fairdataihub/poster-sentry-training-data huggingface dataset:
observation network: a ground truth for ultra-high resolution satellite SST in the Mediterranean nearshore and coastal ocean CAL/VAL for the highly dynamic nearshore areas: cost-effective design ? Nathaniel Bensoussan1, Vincent Rossi1, Christel Pinazo1, Joaquim Garrabou1,2 and T-MEDNet network Successful Coastal Climate Change Observation Network Build and maintain an operative and cost-effective climate change coastal observation network based on collaborative approaches Ground truth for UHR SST? Make the most of in-situ and UHR satellite SST for marine conservation and coastal management Source: Joint analysis of CMEMS EO and T- MEDNet data series. Copernicus OSR#3. TEMPERATURE HF Water column Build relevant data sets for CAL/VAL at the appropriate granularity in the highly dynamic coastal and nearshore areas. Joint analysis of satellite-in-situ data to enhance knowledge on coastal thermal regimes and heat stress while investigating surface to depth connections. Explore the role of fine scale processes in the modulation of marine heatwaves and ecological impacts. Informed science evidence-based conservation strategies to face climate change challenges in coastal area over broad ecological and socio-economics settings. [23 Marine Protected Areas] BUILDING SYNERGIES 2007- 2016 A decade of accelerated SST warming Ocean Warming ULTIMATE GOAL Marine 2017 HEATWAVES # Collaborative observation network Joining local actions in pan- Mediterranean Observation Network # Unique long-term coastal T° series around the Mediterranean Sea • Baselines on thermal regimes • Seasonal cycle • High-frequency dynamics 16 SUSTAINED COOPERATION [17 Marine Res. Labs] Fill knowledge gaps on coastal thermal regimes: long-term and high-frequency time series • Sustained observations Downwelling Upwelling • Across environmental and variability gradients Source: Bensoussan et al. (2019) Copernicus Ocean state report #3, using CMEMS L4REP at 4 km 20 000 000 70 STANDARD PROTOCOLS – Essential Climate, Ocean and Ecosystem variables Box 1 Box 1 Accuracy: 0.21°C Resolution: 0.01°C 2004 2006 2008 2010 2012 2014 2016 2018 Year Depth (m) nbensoussan@gmail.com 1Mediterranean Institute of Oceanography, MIO-AMU-CNRS-IRD, Marseille, France 2Institute of Marine Science, ICM-CSIC, Barcelona, Spain 40
10 0 10 1 10 2 10 3 0 0.25 0.5 log size of signal subgraph misclassification rate incoherent estimator ˆL n b=0.41 ˆL i nc=0.27 ˆL ˆπ = 0.5 size of signal subgraph # signal−vertices coherent estimator ˆL c oh=0.16 200 400 600 800 1000 10 20 30 0.16 0.3 0.4 0.5 10 0 10 1 10 2 10 3 0 0.16 0.25 0.5 log size of signal subgraph misclassification rate some coherent estimators size of signal subgraph # star−vertices zoomed in coherent estimator 400 500 600 15 18 21 0.16 0.3 0.4 0.5 coherent signal subgraph estimate vertex vertex 20 40 60 20 40 60 threshold coherogram 0.04 0.14 0.29 0.55 20 40 60 0 10 20 30 10 0 10 1 10 2 10 3 0 0.25 0.5 0.75 1 log size of signal subgraph misclassification rate incoherent estimator size of signal subgraph # star−vertices coherent estimator 200 400 600 800 1000 10 20 30 0.18 0.3 0.5 0.7 0 20 40 60 80 100 0 0.5 1 # training samples missed−edge rate 0 20 40 60 80 100 0.1 0.2 0.3 0.4 0.5 # training samples misclassification rate coh inc nb Connectome Inference • MR Connectome Automated Pipeline (MRCAP) [1] to infer connectomes • Vertices are neuroanatomical gyral regions [3], edges are estimated tracts using FACT [4] • 49 subjects from the Baltimore Longitudinal Study on Aging; 25 male, 24 female The top two panels depict the relative performances of the incoherent (left) and coherent (right) classiﬁers as a function of their hyper- parameters. The middle two depict misclassiﬁcation rate (left) for a few different choices of # of signal vertices and (right) a zoomed in depiction of the top right panel. The bottom left panel shows the estimated signal subgraph, and the bottom right shows the coherogram. Together, these bottom panels suggest that the signal subgraph for these data is neither particularly coherent or incoherent. (below): The figure below visualizes the twelve signal subgraph nodes. Each subplot shows the signal subgraph induced by one of the 12 signal vertices estimated using the coherent classifier. There are 360 edges in the signal subgraph. Synthetic Data Analysis • Simulations as true to real data as possible suggest model is not wholly unreasonable • Even under true model, we only expect about 50% of the identiﬁed edges are true signal edges with <50 samples • With only a few more samples, both misclassiﬁcation rate and missed-edge rate drop precipitously Model & Classiﬁer • Joint graph/class model • Each edge is an independent binary random variable • A subset of edges comprise the signal subgraph • Bayes plug-in classiﬁer is asymptotically optimal • Robust estimators have better convergence properties than the MLE Connectome Classification: Statistical Graph Theoretic Methods for Analysis of MR-Connectome Data Joshua T. Vogelstein1, William R. Gray1,2, John A. Bogovic1, Susan M. Resnick3, Jerry L. Prince1, Carey E. Priebe1, R. Jacob Vogelstein1,2 1Johns Hopkins University, 2Johns Hopkins University Applied Physics Laboratory, 3National Institutes of Health http://openconnectomeproject.org | {joshuav, willgray}@jhu.edu Monday, November 14, 11
Age-relations for low-mass stars Rocio Kiman (1,2,3), Jacqueline K. Faherty (2), Kelle L. Cruz (1,2,3,4), Jonathan Gagné (5), Ruth Angus (2,4,6), Sarah J. Schmidt (7), Andrew W. Mann (8), Daniella C. Bardalez Gagliuﬃ (2), and Emily Rice (1,2,9) 1) Graduate Center, City University of New York (CUNY), 2) American Museum of Natural History, 3) Hunter College, CUNY, 4) Center for Computational Astrophysics, Flatiron Institute, 5) Université de Montréal, 6) Columbia University, 7) Leibniz-Institute for Astrophysics Potsdam, 8) The University of North Carolina at Chapel Hill, 9) Macaulay Honors College, CUNY I. We are entering a new era that requires low-mass star ages II. While M dwarfs ages are extremely difﬁcult to calculate, we found 892 age-calibrators III. We found the ﬁrst empirical age-activity relation for Hα emission for M dwarfs IV. Future work: By combining different age-indicators in a Bayesian algorithm we plan to improve the estimation of M dwarf ages. https://rkiman.github.io/ M dwarfs are the most numerous stars in the Galaxy1 and are likely to host most small, rocky, and potentially habitable Earth-like exoplanets2 As the ideal exoplanets to characterize are the ones with known age, knowing the age of the host M dwarfs is key to taking full advantage of legacy missions such as TESS, JWST and the Nancy Grace Roman Space Telescope. As current available methods cannot be used to estimate M dwarf ages, empirically-calibrated relations for age-related properties are needed. We compiled a calibration sample of M dwarfs with Hα line strength measurements from the literature: 871 members of young associations identiﬁed with Banyan Σ3: 21 co-moving with white dwarfs with ages calculated using wdwarfdate4 We found: • The active fraction changes with mass and with age. Its evolution changes according to color. • The Hα line strength decreases with increasing age for M dwarfs. • We ﬁt the age-activity relation with a broken power-law, but we did not have enough stars to precisely constrain the braking point or the slope of the decrease after 1 Gyr. References: 1) Bochanski et al. 2010, AJ, 139, 2679; 2) Dressing & Charbonneau 2015, ApJ, 807 3) Gagné et al. 2018, ApJ, 856, 23 4) Kiman et al. in prep. With a proof of concept using a simulated star we show that the age estimation improves (blue) when combining Hα line strength (orange), kinematics (green) and rotation period (red).
A IMPACT OF VESSEL TRAFFIC ON UNDERWATER SOUNDSCAPE AND MARINE MAMMALS IN THE PEARL RIVER DELTA Man Ieng Wong 1 Lindsay Porter 2 Miguel Repas Goncalves 3 Raquel O. Vasconcelos 1 1 Institute of Science and Environment, University of Saint Joseph, Macau S.A.R., China (raquel.vasconcelos@usj.edu.mo) 2 Southeast Asia Marine Mammal Research, Hong Kong S.A.R, China. 3 Strix, Portugal Presence of Indo-Pacific Finless Porpoise did not change after cessation Comparison of mean ± SEM of DPM of Indo- Pacific Finless Porpoise in dry and wet seasons before and after high-speed ferry cessation (Student’s t-tests, n.s.) Hong Kong - On 04.02.2020 the Hong Kong- Macau high-speed ferry service stopped due to the COVID-19 pandemic. This is believed to have significantly changed the aquatic soundscape of South Lantau Island. We aim to investigate the changes in marine biodiversity and occurrence of the Indo- Pacific finless porpoise and the Indo-Pacific humpback dolphin in Hong Kong waters associated with high-speed ferry cessation. Method Between January 2019 and January 2021 we collected 1,372 daily recordings from Passive Acoustic Monitoring stations (SoundTrap ST300HF, Ocean Instruments, NZ) deployed at 6 locations in Mong Tung Wan, Tai Lo Chau, Fan Lau and Peaked Hill. Locations were selected based to their proximity to the Hong Kong-Macau high- speed ferry lane. Acoustic Entropy (H) and Acoustic Complexity Index (ACI) were used as proxies for biodiversity changes using R/Seewave 2.1.6. Detection Positive Minutes (DPM) were used to measure presence of cetaceans (clicks and whistles) using PAMGuard 2.01.05. Our greatest gratitude goes to WWF Hong Kong for providing recording data to make this project feasible. MIW and ROV research supported by FDCT, Macao. The waters of Hong Kong S.A.R. are home to the Indo-Pacific Finless Porpoise (Neophocaena phocaenoides) and the Indo- Pacific Humpback Dolphin (Sousa chinensis) which depend on sound to communicate and for orientation. However, these species are exposed to noise pollution from heavy marine traffic and construction activities. Presence of Indo-Pacific Humpback Dolphin increased after cessation Comparison of mean ± SEM of DPM of Indo- Pacific Humpback Dolphin in dry and wet seasons before and after high-speed ferry cessation (Student’s t-tests, *: p<0.05; n.s.) This work is the first attempt to determine the impact of noise pollution on two key resident marine mammal species in one of the busiest estuaries of the world, as well as to evaluate the potential application of ecoacoustic metrics in assessing habitat biodiversity in the Pearl River Delta. Biodiversity changed after cessation Comparison of median ± 95% CI of ACI and H index before and after high-speed ferry cessation (Mann-Whitney test, ** p<0.01, *** p<0.0001). A significant change in the ACI and H values after ferry cessation suggests increase in biodiversity and soundscape complexity. *** ** *** *** *** ** * *
MATERIALES Y MÉTODOS Las prácticas agroforestales como mecanismo de adaptación al cambio climático Mosquera-Losada MR1*, López-Díaz ML2, Ferreiro-Domínguez N1, Rodríguez-Rigueiro FJ1, Arias Martínez D1, Santiago-Freijanes JJ1, Coello J3, Papadopoulou P4, Rigueiro-Rodríguez A1 1Escola Politécnica Superior. USC. Campus de Lugo. Benigno Ledo s/n. 27002, Lugo, España; 2 Centro Universitario de Plansencia. Universidad de Extremadura. Virgen del Puerto 2, 10600, Plasencia, España; 3Centro Tecnológico Forestal de Cataluña, Ctra. de St. Llorenç de Morunys, Solsona, España; 4Faculty of Agronomy University of Thessaloniki, 54124, Thessaloniki, Greece *mrosa.mosquera.losada@usc.es RESULTADOS (GALICIA) CONCLUSIÓN: Existe una importante variabilidad genética que debe ser evaluada y que permite al agricultor, tras una adecuada selección y uso, una mejor adaptación al cambio climático y por ende incrementar la resiliencia de sus explotaciones. AGRADECIMIENTOS Investigación financiada por el Programa de Desarrollo e Innovación H2020 a la red temática europea Agroforestry Innovation Networks (AFINET, nº727872), el Ministerio de Economía y Competitividad (CTM2016-80176-C2-1-R) con nombre “Sistemas agroforestales para la producción de cereal como estrategia de adaptación y mitigación al cambio climático en el ámbito de la península ibérica” (AGFCLIMA) y la XUNTA DE GALICIA, Consellería de Cultura, Educación e Ordenación Universitaria (“Programa de axudas á etapa posdoutoral DOG nº122, 29/06/2016 p.27443, exp: ED481B 2016/071-0”). Este trabajo se llevó a cabo por la USC para contribuir a los objetivos de la Global Research Alliance sobre gases de efecto invernadero en la agricultura (www.globalresearchalliance.org). La información mostrada no debe ser considerada como que representa el punto de vista de la Alianza en global o sus representantes. - Cataluña - Extremadura - Galicia INTRODUCCIÓN Los eventos extremos asociados al cambio climático pueden causar la destrucción de la cosecha. Los sistemas agroforestales, específicamente los silvoarables, han demostrado ser un sistema de uso sostenible de la tierra que favorece la adaptación al cambio climático. Sin embargo, la sombra generada por el arbolado puede reducir la productividad del cultivo. OBJETIVO Evaluar en tres condiciones climáticas distintas (Extremadura, Galicia y Cataluña) la capacidad de diferentes variedades de cereales a adaptarse a condiciones de sombra. En la fase de invernadero se sembraron diferentes variedades de cereales (diseño de bloques al azar) en condiciones de plena luz y de sombra artificial (30 y 50%) Las variedades mejor adaptadas a las condiciones de sombra en el invernadero se establecieron en el campo bajo especies arbóreas de diferente edad Los resultados se analizaron con ANOVA INVERNADERO - Cebada - Triticale - Trigo Maíz, centeno y trigo CAMPO - Extremadura (Nogal, Encina) - Galicia (Nogal , Castaño) - Cataluña (Nogal) NOGAL CASTAÑO
Tool Studies 2.0 Zum Potenzial von Trans­ formern für die Erkennung und Klassifikation von Soft­ ware-Tools in DH-Publikationen VON KNOCHEN 1. Digitale Tools und die Digital Humanities? Software-Tools spielen in den Digital Humani­ ties eine zentrale Rolle, ja, sind geradezu gen­ re-prägend für diese Disziplin. Aufbauend auf Vannevar Bushs früher Vorstellung von Maschi­ nen als “Erweiterungen des menschlichen Geistes” und J. C. R. Lickliders Folgekonzept ein­ er “Mensch-Computer-Symbiose” ist deren Rolle und ihre erkenntnistheoretischen Implikationen immer wieder diskutiert worden. 2. Forschungsansatz Ziel der Forschung ist die Ana­ lyse von Toolnennungen in den Digital Humanities und deren Zusammenhänge in der Wis­ senschaftsdisziplin. RAUMSCHIFFEN* ZU 3. Von Daten zu Trainingsdaten 4. Klassifikationsmodelle 5. Erste Einsätze der Modelle Manuel Burghardt, Nicolas Ruth, Andreas Niekler Computational Humanities Group, Universität Leipzig 3737 englische Veröffentli­ chungen aus drei DH Jour­ nals, veröffentlicht zwis­ chen 1966 und 2020. Durch die Synthese ver­ schiedener Toolsammlungen (z.B. TaPOR) wird eine manuell gesäuberte Liste von 246 gängigen Tools erzeugt, die möglichst keine ambigen Namen enthält. Mit Hilfe der Liste und einer Wör­ terbuch-basierten Suche werden Das Labeling teilt sich in zwei Ansätze. Binär: Tool vs. Kein Tool Mehrklassig: Toolober­ kategorie einer Taxono­ mie Finale Datensätze Binär 11.211 Negativ- und 7.687 Positivbeispiele Um Korpora nach Toolnennungen durchsuchen zu können, muss ein Klas­ sifikakationsmodell entwickelt werden. Naive Ansätze erwiesen sich als un­ tauglich. Das kontextsensitive Potenzial von Transformer-basierten Sprach­ modellen muss erprobt werden. Sprach­ modell RoBERTa Fine-tuning binär Fine-tuning mehrklassig 0,99 0,94 - 0,99 F1 F1 Sequenz, Label – Paare erzeugt. Die Sequenzen bestehen aus {15 to­ kens, tool, 15 tokens} Im Folgenden wurde der initiale Datensatz aus 3737 Publikationen per Sliding Window in 750.210 Sequenzen geteilt und diese mit beiden Modellen klassifi­ ziert. Bei 1,93% wurde eine Toolnennung erkannt. Mehrklassig no_tool: 11.211 Programming Lan­ guages/Packages: 2102 Text Analysis Tools: 1325 ... (text analysis, plattforms and communication, program­ ming languages, ...) {...} Binär Toolnennungen erkennen und Tools extrahieren Erweiterung von TaPOR Mehrklassig 1970 1980 1990 2000 2010 Welche Toolkategorien sind wie dominant im Laufe der Zeit? 2020 1970 1980 1990 2000 2010 2020 text analysis tools network analysis tools visualization tools platforms and communication exhibition, collection & edition plat­ forms authoring, annotation, editing, pub­ lishing platforms programming languages Stanley Kubricks 2001: A Space Odyssey behandelt in seiner Passage Dawn of Man auf essayistische Weise die Beziehung zwischen Mensch und Werkzeug. In einer zentralen Sequenz verwandelt sich ein Knochen zu ei­ nem Raumschiff und visualisiert damit diese Verhätlnis. *
Unified access to cancer proteogenomics data Caleb M. Lindgren, Hannah Boekweg, David W. Adams, Sadie Tayler, CPTAC Investigators, Samuel H. Payne Department of Biology, Brigham Young University, Provo, UT, USA Abstract We present a new method for data sharing across large collaborations to improve reproducibility and transparency, by creating a Python package that serves as an interface (API) to the multi-omics characterization of tumors from NCI’s CPTAC program. Introduction Cancer data has many audiences, including clinicians, biologists, data scientists and patients. Sharing data and analyses across these diverse audiences is challenging. In particular, we want to simplify the link between data and analysis scripts to enable easier data exploration. We embed NCI’s CPTAC data into a software API. Each tumor type describes samples with clinical, omics, and imaging data. Conclusions The cptac Python package brings cancer data to dispersed collaborative groups. Our package incorporates multiple data sets and lowers the entry barrier, expanding our audience while improving reproducibility and transparency. Acknowledgments: National Cancer Institute (NCI) CPTAC award U24 CA210972. Contact: calebmlindgren@gmail.com; hannahboekweg@gmail.com; sam_payne@byu.edu https://payne.byu.edu github.com/PayneLab @byu_sam Results A Python package, cptac, facilitates access to all CPTAC data. Using the package as the single point of data access unifies and simplifies analysis methods across diverse consortia. Current tumor types include: colon, ovarian, endometrial, renal, breast, lung adeno, glioblastoma and head/neck. Comparing clinical attributes Comparing histology with acetylation Mutation effects on the proteome Comparing multi-omics data Features ●One step installation via pip ●Consistent data and formats across cancers ●Data presented in Pandas dataframes, meaning no need for writing parsers ●API facilitates joining across data types ●Seamlessly works with numeric and graphing libraries (numpy, pandas, matplotlib, seaborn, etc.) ●Versioned data releases ●Package automatically checks that it's up to date, and that the latest version of the data is installed Loading data tables
Chungnam National UniversityThemeasurementsystemwasconstructedwithaPTOtorquemeter(PTOFlansch,SerialNo.70246,MicroManner,Germany)usingatelemetrymethodtomeasurethetorqueandrotationspeedofthePTOdrivingshaftMETHODSRESULTSDept. of Biosystems Machinery Engineering, Chungnam National Univ. BackgroundObjectiveAgricultural tractorSimulation softwareSeverity Analysis of 75kW Agricultural tractorPTO gear Using a field dataMeasurement systemSafety factor simulationMethodField dataPTOgeardesignforagriculturalapplicationsusestheempiricalmethodbecauseofthewiderangeofloadfluctuationsinagriculturalfieldThePTOgearisanimportantpartoftheagriculturaltractorthattransmitsthepowertovariousimplementsThefielddatameasuredduringtherotarytillagewastransformedintotheequivalenttorqueandequivalentrotationspeedField data during rotary tillage and baler operation was obtained through a sensor attached on the PTO shaftWhen the PTO gear is designed, considering the field operation type and severity is necessaryThe maximum, minimum, and average torque and standard deviation during the rotary tillage are 258.17, 0.01, 100.40, and 47.92 Nm. The rated torque of the 75kW agricultural tractor is 269.87 Nm. In addition, the maximum, minimum, and average rotation speed and standard deviation during the rotary tillage are 2555, 1971, 2372, 123 rpm.ThecontactandbendingsafetyfactorsofthePTOdrivinggearanddrivengearduringbaleroperationaregreaterthanthoseduringtherotarytillageandattheratedtorqueKim, Y.J., Chung, S.O., Park, S.J., Choi, C.H., 2011a. Analysis of power requirement of agriculturaltractor by major field operation. J. Biosyst. Eng. 36 (2), 79–88.Kim, Y.J., Lee, D.H., Chung, S.O., Park, S.J., Choi, C.H., 2011b. Analysis of power requirement ofagricultural tractor during baler operation. J. Biosyst. Eng. 36 (4), 243–251.Lee, D.H., Kim, Y.J., Chung, S.O., Choi, C.H., Lee, K.H., Shin, B.S., 2015. Analysis of the PTO load ofa 75kW agricultural tractor during rotary tillage and baler operation in Korean upland fields.J.Terramech. 60, 75-83.A PTO gear was modeled using Romax_Designerand simulated using real field dataThe contact safety factor of the PTO gear during rotary tillage is 1.32 times greater than that during baler operation, while that at the rated torque is 1.53 times greater. The bending safety factor during rotary tillage is 1.62 times greater than that during baler operation, while that at the rated torque is 2.11 times greaterSimulation conditionEquivalenttorque(Nm)Equivalent speed(rpm)Rotarytillage156.552334Baleroperation115.582367Ratedcondition269.872300Equivalent torque෍෍To calculate the equivalent torque and equivalent rotation, the measured data during rotary tillage were divided into 8 levels considering the maximum torque and minimum torque range. The equivalent torque and equivalent rotation speed during the rotary tillage are 156.55 Nm, 2,334 rpm.PTOgearof75kWagriculturaltractorwassimulatedattheratedtorqueconditionandequivalenttorqueduringtherotarytillageconditionsafetyfactorsofPTOgearwerecomparedunderthetwoconditionswhicharerealtorqueconditionandratertorquecondition
BASAL ANGIOSPERMS MONOCOTS EUDICOTS FLC VRN1 VRN2 FLOWERING FLOWERING FLOWERING FLOWERING FLOWERING BTC1 BBX19 FT1 FT2 AcFT2 FLC-independent THE MEMORY OF WINTER IN DIFFERENT PLANT GROUPS BOUCHÉ, WOODS, & AMASINO (2016) - PLANT PHYSIOLOGY POALES ASPARAGALES FABALES CARYIOPHYLLALES BRASSICALES H. vulgare (barley) T. aestivum (wheat) B. distachyon M. truncatula A. thaliana A. alpina C. flexuosa B. vulgaris (beets) A. cepa (onion) DISTINCT PLANT GROUPS EVOLVED DIFFERENT VERNALIZATION SYSTEMS. IN PERENNIALS, FORGETTING WINTER IS IMPORTANT TO SET THE LIFE BEHAVIOR. Find out more at http://dx.doi.org/10.1104/pp.16.01322
Evento Pró Cátedra UNESCO em Economia Criativa e Políticas Públicas O Departamento de Administração e Contabilidade por meio dos grupos de pesquisa - Gestão e Desenvolvimento de Territórios Criativos (GDTEC) e Grupo de Estudos e Pesquisas em Organizações, Sustentabilidade e Tecnologia (GEPOST), estão organizando o evento presencial: Pró Cátedra UNESCO em Economia Criativa e Políticas Públicas Dia: 17/05/2022 (terça-feira) Local: Novo Auditório do CCH I – Anexo do Prédio dos Departamentos de Administração, Contabilidade e Economia Programação: PAINEL 1 NACIONAL - POLÍTICAS, SUSTENTABILIDADE E TURISMO ALTERNATIVO (JUSTO E CRIATIVO) Horário: 14h às 15h45 Coordenadora: Profa. Débora Schneider (UFFS) Apresentadora: Profa. Maria de Fátima Nóbrega (UFCG) - Políticas e Sustentabilidade: hoje... e amanhã? Apresentador: Prof. Layon Cezar (UFV) - Comercio Justo e potenciais diálogos com a economia criativa e turismo Debatedor: Prof. Marcos Knupp (UFOP) PAINEL 2 REGIONAL - AGENDAS, DESENVOLVIMENTO TERRITORIAL E DISTRITOS CRIATIVOS Horário: 16h às 17h45 Coordenadora - Profa. Carolina Lescura (UFOP) Apresentador 1 - Prof. Magnus Emmendoerfer (UFV) - Conectando Agenda Globais com desenvolvimento local - o lugar dos distritos criativos
01 E 02 MARÇO DE 2023 RESTAURAÇÃO COM CIÊNCIA DO RIO DOCE Da Dimensão Edáfica ao Sensoriamento Remoto LOCAL: SALA 236 - BLOCO I3, ICB (UFMG) Foto: Odirlei Simões Saiba mais e se inscreva! RESTAURAÇÃO ECOLÓGICA DO RIO DOCE WOKSHOP DE Design: Walisson Kenedy Siqueira