fairdataihub/poster-sentry-training-data huggingface dataset:
HI grouping overlaid on DES RGB image A serendipitous MeerKAT discovery of an HI-rich grouping of galaxies with megaparsec-scale ﬁlamentary-like structure Overview ●Probing HI in a group environment ●Serendipitous MeerKAT HI grouping discovery ●In the foreground of Abell 3365 at z~0.04 MeerKAT data ●MeerKAT L-band observations (as part of MeerKAT Galaxy Cluster Legacy Survey) ●Combination of 2 ⨉ ~10 hour observations ●4k mode, ~209 kHz channel width (46 km s-1 at z~0.04) ●~52 µJy/beam channel RMS at a Briggs robust weighting of 2 Ancillary data ●DES, an optical imaging survey carried out by the Dark Energy Camera (DECam), we use g, r, i bands for optical counterpart identiﬁcation ●WISE, mid-infrared data used in calculation of stellar mass and star formation rates, where possible Name: Graham Lawrie Email: grahamdavidlawrie@gmail.com Prof. Roger Deane1,2 Prof. Romeel Davé3,4 1. University of the Witwatersrand 2. University of Pretoria 3. University of Edinburgh 4. University of the Western Cape Source-ﬁnding ●Visual source-ﬁnding within the HI data cube using CARTA ●Semi-automated source-ﬁnding with SoFiA 2, using a S+C threshold of 3.4 ●Crossmatching is done using the visual and SoFiA generated catalogues, together with false positive removal with the help of DES imaging Grouping ●We take a simplistic friends of friends approach to qualitatively associate galaxies ●Linking parameters of 1.3 Mpc spatial separation and 350 km/s in velocity separation Conclusion ●We made a serendipitous discovery of an HI-rich galaxy group with numerous galaxy-galaxy interactions shown by HI bridges and tails ●MeerKAT provides us with a powerful tool for probing the environmental effects on cold gas evolution ●MeerKAT appears to be particularly successful at detecting groups of galaxies at z~0.04, potentially providing astronomers with a useful environment in which to probe galaxy evolution Comparison to hydrodynamical simulation ●We compare the MeerKAT group detection to predictions derived from cutting edge cosmological hydrodynamical simulation, SIMBA Davé et. al. 2019 ●FoF is run on the ﬂagship SIMBA box with full physics to ﬁnd 31 analogous HI galaxy groups ●By comparison of the volume a MeerKAT pointing will probe out to z~0.1 we ﬁnd the likeliness of a HI group detection to be 1 detection per ~15 pointings ●Future work includes construction of mock HI galaxies with MARTINI for individual galaxy comparison, see the following example: Acknowledgements: SARAO for data and funding, ILIFU for access to HPC for data reduction, CARTA for data visualisation, SoFiA 2 for source-ﬁnding, SoFiA Image Pipeline for cutout generation, MARTINI for mock data generation, Wits-UK foundation for funding a 6 week research visit to Edinburgh ● HI total intensity HI velocity ﬁeld DES g-band
1. RATIONALE Keep data safe and unaltered for 20 years in a closed off-site storage system Retain original data for audit in case questions about the integrity of a research article are raised Increase compliance with Crick’s core funders’ data management requirements Improving the integrity of research data: building an institutional data archive Minna Ventsel, Research Integrity & Data Specialist The Francis Crick Institute minna.ventsel@crick.ac.uk 3. DATA ARCHIVING FLOW • Crick’s Figshare repository – option to select and upload data files to Figshare at the same time as archiving to increase openness • Metadata fields filled out automatically by the system, drawing details from an uploaded manuscript – to make archiving as easy as possible 2. THE SOLUTION Ticket creation •Researcher submits their manuscript to a journal •Researcher submits a ticket to inform the Library & Information Services team about their manuscript submission •Once ticket submitted, the Data Integrity team creates an archiving folder in researcher’s lab storage space Data •Researcher adds raw data associated with the manuscript to the archiving folder and informs the RI team when completed •The Data Integrity team conducts checks on data/metadata Archiving •Submission approved by the RI team and sent to the archiving team •Data encrypted and compressed •Data is archived in tape storage off-site and cannot be altered – data can now only be retrieved by request Creation of a team to oversee the project and discuss the needs of the archive System design & architecture team come up with the most feasible technology solution IT team start building the system. Preliminary test with one lab at the Crick Wider testing with 2-3 labs Identification of any issues and feedback from users Final changes before official launch First image by pch.vector on Freepik Second image by storyset on Freepik 4. FUTURE INTEGRATION IDEAS
Manufacturing Capability of Micro-Transfer Printing X-Celeprint Inc., Research Triangle Park, NC, www.x-celeprint.com, dgomez@x-celeprint.com David Gomez, Tanya Moore, Matthew A. Meitl, Salvatore Bonafede, Andrew Pearson, Brook Raymond, Tiffany Weeks, Kevin Oswalt, Erich Radauscher, David Kneeburg, Julia Roe, Alin Fecioru, Steven Kelleher, Raja Fazan Gul, Alexandre Ferrell, Antonio Jose Trindade and Christopher A. Bower
PILOT 4 Durable fastening solutions production NON-DESTRUCTIVE INSPECTION SERVICES FOR DIGITALLY ENHANCED ZERO WASTE MANUFACTURING OBJECTIVE Improve the manufacturing process of high-quality large metric fasteners for the wind or aerospace industry to obtain a proper microstructure and hardness by means of non-destructive testing, increasing productivity and reducing the quantity of scraps. PARTNERS INVOLVED CONTEXT Manufacturing process of the fasteners Problems & needs Digital Twin models EXPECTED SCENARIO THE ZDZW PROJECT HAS RECEIVED FUNDING FROM THE EUROPEAN UNION’S HORIZON EUROPE PROGRAMME UNDER GRANT AGREEMENT NO 101057404. VIEWS AND OPINIONS EXPRESSED ARE HOWEVER THOSE OF THE AUTHOR(S) ONLY AND DO NOT NECESSARLY REFLECT THOSE OF THE EUROPEAN UNION. NEITHER THE EUROPEAN UNION NOR THE GRANTING AUTHORITY CAN BE HELD RESPONSIBLE FOR THEM EXPECTED IMPACT ON KPIs END-USER High-performance demanding sectors such as aerospace, energy and biomaterials require good fatigue and mechanical resistance. Induction heat treatment is the main manufacturing process of the fasteners that affect their microstructure and hardness. The objective is to predict the resulting microstructure and the mechanical hardness properties after the different heat treatments carried out, adjusting the necessary parameters to reduce the rejection rate.0 Heading Machine Induction heating machine for heading Thread rolling machine Induction Hardening Tempering furnace AE Insp. Equip. EMAT Ultrasonic Insp. Equip. Digital Twin ERP BIG DATA AI AE Integrity tool AI Hardeness and Microestructure Digital Twin AI EMAT Integrity tool Digital twin ↓ >2h set-up time Reduction of material waste 7.000kg/ year Part energy consumption ↓25% energy consumption Productivity ↑20 units/h Correlate induction processing parameters with the fasteners’ heat treatment, phase diagrams and final products NON- DESTRUCTIVE INSPECTION TECHNIQUES Monitoring the induction hardening process in real-time, acting as a diagnostic method for in- situ monitoring allowing traceability and ↓ scrap rates. Acoustic Emission (AE) inspection to ↓ uncertainty and variability of the production Digital Twin and AI to define the phase formation after hardening and tempering thermal processing to ↑ quality and ↑ consistent final products. 1. 2. 3. ZDZW INTEGRITY INSPECTION SUITE ZDZW solutions No real-time process control  fastener quality control is carried out at the end of the production process Considerable number of reprocessing operations Elevated volume of scraped material No in-situ inspection of microstructure and defects No feedback from the manufacturing processes
Non-thermal plasma treatment of landfill leachate for detoxification of hazardous pollutants Visit the PROMISCES website for more information: https://promisces.eu/ This work is supported by the PROMISCES (Preventing Recalcitrant Organic Mobile Industrial chemicalS for Circular Economy in the soil- sediment-water System) project which has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No 101036449. The equipment used in the investigation is from the Clean&Circle Center of Competence, Grant № BG05M2OP001-1.002-0019: "Clean Technologies for Sustainable Environment - Waters, Waste, Energy for a Circular Economy", financed by the Science and Education for Smart Growth Operational Program (2014-2020) and co-financed by the EU through the ESIF. P. Marinova1,3*, T. Bogdanov2,3, E. Benova3, M. Kirilova3,4, Y. Todorova3,4, I. Yotinov3,4, I. Schneider3,4, Y. Topalova3,4 1 Faculty of Forest Industry, University of Forestry, 1756 Sofia, Bulgaria 2 Medical University of Sofia, Faculty of Medicine, 1431 Sofia, Bulgaria 3 Clean & Circle Center of Competence, Sofia University, 1164 Sofia, Bulgaria 4 Sofia University “St. Kliment Ohridski”, Faculty of Biology, 1164 Sofia, Bulgaria (∗) plamena_dragozova@ltu.bg Cold atmospheric plasma as an alternative method for cleaner Environment Can the additional contaminants affect the degradation of PFAS? More information on poster P2-T10-62 In the treatment of wastewater and sludge with a high content of various pollutants, it is important how the additional contaminants affect the degradation of PFAS. The competitive reactions to the PFAS defluorination occurring during the treatment need to be investigated. Determining the dependence between the concentrations of contaminants as NOx and the suppression in degradation of persuasive compounds will help to increase the degradation ratio and to understand the mechanisms of PFAS degradation. Treatment with microwave plasma torch at continuous flow mode Interaction mechanism: PFAS concentrations in model water and leachate contaminated with Perfluorooctanoic acid (PFOA) Model water with PFAS PFAS C (ug/L) Perfluorooctanoic acid PFOA 2 Perfluoropentanoic Acid PFPeA 2 Perfluorodecanoic acid PFDA 2 Perfluorohexanoic acid PFHxA 2 Perfluorobutanoic acid PFBA 2 RONS in plasma treated model water contaminated with PFAS Treatment with microwave plasma torch at continuous batch mode Treatment with Beta at two configurations: underwater mode surface mode Wave power of 100 W, Argon flow 3 l/m, flow rate of 1.127 ml/min, batch treatment time 2 min Plasma treatment of samples distilled water with PFOA PFOA and RONS concentrations landfill leachate distilled water NO2 NO3 H2O2 Wave power of 30 W (underwater) and 25 W (surface), Argon flow 5 l/m, treatment time 10 min Beta device
Joseph Naar1, François Forget1, Ehouarn Millour1 and Antoine Bierjon1 References: [1] Naar et al., (2021) 10.5194/epsc2021-559 [2] Madeleine, JB., et al. (2009), 10.1016/j.icarus.2009.04.037 [3] Madeleine, JB., et al. (2014), 10.1002/2014GL059861 1Laboratoire de Météorologie Dynamique, UMR CNRS 8539, Institut Pierre-Simon Laplace, Sorbonne Universités, UPMC Univ Paris 06, 4 place Jussieu, 75005, Paris, France. MARTIAN WATER ICE LATITUDE DEPENDENT MANTLE PREDICTED BY IMPROVED CLIMATE MODEL Converging geomorphological evidences point to the deposition of a “Latitude-Dependent Mantle” (LDM) of water ice on Mars up to ~30° latitude in both hemispheres, of age consistent with the latest obliquity rise to 35°. GCM studies can’t explain how ice would accumulate outside the polar regions assuming a permanent reservoir at the north pole like today. We present our simulations at 35° obliquity with the latest improvements of the Mars PCM, with a focus on albedo and thermal inertia. Guys pls give postdoc Introduction Mars PCM settings • 0.08 ecc., Lp=270° mild northern summer • TI feedback with ice accumulation [2] • Radiatively active H2O clouds (RACs) with improved nucleation scheme [1] • Latent heat of ground water ice sublimation /condensation [1] • Sentivity of water frost albedo : α= 0.33 ; α = 0.5 ; α = 0.7 Atmospheric humidity limited by latent heat of ground ice • Water vapor content is 10 times higher than present [2], or even 100 times higher with RACs [3] • Latent heat of ground ice reduces the NPC sublimation and limits atmospheric water vapor Frost deposition outside the polar regions • CO2 albedo parametrization • Improved H2O albedo parametrization : snowfall • Different orbital forcing • Sensitivity to the dust cycle • Planetary Evolution Model (PEM) : evolution of subsurface ice table and thermal inertia • PEM : Microclimate of slopes within PCM cells Future developments Contact me (please) : joseph.naar@lmd.ipsl.fr • NPC is ~20K warmer than present-day Mars • Increased albedo of frost affects the CO2 cycle and acts as a cold trap • Sublimation is maximal when α = 0.7 because of complex retroactions with RACs α= 0.33 : • No ice accumulation outside the NPC Latent heat cooling isn’t sufficient to prevent summertime sublimation α= 0.5 : • Ice accumulates outside the NPC at high latitudes in both hemispheres (not shown) α= 0.7 : • Multi-annual frost deposition down to ~60° latitude North • Thermal inertia feedback enhances ice accumulation Thermal inertia (TI) : • Set to 800 J.m−2.K−1. s− 1/2 in the PCM (lower limit for ice) • TI feedback alone doesn’t allow ice accumulation outside the Northern Polar Cap Main results : • First GCM simulations to compute RACs and latent heat of ground ice at 35° obliquity : « only » ten times more humid than present • Using the NPC as an initial ice reservoir, ice can accumulate outside the polar region if summer sublimation is dampened, by higher frost albedo (e.g. due to snowfall) or increased thermal inertia (pore filling or consolidated subsurface ice) Excursion to 35° obliquity increases insolation and sublimation of the NPC: The Northern Polar Cap (NPC) I would be glad to work with you !
EFSA Partnering Grants- ListeriaPredict: A case study in capacity building at EU level in predictive microbiology F. Butler, U. Gonzales Barron, V. Cadez, L.Iannetti, A. Valero Diaz, G. Redmond, K. Hunt The objective of EFSA Partnering Grants is to enhance capacity across Europe in risk assessment. The focus of ListeriaPredict is applying predictive microbiology techniques to shelf-life studies on Listeria monocytogenes in ready-to-eat foods. Listeria monocytogenes continues to be a major hazard of concern in many ready to eat foods. Predictive microbiology techniques have a critical role in interpretating experimental challenge test data (Fig 1) Introduction • Four partners across Europe form the ListeriaPredict Project - UCD Ireland, IPB Portugal, IZSAM Italy, UCO Spain Methodology The Partnership will train key personnel in recent predictive microbiology advances including Dynamic modelling and Global modelling through focussed workshops and webinar events. Results To date a number of workshops and webinars have taken place across Europe, including: • Workshop - Basic Bioinformatics Skills Relating to Using Genotypic /Phenotypic techniques for Risk Assessment, Dublin November 2021 • Webinar – Case studies on food safety, Dublin May 2022 • Workshop - Modern Predictive Microbiology Analysis in R (PredMicro 2022), Braganza, June 2022 Conclusions Acknowledgments This project directly aligns with the specific objectives of EFSA to promote the building of risk assessment capacity within university and research agencies across Europe. This project ‘showcases’ how small focussed actions can deliver significant impact contributing to the overall goals and objectives of EFSA. The project demonstrates how building and sharing of capacity at organisational level can be achieved through the strategic choice of partners across Europethat each have individual expertise within key elements of predictive microbiology. Further information ListeriaPredict would like to acknowledge the financial assistance of EFSA, AGREEMENT NUMBER – GP/EFSA/ENCO/2020/03 Partnering grants – GA 3, Application of novel predictive microbiology techniques to shelf-life studies on Listeria monocytogenes in ready-to-eat foods Growth curves for L. monocytogenes stored at the three temperatures ( 4.5 oC, * 7.8 oC, 12 oC) predicted by omnibus modelling Participants at a recent ListeriaPredict meeting in Spain, March 2022 For further information, contact the Project coordinator, Francis Butler, UCD, f.Butler@ucd.ie Project website: www.ipb.pt/listeriapredict/
Nationale Forschungsdateninfrastruktur (NFDI) e.V., Albert-Nestler-Str. 13, 76131 Karlsruhe, Vorstand: Prof. Dr. York Sure-Vetter; Eva Lübke (V.i.S.d.P.), Stand: März 2023Unser Ziel: Datenkompetenz im Wissenschaftskontext fördern Die Angebote und Anforderungen an Datenkompetenz Weiterbildungsangebote für Wissenschaftler:innen sind vielfältig und werden in verteilten Systemen bereitgestellt. Das vom BMBF geförderte Projekt Datenkompetenz in NFDI unterstützt durch die gezielte Vernetzung der verschiedenen Akteure den ganzheitlichen und nachhaltigen Aufbau von Datenkompetenz für Wissenschaftler:innen. Angestrebte Ergebnisse: • Bereits bestehendes Angebot zum Thema Datenkompetenz in NFDI erfassen • Weiterführende Bedarfe zum Thema Datenkompetenz in NFDI identifizieren • Zielgruppenorientierte Lösungen und Konzepte entwickeln • Monitoringkonzept entwickeln, um Wirksamkeit der Ansätze langfristig zu überprüfen Expert:inneninterviewsPhase: Basis Ziel: • Identifikation des Bestands und der Bedarfe von Trainingsangeboten im Bereich Datenkompetenz und möglicher Messwerte von Datenkompetenz im Kontext NFDI. • Aufdeckung möglicher Lücken im Aufbau von Datenkompetenz in NFDI und Entwicklung potentieller Strategien zur Behebung, insbesondere durch Nutzung des NFDI-Netzwerkes.Umsetzung: • Durchführung von 9 Expert:inneninterviews.Ergebnis: • Interviews befinden sich derzeit in der Auswertung. Community Workshop I Phase: BasisZiel: • Datenkompetenz Angebote vernetzen und sichtbar machen. • Diskussion über Herausforderungen der Community. Umsetzung: • 4-stündiger virtueller Workshop • Interaktive Break-out Sessions • 186 Teilnehmer:innenErgebnis: • Kartierung der Datenkompetenzangebote auf einer Landkarte. • Basis einer fortführenden Workshopserie.Status Erfassung Phase: Basis Ziel: • Gewinnung eines Überblicks über Aktivitäten und vorhandener Ressourcen im Bereich Datenkompetenz Traniningsangebote.Umsetzung: • Vernetzungsgespräche mit NFDI Konsortien. • Vernetzung über NFDI hinaus. • Recherche.Ergebnis: • Aufbau einer Sammlung bestehender Datenkompetenzangebote. • Sichtbarmachen von Schulungsmaterialien und Weiterbildungsangeboten. • Vernetzung dezidierter Angebote.Anbindung an NFDI-SektionEduTrain Datenkompetenz von Anfang an! Die Sektion befasst sich mit dem Aufbau von Datenkompetenz mit Fokus auf Forschungsdatenmanagement und hochschulbasierter Lehre. Das Projekt arbeitet mit der Sektion zusammen und nutzt Synergieeffekte. Online-UmfragenPhase: Realisationwww.nfdi.de/datenkompetenz/ Ansprechpartnerinnen: Anne Lehmann Sarah Day anne.lehmann@nfdi.de sarah.day@nfdi.de +49 721 988 994 28 +49 721 988 994 27KEY Messages für Phase: Basis • Datenkompetenz wird zur Kernkompetenz von Wissenschaftler:innen. • Die vielfältige Angebotslandschaft muss auffindbar gemacht werden. • Synergien der Akteur:innen sollten genutzt werden.
Assessment of 13 Gambierdiscus strains using neuro-2a and erythrocyte lysis assays Francesco Pisapia, William C. Holland, D. Ransom Hardison, R. Wayne Litaker, Santiago Fraga, Tomohiro Nishimura, Masao Adachi, Lam Nguyen-Ngoc, Véronique Séchet, Zouher Amzil, Christine Herrenknecht, Philipp Hess Scientific poster Gambierdiscus is a genus of benthic dinoflagellates that produce ciguatoxins (CTXs) and maitotoxins (MTXs), which are among the most potent marine toxins known. CTXs are bio-accumulated and biotransformed along the marine food chain and are involved in Ciguatera Fish Poisoning (CFP). Several species have recently been described, and CFP has recently been reported from non-endemic areas, namely the Canary Islands. Little is known about how toxicity varies among species and isolates of Gambierdiscus. This study examined the toxicity of 13 strains of Gambierdiscus, seven from the Pacific Ocean (G. pacificus CCMP 1650, G. sp. VGO 917, G. australes CCMP 1653, G. scabrosus KW070922_1, G. sp. Vietnam, G. caribaeus BILL HI Gam8, G. carpenteri PAT HI Jar7 Gam11), one from the Mediterranean Sea (G. carolinianus Greece Gam2), and five from the North-Eastern Atlantic Ocean (G. australes VGO 1178, G. australes VGO 1181, G. silvae VGO 1167, G. silvae VGO 1180, G. excentricus VGO 791). Algal cells were extracted with methanol, and extracts were partitioned between dichloromethane and aqueous methanol. The toxicity of pre-purified extracts has been evaluated using an ouabain/veratridine neuro-2a assay and a human erythrocyte lysis assay. In general terms, all strains showed hemolytic activity in the aqueous methanol fraction in the range of pg MTX eq/cell, and neuro-2a cytotoxicity in the dichloromethane fraction in the range of fg P- CTX-3C eq/cell. G. excentricus (Canary Islands) was an exception, with a neuro-2a cytotoxicity in the range of pg P-CTX-3C eq/cell, in accordance with data previously reported by Fraga et al. (2011). Keywords: Ciguatera Fish Poisoning, Gambierdiscus, ciguatoxins, maitotoxins, neuro-2a assay, erythrocyte lysis assay.
Phenotypic Screening Phenotypic screening is a type of screening used to identify substances such as small molecules, peptides, or RNAi that alter the phenotype of a cell or an organism in a desired manner. When the molecular mechanism of action is not assumed and does not require knowledge of the molecular target, phenotypic screening can be applied in biological research and drug discovery. Due to the limited success of target-based drug discovery and the increasing need to minimize the risk of late stage attrition due to poor efficacy or off-target activities, phenotypic approaches attract more attention. Many of today's first-in-class drugs with novel mechanisms of action came from phenotypic screening. The biological relevance of the assay systems is deployed and in this respect the commercial availability of unlimited quantities of pure human cell types, particularly those derived from induced pluripotent stem cells, is having a promising impact. Stem cells are fueling the development of many new disease models and with high levels of translation to human biology and disease. These phenotypic assays are increasingly being used in early toxicity testing. Moreover, high content imaging systems have also powered phenotypic drug discovery, facilitating the rapid analysis of increasingly complex multi-parametric measurements of cellular phenotypes or biomarkers. Compounds are screened in cellular or animal disease models to identify compounds that cause a desirable change in phenotype. Only after the compounds have been discovered to determine the biological targets, this is a process known as target deconvolution. The assay types involve co-cultures of primary cells. The simplest phenotypic screens in vivo employ cell lines and monitor a single parameter such as cellular death or the production of a particular protein. Human primary cells were ranked as the cell type most suited (relevant) for phenotypic screening studies, followed by stem cells or iPS-derived phenotypes and then primary cells of animal origin. Cell line monocultures were the biological systems currently most used to conduct phenotypic drug discovery. This was followed by