over each closed contour. These patches serve as the inputs to a new convolutional neural network (CNN) [1] based classifier. The CNN consists of a series of convolutional layers, ReLU layers, and max-pooling layers, followed by two fully connected layers. We classify the patches as single eggs, egg clusters, and debris. The final count is determined by the number of single egg patches and the number of eggs in each cluster. The number of eggs in a cluster is estimated by the area of the egg cluster dividing by that of the average single egg. We divide the patch set into 1440 in training and 160 in testing with augmentation. The classifier is trained using CrossEntropyLoss, Adam optimizer with the base learning rate as 15-4, and 20 epochs. We achieve 92% accuracy in testing, 1% lower than ResNet50 [2]. However, our model takes < 1 second to process one image on CPU, 100 times faster than ResNet50. Building as a science gateway, Aedes mainly consists of a web portal that allows scientists to study the eggs collaboratively online and a backend process that uses the developed DL model to batch process the egg counting. The web portal is implemented in React.js, Java Spring Boot, Postgre SQL, OpenCV.js, and ONNX.js. The backend service is implemented in Pytorch. The science gateway is supported by Jetstream 2 cluster. REFERENCES [1] A. Krizhevsky, I. Sutskever, and G. E. Hinton. Imagenet classification with deep convolutional neural networks. NIPS, pg1097–1105, 2012. [2] K. He, X. Zhang, S. Ren, and J. Sun. Deep residual learning for image recognition. arXiv preprint arXiv:1512.03385,2015. Presented at Gateways 2022, San Diego, USA, October 18–20, 2022. https://zenodo.org/communities/gateways2022/?page=1size=20


An introduction and overview to the new SPNHC publication 'Best Practices in the Preservation and Management of Fluid-Persevered Biological Collections'. Mr Julian Carter1, Mr Dirk Neumann2,3, Mr John Simmons4 1Amgueddfa Cymru National Museum Wales (UK), Cardiff, United Kingdom, 2Staatliche Naturwissenschaftliche Sammlungen Bayerns, Zoologische Staatssammlung, , Munich, Germany, 3Leibniz Institute for the Analysis of Biodiversity Change, Centre of Natural History of the University of Hamburg (LIB-CeNak), Hamburg, Germany, 4Museologica, Bellefonte, USA BEST PRACTICES IN THE PRESERVATION AND MANAGEMENT OF FLUID-PRESERVED BIOLOGICAL COLLECTIONS is a newly published book that establishes effective and achievable standards for the maintenance and care fluid collections of different sizes. The best practice recommendations are holistic and take into account resource limitations for maintaining collections in stable condition. Additional recommendations are provided in three un-ranked categories that reflect the differences in institutional curation capacity, storage environment, collection size, laboratory facilities, frequency of specimen use, and available resources (e.g., budget, collection care staff) in major research collections vs. smaller regional collections. The development of these best practices began with a 2013 initiative funded by a Clothworkers Foundation grant directed by Chris Collins (NHM London) and were further refined in workshops at SPNHC conferences in Cardiff (2014), Berlin (2016), and Denver (2017); an experts meeting at the Smithsonian (2018) directed by by Catharine Hawks; and a symposium on the “Preservation of Natural History Wet Collections: Feedbacks and Prospects” (Paris 2018) organized by Sophie Cersoy, Julian Carter, Marc Herbin, Dirk Neumann, and Véronique Rouchon. Information and critical comments from these interactive meetings served as a framework to enhance our understanding of the care and conservation of fluid preserved objects and develop key questions and baselines for future research. This presentation will summarise the way this book has brought together current collective knowledge on the management and care of fluid preserved collections while also drawing attention to how much we still do not understand. This enables the community to more clearly identify and prioritise the collaborative research needed to further enhance our understanding of these valuable and unique collections.


USING THE IMAGING FLOW CYTOBOT (IFCB) TO BETTER UNDERSTAND PARTICLE SIZE DISTRIBUTION AND BLOOM DYNAMICS IN CENTRAL CALIFORNIA. Kendra Hayashi and Raphael Kudela University of California, Santa Cruz, Santa Cruz, CA Introduction Imaging flow cytobots (IFCBs) are powerful tools for understanding bloom dynamics in marine and freshwater environments. In addition to autonomously generating high resolution images, particle size and volume are derived during image analysis and provide important components to assessing the ecology of aquatic systems. Particle size distribution (PSD) is critical for calculating radiative transfer and often drives trophic dynamics. Here we use PSD derived from estimated spherical diameter (ESD) calculated from IFCB images to assess IFCB performance and phytoplankton community dynamics at the Santa Cruz Wharf (SCW) and San Francisco Bay (SFB). IFCB settings and PSD Conclusions Universal PMT settings on IFCBs do not yield similar results; each instrument must be optimized for its deployment environment and specific data acquisition requirements. Over the 3 years analyzed, PSDs in SFB appeared to be stable and consistently follow a power law model, even in the central bay where ocean water and tidal mixing strongly influence the phytoplankton community. Variations from the global mean are associated with unusual events in a geographic location. Unlike SFB, the SCW PSDs are less consistent with a fair amount of daily variation complicating simple analyses of PSDs. SCW PSDs reflect an increase of dinoflagellates in the phytoplankton community documented in 2018 (Fisher et al. 2020) and continuing to the present. The dinoflagellate “signature” is seen at all levels of the data (from individual samples to global averages). IFCBs are being used more widely, with automated image classification lagging as the image libraries are being built and tested. PSDs could be a quick and easy way to assess phytoplankton community dynamics in novel locations as we wait for the classifiers to come online. They could also be used as a rapid QA/QC test to assess data quality of larger datasets. Literature Cited • Fisher et al. 2020. Return of the “age of dinoflagellates” in Monterey Bay: Drivers of dinoflagellate dominance examined using automated imaging flow cytometry and long- term time series analysis. Limnol. Oceanogr. 65: 2125-2141. • Reynolds et al. 2010. Measurements and characterization of particle size distributions in coastal waters. JGR. 115: C08024. • Zhou et al. 2022. _fdapace: Functional Data Analysis and Empirical Dynamics_. R package version 0.5.9, https://CRAN.R-project.org/package=fdapace. Acknowledgments Thank you to John Negrey and the Kudela Lab for comments, suggestions, and statistical analysis (JN). This work was supported by Cal-HABMAP which represents multiple organizations and partners who contribute to the operation and maintenance of the IFCB network. Core funding has been provided by NOAA, including the IOOS, ECOHAB, and MERHAB programs, NASA, California Sea Grant, California Ocean Protection Council, and numerous in-kind contributions from our partners and stakeholders. Initial purchase and development of the IFCBs was supported by NA16NMF4270263 (Saltonstall Kennedy) and NA14NOS0120148 (NOAA OTT). Results • IFCBs detected varying sizes of microspheres as expected based on the specifications of the instrument (Fig 1) • The IFCBs performed similarly to other particle imaging systems (Reynolds et al. 2010). • ESD measurements of the beads were different from the expected values but were consistent within any given size. • Two instruments sampling side by side with identical PMT values yielded different PSDs and phytoplankton communities (Fig 2). • Sensitive PMT settings increase the ESD range and detect higher numbers of smaller particles (Fig 2a). • PMT settings strongly influence the phytoplankton community structure (Fig 2b). Results SCW PSDs do not consistently follow a simple power law


Searching for pulsars in the Small Magellanic Cloud Emma Carli +Lina Levin, Ben Stappers and the TRAPUM team Why? How? Discoveries! Rare: of ~3k pulsars discovered, 31 are extragalactic Galactic properties impact Neutron Star population If double NS discovery: update extragalactic NS merger rates FRBs and magnetars Tied-array beams: ~800 timeseries with high frequency resolution recorded simultaneously on multiple sources Immediate multibeam localisation to ~1" precision On-site search for single and binary pulsars Supernova Remnants MeerKAT beams MeerKAT image of SMC: Cotton et al. 2024 Danielle Futselaar 7 radio pulsars discovered and timed: known population doubled First three young pulsars discovered in this galaxy, all of which have glitched within 1.5 years, two in Pulsar Wind Nebulae See Carli et al. 2022, Carli et al. (submitted) Find out more: trapum.org E-mail me: emma.carli@manchester.ac.uk MeerKAT Murriyang Parkes CSIRO / Shaun Amy DEM S5 Supernova Remnant and Pulsar Wind Nebula 1'


The Need For a Digital Preservation Community of Practice Every organisation dependant on digital materials has digital preservation needs Collaboration and connection are essential for success in digital preservation Cross-disciplinary forums allow both experienced individuals and organisations to exchange digital preservation best practice and advice Digital preservation and training needs to be more accessible in the Australasian region “I’m just beginning to get a grip on digital curation and preservation … The community of practice idea is an underutilised one. It means colleagues can learn together and access the same pool of expertise.” - Fiona Blackburn, AIATSIS “Auspreserves is an inclusive space for experts and beginners alike to work together to solve digital preservation problems.” - Elise Bradshaw, PROV Digital preservation is one of the most collaborative fields I’ve encountered in a long professional career, and Australasia Preserves is a vital mechanism for collaboration in this region.” - Prof. Ross Harvey Australasia Preserves Key Highlights Australasia Preserves helps build local and global relationships, enabling sharing of digital preservation knowledge and experience The Australasia Preserves community of practice is a group of people who share an interest in the field of digital preservation Being part of a community of practice provides opportunities to develop personally and professionally. Find Ali at IDCC20 to find out more about the Australasia Preserves community of practice or tweet us: AliIcecream JayeChats #AusPreserves Presenter: Ali Hayes-Brady, Monash University Co-Author: Jaye Weatherburn, The University of Melbourne @ @ A digital preservation community of practice for Australia, New Zealand, and the broader Australasian region. AUS PRESERVES CO-ORGANISERS: Jaye Weatherburn, The University of Melbourne; Matthew Burgess, State Library of New South Wales; Ali Hayes-Brady, Monash University; Rachel Tropea,The University of Melbourne; Carly Lenz, Archives New Zealand; Jan Hutar, Archives New Zealand; Lachlan Glanville, The University of Melbourne; Carey Garvie, National Archives of Australia; Elise Bradshaw, Public Record Office Victoria Australasia Preserves established at The University of Melbourne Mar- Apr Nov Feb Jun pt 1 Jun pt 2 Sept Feb Jul Online forum created and monthly online meetings begin State Library of New South Wales organises face-to- face meetings with lightning talks and a panel discussion. “Digital Preservation for All” face-to-face event hosted by the Australian Institute of Aboriginal and Torres Strait Islander Studies (AIATSIS) and supported by AARNet Australasia Preserves turns one at IDCC19 and hosts the first Digital Preservation Carpentry Workshop A monthly meetup co- organised by AIATSIS and the National Library of Australia for Australasia Preserves about Digital Curation in the Indigenous Data Network “Introduction to Automation for Archivists” a workshop created by Jarrod Harvey, an AusPreserves member, held for the first time Monthly meeting focussed on Digital Preservation Education in Australian and New Zealand Universities 2018 2019 AUSTRALASIA PRESERVES 2 YEARS ON Australasia Preserves Illustration by Matthew Burgess (CC BY-NC-SA 4.0), www.matthewburgess.net; Tagline by Lachlan Glanville


The metrics for a code fragment № Name Description / Comment 1–62 Number of keywords: continue, for, new, switch, assert, synchronized, boolean, do, if, this, break, double, throw, byte, else, case, instanceof, return, transient, catch, int, short, try, char, final, finally, long, strictfp, float, super, while (total and average among lines of code for each) Represents the contents of the code fragment 63–64 Number of characters in the fragment (total and average among lines of code) Represents the size of the fragment 65 Number of lines in the fragment Represents the size of the fragment 66–67 Nesting area of the fragment (total and average among lines of code) Represents the complexity of the fragment 68–69 Number of characters in the enclosing method (total and average among lines of code) Represents the size of the enclosing method 70 Number of lines in the enclosing method Represents the size of the enclosing method 71–72 Nesting area of the enclosing method (total and average among lines of code) Represents the complexity of the enclosing method 73–74 Number of references to fields from the enclosing class (total and average among lines of code) Represents the coupling with the enclosing class through its fields. Important when copying from another class. 75–76 Number of calls of methods from the enclosing class (total and average among lines of code) Represents the coupling with the enclosing class through its methods. Important when copying from another class. 77–78 Coupling with the enclosing class (total and average among lines of code) The sum of the two metrics above


PROF. BUJAR BAJCINOVCI © INTERACTIVE KINETIC ARCHITECTURE PROGRESSIVE DESIGN PRINCIPLES RESEARCH CENTRES AND LABORATORIES


1Galter Health Sciences Library, Northwestern University 2Altmetric, 3Oregon Health & Science University, 4VIVO Introduction While there are projects and ongoing efforts to better understand the diverse roles that professionals take on when contributing to the scholarly ecosystem, it is clear that more work is needed to fully explore the area of contributorship roles. Several leaders in this area have proposed projects to define an informatics infrastructure that enables the collection and dissemination on contributor attribution data to various stakeholder audiences. Projects of that nature bring excitement and expectation, as we wait to see where they will take us and how greatly they will impact the scholarly ecosystem. Perhaps most important is the need to accomplish this work in an open, collaborative manner, leveraging data standards along the way to enable interoperability and integration with existing architectures. Methods Contribution Ontology Goals Discussion Working with FORCE11 Attribution of Work in the Scholarly Ecosystem Karen E. Gutzman1, Stacy Konkiel2, Marijane White3, Matthew Brush3, Violeta Ilik1, Mike Conlon4, Melissa Haendel3, Kristi L. Holmes1, FORCE11 Attribution Working Group, OpenVIVO Working Group As research is driven forward by technological advances, the composition and structure of the research team is also evolving. Professionals from a wide array of backgrounds contribute to scientific breakthroughs and discoveries, often in ways that are not easily recognizable using traditional measures of scholarly impact. Metrics and indicators that are limited to grants and publications often cause these diverse contributions to be overlooked and undervalued. The lack of adequate representation can affect large swaths of the current scholarly ecosystem, such as career advancement, financial incentives, funding acquisition, and scholarly recognition. In this project we have outlined a list of contributor roles identified by the Force 11 Attribution Working Group. Contributor roles from existing taxonomies were leveraged (CRediT) and further enhanced with more finely-resolved contributor roles based on an in-depth investigation of activities and outputs. We have also collated and reviewed existing efforts on scholarly contribution taxonomies to determine their unique aspects, and how they complement each other. We reviewed the landscape of taxonomies and systems in order to compare and contrast key types of contributions. We also considered the objectives needed to create a contributorship model that is robust enough to cover various fields of research, and specific enough to adequately describe contribution in a meaningful way. Relevant Projects and Groups • Review and summarize the objectives of the projects listed above to determine how much they overlap - can a core set of objectives, perhaps with extensions, be defined? • Review and summarize key types of scholarly products and the roles that people have in relation to them, resulting from the Force15 workshop and from other efforts, such as the NISO Alternative Metrics Working Group • Landscape review, comparing and contrasting key types of contributions across the different taxonomies/systems • Recommendations for publishers, IRs, research profiling systems to implement Projects: • Project CRediT • OpenRIF (VIVO-ISF ontology) • PROV • Becker Model for Assessing Research Impact • Transitive Credit • Academic Careers Understood through Measurements and Norms (ACUMEN Project) • Scholarly Contributions and Roles Ontology (SCoRO) Groups: • Global Alliance for Genomics and Health (GA4GH) • National Information Standards Organization (NISO) FORCE16 submission form that contains “Project Role” field. Ontology available on Github: https://github.com/openrif/contribution-ontology Brainstorming session on output types at the Contribution and Attribution in the Context of the Scholar workshop at Force2015, Oxford. Results We found there to be a diverse land


art driven innovation for the purpose of good partnerships for a sustainable, just and inclusive future eveline wandl-vogt technologies & tools trends & mindset knowledge & skills values & purpose humanity centered SDGs as value drivers- for city making knowledge4 development the eveline.wandl-vogt@oeaw.ac.at 09_2022 @caissarl @arselectronica #k4h+ @oeaw #explorations4u templates by adioma.com open innovation research infrastructure © ewv 2017 | with e.g. ars electronica, km-a, CERN ideasquare, metalab (at) harvard & topothek.AT AERI k4h+ exploration space design thinking participation experimentation agile organisations knowledge 4 development partnership aiming to create, drive and implement the agenda knoweldge 4 develpoment and in doing so contribute to agen- da 2030 and the sustainable development goals SDGs envisioning Vienna 2030 toolkit We developed a toolkit to connect the SDGs with perceptions about digital futures. For this we prepared a three steps interaction around ques- tions of sustainability and prospective visions for 2030 in the context of a socially inclusive city of Vienna, with a participative methodology between a qualitative and quantitative ap- proach. The toolkit has been testted in various learning settings and is available online free of charge. open science sharing economy breakthrough technologies & humanitarian values ThePort humanitarian hackathon ThePort @ CERN „We combine creative minds from CERN and non- profit organisations in interdicsiplinary teams to work on humanitarian technology related benefits for society“ [ThePort Association / Website] selforganization artistic methods in the classroom & SDGs Classroom Multi-sensory Practices For Collaborative Liveable Worlds We created a reader to foster sustainable under- standing and collaborative parctices from a class- room perspective, as one of our results of being awarded the Citizen Science Award 2022. We offer easy to go scenarios for 10 up to date sonic me- thodologies against a background of biocultural diversity, as outlined in our awarded project „Our Planetary Garden“. Starting from the challenge of obesity, with USPs cultural knowledge, experience and values as well as brain stimulation and observation (EEG) we designed a meaningful APP with innovative learning features against the background of AI. Emergent Topographies of Vienna & Artificial Flora (at) Spatial AI Ecologies WeQ


The Hard Part A data set could meet the 15 FAIR principles but still not satisfy data users. For users, findable and accessible are about interfaces but FAIR is not about interfaces. FAIR principles enable interfaces, but they do not design them. An organic or use-case based approach works best for designing useful data systems. User advisory groups work best when they advise on specific discovery or access issues around real science problems. Interdisciplinary use cases are less well developed and more challenging. They are often either very generic or extremely bespoke making them particularly challenging to address in a broadly useful way. Users don’t always know what they want until they see it. They are not always aware of what new technologies can do. Large Language Models and cloud- services show promise in making (big) data more discoverable and accessible, and potentially interoperable. Multiple NASA repositories are doing work in these areas, but they need to coordinate their efforts more to develop useful services that address those challenging interdisciplinary use cases. Metadata remain at the heart of FAIR and the services required by users. In interdisciplinary and interoperable use cases the relationships between concepts becomes critical. Verbs may be more important than nouns in information modelling and representation. FAIR Data at Scale to Enable Open Science Mark Parsons (0000-0002-7723-0950), Robert Downs (0000-0002-8595-5134), Samrawit Gebre (0000-0002-8963-4856), Lan Jian (0000-0002-6849-5527), Julie Imig (0000-0003-2025-3585), and Anne Raugh (0000-0002-8300-9443). AGU 2023 Fall Meeting, San Francisco, CA, USA, 2023-12-14. IN41B-0586. Making data FAIR is easy. Making users happy is hard. Making new, interdisciplinary users happy is really hard. Background “Data can be FAIR [Findable, Accessible, Interoperable, Reusable]1 or Open, both or neither. The greatest potential reuse comes when data are both FAIR and Open. So the goal is to align and harmonise FAIR and Open data policy.” Quote and figure from the mighty Sarah Jones 0000-0002-5094-7126 Through a survey, a couple webinars, and a 150-person workshop in September in Boulder CO, the NASA Science Mission Directorate (SMD) has been working to define what the FAIR Principles mean in alignment with its new Science Information Policy (SPD-41a).2 The “Easy” Part OK, maybe its not easy but FAIR is increasingly well- defined. NASA repositories were able to agree pretty quickly on what the 15 principles meant. Standards and specifications already exist that help meet the FAIR principles, they just need to be more consistently applied at an SMD level. Work is needed but it is defined, achievable work. A SMD Working Group is developing guidance for repositories. It will be easier for new data as we build processes that allow data to be “born FAIR”. Interoperable is the hardest part of FAIR, because its about semantics and relationships. It needs to start at the discipline level while also considering the broader level. See developing work in Earth Science by Ge Peng et al. at poster IN41B-0579. Please comment on our initial guidance “Worst is solving a general problem. Best to solve a specific problem and use that to fix the next specific problem.” - a NASA data user “There is no nominal example of what a repository does.” - a NASA repository manager FAIR Data Open Data increasing degrees increasing degrees The 15 FAIR principles are geared toward machine actionability, but the human users ultimately define what is FAIR in practice. FAIR logo by SangyaPundir. Background people and gear figure created by Ifanicon from Noun Project “Hard” “Easy” Next Steps • Complete a high-level, SMD-wide guidance document on “How to be FAIR”. • Build from that guidance to develop a SMD-wide, base-level, assessable FAIRness metric. • Collaborations are developing around cloud-services, LLMs, and metadata harmonization. • Next year’s workshop will focus on user engagement and a m


Solar as a Solution Solar Photovoltaic panels (PV) are a way to convert solar radiation into usable DC electricity. Solar radiation is radiant energy emitted by the sun. Photons are tiny packets of energy that travel millions of miles to earth and eventually collide with our solar PV modules. When they strike the PV cells their energy excites the electrons, creating usable DC electricity. The Energy Research Team is applying these concepts at DCMS by installing a 3.6 kilowatt solar PV array. Once the panels were installed on the roof, they were connected to the AC units. While the AC units were already the highest efficiency available they still tripled DCMS’s energy usage. The main goals of our project were to make DCMS more energy efficient by offsetting the grid usage and to also, demonstrate living sustainability can easily become common. SMALL ISLAND RESILIENCY STUDY: Energy Matters at the Local Level Deep Creek, Eleuthera, The Bahamas Ruby Bagwyn, Matthew Brown, Cecilia Compton, Martine Lavelle, Everett Moore, Cecelia Pilgrim Advisors: Bryan Carroll & Sarah Emrich Conclusion: The Bahamas is too reliable on diesel. Small Island Developing States still exclude alternative forms of energy. The goal is to set out to demonstrate that these alternatives are not out of reach for SIDs. To recap what the Energy Research Team did at the Deep Creek Middle School is they performed an energy audit to educate students and staff the reality of real time energy use in their classrooms. Then a baseline checklist was created for which the school and other buildings can measure energy conservation and sustainability. Lastly they installed air conditioning paired with a 3 kW solar array to cool the classrooms and do so without burning fossil fuels. Renewable energy is a symbol of sustainability, one of the three defining pillars of The Island School. Using what students have learned about sustainability we want to capitalize on the semester’s work, to catalyze the community and the country. Many small changes lead to one massive change. If all SIDS can see that solar is viable option for diesel, if even on a small-scale, this message can be spread wide. The community is proud that both The Island School and DCMS have taken steps towards a more sustainable future, and in doing so, demonstrating to the students and community members there is another way forward by thinking globally and acting locally. Energy Investigation The Energy Research Team began the improvement of DCMS’s sustainability by getting a better picture of their energy usage before and after the air conditioning was installed (AC). First, the team analyzed historical energy bills from 2016. From analyzing this, it was concluded that each month, Room 1, 2 and 3 used approximately 350 kWh, 50 kWh and 125 kWh respectively, as can be seen on Graph 1. The team then started collaborating with the DCMS Grade 8 students to collect data for after the AC was installed. This allowed the students to get directly involved with the project and get a first hand look at the energy they’re consuming as a school. The students collected data from their school’s energy meter every day, which allowed the team to have a daily record of energy usage. After analyzing this data, it was concluded that after the AC was installed there was a drastic increase in energy usage, Room 1, 2 and 3 usage to approximately 40kWh, 25 kWh and 23 kWh respectively, as can be seen on Graph 2. Graph 1 shows the historical electrical bills compared to a bill post AC. This increase in energy usage was expected, due to the high energy demand of the air condition systems. However, the solar panel array that the team installed is designed specifically to offset this usage. Energy in the Bahamas The Bahamas is near totally reliant on imported foreign diesel (Bahamas National Energy Policy). Diesel is refined from crude oil, which is a naturally occurring mineral oil that can be refined into various fuels and other petroleum-


AerosolsopticalpropertiesinTitan’s detachedhazelayerbeforetheequinox B. Seignovert1, P. Rannou1, P. Lavvas1, T. Cours1 and R.A. West2,1 1GSMA, UMR CNRS 6089, Université de Reims Champagne-Ardenne, France, 2JPL, California Institute of Technology, Pasadena, California, USA Contact: univ-reims@seignovert.fr Introduction First observed in the 80’s by Voyager 1 and 2 ﬂybys [1, 2], Titan’s atmosphere presents a complex stratiﬁed succession of haze layers above the main haze. One of these layers, the Detached Haze Layer (DHL), presented a large extent at 350 km and could be seen all along the limb surrounding Titan between 90◦S up to 45◦N. Voyager 2 radial intensity scans at high phase angles [3] reveal an important depletion of the aerosol particle density below this layer. The arrivial of the Cassini spacecraft in the Saturnian System in 2004, was a unique opportunity to investigate the persistence of the DHL over time [4]. The Imaging Science Subsystem (ISS) instrument on board performs a continuous survey of the Titan’s atmosphere. In 2011, West et al. [5] conﬁrm the persistence in time of the DHL at the equator at 500 km before the equinox followed by a collapse at 380 km in 2008. Recent observations conﬁrmed its disappearance in 2012 and a new emergence is reported in early 2016 [6]. This seasonal cycle, predicted by previous Global Circulation Models (GCM) [7, 8, 9], tended to be conﬁrmed by theses recent observations. In this study our purpose is to characterize the physical properties of the DHL and its latitudinal variability during the 2005-2007 period. Observations To determine the properties of the aerosols in the DHL, we made a survey over the ISS images taken with the Nar- row Angle Camera (NAC) before its collapse in 2008 [5]. We limit our analysis on the CL1-UV3 ﬁlter (λ=338 nm) where only the aerosols scatter and to minimize the mul- tiple scattering. Table 1: List of ISS NAC images used in CL1-UV3 ﬁlter ISS ID Date Phase Pix. Scale N1506288442 2005/09/24 145◦ 5.5 km N1506300441 2005/09/25 151◦ 5.5 km N1509304398 2005/10/29 155◦ 6.1 km N1521213736 2006/03/16 68◦ 7.3 km N1525327324 2006/05/03 147◦ 7.2 km N1540314950 2006/10/23 120◦ 5.7 km N1546223487 2006/12/31 66◦ 7.4 km N1551888681 2007/03/06 143◦ 7.9 km N1557908615 2007/05/15 25◦ 7.8 km N1557919415 2007/05/15 25◦ 8.2 km N1559282756 2007/05/31 20◦ 7.7 km N1562037403 2007/07/02 14◦ 7.8 km N1567440117 2007/09/02 20◦ 7.9 km N1570185840 2007/10/04 27◦ 7.3 km N1571476343 2007/10/19 80◦ 8.2 km Figure 1: (left) Overexposed and contrasted ISS NAC N1551888681. (right) Same image inverted with geo-reference grid, sub-spacecraft point (SC), Spice Kernels predicted center (SK) and photometric equator (PE). Vertical proﬁle, altitude and light curve For each image the limb proﬁles are extracted by 5◦bins in latitude on the illuminated side of Titan and smooth with a moving average. The local maximum I/F corresponding to the DHL is located in altitude and intensity. The DHL presents a very high stability in altitude (500±8 km) for all latitude lower than 45◦N. The I/F light curve content information about the shape of the aerosols. 400 420 440 460 480 500 520 540 0.005 0.02 0.03 0.05 0.01 Altitude (km) I/F () ISS data Moving average proﬁle Average box DHL peak Oct Jan 2006 Apr Jul Oct Jan 2007 Apr Jul Oct 90 ◦S 60 ◦S 30 ◦S 0 ◦ 30 ◦N 60 ◦N 450 465 465 480 495 495 495 495 495 510 510 510 510 450 460 470 480 490 500 510 DHL altitude (km) 0.001 0.01 0◦ 20◦ 40◦ 60◦ 80◦ 100◦ 120◦ 140◦ 160◦ 180◦ I/F () Phase angle () DHL peak Figure 2: (left) N1551888681 vertical proﬁle between 0 to 5◦N. (middle) Altitude of the DHL as function of time and latitude. (right) Light curve on the local maximum I/F between 0 and 5◦N. Atmospheric and scattering model We consider that above the DHL, the atmosphere of Titan is optically thin and the incoming ﬂux from the Sun is not signiﬁcantly attenuated down to the DHL, then the output ﬂux can be simply described as: I/F = ω · P(θ) 4 · 1 −e−τext with τext


aRK Z arbeitsKreis RömischeKaiserZeit römische kochkunst Die Küche der römischen Zeit war sehr vielfältig und es gab große Unterschiede im Ernährungsverhalten. Die gesellschaftlichen Eliten legten Wert auf teure Weine und aufwändig zubereitete Speisen, die breiteren Bevölkerungsschichten waren hingegen auf einfachere Kost angewiesen. Neben zahlreichen Gerichten zum Backen, Braten und Kochen erfreuten sich Süßspeisen großer Beliebtheit. In fenicoptero Fenicopterum eliberas ... Adicies in mortarium piper, cuminum, coriandrum, laseris radicem, mentam, rutam, fricabis, suffundis acetum, adicies caryotam ... et inferes. Idem facies et in psittaco. Für Flamingo Rupfe den Flamingo ... Gib in einen Mörser Pfeffer, Kümmel, Koriander, Laserwurzel, Minze und Raute und zermahle es, gieße Essig hinzu, gib Datteln hinein ... und serviere. Dasselbe mache auch mit Papagei. Apicius, de re coquinaria (Über die Kochkunst) 6, 6, 1 J. André, Essen und Trinken im alten Rom (Stuttgart 2013) J. Meurers-Balke – T. Kaszab-Olschewski (Hrsg.), Grenzenlose Gaumenfreuden. Römische Küche in einer germanischen Provinz (Mainz 2010) R. Maier (Hrsg.), Apicius. De re coquinaria. Über die Kochkunst. Lateinisch-Deutsch. Übersetzung und Kommentar (Stuttgart 1991) vielfalt flamingo literaturhinweise Text und Layout: D. Hagmann – A. Langendorf – R. Weitlaner 2014 Abbildung: Obstarrangement mit gläserner Schale, Topf und Amphora Casa di Julia Felix, Pompeii 2. Pompeianischer Stil © Zenodot Verlagsgesellschaft mbH Druck: A. Sulzgruber, Institut für Klassische Archäologie, Universität Wien Plakat_1.indd 1 19.05.2014 14:22:22


CRIRES+ at the Very Large Telescope Oered from ESO Period 108, starting 2021-10-01 with the following limitations: @alexislavail alexis.lavail@physics.uu.se Spectral grasp ~ 0.3 μm* *varies with wavelength Collecting power ⌀ 8 metres at VLT UT3 Melipal Expected RV precision 3 m/s Calibration sources UNe lamp Gas cells Fabry-Perot étalon Wavelength coverage Y J H K L M 0.95 μm 5.2 μm spectroscopy R >80000* (0.2" slit-width) R ~50000 (0.4" slit-width) Resolving power *nominally R ~100,000 for the 0.2" slit R>~80,000 was measured at commissioning. We investigate and try to mitigate this. only spectroscopy (no spectropolarimetry) In AO: natural guide star = target = guiding star no extended targets (only compact sources) No AO: target = guiding star The Call for Proposals is out! https://www.eso.org/sci/observing/phase1/p108/ Alexis Lavail1,2 & the CRIRES+ consortium 1. Uppsala University 2. The Swedish Collegium for Advanced Study More info at https://www.eso.org/sci/facilities/paranal/instruments/crires.html The proposal submission deadline is 12:00 CET on 2021-03-25 Online poster at: http://aalex.is/posters/cs20p5


Mining in the Green and Digital Era European 4 EU demo cases 1 replication demo in South Africa 10 different raw materials including 4 CRMs 10 mines around Europe TWITTER: @MastermineEU LINKEDIN: MASTERMINE Project WEBSITE: www.mastermine-project.eu E-MAIL: mastermine.euproject@gmail.com


TASKS RELATIONS ATRIUM WP7 end-user researchers workshops and trainings service and providers skills initiatives gaps usability training materials require connectedTo attend acquire increase teachAt identify improve use identify identify identify identify articulate coordinate contact KEY TERMS NETWORKING WORKSHOPS WP7 GOALS T7.3 The ATRIUM Curriculum General assessment of the skills require d for the active use of services provided by ATRIUM RIs (atten tion to the digital gap) Set of recommendations on topics and modalitie s of training materia ls available and to be developed as part of the ATRIUM Curriculum (T7.3) Assessment methods: desk research (build on previous work) surveys workshops feedback from the forums/training (T7.2) T7.2.1 The ATRIUM Researcher Forum: fostering two-way communication understanding researchers’ needs involving service improvement facilitating the use/reuse of services T7.2.2 The ATRIUM Mutual Learning Exercises (MLE) for providers: addressing (meta)data interoperability facing quality challenges sharing knowledge discussing best practices FitSM training Developing an integrated set of courses (hosted , maintained, and sustain ed on DARIAH-Campus) Embedding the description of ATRIUM services into the pedagogical narrativ e focused on cross-disciplinary digit al methods, wide-ranging competenc ies (FAIR, OS) & disciplinary-spec ific training requirements Maximising the potential of ATRIUM datasets , workflows, demonstrato rs & services to be used in educational settings Creating a robust framework for open peer review assessment o f different research outputs (da ta publications, training materia ls, software, exhibitions, interac tive visualisations, etc.) Contributing to maximise the quality and impact of Arts an d Humanities research in Euro pe in the context of initiatives s uch as CoARA Incentivising Arts and Humanities users t o follow the principl es of Open Science FOSTERING CROSS-DISCIPLINARY RESEARCH THROUGH TRAINING AND OPEN SCIENCE PROJECT GOAL Authors: Cezary Rosiński cezary.rosinski@ibl.waw.pl Tomasz Umerle tomasz.umerle@ibl.waw.pl T7.1 The ATRIUM Skillset Assessment SKILLS AND GAPS STRUCTURED LEARNING MAXIMIZE IMPACT Facilitating workshops and training sessions t o connect end-us er researchers with serv ice and data providers Transforming training materials into onlin e course curricula a nd organize formal and informal sessions Improving research outcomes by implementing a peer-revie w assessment framework for t he humanities and expand ing impact through exte rnal engagement Assessing skills essential for the arts an d humanities communi ty and identifying gaps in transfer T7.2 The ATRIUM Bridge T7.4 The ATRIUM Peer Review Framework ATRIUM's project goal is to advance frontier knowledge and facilitate access to leading research infrastructures in arts and humanitie s (DARIAH), archaeology (ARIADNE), languages (CLARIN), and scholar ly communication (OPERAS). The Work Package 7 (WP7) of the proj ect focuses on promoting interdisciplinary research through training and open science initiatives.


Handreichung zu Video-Uploads auf Video-Plattformen Werden personenbezogene Daten verarbeitet? Sind die Verantwortlichen für die Datenverarbeitung bekannt und klar deﬁniert? Welche Verarbeitungsgrundlage wurde gewählt? Sind die Vortragenden DSGVO- konform informiert? Sind die Rechte der Vortragenden vorgesehen bzw. berücksichtigt? Ist eine automatisierte Analyse des Videos mittels Machine Learning geplant? Beﬁndet sich die Video-Plattform mit Sitz oder Speicherorten außerhalb der Europäischen Union? Personenbezogene Daten sind Daten mit Informationen über eine Person, über die eine Person auch identiﬁziert werden kann. Beispielsweise Stimme, Aussehen, Körperbewegungen/Gangart, Schreibstil, etc. Jede Art von Video enthält, sofern Personen darauf zu sehen oder zu hören sind, personenbezogene Daten. Je mehr Daten von einer Person zu sehen sind, desto leichter ist sie identiﬁzierbar. Ist dagegen nur Text (z.B. Vortragsfolien) zu sehen, ist das Video wahrscheinlich frei von personenbezogenen Daten. Das Datenschutzrecht ist auf das Video nicht anwendbar. Die Prüfung endet hier. Ja, mein Video enthält personenbezogene Daten. Nein. Verantwortliche:r – Verantwortliche:r Beide Beteiligten bestimmen teilweise oder vollständig gemeinsam über die Zwecke und Mittel der Datenverarbeitung. Verantwortliche:r – Auftragsverarbeiter:in Die verantwortliche Stelle entscheidet allein darüber, was und wie die auftragsverarbeitende Stelle verarbeitet. Wird eine Video-Plattform gewählt, bei der eine Person/ Institution keine alleinige Kontrolle über Mittel und Zwecke der Datenverarbeitung hat, ist von dieser Konstellation auszugehen. Sie ist der/dem Redner:in klar und transparent mitzuteilen. Hier liegt in der Regel ein Vertrag zwischen den Beteiligten vor, der die Aufgabe (z.B. Produktion eines Videos) klar benennt und begrenzt. Die Auftragsverarbeitung erfüllt also nur fremde, keine eigenen Zwecke. Ja. Ja. Ja. Ja. Nein. Einwilligung, Art. 6 Abs. 1 lit. a DSGVO wissentliche und willentliche Zustimmung in die Datenverarbeitung Vertrag, Art. 6 Abs. 1 lit. b DSGVO beidseitig ausgehandelte Vereinbarung mit Leistung und Gegenleistung Berechtigtes Interesse, Art. 6 Abs. 1 lit. f DSGVO einseitige Feststellung eines überwiegenden Interesses an der Datenverarbeitung, die unbedingt notwendig ist oder oder Die Redner:in willigt ein, dass das Video auf einem Video- Portal hochgeladen wird und somit der Öﬀentlichkeit zur Verfügung steht. Der Vortrag ist Teil der Tätigkeit der Redner:in, beispielsweise als Professor:in oder Dozent:in. Es ist im eigenen Interesse des Instituts, das Video zu veröﬀentlichen. Beispielsweise handelt es sich um Videos zur eigenen wissenschaftlichen Tätigkeit der Mitarbeiter:innen. Der Upload bzw. die Verwendung des Videos für den geplanten Zweck verstößt gegen das Datenschutzrecht. Ich habe keine rechtliche Grundlage für die Verarbeitung, die ich nennen kann. Erhebung bei betroﬀener Person Art. 13 DSGVO ✓ Name und Kontaktdaten der verantwortlichen Stelle, ggf. Vertretung ✓ ggf. Kontaktdaten des/der Datenschutzbeauftragten ✓ Zweck(e) und Rechtsgrundlage(n) der Datenverarbeitung ➞ Art. 6, 9 DSGVO ✓ bei "berechtigtem Interesse": genaue Angabe dieser Interessen der verantwortlichen Stelle oder Dritter ✓ wenn vorhanden: Empfänger/Kategorien von Empfängern der personenbezogenen Daten ✓ wenn vorhanden: Absicht, Daten in ein Drittland (z.B. USA) zu übermitteln; eingeschlossen der Hinweis auf ein Vorliegen/ Fehlen eines Angemessenheitsbeschlusses ✓ sofern geplant: Speicherdauer ✓ Hinweise auf Betroﬀenenrechte: Recht aus Auskunft; Recht auf Berichtigung/Löschung; Einschränkung der Verarbeitung; Widerspruchsrecht; Recht auf Datenübertragbarkeit (sog. Interoperabilität) ✓ bei Einwilligung als Rechtsgrundlage: Hinweis auf Widerrufbarkeit der Einwilligung (Ob und Wie) ✓ Hinweis auf Beschwerderecht bei (zuständiger) Aufsichtsbehörde ✓ bei gesetzlicher Verpﬂichtung zur Verarbeitung: Angabe der gesetzlichen Grundlage; auch Information über Konsequenzen e