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L'enquête sur les élèves et étudiants en formation aux professions sociales a pour objectifs de mieux connaître les caractéristiques des élèves et étudiants suivant les formations sociales entrant dans le champ de l'enquête, et d'en mesurer les évolutions. Tous les élèves et étudiants effectuant une rentrée en cours de l'année de l'enquête, dans au moins une de ces formations, sont ainsi interrogés sur leur situation au regard de la formation suivie (situation vis-à-vis de l’emploi, financement de la formation, mode d'admission, etc.), leur parcours scolaire, leur niveau de diplôme, leur plus haut niveau scolaire atteint, etc. En outre, ils sont interrogés sur une thématique spécifique, changeant à chaque édition de l'enquête. Ainsi, les élèves et étudiants seront interrogés, en 2022, sur l'attractivité des métiers ainsi que sur l'impact de la crise sanitaire liée à la Covid-19 sur leur formation et leur vision du métier. Le résultats de cette enquête servent, en particulier, à analyser la démographie des professions du sanitaire et du social, tant au niveau national que régional. Ils sont aussi utilisés à des fins budgétaires (détermination prévisionnelle des bourses) ou pour le suivi de mesures plus ponctuelles.

Cheer America Holiday Cheer 2022, the Cheer America Holiday Cheer 2022 are under way in USA. WATCH CHEER ONLINE HERE Not since 2006 have the Socceroos made the knockout stage while Belgium have never played a last-16 game at the World Cup, and with a ferocious backing in Qatar they will be under pressure to grab a vital win today.dfhfgfgdh We have reached the semi-finals of the tournament involving the tour's top eight players/pairs across the five events of men's singles, women's singles, men's doubles, women's doubles, and mixed doubles at Nimibutr Arena on Saturday, 10 December 2022. VOLUNTEERS The Race Organizing Committee is seeking volunteers to fill various positions on December 09 & 10, 2022. More information here. Τhe curated data provided by the LitCovid hub2.gdgdgdffdh These data have been cleaned and integrated with data from COVID-19-TweetIDs and from other sources (e.g., PMC). The result was dataset of 500,314 unique articles along with relevant metadata (e.g., the underlying citation network). We utilized this dataset to produce, for each article, the values of the following impact measures:dfhgf Influence: Citation-based measure reflecting the total impact of an article. This is based on the PageRank3 network analysis method. In the context of citation networks, it estimates the importance of each article based on its centrality in the whole network. This measure was calculated using the PaperRanking (https://github.com/diwis/zdhPaperRanking) library4.dgfdhfd The washers dataset features 70 defective parts. The gears and screws datasets feature 35 defective, 35 intact and several hundred unannotated parts. Some defects, such as notches and holes, are visible in most images (illuminations) with intensity and texture variations among them, while others, such as scratches, are only visible in a few.fghgj We split the datasets into train and test sets. The train sets contain 32 samples, and the test set 38 samples. Each sample comprises 108 images (each captured under a different illumination angle), an automatically extracted foreground segmentation mask, and a hand-labeled defect segmentation mask.fghgfj This dataset is challenging mainly because: each raw sample consists of 108 gray-scale images of resolution 512×512 and therefore takes 27MB of space; the metallic surfaces produce many specular reflections that sometimes saturate the camera sensors; the annotations are not very precise because the exact extent of defect contours is always subjective; the defects are very sparse also in the spatial dimensions: they cover only about 0.2% of the total image area in gears, 0.8% in screws, and 1.4% in washers; this creates an unbalanced dataset with a highly skewed class representation. gfhj The dataset is organized as follows: each sample resides in the Test, Train, or Unannotated directory; each sample has its own directory which contains the individual images, the foreground, and defect segmentation masks; each image is stored in 8-bit greyscale png format and has a resolution of 512 x 512 pixels; Image file names are formatted using three string fields separated with the underscore character: prefix_sampleNr_illuminationNr.png, where the prefix is e.g. washer, the sampleNr might be a three-digit number 001, and the illuminationNr is formed of 3 digits, first corresponding to the elevation index (1 - highest angle, 9 - lowest angle), and the additional two corresponding to the azimuth index (01-12). Each dataset contains light_vectors.csv, which contains the illumination angles (in lexicographic order of the illuminationNr), and light_intensities.csv that contains the numbers corresponding to the light intensity on the scale from 0 to 127. Please, be aware, that the azimuth angles were not calibrated and might be a few degrees misaligned.fdhfgj These data have been cleaned and integrated with data from COVID-19-TweetIDs and from other sources (e.g., PMC). The result was dataset of 500,314 unique articles along with relevant metadata (e.g., the underlying citation network). We utilized this dataset to produce, for each article, the values of the following impact measures:sdgfdfhfggh Influence: Citation-based measure reflecting the total impact of an article. This is based on the PageRank3 network analysis method. In the context of citation networks, it estimates the importance of each article based on its centrality in the whole network. This measure was calculated using the PaperRanking (https://github.com/diwifss/PaperRanking) library4.sddfghfggd Influence_alt: Citation-based measure reflecting the total impact of an article. This is the Citation Count of each article, calculated based on the citation network between the articles contained in the BIP4COVID19 dataset.sddggf safs Popularity: Citation-based measure reflecting the current impact of an article. This is based on the AttRank5 citation network analysis method. Methods like PageRank are biased against recently published articles (new articles need time to receive their first citations). AttRank alleviates this problem incorporating an attention-based mechanism, akin to a time-restricted version of preferential attachment, to explicitly capture a researcher's preference to read papers which received a lot of attention recently. This is why it is more suitable to capture the current "hype" of an article.asdfujsgdg Colour Science for Python Colour is an open-source Python package providing a comprehensive number of algorithms and datasets for colour science. sdg It is freely available under the New BSD License terms.uiuol Colour is an affiliated project of NumFOCUS, a 501(c)(3) nonprofit in the United States Draft Release Notes The draft release notes of the develop branch are available at this url.uiu Sponsors We are grateful 💖 for the support of our sponsors. If you'd like to join them, please consider becoming a sponsor on OpenCollective.uiu Features Colour features a rich dataset and collection of objects, please see the features in the documentation for more information.iu User Guid Installation Colour and its primary dependencies can be easily installed from the Python Package Index by issuing this command in a shell:oluip $ pip install --user colour-science The detailed installation procedure for the secondary dependencies is described in the Installation Guide. Colour is also available for Anaconda from Continuum Analytics via conda-forge:oiup $ conda install -c conda-forge colour-science Tutorial The static tutorial provides an introduction to Colour. An interactive version is available via Google Colab.oui How-To The Google Colab How-To guide for Colour shows various techniques to solve specific problems and highlights some interesting use cases. Contributing If you would like to contribute to Colour, please refer to the following Contributing guide.oi Colour by Colour Developers Copyright 2013 Colour Developers – colour-developers@colour-science.org This software is released under terms of New BSD License: https://opensource.org/licenses/BSD-3-Clause https://github.com/colour-science/colourolip sf Popularity alternative: An alternative citation-based measure reflecting the current impact of an article (this was the basic popularity measured provided by BIP4COVID19 until version 26). This is based on the RAM6 citation network analysis method. Methods like PageRank are biased against recently published articles (new articles need time to receive their first citations). RAM alleviates this problem using an approach known as "time-awareness". This is why it is more suitable to capture the current "hype" of an article. This measure was calculated using the PaperRanking (https://github.com/diwis/PaperRanking) library4.sfbsdf Social Media Attention: The number of tweets related to this article. Relevant data were collected from the COVID-19-TweetIDs dataset. In this version, tweets between 23/6/22-29/6/22 have been considered from the previous dataset.ftgujyol We provide five CSV files, all containing the same information, however each having its entries ordered by a different impact measure. All CSV files are tab separated and have the same columns (PubMed_id, PdfMC_id, DOI, influence_score, popularity_alt_score, popularity score, influence_alt score, tweets count).yjytik Rich offline experience, periodic background sync, push notification functionality, network requests control, improved performance via requests caching are only a few of the functionalities provided by the Service Worker (SW ) API. This new technology, supported by all major browsers, can significantly improve users’ experience by providing the publisher with the technical foundations that would normally require a native application. Albeit the capabilities of this new technique and its important role in the ecosystem of Progressive Web Apps (PWAs), it is still unclear what is their actual purpose on the web, and how publishers leverage the provided functionality in their web applications. In this study, we shed light in the real world deployment of SWs, by conducting the first large scale analysis of the prevalence of SWs in the wild.huiuop We see that SWs are becoming more and more popular, with the adoption increased by 26% only within the last 5 months. Surprisingly, besides their fruitful capabilities, we see that SWs are being mostly used for In-Page Push Advertising, in 65.08% of the SWs that connect with 3rd parties. We highlight that this is a relatively new way for advertisers to bypass ad-blockers and render ads on the user’s displays natively.ik

Pourcentage de l’effectif qui prévoit de continuer à faire principalement du télétravail une fois la pandémie de la COVID-19 terminée, selon le Système de classification des industries de l’Amérique du Nord (SCIAN), l’effectif de l’entreprise, le type d’entreprise, l’activité de l'entreprise et la propriété majoritaire, troisième trimestre de 2021.

[NFL=2022] Sunday Night Football Live Streaming free Watch NFL Games [LIVE+Streams]* Cowboys vs Colts live stream free: How to watch NFL Week 13 [Whereto-watch ]* Dallas Cowboys vs. Indianapolis Colts Live How to Watch NFL Week 13 Games Live free WATCH NFL GAME 2022 LIVE Which NFL teams are playing this week? And what channels are airing the games? Here’s this week’s lineup. (The home team is listed second.) Sunday, Dec. 4 Green Bay Packers vs Chicago Bears, 1:00 p.m. ET on Fox Pittsburgh Steelers vs. Atlanta Falcons, 1:00 p.m. ET on CBS New York Jets vs. Minnesota Vikings, 1:00 p.m. ET on CBS Jacksonville Jaguars vs. Detroit Lions, 1:00 p.m. ET on Fox Tennessee Titans vs. Philadelphia Eagles, 1:00 p.m. ET on Fox Cleveland Browns vs. Houston Texans, 1:00 p.m. ET on CBS Washington Commanders vs. New York Giants, 1:00 p.m. ET on Fox Denver Broncos vs. Baltimore Ravens, 1:00 p.m. ET on CBS Miami Dolphins vs. San Francisco 49ers, 4:05 p.m. ET on Fox Seattle Seahawks vs. Los Angeles Rams, 4:05 p.m. ET on Fox Los Angeles Chargers vs. Las Vegas Raiders, 4:25 p.m. ET on CBS Kansas City Chiefs vs. Cincinnati Bengals, 4:25 p.m. ET on CBS Indianapolis Colts vs. Dallas Cowboys, 8:20 p.m. ET on NBC Not since 2006 have the Socceroos made the knockout stage while Belgium have never played a last-16 game at the World Cup, and with a ferocious backing in Qatar they will be under pressure to grab a vital win today.dfg Τhe CORD-19 dataset released by the team of Semantic Scholar1 anddg Τhe curated data provided by the LitCovid hub2.gdgdf These data have been cleaned and integrated with data from COVID-19-TweetIDs and from other sources (e.g., PMC). The result was dataset of 500,314 unique articles along with relevant metadata (e.g., the underlying citation network). We utilized this dataset to produce, for each article, the values of the following impact measures:dgf Influence: Citation-based measure reflecting the total impact of an article. This is based on the PageRank3 network analysis method. In the context of citation networks, it estimates the importance of each article based on its centrality in the whole network. This measure was calculated using the PaperRanking (https://github.com/diwis/zdhPaperRanking) library4.dgfd These data have been cleaned and integrated with data from COVID-19-TweetIDs and from other sources (e.g., PMC). The result was dataset of 500,314 unique articles along with relevant metadata (e.g., the underlying citation network). We utilized this dataset to produce, for each article, the values of the following impact measures:sdgfdfggh Influence: Citation-based measure reflecting the total impact of an article. This is based on the PageRank3 network analysis method. In the context of citation networks, it estimates the importance of each article based on its centrality in the whole network. This measure was calculated using the PaperRanking (https://github.com/diwifss/PaperRanking) library4.sddfggd Influence_alt: Citation-based measure reflecting the total impact of an article. This is the Citation Count of each article, calculated based on the citation network between the articles contained in the BIP4COVID19 dataset.sddggf safs Popularity: Citation-based measure reflecting the current impact of an article. This is based on the AttRank5 citation network analysis method. Methods like PageRank are biased against recently published articles (new articles need time to receive their first citations). AttRank alleviates this problem incorporating an attention-based mechanism, akin to a time-restricted version of preferential attachment, to explicitly capture a researcher's preference to read papers which received a lot of attention recently. This is why it is more suitable to capture the current "hype" of an article.asdsgdg sf Popularity alternative: An alternative citation-based measure reflecting the current impact of an article (this was the basic popularity measured provided by BIP4COVID19 until version 26). This is based on the RAM6 citation network analysis method. Methods like PageRank are biased against recently published articles (new articles need time to receive their first citations). RAM alleviates this problem using an approach known as "time-awareness". This is why it is more suitable to capture the current "hype" of an article. This measure was calculated using the PaperRanking (https://github.com/diwis/PaperRanking) library4.sfbsdf Social Media Attention: The number of tweets related to this article. Relevant data were collected from the COVID-19-TweetIDs dataset. In this version, tweets between 23/6/22-29/6/22 have been considered from the previous dataset. We provide five CSV files, all containing the same information, however each having its entries ordered by a different impact measure. All CSV files are tab separated and have the same columns (PubMed_id, PdfMC_id, DOI, influence_score, popularity_alt_score, popularity score, influence_alt score, tweets count).

L'enquête sur les élèves et étudiants en formation aux professions sociales a pour objectifs de mieux connaître les caractéristiques des élèves et étudiants suivant les formations sociales entrant dans le champ de l'enquête, et d'en mesurer les évolutions. Tous les élèves et étudiants effectuant une rentrée en cours de l'année de l'enquête, dans au moins une de ces formations, sont ainsi interrogés sur leur situation au regard de la formation suivie (situation vis-à-vis de l’emploi, financement de la formation, mode d'admission, etc.), leur parcours scolaire, leur niveau de diplôme, leur plus haut niveau scolaire atteint, etc. En outre, ils sont interrogés sur une thématique spécifique, changeant à chaque édition de l'enquête. Ainsi, les élèves et étudiants seront interrogés, en 2022, sur l'attractivité des métiers ainsi que sur l'impact de la crise sanitaire liée à la Covid-19 sur leur formation et leur vision du métier. Le résultats de cette enquête servent, en particulier, à analyser la démographie des professions du sanitaire et du social, tant au niveau national que régional. Ils sont aussi utilisés à des fins budgétaires (détermination prévisionnelle des bourses) ou pour le suivi de mesures plus ponctuelles.

Le questionnaire a été diffusé en ligne du 9 avril 2020 au 7 juin 2020 sur http://sphinx2.espe.univ-amu.fr/v4/s/9ab5go Il a recueilli 4071 réponses.

Policy Brief n° 3; Jusqu’à quel point le Covid-19 perturbe-t-il notre vie de tous les jours ? Comment la population française vit-elle le confinement ? Dans quelles mesures les inégalités sociales sont-elles exacerbées et la cohésion sociale menacée ? Le projet CoCo apporte des éléments de réponse à ces questions d’actualité en comparant les conditions de vie en France avant et après le blocage. Il s’agit du troisième rapport préliminaire de la série. Nous analysons ici la façon dont la société française a fait face aux 6 premières semaines de confinement, notamment en ce qui concerne les changements de conditions de travail et de vie sociale.Les français actifs se sont répartis en 3 tiers : un tiers des travailleurs a continué à se rendre sur son lieu de travail, un autre tiers a télétravaillé tandis que les autres ont cessé de travailler. Les femmes avec un enfant en bas âge ont plus fréquemment arrêté de travailler. Les télétravailleurs font partie du segment moyen-supérieur de la distribution des revenus. A l’inverse le travail à l’extérieur du domicile concerne les plus modestes. Les conditions de travail des travailleurs à distance sont meilleures que pour les autres. Les télétravailleurs souhaitent poursuivre cette expérience. La division du travail domestique est plus égalitaire dans les ménages où la femme travaille au domicile. Les hommes prennent peu part aux activités d’éducation. La forte croissance de l’usage des réseaux sociaux et des relations de voisinage a compensé la baisse de la sociabilité. La contagiosité du virus a d’abord été liée à la géographie, elle est désormais dépendante des conditions d’emploi. Les personnes qui ont dû se rendre sur leur lieu de travail ont été plus touchées. Les niveaux de bien-être perçu ont baissé au début du confinement, mais ils ont retrouvé et même dépassé les niveaux d’avant la crise.

Article en ligne; Devant l’injonction à « vivre avec le virus », on peut s’interroger sur les modalités de cette cohabitation nouvelle. L’anthropologue Charlotte Brives propose ici la boussole de la pluribiose, d’un vivant affecté par ses relations et ses rencontres, afin d’inventer des politiques alternatives pour « devenir avec » plutôt que de s’obstiner à « vivre malgré ».