A Tale of Two Telescopes: Identifying Kepler False Positives Using TESS Data Drake Lehmann𝟏and Andrew Vanderburg2,1 University of Wisconsin Madison1 and Massachusetts Institute of Technology2 We have also recreated a plot by Coughlin et al. (2014) in which we match Kepler Objects of Interest to themselves. In these plots, sigma P is the closeness in period, and sigma T is the closeness in the time of transit. The red box in the Coughlin plot “…corresponds to significant, real, physically caused matches” (Coughlin et al. , 2014). These matches are likely false positives. Current Results Next Steps and Conclusion Introduction There are many planet candidates identified by Kepler and TESS space telescopes that have yet to be confirmed as planets or false positives. False positives are signals that look like there is an exoplanet orbiting a star, but the exoplanet does not actually exist. There are many causes behind false positives. One common cause is background eclipsing binary stars. These eclipsing binaries emit enough light to contaminate the data of nearby stars, making it seem like there is an orbiting exoplanet. Another cause behind false positives are detector artifacts like column anomaly and image crosstalk. These technical problems causes smearing and pixel bleeding which can contaminate many stars with false positive signals. Having false positives in the catalogs of real planets damages the integrity of these lists. It is important that we identify these false positives and remove them from the sample of possible planets. This way, we boost our confidence in the surviving signals. In order to investigate possible false positives, we use a method called ephemeris matching. To do this, we combine data collected by TESS and Kepler space telescopes to create light curves from many unrelated stars that are close to each other. From these light curves, we can find the orbital period of exoplanet candidates and eclipsing binaries. However, if multiple light curves show the same period, then the exoplanet in question is likely a false positive. This is because it is very unlikely that two different and unrelated stars would give the same exact orbital period. We need data collected by TESS in addition to Kepler, because Kepler only collects data from specific pixels (see figure A for an example). However, TESS takes full frame images every 30 minutes. By combining both data sets, we can confirm or rule out more planets than either would by itself. We are currently working on incorporating TESS data into our code so we can use a sample of TESS data to search for Kepler matches. Michelle Kunimoto and Chelsea Huang have kindly provided a list of eclipsing binaries detected by TESS in the Kepler field which we are using to match against Kepler planet candidates. Once we’ve completed this work, we can be more confident in the surviving planets. Figure C is Coughlin et al. (2014)’s plot and figure D is our recreation. This shows us that our code is successful in matching Kepler data. Now that we know our code works, we can move onto incorporating TESS data into the code. So far, we’ve written code to plot the light curve of a star and line up the orbital period of the potential exoplanet with the dips of light. We’ve confirmed that this works by testing known false positives. On the right, we show an example of finding the light curve and matching the orbital period from another star close by. Because the lines line up with the dips, this is most likely a false positive. Approach Our first step is to write code that plots the light curves of stars from both Kepler and TESS that are close to each other and line up the orbital periods of the potential exoplanets. This is so we can see what a single false positive looks like in a plot. We show an example of this in figure B. Our second step is to write code that searches for ephemeris matches using the procedure provided by Coughlin et al. (2014). We will test this code on Kepler da


Tomographie aux rayons X pour évaluer la composition corporelle des carcasses de porcs ibériques Maria FONT-I-FURNOLS, Albert BRUN, Marina GISPERT IRTA -Qualité du Produit, Finca Camps i Armet, 17121 Monells, Catalogne, Espagne maria.font@irta.cat Avec la collaboration de Albert ROSSELL, Adrià PACREU et Agustí QUINTANA (IRTA) Computed tomography to assess body composition of Iberian pig carcasses Iberian pigs are an autochthonous breed with a higher fat content than commercial white pigs. Computed tomography scanning allows non-destructive evaluation of carcass composition. The aim of this study was to assess, using computed tomography, the carcass composition of pure Iberian pigs and crossbreeds of Iberian pigs and white pigs to visualize differences in the distribution of fat and muscle in the anatomical regions of the ham and the loin. For this purpose, two 100% Iberian pig carcasses and four carcasses of crossbreeds of Iberian pigs (50%) were scanned with computed tomography equipment. The scanning procedure was helical, at 140 kV, 145 mA, a 512 × 512 matrix, and 10 mm thickness. Additionally, information on more than 120 carcasses of white pigs was used to obtain mean values. Images were analysed with a program purpose-built in Matlab and with VisualPork software. Results show both visually and quantitatively differences in the distribution of the volume of fat and of muscle in the three pig genotypes. The 100% Iberian carcasses had much more fat than lean. Fat and lean percentages were similar for the 50% Iberian carcasses. Finally, white pig carcasses had much less fat than lean. It can be concluded that carcass composition depends greatly on genotype and that computed tomography can visualize these differences without needing to cut carcasses. INTRODUCTION La race autochtone des porcs ibériques se caractérise par une teneur élevée en gras par rapport aux races « industrielles » de porcs blancs (Mayoral et al., 1999 ; Ayuso et al., 2014 ; Martínez-Mancipe et al., 2016). La tomographie aux rayons X permet d’évaluer la composition des carcasses d’une manière non destructive à la fois chez les animaux vivants et sur les carcasses (Font i Furnols et al., 2009 ; Carabús et al., 2014). L'atténuation des rayons X (mesurée en unités Hounsfield, HU) dépend de la densité du tissu traversé ; on obtient ainsi une image de l'intérieur du corps où chaque pixel a une valeur Hounsfield. Le maigre correspond à des valeurs HU positives et le gras à des valeurs HU négatives (Font i Furnols et al., 2009). Cette étude a pour objectif d’évaluer, avec la tomographie aux rayons X, la composition corporelle des carcasses de porcs ibériques de race pure, de porcs croisés ibériques et de porcs « blancs » pour visualiser les différences de distribution du gras et du maigre dans la région anatomique de la longe et du jambon. 1. MATERIEL ET METHODES 1.1. Carcasses Deux carcasses de porc 100% ibériques et quatre carcasses de porcs 50% ibériques – 50% Duroc ont été obtenues dans deux abattoirs. À 24-48 h post mortem les carcasses ont été radiographiées aux rayons X avec l’équipement General Electric HiSpeed Zx/I en mode hélice, 140 kV, 145 mA, matrice 512x512, 10 mm d'épaisseur, champ de vision 460 mm et algorithme de reconstruction STD+. Les données de plus de 120 carcasses de porcs blancs, radiographiées dans les mêmes conditions que les précédentes, ont été utilisées pour obtenir une valeur moyenne. 1.2. Analyse d’images Les images ont été analysées avec les logiciels Matlab (R2007b© MathWorks Inc., Natick, MA, USA) et VisualPork (Bardera et al., 2012). Le volume associé à chaque valeur Hounsfield a été obtenu pour chaque carcasse, et un volume moyen des carcasses de porc pour chaque génotype a été calculé. Pour la comparaison entre génotypes, le volume entre +1 et +130 HU a été considéré comme du maigre et le volume entre -120 et 0 HU a été considéré comme du gras. Le pourcentage de volume maigre par rapport au total (maigre + gras) a été calculé.


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 !


Actividad Cueva Emiral (ss. VII-X) Plenomedieval (ss. X-XIII) "La cerámica medieval y moderna de la prospección del proyecto Verasur en la depresión de Vera” Alba Mª Molina Fernández (Universidad de Granada) e.albammf95@go.ugr.es "I Congreso Internacional de Arqueología Bayra. La producción cerámica en el siglo XVI. Bayra y el sureste de la península ibérica, desde el Mediterráneo al Atlántico" Nuestro estudio se ha basado en la identificación mediante la observación macroscópica, el dibujo arqueológico y la comparación bibliográfica de cerámicas medievales y modernas recogidas en la prospección que realizó el proyecto Verasur en la cuenca de Vera en 2021. Dicho proyecto, dirigido por por M. Murillo Barroso y B. Legarra Herrero, estuvo financiado por la Este póster muestra algunos de los resultados que forman parte de un trabajo más extenso que será presentado como Trabajo de Fin de Máster tutorizado por A. García Porras y mentorizado por M. Alonso Valladares. Si bien el TFM desarrollará objetivos más diversos, en este póster nos centraremos en la localización de los yacimientos en los que hemos reconocido cerámicas medievales y modernas y sus posibles afecciones a través de la observación de elementos del paisaje. La depresión de Vera se sitúa en una amplia llanura del área centro-septentrional de Almería que se ve atravesada por el paso de los ríos Almanzora, Antas y Aguas. Se trata de un espacio de amplias llanuras que se dispone entre el mar Mediterráneo al este y un paisaje montañoso hacia el interior conformado por las sierras Almagrera, Almagro, Lisbona, Bédar y Cabrera. Estas aptitudes geográficas han favorecido que se trate de una zona nuclear de ocupación humana. Se trata de un yacimiento que L. Siret nombró originalmente “Cabezo del Pajarraco” y en el que señaló restos neolíticos y protohistóricos. En la actualidad queda dividido en dos áreas por el paso de la carretera Vera-Garrucha, lo que, junto a la excavación de trincheras durante la guerra civil, ha alterado el yacimiento. También encontramos cuevas y estructuras que pueden haber contribuido a su afección. Se han identificado restos cerámicos de todas las etapas a excepción de la nazarí (ss. XIII-XV). 1.A: tinaja de borde entrante engrosado. Este tipo de cerámicas de almacenamiento se caracterizan por presentar un borde que se une al cuerpo, sin cuello, resultando similares al dolium romano. Aunque perduran aún en época emiral, son mayormente comunes durante la tardoantigüedad. 1.B: base de almacenamiento. Presenta una pasta bastante tosca con signos de haber sido confeccionada a torno y a mano. Este tipo de fabricaciones mixtas se mantienen en el sureste peninsular hasta el s. VIII. 1.C-D: jarrita/o que presentan decoración pintada en manganeso. Este tipo de producciones son muy populares en el sureste peninsular entre los ss. X- XIII perdurando hasta finales de época nazarí. 1.E: mortero de base plana y vidriado verde al interior. Podemos datarlo entre los ss. XV-XVI. 1.F: base de plato con fondo estannífero. Llama la atención el salto cronológico de ocupación en la zona, ya que sólo hemos identificado cerámicas tardoantiguas y modernas. Quizá estas últimas estén relacionadas con el comienzo de la explotación agrícola en la zona en épocas más recientes. Cabezo María se encuentra sobre un cerro volcánico de la Sierra de Bédar (Antas). Domina la depresión de Vera con una altura máxima de 256 m.s.n.m. Lo corona la ermita de Santa María que le da nombre (s. XVI). La bibliografía académica afirma que en Cabezo María aparecen indicios del que podría haber sido el poblado altomedieval más extenso encontrado en la depresión de Vera. Sin embargo, a día de hoy se encuentra diseminada por canteras y estructuras que podrían haber favorecido su pérdida. A sus pies queda Qurénima, una necrópolis descubierta por los hermanos Siret a finales del s. XIX. Habría funcionado durante el Bronce y el Primer Hierro. En la actualidad está llena de campos de cultivo y de embalses de


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.


Asteroseismology of Ruprecht 147 Mikkel N. Lund1∗, Jason L. Curtis2, Allyson Bieryla3, Luca Casagrande4, David W. Latham3, Karsten F. Brogaard1, Andrea Miglio5,6, Sarbani Basu7, J. M. Joel Ong7,8, Aldo M. Serenelli9,10, et al. Introduction Ruprecht 147 (NGC 6774) is the nearest old open cluster, located at a distance of approximately 300 pc and with an age of around 2.5 Gyr. Initially discovered by Ruprecht in 1966, the cluster remained largely unnoticed for decades until it was “re-discovered” by Curtis et al. in 2013. Since then, it has been the focus of several studies, particularly on the calibration of gyrochronology (e.g., Curtis et al., 2020). During Campaign 7 of the K2 mission (Howell et al., 2014), many known members of Ruprecht 147 were targeted for ∼1-min cadence observations. Additionally, the central part of the cluster was observed with a superstamp at a 30-minute cadence (Figure 1). In this study (Lund et al., in prep.), we are performing a detailed asteroseismic analysis of Ruprecht 147, aiming to establish it as one of the best asteroseismically constrained open clusters available. Fig. 1: Left: Sky plot containing part of Ruprecht 147. Circular and triangular markers indicate targets from Curtis et al. (2013); Red and gold markers indicate targets observed during K2 C7 for which pixel stamps were defined by the mission. Seismic signals were detected for the gold ones. Right: K2 superstamp superstamp with targets given as in the left panel. Methods All data from K2 were processed using the K2P2 pipeline (Lund et al., 2015). The power density spectra for all targets were searched for asteroseismic excess power, and global asteroseismic parameters were measured for stars with identified excess power. Individual mode frequencies were extracted for a subset of these stars using peak-bagging techniques (following Lund et al., 2017; Davies et al., 2015). Spectroscopic observations for the asteroseismic targets were obtained using the Magellan Inamori Kyocera Echelle (MIKE) and the Tilling- hast Reflector Echelle Spectrograph (TRES). A smaller subset of tar- gets was observed using the UVES and GIRAFFE spectrographs on the FLAMES instrument at VLT. Additionally, effective temperatures were measured using the infrared flux method (IRFM; Casagrande et al., 2020). 1Stellar Astrophysics Centre, Aarhus University, DK (∗mikkelnl@phys.au.dk) | 2Department of Astronomy, Columbia University, USA | 3Center for Astrophysics, Harvard- Smithsonian, USA | 4Research School of Astronomy and Astrophysics, Mount Stromlo Observatory, The Australian National University, AUS | 5INAF - Osservatorio di As- trofisica e Scienza dello Spazio, Bologna, ITA | 6Department of Physics and Astronomy, Università di Bologna, Bologna, ITA | 7Department of Astronomy, Yale University, USA | 8Institute for Astronomy, University of Hawai‘i, Honolulu, USA | 9Institute of Space Sciences (ICE, CSIC) Campus UAB, ESP | 10Institut d’Estudis Espacials de Catalunya (IEEC), Barcelona, ESP Results We have extracted asteroseismic parameters for a total of 33 members of Ruprecht 147. What sets Ruprecht 147 apart from other clusters studied using asteroseismology is that oscillations can be analyzed for stars ranging from the main-sequence (MS) to the red giant branch (RGB), as shown in Fig. 2. Importantly, several of the asteroseismic stars reside near the cluster turn-off, where isochrones are most distin- guishable. 10 20 30 40 50 60 EPIC 219437560 400 600 800 10 20 30 40 EPIC 219630458 600 800 1000 1200 10 20 Power density (ppm2 /µHz) EPIC 219495504 600 800 1000 Frequency (µHz) 10 20 EPIC 219684426 600 800 1000 1200 0 400 800 1200 1600 Frequency (µHz) 10 20 EPIC 219609927 0.0 0.2 0.4 0.6 0.8 1.0 Frequency mod ∆ν (∆ν) 800 1000 1200 1400 1600 0 10 20 30 40 Frequency spacing (µHz) PS ⊗PS 0 10 20 30 40 50 Frequency spacing (µHz) PS ⊗PS 0 10 20 30 40 50 Frequency spacing (µHz) PS ⊗PS 0 10 20 30 40 50 60 Frequency spacing (µHz) PS ⊗PS 0 10 20 30 40 50 60 70 Frequency s


This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 862357 Legume-based intercropping: A pathway to reduced N2O emissions from agriculture? Methods Treatments Barley (Hordeum vulgare ‘Laureate’) and pea (Pisum sativum ‘Prophet’) were planted in isolation (Sole crop) and together (Intercrop) using three fertilizer rates (Table 1) Plots organized in a randomized block design, replicated four times (Fig 1). Luke Harrold, Kairsty Topp, Christine Watson & Robin Walker Introduction Intercropping of legumes with cereal crops can play a crucial role in the path towards sustainable agriculture and achieving net-zero. Literature and IPCC report suggests a reduction in N2O emissions in legume intercropped systems. However, reductions have been shown to be dependent on the variety of pea used. We tested if legume-based intercropping systems (pea/barley) can support sustainable farming by balancing environmental (N₂O emission, soil health) and economic (yield) goals. Figure 2 – Gas sampling from static chamber. Two static chambers per subplot. Photo by Robin Walker. Results Nitrous oxide emissions Intercrop with half-rate or without added N emitted the same amount of N2O over a 114 day period as sole barley with full-rate N addition (Fig 4). With no synthetic nitrogen addition the pea treatment maintained a cumulative N2O emission that does not significantly differ from the barley which received 120 kg N ha-1 (Fig 4). N₂O flux closely linked to soil water content, peaks corresponding to higher soil moisture (Fig 3). N addition to barley doubled mean N₂O emissions over 114 days compared to no-N barley (Figure 4). Periodically soil samples were taken to determine mineral N (NH4 + and NO3 -). Soil moisture and temperature probes measured continuously on an hourly basis. Conclusions Intercropping of these varieties of barley and pea failed to reduce N2O emission over 114 days even with no synthetic nitrogen addition. Pea added sufficient nitrogen to maintain the same yield-to-seed ratio for barley as the full rate fertilizer treatment and a half rate of N led to a greater barley yield-to-seed ratio when intercropped. Other pea varieties have been shown to reduce N2O in intercropping systems suggesting that the right mix of cereal/legume would need to be found for particular soil types/region. Figure 4 – Cumulative emission of N2O over 114 days Treatment Fertiliser Sole crop Barley (Laureate) Full N 120 kg/ha Sole crop Pea (Prophet) No N Intercrop Barley/Pea No N Intercrop Barley/Pea Half N 60 kg/ha Sole crop Barley No N Table 1 – Crop treatment including fertilizer addition Figure 3 – N2O flux and soil moisture over 74 days. Solid lines show the flux of N2O over time with the left-hand y-axis. Dashed lines show the soil moisture content (%) overtime with the right-hand y- axis. Standard error is shown. Gas sampled from chambers on days 1,2,4,8 and 10 then twice a week for four weeks followed by once per month until experiment end. N2O concentration measured via gas chromatograph. Also measured Bulk density Infiltration Soil carbon (POXC) Soil structure (VESS) Earthworm count Figure 1 – Plot layout, external plots used for GHG sampling (Fig 2) and destructive harvesting (described below) and internal plots used for yield. @SoilandGas Figure 5 – a) Yield of barley, the mass of pea has been removed b) barley yield normalised by sowing rate Much of the N2O derived from the pea-only treatment seems to be associated with a wetting event. A similar peak is evident in the barley with full nitrogen addition but to a lesser degree. Yield Despite having half the sowing rate, the two intercrop treatments have the same yield as the unfertilised barley (Bar_NoN) treatment at full sowing rate (Fig 5a). Similarly, despite receiving no fertilizer the unfertilised intercrop achieved half the yield of the fertilised full sowing rate barley (Bar_FullN) resulting in the same yield per


Results: Broad range of retained atmospheric masses Observational implications Residual H/He Atmospheres of Super-Earths William Misener & Hilke Schlichting (University of California, Los Angeles) Full paper: MNRAS 503:5658 TESS Science Conference 2 – August 2021 Figure 4: Evolution in atmospheric mass fraction f with time for two sets of planets: (a) with set Teq and varying Mc and (b) with set Mc and varying Teq. Dots mark time at which tcool=tloss Figure 6: Contours of log10fret, in orange, for finit=0.03. Super-imposed are planets with well-measured radii and masses. TESS planets are marked by crosses, those discovered by others are marked by dots. Planets are colored by their K band magnitude (planet data from Exoplanet Archive) • Fig. 6 demonstrates many known planets, including TESS discoveries, could have retained substantial residual atmospheres after core-powered mass loss • A number of these planets are amenable to further characterization with transmission spectroscopy • Such studies will be able to distinguish residual H/He atmospheres from those composed of heavier outgassed species • Mass fraction retained varies orders of magnitude across super- Earth regime, from <10-8 (negligible) to 10-2 (sub-Neptune) • Generally matches analytic trends • Exact values vary due to variation in Rrcb at which tcool=tloss • After spontaneous mass loss, if planet maintains atmosphere with larger heat capacity than its core, atmosphere will cool and contract, cutting off atmospheric mass loss →sub-Neptune (Fig. 1a) • If core has larger heat capacity than atmosphere, Ccore > Catm, its cooling will inhibit contraction, leading to continued mass loss →super-Earth • If planet can never cool more quickly than it loses mass →atmosphere entirely stripped (Fig. 1b) • If it can cool more quickly, atmosphere resumes contraction and mass loss ceases →thin H/He atmosphere saved (Fig. 1c, Fig. 2) Figure 1: schematic of the evolution of sub-Neptune and super-Earth planets from disk dispersal. Super-Earth atmosphere evolution References • Retained atmospheric mass is f at which tcool becomes shorter than tloss • Analytic form (plotted in Fig. 3): • Higher mass and lower equilibrium temperature planets retain more massive primordial atmospheres • Assumes Rrcb=2Rc when timescales become equal fret / M 3/2 c T −1/2 eq exp [M 3/4 c T −1 eq ] Main Takeaways Motivation • Previous work has shown core-powered mass loss can reproduce the observed dichotomy of super-Earths and sub-Neptunes (e.g., Ginzburg et al. (2016), Gupta & Schlichting (2019), Berger et al. (2020)) • But what is the long-term imprint of this mass loss process on super-Earth atmospheres? Mechanism • As core-powered mass loss unbinds overlying atmospheres, super-Earth cores can cool more quickly • These planets’ cooling timescales eventually become shorter than their mass loss timescales, allowing super-Earths to keep small residual H/He envelopes Results • The mass of these retained envelopes increases with planet mass and semi-major axis • The retained atmospheric mass fraction, fret, ranges from <10-8 to 1% of the planet’s total mass and is of order 10-3 for a 5 Earth mass planet at Teq = 1000 K Importance • Retaining such quantities of H/He reduces the atmosphere's mean molecular weight compared to an outgassed secondary atmosphere • This signature could be observable today or in the near future via transmission spectroscopy (e.g., Benneke & Seager (2012), Fortney et al. (2013), Greene et al. (2016)) • Large amounts of retained H/He after core-powered mass loss would affect the early geochemistry and rock-atmosphere interactions of this common class of planet (e.g., Wordsworth et al. (2018), Doyle et al. (2019), Seager et al. (2020)) • It therefore affects their potential habitability • Such tenuous atmospheres may be susceptible to further processing, e.g. by long-term photo- evaporation • TESS and related missions have found and continue to find excellent candidates to test these


NEW APPROACH TOWARDS SMART BIOSENSORS: AI-MEMRISTIVE BIO-DETECTION CENTRE FOR MICROSYSTEM TECHNOLOGY (CMST) Student: Manel Bouzouita Supervisors: Ioulia Tzouvadaki, Zayer Fakhreddine ABSTRACT Memristors offer high density, low energy consumption, memory effect capability, and advanced sensing capabilities, making them ideal for revolutionizing nonvolatile memory. We are developing a nanosensor with low power consumption that uses machine learning to accurately and efficiently detect biomolecules. Our simulations and machine learning classification models confirm the potential for a reliable and seamless AI-powered biosensing platform that could revolutionize biological system monitoring. State of Art Non-volatile memory devices • Non-volatile memory is a form of computer memory that can maintain stored data even when power is turned off. • It commonly pertains to semiconductor memory chips, containing information in floating-gate memory cells made up of floating-gate MOSFETs, which include NAND flash and solid-state drives (SSD) as flash memory storage[1]. • Memristors have the capability to remember their final state even after the current flow has been stopped, thereby rendering them a useful option for non-volatile memory[2]. Dynamic Memristor: Memristive Crossbar (MCR) structure • The formation and rupture of conductive filaments with nano-scale width are observed to occur across the entirety of the oxide layer, resulting in the desired set and reset transitions (figures 1.1 1.2 1.3 1.5). These phenomena are contingent upon the threshold voltage bias and the impact of joule heating[5]. • The MCR refers to an advanced physical model of a metal oxide memristor (figure 1.3) that draws its inspiration from Sungho Kim's research. • It considers various factors that impact resistive switching behaviors, such as electric field, temperature, oxygen vacancy concentration gradient, and material parameters [3]. Memristive Biosensing • A memristive biosensor is a non-volatile memory device that is capable of sensing while functionalized. • The silicon nanowire-based biosensor (figure 2)is composed of two back-to-back Schottky diodes with opposite functions [5]. • The metal oxide memristive biosensor is made of Metal-Insulator-Metal (MIM) capacitive resistive (MCR) architecture (figure 3) and comprises a unipolar metal oxide memristive device. AI advanced Biosensing • Employing supervised machine learning techniques in the context of memristive biosensors encompasses several key aspects, with output labelling being a pivotal attribute. • This process enables the categorization of sensor output data into distinct groups, contingent upon the specific model and encoding scheme chosen for the analysis. • This preprocessing involves a sequence of stages, including: – Data extraction from the memristive biosensor. – Treatments such as filtration and scaling. These preparatory measures are instrumental in ensuring that the data fed into the algorithm is: devoid of noise, exhibits high reliability, and offers the utmost accuracy, • The ML intervention for biosensing has a corrective capability of enhancing the sensor's specificity and bolstering its ability to detect anomalies, consequently underlining the promise of delivering high specificity and anomaly-free detection outcomes[6]. System Overview: AI-Based Memristive Biosensing Primary Results And Discussion Results of Dynamic MCR modelling: Figure 5 Results of ML modelling: Table 1 Contact Manel.Bouzouita@ugent.be www.ugent.be/elis Universiteit Gent @ugent Ghent University Acknowledgement The research endeavor was made possible thanks to generous financial support from the esteemed University of Monastir and the distinguished Faculty of Sciences of Monastir, Tunisia. Such funding has allowed for the pursuit of valuable knowledge and advancements in the respective fields of study. Fig.(2) Fig.(1) References [1] ‘Non-volatile memory’, Wikipedia. Sep. 07, 2023. Accessed: Oct. 02, 2023. [Onlin


Salinidad y pH determinan los patrones de distribución de la macrofauna asociada a manglares en restauración en Isla del Carmen, México Introducción Objetivos Materiales y Métodos Resultados Nancy Yolimar Suárez-Mozo1, Gabriel M. Moulatlet3, Rosela Pérez-Ceballos1,2, Mariana V. Capparelli1* 1Estación El Carmen, Instituto de Ciencias del Mar y Limnología, Universidad Nacional Autónoma de México, Carretera Carmen-Puerto Real km 9.5, 24157 Ciudad del Carmen, México. 2Consejo Nacional de Humanidades de Ciencias y Tecnologías (CONAHCYT), Mexico. 3Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona, USA. *mcapparelli@cmarl.unam.mx Variables ambientales Composición de moluscos y crustáceos Discusión Degradado Referencias Composición de moluscos y crustáceos vs. variables ambientales 1274 abundancia total 10 spp Moluscos 5 spp Crustáceos Síguenos en Instagram Parámetros ambientales • Temperatura • Salinidad • pH • Nitritos • Nitratos • Amonio • Fosfatos • Sulfuros Sedimentos: tamaño de grano, carbonatos y materia orgánica Organismos estudiados: Moluscos y crustáceos Análisis de datos • Variables ambientales: PCA • Composición de especies: abundancias, número de especies, análisis de ordenación Análisis estadísticos: • Árbol de decisiones (Linktree) • Distribución de especies: diagrama de sombras y clúster Estrategia de muestreo Nivel de restauración de manglares: • Natural • Degradado • Restaurado • 10 estaciones Área de estudio Isla del Carmen La ONU declaró 2021-2030 como el decenio de la "Restauración de los Ecosistemas" y las "Ciencias Oceánicas”1. Durante la restauración de manglares, ocurren cambios físicos, disminuye la salinidad y se establecen condiciones ideales para los organismos2. La restauración de manglares requiere un análisis temporal y la incorporación de variables bióticas y abióticas. Figura 2. Abundancia de individuos de Moluscos (negro) y Crustáceos (gris) para cada uno de los sitios muestreados. Figura 3. Número total de especies para cada uno de los sitios muestreados. Figura 1. Análisis de componentes principales (PCA) de variables ambientales medidas en 10 estaciones en diferentes áreas de restauración. Porcentaje de variabilidad por eje y las variables se muestran como vectores. Figura 4. Análisis de LINKTREE con agrupaciones ambientales y faunísticas correlacionadas con el nivel de restauración de manglares. Figura 5. Diagrama de sombras de muestras y especies según el nivel de restauración. El sombreado en negro representa la presencia de especies. Figura 6. Ocurrencia de fauna de crustáceos y moluscos encontrada en tres niveles de restauración (restaurado, natural y degradado) en relación con las concentraciones de salinidad. • La restauración hidrológica mejora las condiciones ambientales, pero la salinidad sigue siendo alta en manglares restaurados, lo que afecta la diversidad de especies y su recolonización. • La restauración ha permitido un aumento de la diversidad de cangrejos y moluscos en comparación con sitios degradados, pero la abundancia de especies varía según los tiempos de restauración. • El cambio climático intensifica los desafíos de la restauración, como la salinización, lo que afecta negativamente la composición de especies y la funcionalidad del ecosistema. Restaurado Natural Degradado Salinidad (UPS) R2016 N3 R2010 N1 N4 R2020 N2 R2015 D1978 D2004 0 20 40 60 80 100 A% A B C D E F G Analizar cómo la diversidad de cangrejos y moluscos, se ve influenciada por las condiciones de manglares en distintos niveles de restauración y qué variables abióticas pueden ser cruciales para restablecer estos organismos biológicos. Salinidad pH Los cangrejos y los moluscos forman parte de los grupos dominantes de invertebrados en los manglares y desempeñan importantes funciones ecológicas3. 1Ferreira, A.C., Freire, F.A.M., Rodrigues, J.V.M., Bezerra, L.E.A., 2022. Mangrove Recovery in Semiarid Coast Shows Increase of Ecological Processes from Biotic and Abiotic Drivers i


Study on Optimal Dose of Sodium Valproate (VPA) in Treating Bipolar Mood Disorder (BMD) Patients in Hospital Melaka Chong Lai Peng1,Siti Rahmah Johari1, Lim Kar Ying1, Tay Eek Poei1,Ng Siok Shen1, Koo Suk Kuan1 P-73 Institutional logo (optional) NMRR NO: NMRR-17-2035-36555 Discussion Methodology Conclusion Results Variable With Admission (N = 20) Median (IqR) Without Admission (N = 29) Median (IqR) Z stat * p value* VPA dose 921.5 (371) 600 (396) -2.93 0.003 Serum level 65.5 (57.8) 46.5 (18.3) -0.428 0.668 Variable Acute BMD (N = 20) Mean (SD) Remission (N = 20) Mean (SD) Mean of Dose difference (95% CI) T stat (df) p value* VPA dose 984.2 (318.5) 935.6 (318.6) -48.6 (-197.951, 100.751) -0.681 (19) 0.504 Serum level 67.6 (33.3) 59.9 (43.1) -7.67 (-33.31, 17.97) -0.707 (7) 0.502 Table 1: Comparison VPA doses and serum level between patients with history of admission and without admission in Hospital Melaka Table 2: Comparison VPA doses and serum level during acute and remission phase among patients have been admitted in Hospital Melaka Sodium Valproate (VPA) has been commonly used as mood stabilizers worldwide in treating Bipolar Mood Disorder (BMD). Suboptimal dosing or poor clinical responses towards VPA often resulted in relapse episodes among BMD patients. Evaluation of aggressive initial dosing and serum level with efficacy and BMD relapses are crucial in maximizing clinical benefits while minimizing undesirable adverse events or incidence of relapses. This study aims to determine the optimal dose of VPA in management of BMD. A cross sectional study was conducted in Psychiatric Clinic Hospital Melaka from August 2017 till August 2019. Statistical analysis was done by using SPSS version 21. A value of p< 0.05 was considered statistically significant. Patients with history of relapse requiring hospitalization were on higher dose and achieved higher serum level of VPA than patients without history of relapse although the latter was not statistically significant. The median serum level in non relapse patient was lower than the recommended target range of 50-125 mcg/ml. In the subgroup of patients with history of relapse requiring admission, neither mean dose nor serum level of patients before and after admission was significantly different. Other studies have revealed possible correlation between severity of disease and serum level of VPA required for disease stabilisation. Nevertheless, other contributing factors such as age, body weight and concomitant therapy need to be taken into consideration. As for safety profile, 12 patients on VPA reported at least one adverse effect, with most common adverse effect being sedation and weight gain. None of the adverse effect resulted in withdrawal of therapy. Our study was unable to determine an optimal dose of VPA in the management of BMD. Future study should include other contributing factors that may affect disease control. *Mann Whitney test *paired t-test Acknowledgement We would like to express our gratitude and appreciation to Director General of Health, Director of GHM, Chief Pharmacist of GHM, Psychiatric Clinic Hospital Melaka, and those who have directly and indirectly contributed to the success of this study. Introduction 1Hospital Melaka, Ministry of Health Figure 1: Flowchart describing study flow and data collection process for the analysis of VPA doses and serum level Figure 2: Adverse events among BMD patients treated with VPA Sedation Weight Gain Thrombocytopenia Oedema Others Tremor BMD pt on VPA n=68 Without admission* n = 41 With admission* n= 27 Recruited n=29 VPA dosing and serum level Recruited n=20 *Admission: hospitalization due to disease relapse #Excluded due to incomplete data Excluded# n=12 Excluded# n=7


The widelywidely--used online mixing system has a small range of mixture ratio and a detection problem at small flow ratio used online mixing system has a small range of mixture ratio and a detection problem at small flow ratio of pesticide. This paper developed an online of pesticide. This paper developed an online--mixing system, which mixed pesticide into carrier directly.mixing system, which mixed pesticide into carrier directly.The The pesticide were injected to the mixer from pesticide tang through a piston pump, witch controlled by stepper pesticide were injected to the mixer from pesticide tang through a piston pump, witch controlled by stepper motor. A solenoid valve was used to control water flow into the buffer tank; the water level of the buffer tank was motor. A solenoid valve was used to control water flow into the buffer tank; the water level of the buffer tank was controlled using two liquid level sensor feedback. The water flow rate of the spray pump from the buffer tank was controlled using two liquid level sensor feedback. The water flow rate of the spray pump from the buffer tank was measured using a turbine flowmeter. According to the water flow rate, the proportion of pesticide was injected into measured using a turbine flowmeter. According to the water flow rate, the proportion of pesticide was injected into the mixer with water together. The mixture of pesticide and water was sprayed to the target. the mixer with water together. The mixture of pesticide and water was sprayed to the target.During During the spraying, water and pesticide was measured at the same time, the maximum error of the mixture ratio the spraying, water and pesticide was measured at the same time, the maximum error of the mixture ratio was 6.75%. The maximum error of mixture uniformity was 6.33%, and the variation coefficient was 7.91%. was 6.75%. The maximum error of mixture uniformity was 6.33%, and the variation coefficient was 7.91%. The The system proposed supplied the water and pesticide in proportion, and the range of the mixture ratio was 100:1 ~ system proposed supplied the water and pesticide in proportion, and the range of the mixture ratio was 100:1 ~ 1000:1, it can satisfy the requirements of spraying in paddy field. 1000:1, it can satisfy the requirements of spraying in paddy field.The The experiment was used the cochineal solution as the pesticide, the next step will be to carry out field experiments experiment was used the cochineal solution as the pesticide, the next step will be to carry out field experiments with real pesticides. with real pesticides.Design and experiment of online mixing spraying Design and experiment of online mixing spraying system systemAdress Adress：：483# 483# WushanWushanStreet, Street, TianheTianheDistrict, Guangzhou, P.R. China District, Guangzhou, P.R. ChinaWebsite Website：：http://www.nyhklm.org/http://www.nyhklm.org/Contact Contact：：LianLianHU HUTel Tel：：+86+86--2020--38676975 Fax38676975 Fax：：+86+86--2020--85280158 Email85280158 Email：：lianhu@scau.edu.cnlianhu@scau.edu.cnCollege of Engineering, South China Agricultural University College of Engineering, South China Agricultural UniversityKey Laboratory of Key Technology Key Laboratory of Key Technologyon Agricultural Machinery and Equipment, Ministry of Education on Agricultural Machinery and Equipment, Ministry of Educationonline online mixingmixingspaying system spaying system Meng Zhang, Lian Hu, Qibao Yuan, Runmao Zhao, Lingmao Tang, Hao Zhou, Tong Wu MAX MIN Water Pesticide 控制板 Controller Precision plunger pump Level switch A Level switch B Flowmeter Solenoid Buffer Tank Mixer 0 100 200 300 400 500 600 700 800 900 1000 Artificial mixture Machine mixing 1 Machine mixing 2 Machine mixing 3 Measuring point concentration/ppm Buffer tank left Middle Right The Theconcentration of the measurement points concentration of the measurement points


www.postersession.comXXIX International Conference on Neutrino Physics and Astrophysics, June 22 to July 2, 2020. XXIX International Conference on Neutrino Physics and Astrophysics, June 22 to July 2, 2020. Exposure-background duality in the searches of neutrinoless double beta decay M. K. SinghInstitute of Physics, Academia Sinica, Taipei, Taiwan Institute of Physics, Academia Sinica, Taipei, Taiwan Based on: M. K. Singh, H. T. Wong et al., Phys. Rev. D 101, 013006 (2020). Background can be predicted. Poisson statistics handles: (i) Low background; (ii) Rare processes. Model - Inverse correlation between G0ν and |M0ν|2. Decay rates (1 event/ton-yr with full efficiency) are similar at given <mββ> and constant gA. No favored 0νββ isotope. ∑ (ton-year) . ɛ𝐑𝐨𝐈 𝑵𝐨𝐛𝐬 𝟎ν α 𝟏 <𝒎𝜷𝜷> 𝟐 Realistic interpretation lies within a factor of [0.5, 2.0]. RoI = w1/2 (FWHM): Not the optimal choice when B0 →0. Alternative choice: RoI ≡w3σ (Qββ ± 3σ), thus εRoI ≅100%. Better sensitivity by a factor of εRoI (w1/2 = 0.76). Covered 𝑻𝟏/𝟐 𝟎𝝂is 32% longer, or Σ is 24% less. Background Index (BI) defined as: BI= 𝐁𝟎(𝐑𝐨𝐈) ∑ Universally applicable. BI < 0.21 counts/w1/2-ton-yr cover <𝒎𝜷𝜷𝟗𝟓% 𝐈𝐇> BI < 0.033 counts/w1/2-ton-yr cover <𝒎𝜷𝜷− 𝐈𝐇> Standard-Model-allowed irreducible background 𝒁 𝑵𝑨𝜷𝜷→ 𝒁+𝟐 𝑵−𝟐𝑨𝜷𝜷+ 𝟐 𝒆+ 𝟐 𝝂[Goeppert-Mayer, 1935] Worse resolution (Δ) Larger RoI Larger 2νββ Background Resolutions under BImin conditions Δ ≤ (0.3-0.9)% cover <𝒎𝜷𝜷− 𝐈𝐇> Δ ≤ (0.1-0.3)% cover <𝒎𝜷𝜷− 𝐍𝐇> ♣MJD Best Resolution Δ(76Ge) = 0.12% BI < 6×10−10 counts/(w1/2-ton-yr) Covering <𝒎𝛃𝛃−𝐍𝐇> will require large and costly exposure. Reduction of BI will be playing increasingly significant. Same exposure can probe longer 𝑻𝟏/𝟐 𝟎ν and smaller <mββ> with decreasing background. ▲Half-life in Mass Mechanism : 𝟏 𝑻𝟏/𝟐 𝟎𝝂 = 𝑮𝟎𝝂𝒈𝑨 𝟒𝑴𝟎𝝂𝟐<𝒎𝜷𝜷> 𝒎𝒆 𝟐 ▲Effective Mass: <mββ> = |U𝒆𝟏 𝟐|m1 + |U𝒆𝟐 𝟐|m2eiα + |U𝒆𝟑 𝟐|m3eiβ| ▲Experimentally measurable Half-life: ▲Combined Half-life: 𝑻𝟏/𝟐 𝟎𝝂= 𝒍𝒏𝟐. 𝑵𝑨𝜷𝜷. 𝒕𝐃𝐀𝐐. ɛ𝑹𝒐𝑰 𝑵𝒐𝒃𝒔 𝟎𝝂 = 𝒍𝒏𝟐. 𝑵𝑨 𝑴(𝑨𝜷𝜷) . ∑. ɛ𝑹𝒐𝑰 𝑵𝒐𝒃𝒔 𝟎𝝂 𝑴𝟎𝝂𝟐[𝒈𝑨 𝟒. 𝑯𝟎𝝂] = 𝟏 <𝒎𝜷𝜷>𝟐 𝟏 ∑. 𝑵𝒐𝒃𝒔 𝟎𝝂 ɛ𝑹𝒐𝑰; 𝑯𝟎𝝂≣𝒍𝒏𝟐 𝑵𝑨 𝑴𝑨𝜷𝜷.𝒎𝒆𝟐 Formulation Discovery Potential ∑𝐢=𝟎 𝐍𝐨𝐛𝐬 𝟑𝛔−𝟏 𝐏𝐢; 𝐁𝟎≥𝟏−𝟎. 𝟎𝟎𝟏𝟑𝟓 ∑𝐢= 𝐍𝐨𝐛𝐬 𝟑𝛔 ∞ 𝐏𝐢; [𝐁𝟎+ 𝐒𝟎] ≥𝟎. 𝟓 Only integer counts can be observed in an experiment. Theme Theme::T To reach the following target sensitivities: (i) <𝒎𝜷𝜷− 𝐈𝐇> = 1.4×10-3 eV, (ii) <𝒎𝜷𝜷+ 𝐈𝐇> = 5.1×10-2 eV, (iii) <𝒎𝜷𝜷𝟗𝟓% 𝐈𝐇> = 2.0×10-2 eV (iv) <𝒎𝜷𝜷− 𝐍𝐇> = 7.8×10-4 eV, (v) <𝒎𝜷𝜷+ 𝐍𝐇> = 4.3×10-3 eV, (vi) <𝒎𝜷𝜷𝟗𝟓% 𝐍𝐇> = 3.0×10-3 eV. Relating 𝑻𝟏/𝟐 𝟎𝝂with <mββ> - Model for |M0ν| Required Exposure and Background Limiting Irreducible Background Summary Conversion to Realistic Configurations Considered: IA = 100%, εexpt = 100% and “unquenched” free nucleon value of gA =1.27 Conversion: In realistic experiments: Σ’ ≃Σ. 𝟏 IA . 𝟏 ɛexpt .WΣ(gA) and BI’(Σ’) ≃BI· Σ Σ’ § Neutrinoless double beta decay (0νββ) [Furry, 1939] 𝒁 𝑵𝑨𝜷𝜷→ 𝒁+𝟐 𝑵−𝟐𝑨𝜷𝜷+ 𝟐 𝒆 ●Forbidden in Standard Model !!! ●∆L = 2 !!! § Observation of 0νββ implies new physics:● ●Neutrinos Neutrinosare areMajorana Majoranaparticles particles( (νν= =ത ν) )● ●Lepton Leptonnumber numberviolations violations● ●Effective Effectivelight lightMajorana MajoranaNeutrino NeutrinoMass Mass< <mmββββ>>≠≠0 0 § Energetically possible for 35 nuclei ●A few are experimentally relevant § Present work: Required Exposure vs Background Introduction STEP-1 STEP-2 R. G. H. Robertson, Mod. Phys. Lett. A 28, 1350021 (2013). Target exposure: Next-generation 0νββ projects 10 ton-year to cover IH GERDA: Background level = 𝟏. 𝟎−𝟎.𝟒 +𝟎.𝟔counts/keV-ton-yr or BI ∼3 counts/w1/2-ton-yr. Choice: BI ≡ BI0 = 1 count/w1/2-ton-yr requires 110 ton-yr cover <mββ>− 𝐈𝐇 11 Mton-yr cover <mββ>− 𝐍𝐇 Suppression in BI: [1 to 10−3] counts/(w1/2-ton-yr) contributes reduction in exposure BImin equivalently Σmin condition: Single observed event can establish signal at 𝐏𝟓𝟎 𝟑𝛔 Preferred hardware specification space Σ=10 ton-yr Next generation: BImin<5.1×10−5 counts/w1/2-ton-yr <mββ> > (5.8×10−3)eV <mββ>+ 𝐍𝐇= 4.3×10−3eV Be


Attoclock revisited on electron tunnelling time Cornelia Hofmann1,2, Alexandra S. Landsman1,3, Ursula Keller2 Attoclock Method [1-3] 1Max Planck Institute for the Physics of Complex Systems, 01187 Dresden, Germany 2Department of Physics, Institute of Quantum Electronics, ETH Zurich, 8093 Zurich, Switzerland 3Max Planck Postech/Department of Physics, Pohang, Gyeongbuk 37673, Republic of Korea [1] Hofmann, et al., http://arxiv.org/abs/1901.07015 [2] Eckle, et al., Science, 322, 1525-1529 (2008) [3] Landsman, et al., Optica 1, 343 (2014) [4] Dörner, et al., Phys. Rep. 330, 95 (2000) [5] Weger, et al., Opt. Express 21, 21981–21990 (2013) [6] Camus, et al., Phys. Rev. Lett. 119, 023201 (2017) [7] Wigner, Phys. Rev. 98, 145–147 (1955) [8] Fortun, et al., Phys. Rev. Lett. 117, 010401 (2016) [9] Sainadh, et al., http://arxiv.org/abs/1707.05445 [10] Bray, et al., Phys. Rev. Lett. 121, 123201 (2018) [11] Ivanov, Kheifets, Phys. Rev. A 89, 21402 (2014) [12] Hofmann, et al., New J. Phys. 18, 043011 (2016) [13] Teeny, et al., Phys. Rev. Lett. 116, 063003 (2016) [14] Ni, et al., Phys. Rev. A, 98, 013411 (2018) [15] Ivanov, et al., Comm. Phys. 1, 81 (2018) [16] Emmanouilidou, et al., J. Phys B: At. Mol. Opt. Phys. 48, 245602 (2015) [17] Majety, Scrinzi, J. Mod. Opt. 0340, 1–5 (2017) [18] Reiss, J. Phys B: At. Mol. Opt. Phys. 47, 204006 (2014). [19] Büttiker, Phys. Rev. B 27, 6178–6188 (1983) References Principle: final photoelectron momentum encodes moment when electron first entered the laser field dominated continuum Measurements: ● helium ionized by strong-field near IR ● ● Keldysh Parameter between 0.75 and 4 ● COLTRIMS [4] & VMIS [5] experimental setup ● random Carrier-Envelope-Offset phase ● observable: streaking offset angle of the photoelectron momentum distribution Other Experiments Krypton/argon Attoclock [6] ● Comparing streaking angle between two species ● gas mixture in COLTRIMS [4] ● Wigner trajectory [7] calculations with delay matches Non-Adiabatic Effects Dipole Approximation Summarized Influence on Attoclock Interpretation [1] Larmor time [19] and Feynman Path Integral method [3] yield estimates comparable to measured Attoclock tunnelling delays Acknowledgements Assumptions Single Active Electron (SAE) Time Reconstruction: ● Single Classical Trajectory (SCT) simulation assuming instantaneous tunnelling ● offset angle = ellipticity correction + delay BEC of rubidium atoms in optical lattice [8] ● kicked lattice → oscillating wave packet ● lattice turned off → instantaneous momenta mapped to location on detector ● D2 (tunnelled) is delayed compared to D1 (reflected) Atomic hydrogen Attoclock [9] ● Measurement compared to TDSE agree ● approximation for Coulomb scattering [10] ● TDSE with Yukawa potential: ● tunnelling delay ● ionisation time extracted from experiment Attoclock assumption ● tunnelling most probable when field is at maximum ● = peak of the pulse envelope = 0 approaches solving the TDSE ● probability current density [13] maximised at < 0 ● classical packpropagation after TDSE forward calculation [14] finds classical turning point ● instantaneous ionization rate depending on fluctuations of the strong field [15] contradicts = 0 → starting time before the peak of the envelope would result in even larger extracted tunnelling delays Post-ionization [16] ● classical trajectories ● 2 electrons (bound- free) yields same result as SAE assuming perfect screening Full process [17] ● TDSE calculation where one electron is allowed to ionise ● compared to SAE TDSE ● no electron correlation visible in the angular photoelectron momentum distribution ● agreement with non-adiab. calibrated measurement for time-dependent Schrödinger equation (TDSE) [11] ● initial transverse momentum → lower field strength calibration for same data [12] ● energy gain → shorter exit radius → still remaining offset angle difference ● near IR ≈ 800 nm wavelength ● Intensity below 8∙1014 W/cm2 → spatial dependence of the electric field neglected → magn


Acknowledgments & References The modeling study is partially funded by the Geological Society of America and American Association of Petroleum Geologist. We thank Husky Energy for the general support of our modeling lab. We also thank TGS/Nopec Geophysical Company, ConocoPhillips, Canadian Department of Natural Resources, Canada-Nova Scotia Offshore Petroleum Board, and Suncor Energy for providing the seismic data used in this study. A special thanks also goes to Schlumberger for providing Petrel, the software tool that we use to interpret the seismic data. Withjack, M. O. and Callaway, S., 2000. Active normal faulting beneath a salt layer: An experimental study of deformation patterns in the cover sequence. AAPG Bulletin, v. 84, no. , p. 627-651. Eisenstadt, G. and Sims, D., 2005. Evaluating sand and clay models: do rheological differences matter? Journal of Structural Geology, v. 27, p. 1399-1412. Withjack, M. O., Schlische, R. W., Olsen, P. E., 2010. Development of the passive margin of eastern North America - Mesozoic rifting, igneous activity, and breakup, in Roberts, D. G., and Bally, A. W., eds., Phanerozoic Regional Geology of the World. Summary & Future Work Thickness of clay layer affects deformation patterns Distribution of clay layer may affect deformation patterns Kinematic model of Orpheus rift basin Future Work The modeling results and strain analysis suggest that the internal clay layer underwent not only folding but also thickness changes during deformation. Model A (thin clay) Standard Model (Initial depth 1 cm) Model D (Initial depth 0.5 cm) Varying depth of clay layer Multiple internal clay layers Model C (thick clay) 1 2 3 5 3 km a Late Triassic ? 3 km c ROU ROU CAMP-related intrusions Buckle folds Detached thrust faults Latest Triassic - earliest Jurassic ? 3 km b Deposition of interbedded salt and salt impurites Late Triassic ? Late Rifting: Minibasins and CAMP Intrusion Middle Rifting: Upper Argo Formation Early Rifting: Lower Argo Formation ROU 4 (Left) Map showing early Mesozoic rift basins (green areas), including Orpheus rift basin, as part of eastern North American rift system formed during break-up of Pangea and general stratigraphy of the Orpheus rift basin. The Orpheus rift basin contains Late Triassic-Early Jurasssic salt of the Argo Formation. Note the presence of salt impurities within the Argo salt. ROU: Rift-onset unconformity; BU: Breakup unconformity; AvU: Avalon unconformity: CU: Cenozoic unconformity; CAMP: Central Atlantic Magmatic Province. Yellow line is the seismic line shown in this study. (Below) Similarities between modeling results (Model A) and structures in Orpheus rift basin. Similar to the models, buckle folds in the synrift section of the Orpheus rift basin are present adjacent to a sedimentary load (i.e., minibasin). Seismic line is 1:1 at 4.5 km/s. 5 km 1 s (TWTT) North South 5 cm Prerift Postsalt minibasin Postrift Synrift salt Igneous sheets Synrift presalt Comparison with Natural Examples Boudins Overturned folds Minibasin Upright gentle folds 400 km North Atlantic Ocean North America N Orpheus Basin modified from Withjack et al. (2010) Period PERMIAN & OLDER TRIASSIC Postrift Prerift Synrift EARLY JURASSIC & YOUNGER Late Early Mid Strati- graphy Tectonic Stages AvU CU BU CAMP Mini- basin ROU Argo Salt Preliminary Modeling Results: Models with various depth of internal clay Time: 5 hours 5 cm Standard Model (Putty:Clay = 4:1) Initial depth of clay layer: 1 cm Model C (Putty:Clay = 4:1) Initial depth of clay layer: 0.5 cm 5 cm Time: 5 hours 40 30 0 10 20 Extension (%) Strain analysis of the internal clay layer Line of equal value Shortening (%) 30 40 20 10 Standard Model Model A Model B Model C Strain Analysis Percentage of extension vs shortening of the internal clay layer in all models. The amount of shortening in all models is less than the amount extension. Zone of extension Zone of shortening % Extension or shortening = (Lf-Lo)/Lo x 100% Lf = Final Length; Lo = Ori


Hybrid genome assembly of the northern acorn barnacle, Semibalanus balanoides Rebecca Elyanow, Bianca Brown, Joaquin Nunez, David Rand Brown University, Center for Computational Biology, 115 Waterman st., Providence, RI 02906 III. Methods I. Introduction Assembly of Illumina data with SOAPdenovo VI. Conclusion References V. Genome size estimation VII. Future work Barnacles have long been recognized as good model organisms in the field of population ecology and have been well studied in this context. However, little is known about the genomic structure and evolution of barnacle species. The burgeoning field of ecological genomics aims to merge insights from the fields of ecology and genomics into a unified understanding of how a population has been shaped by its environment, from a cellular level to an ecological level. The goal of this project is to develop the northern acorn barnacle, Semibalanus balanoides, as a robust model for ecological genomics. The first step in achieving this goal is to create a draft genome for S. balanoides, which will provide a reference for any future genomic studies. Assembly Metrics Mapping of Illumina reads BLAST results 1. Estimate allele frequencies of barnacles from different microhabitats (high and low tide) through pool-sequencing. See poster 209 for preliminary work. 2. Identify bacterial species that compose microbiome of S. balanoides in different microhabitats. See poster 397 for preliminary work. 3. Perform transcriptome assembly using RNA-seq data and annotate functional sites on the genome 1305 2232 18455 20986 0 5000 10000 15000 20000 25000 SOAPdenovo dipSPAdes Canu DBG2OLC N50 ASSEMBLY N50 31 98 380 525 0 100 200 300 400 500 600 SOAPdenovo dipSPAdes Canu DBG2OLC GENOME SIZE (MB) ASSEMBLY Genome Size (Mb) 2.43 15.67 56.56 70.83 0 10 20 30 40 50 60 70 80 SOAPdenovo dipSPAdes Canu DBG2OLC PERCENT OF MAPPED READS ASSEMBLY Percentage of Illumina reads mapped to assembly II. What is hybrid genome assembly? Hybrid genome assembly is the process of joining raw sequencing data into long contigs using both short-read and long-read data. • Long-reads are easier to assemble than short reads because they contain long range information and can span repeats Short paired-end read from Illumina sequencing: 2x100bp Long-read from PacBio sequencing: 6,258bp • Short-reads have a much lower error rate than long reads (0.1% vs 10%) • By combining long and short-reads together, we leverage both the long-range information from long-reads and the low error-rate of short reads Assembly of Illumina data with dipSpades Assembly of PacBio data with Canu Hybrid assembly of Illumina and Pacbio data with DBG2OLC IV. Results Raw Illumina paired-end reads SOAPdenovo assembly Raw Illumina paired-end reads Raw PacBio SMRT Cell reads Canu error- correction Raw Illumina paired-end reads DBG2OLC assembly Raw PacBio SMRT Cell reads dipSPAdes assembly Sparc consensus calling Canu trimming Canu assembly • 237 million paired-end 85bp Illumina reads were assembled by dipSPAdes • dipSPAds is designed for diploid, highly polymorphic genomes • dipSPAdes assembles haplocontigs (representing both haplomes) then produces consensus contigs and performs haplotype assembly • 237 million paired-end 85bp Illumina reads were assembled by SOAPdenovo • Contigs longer than 1kb were selected • 3 million PacBio SMRT cell reads with an average length of 6kb were assembled with Canu • The MinHash Alignment Process (MHAP) is used to detect overlapping reads and correct errors • Non-confident regions are removed through trimming • Trimmed reads are assembled with the Celera assembler • 3 million PacBio SMRT cell reads and 237 million Illumina reads were assembled with DBG2OLC • DBG2OLC uses de Bruijn Graph (DBG) to construct contigs from Illumina reads, which are used to correct PacBio reads. Corrected PacBio reads are assembled using an Overlap Layout Consensus (OLC) • Parameter tuning increased the assembly size from 409Mb to 525Mb 0 0.1 0.2 0


The authors acknowledge support from the Climate Compatible Growth programme (#CCG) and the UK Partnering for Accelerated Climate Transition (UK PACT) programme of the UK's Foreign Development and Commonwealth Office (FCDO). The views expressed in this research do not necessarily reflect the UK government’s official policies. REFERENCES • UNESCO. 2021. ‘UNESCO Recommendation on Open Science’. SC-PCB- SPP/2021/OS/UROS. Paris, France: UNESCO. • Wilkinson, Mark D., Michel Dumontier, IJsbrand Jan Aalbersberg, Gabrielle Appleton, Myles Axton, Arie Baak, Niklas Blomberg, et al. 2016. ‘The FAIR Guiding Principles for Scientific Data Management and Stewardship’. Scientific Data 3 (1): 160018. • Open Data Charter. 2015. ‘International Open Data Charter’. opendatacharter.net. There is an increased recognition of the need for openness, transparency, and accessibility of both governance and technical aspects of long-term systems planning, including data to inform the planning process. In Kenya, the new constitution is pushing for reforms aiming at increasing the participation of institutions and county govt. into decision-making processes. This is valid for energy data management and governance. Hence, this paper investigates: how can an open data approach to data management and governance effectively support robust and inclusive long-term energy planning in Kenya? RESULTS Overlap of roles and responsibilities System Design: aiming for up-to-datedness, accuracy, security, and reliability. • Centralised system with controlled access, need for easy data aggregation/disaggregation function Transparency and Accessibility: • Positive: data as resource to support decision- making in society and create trust) • Critical: fear of data being misused, distorted, expose to scrutiny. Open Data value: positive, but with concerns (i.e. credibility, up-to-datedness, security). • Strengths: free and easy accessibility, good formatting, useful for complementing and validating existing datasets. • Weaknesses: highly aggregated, outdated, non- validated, non-credible. METHODOLOGY 1. Stakeholders’ mapping: National + County govt., energy utilities, statistical office, energy regulator, International Organisation 2. Qualitative Document Analysis • 2010 Constitution of Kenya • 2018 National Energy Policy • 2019 Energy Act 3. Semi-structured Interviews: • 10 stakeholders • focus on: system design, transparency and accessibility, the value of open data 4. Assessing the evidence against open science values and principles • UNESCO Recommendation on Open Science • Findable, Accessible, Interoperable, Reusable (FAIR) Data • International Open Data Charter (ODC) NEXT STEPS: UK PACT project, year 2 • Supporting stakeholders in identifying common datasets of interest and comfortable ‘degree of openness’ for data sharing • Prototyping an energy data repository DISCUSSION AND CONCLUSIONS Open data can address the following: supporting collaboration and simplified data processing; data accessibility, retrievability, and coherence; enabling accountability and citizens awareness. Main challenges: 1) contradictory understanding of what open data entails and how it can be realised in practice affects their suitability; 2) principles and practices differ and require to find compromises. Recommendations: • Need for further investigation as to what resources, expertise and infrastructure is available to handle energy data in Kenya. • Need for considering various degree of openness, as to best fit the Kenya context. County-level planning SIG Energy Data renewable energy data energy resources data energy infrastruct. data petroleum data renewable resources maps electricity T&D data County Governments Grid Operator(s) Cabinet Secretary National Government REREC EPRA Data Governance and Open Science in Energy Planning: A case study of the Kenyan ecosystem A. Beltramo, A. Leonard, J. Tomei, W. Usher Agnese Beltramo, Email: beltramo@kth.se Authors’ affiliations:


CONTACTS project-matel project_matel www.project-matel.eu Next generation of OEIC-based devices: wide-bandwidth, minimized losses & multifunctionality in miniaturized form factors Strengthening the EU's industrial capability in photonics and microelectronics Green and digital manufacturing approach fostering chemicals and waste minimization European strategic autonomy in OEICs Lowering the barriers for OEIC uptake by high- tech SMEs Expected Impacts To demonstrate and validate at TRL5 advanced OEICs for two applications: i) Display & Recreation: AR display featuring a 2D light source ii) Health: Biophotonic sensors. The EU-funded project “MatEl” consists of four pillars encompassing new integration schemes for (i) chip manufacturing (WP2), (ii) advanced materials integration on OEIC (WP3), (iii) Hybrid integration of advanced materials using laser based technologies (WP4) and (iv) PIC & IC packaging and assembly technologies in order to enable the development of two use applications (WP5). This will be achieved by consistently pursuing the following objectives: TECHNICAL OBJECTIVES AR AR display featuring a 2D light source for light-field with on-chip RGB lasers and OEIC-based demultiplexer. Bio-photonic sensors for reliable and low-cost detection of Covid-19 featuring integrated on-chip VCSEL at 850 nm and Graphene-based photodetector. BIO sensing APPLICATIONS Europe’s leading position in photonics and electronics can only be secured by adapting to the next generation of optoelectronic devices requirements: high performance, multi- functionality and cost efficiency in miniaturized footprint. These can only be achieved if novel schemes for on-chip integration emerge. Silicon nitride (Si3N4) is a promising candidate for optoelectronics applications; next to silicon photonics and indium phosphide, Si3N4 photonic integrated circuits have broad spectral coverage and low propagation losses. Still, Si3N4 itself has no active effect (except thermal tuning) and active functionality can be demonstrated either by integrating active components or active materials. The on-chip integration of III-V and II-VI semiconductors on Si3N4 is complicated and costly. The EU-funded project “MatEl” introduces a novel, on-chip integration scheme enabling accurate and fast alignment and bonding of any type of chip package on Si3N4. MatEl will combine laser transfer (LIFT) and laser soldering processes to demonstrate next-gen applications, which will accelerate the industrial adoption of hybrid optoelectronic integrated circuits (OEICs) - offering high-performance, multi-functionality and cost efficiency in a miniaturized footprint. MatEl’s innovative solution, enhanced by the monolithic integration of advanced materials – graphene and high-quality PZT, will thus be demonstrated for two selected next-gen devices at TRL5: CONSORTIUM 1- National Technical University of Athens, Heroon Polytechniou 9 Zographou Campus, 157 80 Athens, Greece 2- LIONIX INTERNATIONAL BV, Hengelosestraat 500, 7521 AN Enschede, Netherlands 3- PHIX BV, De Veldmaat 17, 7522 NM Enschede, Netherlands 4- GRAPHENEA SEMICONDUCTOR SL, Ps Mikeletegi 83, 20009 Donostia, Spain 5- SURFIX BV, Agro Business Park 2, 6708 PW Wageningen, Netherlands 6- AMIRES SRO, Na Okraji 335/42, 162 00, Praha 6, Czech Republic 7- PIEMACS SARL, Epfl Innovation Park, Batiment C, 1015, Lausanne, Switzerland 8- CREAL SA, Chemin De La Dent D'oche 1a, 1024, Ecublens, Switzerland K. Andritsos , M. Makrygianni , F. Zacharatos , S. Kamyar , E. Schreuder , R. Dekker , K. Obara , M. Milosevic , A. Centeno , A. Zurutuza , W. Knoben , M. Messina , M. Chopart , R. Pašek , S. Bagdzevicius , R. Matloub , P. Muralt , J. Gamet , A. Kvasov , I. Zergioti 1 1 1 1 2 2 3 3 4 4 5 6 6 6 7 7 7 7 8 2 MatEl: PZT and Graphene MATerials innovations for advanced opto-Electronic applications in AR and biosensing Acknowledgements: The authors would like to acknowledge funding from the EU Horizon Europe R&I programme under grant agreement 1010


The East African Lake Malawi haplochromine cichlid flock represents one of the largest and most diverse adaptive radiations on earth, with over 700 species of fish. It is an important model system with which to understand ecological diversification, sexual selection and speciation. Our analyses focused on four sympatric species of the endemic deep-water genus Diplotaxodon (fig. 1), previously found to differ significantly in morphology and male monochromatic nuptial color [1] and proposed as an example of sympatric speciation. Introduc)on Single digest RADseq (SbfI) 50 individuals; ~3.5M reads/ind 5 populations > 8 individuals per pop Methods Genomic diﬀeren)a)on among deep-‐water cichlid species References The genomic architecture of speciation in the Lake Malawi deep water cichlid genus Diplotaxodon Christoph Hahn & Domino Joyce School of Biological, Biomedical and Environmental Sciences, University of Hull 1. Genner et al. 2007. MolEcol. 2. Catchen et al. 2013. MolEcol. 3. Jombart & Ahmed 2011. Bioinformatics. 4. Brawand et al. 2014. Nature. 5. Conesa & Goetz. 2008. Int. J. Plant Gen. 6. Foll & Gaggiotti. 2008. Genetics. 7. Coop et al. 2010. Genetics. @EvoHull https://github.com/chrishah Acknowledgements This is a collaboration with Dr Martin Genner, and is funded by NERC grant number NE/ K000829/1. Principal data processing using STACKS [2], adegenet [3] and custom scripts (https://github.com/chrishah). Genome scans are based on the recently published genome of Metriaclima zebra [4]. Functional annotation of genes obtained using Blast2GO [5]. Fig. 2: Number of candidate outlier loci identified using STACKS [1], BayeScan [6], and Bayenv2 [7]. . Fig. 1: Principal component analysis (PCA) based on > 25,000 SNPs, differentiating the 4 putative Diplotaxodon species. . We used Principal Component scores (PC1) inferred from morphological data in [1] as proxy to specifically identify genomic regions associated with morphological differentiation between species (fig. 3). Normalized P C 1 s c o r e s w e r e u s e d a s ‘environmental factors’ in Bayenv2 [7]. Fig 3: Transformed bayes factor ranks averaged across 10 independent Bayenv2 runs. The vertical red line delimits the 95th average rank percentile as threshold for candidate loci. The inset shows the species wide PC1 scores [1] used as ‘environmental factors’ in the analyses. Divergent genomic regions between Diplotaxodon species are enriched for genes controlling craniofacial- eye development (see fig. 4). Our results indicate that the increasingly narrow, short wave- length light-spectra at greater water depths pose unique selective constraints and are likely key drivers of ecological and sexual selection and ultimately speciation in this group of Lake Malawi cichlids. Fig 4: (A-F) Pairwise divergence (FST) across three selected scaffolds. Displayed are observed values and kernel smoothed averages. Red dots represent candidate outlier loci identified by STACKS (p < 5e-7). Y axes range 0 < FST < 1. (A) Di_1 vs Di_2; (B) Di_1 vs Di_4; (C) Di_1 vs Di_5; (D) Di_2 vs Di_4; (E) Di_2 vs Di_5; (F) Di_4 vs Di_5. (G) Average transformed ranks inferred from the ‘morphology informed’ Bayenv analyses (fig. 3). Red dots represent average ranks in the 95th percentile. D. limnothrissa black pelvic (Di_2) D. macrops black dorsal (Di_1) D. macrops ngulube (Di_5) D. macrops offshore (Di_4) c.hahn@hull.ac.uk A B C D E F G Fig. 4 (contd): Rectangles at the bottom represent genes within 15kb windows of candidate outlier SNPs (craniofacial- or eye development). X axes scale: 100kb/tick. Find it on figshare


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.


Innovative Research for a Sustainable Future www.epa.gov/research Richard Judson l email: judson.richard@epa.gov l 919-449-7514 Retrospective Mining of Toxicology Data to Discover Multispecies Effects: Anemia as a Case Study Richard Judson, Charles Wood, Grace Patlewicz, Jeremy Fitzpatrick, Matt Martin U.S. Environmental Protection Agency, Office of Research and Development Introduction Methods Results 1: Database Summary Results 2: Individual Chemicals Conclusions Retrospective inspection of In vivo toxicology data is subject to multiple sources of uncertainty: 1. Lack of control of some key experimental variables: Variability of animals even within the same strain, exact details of diet and animal handling protocols, etc. 2. Statistical issues: Studies are rarely repeated so that experiment-to- experiment variability is rarely characterized. The number of animals used in each dose group may be insufficient to see rare events, etc. 3. Negative results and effects not measured can be hard to distinguish: In guideline studies, specified effects should be examined, and any treatment- related effects recorded. However, this may not be always followed, and some effects not specified by the guidelines may be recorded when seen. 4. Observer bias: When a severe type of toxicity is seen (e.g. a neoplastic lesion), less severe or benign (but treatment-related) effects may be ignored, or not recorded, or recorded in a limited way. Similarly, differences in lesion thresholds among pathologists may influence treatment-related effects. 5. Variability over time in terminology: While this can be managed somewhat by the use of controlled vocabulary onto which the original effect descriptions can be mapped, there are cases where effects are better understood as time goes on and one original term is split into two, so that the exact effects seen in earlier studies are obscured. 6. Transcription errors: In the process of transcribing data from notebooks to initial study reports to published study summaries to a multi-chemical database, there will be transcription errors. 7. Interpretive issues: When data across multiple studies are collated, contextual information such as incidence, severity, dose, or effect groupings may be lost. Goal: Conduct a case study of these issues for chemically-induced anemia. This poster does not necessarily reflect U.S. EPA policy U.S. EPA ToxRefDB Guideline Acceptable CHR (rat, mouse, dog), SUB (rat) 658 chemicals, 1738 studies 441 studies: anemia-positive Harmonize terminology Anemia ≥ 2 / 3 decrease RBC (red blood cell count) HGB (hemoglobin) HCT(hematocrit) Review original reports for all studies in all chemicals with 2 species anemia-positive Clean database: 49 chemicals Studies mechanistically classified Figure 1: Fraction of tested chemicals showing anemia below doses where body-weight decreases are seen (black, bottom), at doses where body-weight decrease is seen (dark gray, middle), and where anemia is not seen (light gray, top). The numbers indicate the total number of chemicals in the database for each species / study-type combination. After manual review DB class Positive Negative Ambiguous Unknown Before manual review Positive 212 2 4 0 Negative 24 128 11 24 Ambiguous 6 2 16 0 Table 1: Concordance between initial database entry and results of manual review. Each cell contains the number of studies in each class before and after the review. Positive (2 or more of RBC, HGB, HCT), Negative (0), Ambiguous (1), Unknown (manual review found that hematology values were not measured in the study). species / study 1 species / study 2 Reproduced Not Reproduced Fraction reproduced rat SUB rat CHR 18 2 0.90 rat CHR dog CHR 13 2 0.87 rat CHR rat SUB 18 4 0.82 rat SUB rat SUB 16 4 0.80 rat SUB dog CHR 11 4 0.73 mouse CHR rat CHR 11 4 0.73 mouse CHR rat SUB 13 7 0.65 dog CHR rat SUB 11 6 0.65 dog CHR rat CHR 13 8 0.62 rat CHR mouse CHR 11 11 0.50 mouse CHR dog CHR 6 6 0.50 rat SUB mouse CHR 13 14 0.48 dog CHR mouse CHR


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


Rapid alignment of text to the UMLS and integration into a VIVO repository Stony Brook Medicine Janos G. Hajagos Acknowledgements: The Stony Brook Medicine SUNY Reach team created the infrastructure and generated the data used in this analysis. Members of the team include: Erich Bremer, Barbara Chandler, Moises Eisenberg, Jizu Zhi, Tammy DiPrima, and Andrew White. A prototype disproportion- ate analysis tool was developed by Alex Schultz. This is an extension of work supported through CTSAconnect. CTSA 10-001: 100928SB23 Uniﬁed Medical Language System (UMLS) The goal of this research is to extract SUIs (String Unique Identiﬁers) from text associated with a faculty member‘s VIVO proﬁle. SUIs unlike CUIs (Concept Unique Identiﬁers) do not have a conceptual meaning. A single SUI can be linked to several concepts. As an example, below the SUI (S0004723) is linked to two diﬀerent CUIs (C0580209 & C1302752). It is diﬃcult for any automated system to determine with 100% accuracy the contextual meaning of a word or a phrase. The approach taken here is to utilize the sta- tistical patterns in the data to automate the process of tagging large quantities of text. With SUIs there is still a path on the graph to a conceptual meaning. . An extract from MRCONSO showing the relationships between SUIs and CUIs The SUNY REACH site <http://reach.suny.edu/> and the data set Generating RDF for import into VIVO The VIVO 1.5 ontology around research area Identifying what fragments make a researcher unique For the analysis the UMLS release 2012ab was utilized. Stony Brook maintains a SPARQL endpoint: http://link.informatics.stonybro ok.edu/sparql/ A short text alignment service: http://link.informatics.stonybro ok.edu/MeaningLookup/ To align MeSH CUIs and get abstracts and titles from articles two web services (2013 XML): http://link.informatics.stonybro ok.edu/weaver/pubmed2cuis?p mid=21325273 and http://link.informatics.stonybro ok.edu/weaver/pubmed2abstra ct?pmid=10343245 Filter fragments through a UMLS source vocabulary Sample alignment results NCIt is a source vocabulary Breaking text into fragments Natural language processing, abbreviated as NLP, is an active area of research and devel- opment. NLTK is a well supported NLP toolkit for the Python language. There is even a free book: <http://nltk.org/book/>. The following features were utilized: parsing paragraphs into sentences, parsing sen- tences into words, and removing common stop words. Phrases were matched up to the length of fours words. Only a small subset of the features of the NLTK were used in this research. Utilizing NLTK in the iPython shell How well did the raw alignment method work? Excerpt from the VIVO faculty member’s html page: “During the last several years, he has focused his eﬀorts on the prevention of colon cancer using traditional NSAIDs, NO- donating NSAIDs and other pharmacologi- cal agents. He has also pioneered the appli- cation of infrared spectroscopy to biology with emphasis on cancer holding several relevant patents. A new area of work con- cerns the use of nanotechnology in the pre- vention of cancer.” Terms extracted from the article abstract Terms extracted from article titles MeSH from Medline expert tagged articles Comparison for a single VIVO faculty member Number of articles with abs tracts Number of faculty Number of matched fragments Number of s entences 48,893 621,686 521 5,686 Number of articles Number of faculty Number of matched fragments 216,842 683 22,372 Number of MeS H Number of articles Number of faculty 706 21,954 351,273 Counts on analyzed abstracts Counts on analyzed article titles Counts on Medline MeSH Overall top phrases extracted from article abstract Disproportionate or Market Basket Analysis 1. Compute all possible combination of fragments within a sentence that do not overlap 2. Aggregrate the co-occurrence of the two fragments (pair count) 3. Count the number of times each fragment occurs overall (total fragment count) 4. Calculate the


0.001 0.01 0.1 1 10 0 50 100 150 200 Flux Density [Jy/arcsec2] Radius [au] Notsu+2019 Band7 0ï360deg Isella+2018 Band6 0ï360deg 1 10 100 r [AU] 0 0.2 0.4 0.6 0.8 z/r 101 102 103 50K 300K 1000K H2O gas Central Star Grain growth and destructions Grain falling Silicate＋ H2O ice Silicate H2O snowline    H2O freeze    H2O evaporation 1 10 100 r [AU] 0 0.2 0.4 0.6 0.8 z/r 10-12 10-11 10-10 10-9 10-8 10-7 10-6 10-5 10-4 nH2O,gas/nH Photo- dissociate H2+OH->H2O+H freeze-out Water and 13C17O lines, and multiple ring and gap structures of the protoplanetary disk around HD 163296 observed by ALMA Shota Notsu1,2 (shota.notsu@riken.jp), Alice S. Booth2,3, Catherine Walsh3, John D. Ilee3, Eiji Akiyama4, Hideko Nomura5, Tomoya Hirota5, Takashi Tsukagoshi5, Mitsuhiko Honda6, T. J. Millar7, Chunhua Qi8 1 Star and Planet Formation Laboratory, RIKEN, Japan 2 Leiden Observatory, Leiden University, The Netherlands 3 University of Leeds, UK 4 Niigata Institute of Technology, Japan 5 NAOJ, Japan 6 Okayama University of Science, Japan 7 Queen’s University Belfast, UK, 8Harvard/CfA, USA Observationally locating the position of the H2O snowline (e.g., Hayashi et al. 1981, 1985) in protoplanetary disks is crucial for understanding the dust evolution and planet formation processes, and the origin of water on the Earth. The velocity profiles of emission lines from disks are usually affected by Doppler shift due to Keplerian rotation. Therefore, the line profiles are sensitive to the radial distribution of the line-emitting regions. In our previous works (Notsu et al. 2016, ApJ, 827, 113; 2017, ApJ, 836, 118; 2018, ApJ, 855, 62), we calculated the chemical composition of the disks around a T Tauri star and a Herbig Ae star using chemical kinetics and various water line profiles. We found that the water lines with small Einstein A coefficients and relatively high upper state energies are dominated by emission from the hot midplane region inside the H2O snowline, and therefore through analyzing their line profiles the position of the H2O snowline can be located. Since the fluxes of these lines from Herbig Ae disks are larger than those from T Tauri disks, the possibility of a successful detection is expected to increase for a Herbig Ae disk. There are several best candidate water lines that trace the position of the H2O snowline within the coverage of ALMA. Recently, we got the upper limit fluxes of submillimeter ortho-H216O 321 GHz, para-H218O 322 GHz, and HDO 335 GHz lines from the disk around the Herbig Ae star HD 163296, using ALMA (Notsu et al. 2019, ApJ, 875, 96). These water lines are considered to be the candidate water lines to locate the position of the H2O snowline, based on our model calculations. We compared the upper limit fluxes with the values calculated by our model calculations with dust emission, and we constrained the line emitting region and the dust opacity from the observations. We also detected multiple ring and gap patterns in the 0.9 mm (ALMA Band 7) dust continuum emission with 15 au spatial resolution, whose positions are consistent with those indicated by other observations (e.g., Isella et al. 2018). Future observations of the submillimeter water lines with longer observation time are required to clarify the position of the H2O snowline in the disk midplane. In addition, we also detected the rarest stable CO isotopologue, 13C17O, in a disk for the first time (Booth et al. 2019, ApJL, 882, L31). We compared our observation with the existing detections of other CO isotoplogues in the HD163296 disk. We found that this line is optically thin within the CO snowline and will be thus a robust tracer of the bulk disk CO gas mass. We showed that this disk will be 2-6 times more massive than previously estimates. Aul Eup nu Elow nl Aul : Einstein A coefficient [s-1] Eup: Energy in upper state [K] r z obs. s i nu & nl：LTE distribution (snowline tracer: OK) Φ(ν)：emission profile (Kepler & thermal velocity) τul：optical depth (H2O