468 research outputs found
Computing optical flow using fast total variation
During my internship, I was in charge of implementing a GPU version of the optical flow algorithm. The optical flow algorithm is based on the total variation features described in my bibliography
Compte rendu de l'excursion de la Société Géologique Suisse du 1 au 3 octobre 1979: coupe Préalpes-Helvétique-Pennique en Suisse occidentale
The purpose of the 1979 excursion of the Swiss Geological Society was to show the recent interpretations in several key areas on the cross section through the Alps of Western Switzerland. Several new results are published here for the first time in a preliminary way: for the Prealps, new data on the composition of the submediane zone (north-penninic mélange) in the Meiel area. -Description of the Middle Jurassic paleokarst of the Gummfluh (briançonnais paleogeographic domaine, nappe of the Préalpes médianes rigides).
-Progress report on the study of deformation, metamorphism and K-Ar ages along the Gummfluh thrust. Consequences for the cinematics of the préalpine nappes
EQUIPE DE ROBÓTICA MÓVEL - WESTBOTS
A robótiva móvel é amplamente utilizada em situações de risco e em situações de exploração. A utilização de robôs autônomos para realização de exploração espacial, de robôs radiocontrolados para desarmar bombas e para inspeção de tubulações inacessíveis à seres humanos, são alguns dos exemplos de aplicação. Em meados do ano de 2007 professores e alunos do curso de Engenharia Elétrica iniciaram as pesquisas nesta área afim de aplicar conhecimentos de engenharia e promover o desenvolvimento tecnológico. Atualmente a equipe de robótica intitulada WestBots é composta por dois professores orientadores e por dez alunos do curso de Engenharia Elétrica. Dentre estes alunos ressalta-se que um é bolsista e os outros nove são voluntários. Desde sua criação a equipe já participou de quatro competições nacionais. A última participação aconteceu em julho de 2016 na maior competição de robótica da América Latina. O XII Winter Challenge foi realizado no instituto Mauá em São Caetano do Sul - SP. Nesta edição a equipe participou com um total de cinco robôs, sendo três na categoria Sumô Autônomo 3kg e dois robôs na categoria Seguidor de Linha Pro. Palavras-chave: Robótica Móvel. Robôs Autônomos. Engenharia Elétrica
Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context
Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts
Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas
Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN
Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas
This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing
molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin
Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images
Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images
of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL
maps are derived through computational staining using a convolutional neural network trained to
classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and
correlation with overall survival. TIL map structural patterns were grouped using standard
histopathological parameters. These patterns are enriched in particular T cell subpopulations
derived from molecular measures. TIL densities and spatial structure were differentially enriched
among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial
infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic
patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for
the TCGA image archives with insights into the tumor-immune microenvironment
Race-free estimated glomerular filtration rate equation in kidney transplant recipients:development and validation study
OBJECTIVE: To compare the performance of a newly developed race-free kidney recipient specific glomerular filtration rate (GFR) equation with the three current main equations for measuring GFR in kidney transplant recipients.DESIGN: Development and validation study SETTING: 17 cohorts in Europe, the United States, and Australia (14 transplant centres, three clinical trials).PARTICIPANTS: 15 489 adults (3622 in development cohort (Necker, Saint Louis, and Toulouse hospitals, France), 11 867 in multiple external validation cohorts) who received kidney transplants between 1 January 2000 and 1 January 2021.MAIN OUTCOME MEASURE: The main outcome measure was GFR, measured according to local practice. Performance of the GFR equations was assessed using P 30 (proportion of estimated GFR (eGFR) within 30% of measured GFR (mGFR)) and correct classification (agreement between eGFR and mGFR according to GFR stages). The race-free equation, based on creatinine level, age, and sex, was developed using additive and multiplicative linear regressions, and its performance was compared with the three current main GFR equations: Modification of Diet in Renal Disease (MDRD) equation, Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) 2009 equation, and race-free CKD-EPI 2021 equation. RESULTS: The study included 15 489 participants, with 50 464 mGFR and eGFR values. The mean GFR was 53.18 mL/min/1.73m 2 (SD 17.23) in the development cohort and 55.90 mL/min/1.73m 2 (19.69) in the external validation cohorts. Among the current GFR equations, the race-free CKD-EPI 2021 equation showed the lowest performance compared with the MDRD and CKD-EPI 2009 equations. When race was included in the kidney recipient specific GFR equation, performance did not increase. The race-free kidney recipient specific GFR equation showed significantly improved performance compared with the race-free CKD-EPI 2021 equation and performed well in the external validation cohorts (P 30 ranging from 73.0% to 91.3%). The race-free kidney recipient specific GFR equation performed well in several subpopulations of kidney transplant recipients stratified by race (P 30 73.0-91.3%), sex (72.7-91.4%), age (70.3-92.0%), body mass index (64.5-100%), donor type (58.5-92.9%), donor age (68.3-94.3%), treatment (78.5-85.2%), creatinine level (72.8-91.3%), GFR measurement method (73.0-91.3%), and timing of GFR measurement post-transplant (72.9-95.5%). An online application was developed that estimates GFR based on recipient's creatinine level, age, and sex (https://transplant-prediction-system.shinyapps.io/eGFR_equation_KTX/). CONCLUSION: A new race-free kidney recipient specific GFR equation was developed and validated using multiple, large, international cohorts of kidney transplant recipients. The equation showed high accuracy and outperformed the race-free CKD-EPI 2021 equation that was developed in individuals with native kidneys.TRIAL REGISTRATION: ClinicalTrials.gov NCT05229939.</p
A pre-registered, multi-lab non-replication of the Action-sentence Compatibility Effect (ACE)
The Action-sentence Compatibility Effect (ACE) is a well-known demonstration of the role of motor activity in the comprehension of language. Participants are asked to make sensibility judgments on sentences by producing movements toward the body or away from the body. The ACE is the finding that movements are faster when the direction of the movement (e.g., toward) matches the direction of the action in the to-be-judged sentence (e.g., Art gave you the pen describes action toward you). We report on a pre-registered, multi-lab replication of one version of the ACE. The results show that none of the 18 labs involved in the study observed a reliable ACE, and that the meta-analytic estimate of the size of the ACE was essentially zero.Fil: Morey, Richard. Cardiff University; Reino UnidoFil: Kaschak, Michael. Florida State University; Estados UnidosFil: Díez Álamo, Antonio. Universidad de Salamanca; España. Arizona State University; Estados UnidosFil: Glenberg, Arthur. Arizona State University; Estados Unidos. Universidad de Salamanca; EspañaFil: Zwaan, Rolf A.. Erasmus University Rotterdam; Países BajosFil: Lakens, Daniël. Eindhoven University of Technology; Países BajosFil: Ibáñez, Santiago Agustín. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de San Andrés; Argentina. University of San Francisco; Estados Unidos. Universidad Adolfo Ibañez; Chile. Trinity College Dublin; IrlandaFil: García, Adolfo Martín. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de San Andrés; Argentina. University of San Francisco; Estados Unidos. Universidad Nacional de Cuyo. Facultad de Educación Elemental y Especial; Argentina. Universidad de Santiago de Chile; ChileFil: Gianelli, Claudia. Universitat Potsdam; Alemania. Scuola Universitaria Superiore; ItaliaFil: Jones, John L.. Florida State University; Estados UnidosFil: Madden, Julie. University of Tennessee; Estados UnidosFil: Alifano Ferrero, Florencia. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Bergen, Benjamin. University of California at San Diego; Estados UnidosFil: Bloxsom, Nicholas G.. Ashland University; Estados UnidosFil: Bub, Daniel N.. University of Victoria; CanadáFil: Cai, Zhenguang G.. The Chinese University; Hong KongFil: Chartier, Christopher R.. Ashland University; Estados UnidosFil: Chatterjee, Anjan. University of Pennsylvania; Estados UnidosFil: Conwell, Erin. North Dakota State University; Estados UnidosFil: Wagner Cook, Susan. University of Iowa; Estados UnidosFil: Davis, Joshua D.. University of California at San Diego; Estados UnidosFil: Evers, Ellen R. K.. University of California at Berkeley; Estados UnidosFil: Girard, Sandrine. University of Carnegie Mellon; Estados UnidosFil: Harter, Derek. Texas A&m University Commerce; Estados UnidosFil: Hartung, Franziska. University of Pennsylvania; Estados UnidosFil: Herrera, Eduar. Universidad ICESI; ColombiaFil: Huettig, Falk. Max Planck Institute for Psycholinguistics; Países BajosFil: Humphries, Stacey. University of Pennsylvania; Estados UnidosFil: Juanchich, Marie. University of Essex; Reino UnidoFil: Kühne, Katharina. Universitat Potsdam; AlemaniaFil: Lu, Shulan. Texas A&m University Commerce; Estados UnidosFil: Lynes, Tom. University of East Anglia; Reino UnidoFil: Masson, Michael E. J.. University of Victoria; CanadáFil: Ostarek, Markus. Max Planck Institute for Psycholinguistics; Países BajosFil: Pessers, Sebastiaan. Katholikie Universiteit Leuven; BélgicaFil: Reglin, Rebecca. Universitat Potsdam; AlemaniaFil: Steegen, Sara. Katholikie Universiteit Leuven; BélgicaFil: Thiessen, Erik D.. University of Carnegie Mellon; Estados UnidosFil: Thomas, Laura E.. North Dakota State University; Estados UnidosFil: Trott, Sean. University of California at San Diego; Estados UnidosFil: Vandekerckhove, Joachim. University of California at Irvine; Estados UnidosFil: Vanpaeme, Wolf. Katholikie Universiteit Leuven; BélgicaFil: Vlachou, Maria. Katholikie Universiteit Leuven; BélgicaFil: Williams, Kristina. Texas A&m University Commerce; Estados UnidosFil: Ziv Crispel, Noam. BehavioralSight; Estados Unido
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