6,534 research outputs found
The Future of Canadian Climate Policy — with Marc Lee
No full textMarc Lee is a Senior Economist at the Canadian Centre for Policy Alternatives\u27 BC Office. In addition to tracking federal and provincial budgets and economic trends, Marc has published on a range of topics from poverty and inequality to globalization and international trade to public services and regulation. Marc is the Co-Director of the Climate Justice Project, a research partnership with UBC\u27s School of Community and Regional Planning that examines the links between climate change policies and social justice.Resources:Climate Justice Project: www.policyalternatives.ca/projects/cli…tice-projectMarc Lee\u27s Posts on Policy Note: www.policynote.ca/author/marclee/Canadian Centre for Policy Alternatives: www.policyalternatives.ca/Marc\u27s Twitter: twitter.com/MarcLeeCCPA International Panel on Climate Change, 2021 report: www.ipcc.ch/report/ar6/wg1
Climate Justice & Inequality: The Future of Canadian Climate Policy — with Marc Lee
No full textMarc Lee is a Senior Economist at the Canadian Centre for Policy Alternatives\u27 BC Office. In addition to tracking federal and provincial budgets and economic trends, Marc has published on a range of topics from poverty and inequality to globalization and international trade to public services and regulation. Marc is the Co-Director of the Climate Justice Project, a research partnership with UBC\u27s School of Community and Regional Planning that examines the links between climate change policies and social justice.Resources: Climate Justice Project: https://www.policyalternatives.ca/projects/climate-justice-projectMarc Lee\u27s Posts on Policy Note: https://www.policynote.ca/author/marclee/Canadian Centre for Policy Alternatives: https://www.policyalternatives.ca/Marc\u27s Twitter: https://twitter.com/MarcLeeCCPA International Panel on Climate Change, 2021 report: https://www.ipcc.ch/report/ar6/wg1
UKMARC AMC: Draft Rev 4.0: UK MARC format for archives and manuscripts control (UK MARC AMC)
No full textThis draft is the first attempt to establish a UK MARC specifically for Archives and Manuscripts Control since the British Library indicated that it would countenance such extensions to the national UK MARC format. In order to keep consistency with the general UK MARC format, standard UK MARC subject fields are not included in this document, since they should be taken from the latest version of the UK MARC manual. {A note of them should perhaps be included in UK MARC AMC.} {NB Text in braces is intended to be explanatory material for readers of this draft}. Certain other fields have not been included that might occasionally be used in the cataloguing of archival materials but would generally only be used for such materials in organizations which were combining archive
databases with library databases. This MARC version is intended for use with descriptions of archive or anuscript material that follow, or fit, the traditional style of cataloguing: we assume that these will normally relate
to paper or parchment originals. It is not intended for use with descriptions of other kinds of material. For these, fields may be drawn from the appropriate UK MARC document. MARC versions for use with archives in special formats should be developed, in order to complete the full range of facilities available to archivists and curators
MARC 21 para recursos contínuos
No full textTranslation and adaptation of the MARC 21 Format for Bibliographic Data, and MARC 21 Format for Holdings Data, Network Development and MARC Standards Office, Library of Congress, USA, by Angela Salles. Rio de Janeiro, 2010. 2 v. V.1 MARC 21 format for bibliographic data (updated until October 2010). V.2 MARC 21 format for data collection (Holdings) (updated until October 2008)
MARC 21 para recursos contínuos.
No full textTradução e adaptação de MARC 21 Format for Bibliographic Data e MARC 21 Format for Holdings Data, da Network Development and MARC Standards Office, da Library of Congress, USA, por Angela Salles
Friends of the Greenwood Library Presents Marc Leepson
No full textOn Tuesday, September 11, 2012 the Friends of the Janet D. Greenwood Library hosted its fall event, which featured an evening with Marc Leepson. Leepson is a journalist, historian and the author of seven books, including Lafayette: Lessons in Leadership from the Idealist General (Palgrave/Macmillan, 2011), a concise biography of the famed Marquis de Lafayette
Caractérisation des maladies neuromusculaires : évaluation des biomarqueurs, segmentation et synthèse par apprentissage profond de l'IRM des membres inférieurs
No full textLa grande famille des maladies neuromusculaires (NMD) comprend plus de 200 maladies affectant le système nerveux périphérique. Dans ce cas, les muscles ne se contractent pas correctement, ce qui entraîne une faiblesse musculaire, voire une perte de la fonction motrice. Le principal défi associé à ces maladies est de trouver des mesures de caractérisation robustes, ou biomarqueurs.L'un des principaux symptômes, commun à toutes les NMD, est l'infiltration graisseuse. Ce phénomène consiste en un remplacement progressif du muscle par de la graisse, ce qui entraîne une perte graduelle de la fonction musculaire.L'imagerie par résonance magnétique quantitative (IRMq) permet de quantifier la fraction adipeuse (FA), qui est un biomarqueur populaire pour évaluer l'évolution de l'infiltration adipeuse. Cependant, le grand volume de données associé à l'IRMq nécessite le développement de méthodes de traitement d'images pour permettre la mesure automatique des biomarqueurs.Plus précisément, nous devons localiser les régions d'intérêt (ROI), c'est-à-dire les tissus musculaires sur les images IRM. Cette étape, connue sous le nom de segmentation, peut être réalisée automatiquement à l'aide de modèles d'apprentissage profond (DL) basés sur des réseaux neuronaux convolutifs (CNN).Pourtant, il y a un manque d'investigation sur ce sujet dans le domaine des NMD. Nous proposons donc d'évaluer 5 CNN de pointe sur la base de critères géométriques et cliniques.Nous avons déterminé que nnUNet était la meilleure méthode de segmentation automatique par CNN pour la segmentation musculaire par IRM, grâce à ses propriétés d'optimisation des hyperparamètres. Cette méthode réduit considérablement le temps de segmentation, avec un taux de fiabilité élevé.Une fois les régions d'intérêt (ROI) localisées, la valeur du biomarqueur est déterminée dans cette région sur les cartes IRMq. La valeur conventionnelle du biomarqueur est alors la moyenne des intensités de la carte IRMq dans cette région donnée. Cependant, il existe de nombreuses façons de décrire la distribution de l'infiltration de graisse dans une région, en exploitant ses caractéristiques texturales.Nous proposons d'utiliser les caractéristiques texturales, à savoir les radiomics, et d'évaluer leur potentiel comme nouveaux biomarqueurs des NMD, en comparaison avec les biomarqueurs précédents.Nos résultats montrent que ces biomarqueurs basés sur la texture fournissent une description plus complète de la texture et permettent de suivre l'évolution de l'atteinte de la maladie, ce qui en fait un biomarqueur sensible et pertinent pour la NMD.Enfin, l'IRM NMD a un besoin crucial de données. Les méthodes de traitement d'images utilisant la DL nécessitent de vastes ensembles de données d'entraînement, les plus diversifiées possible.Les solutions existantes impliquent la création de données synthétiques pour étendre ou compléter l'ensemble des données d'entraînement des modèles DL.Pour s'assurer de la diversité des images produites, il est essentiel de contrôler la texture présente sur celles-ci. En particulier, pour les IRM NMD, nous devons être en mesure de synthétiser des images de patients à différents stades de la pathologie afin de garantir la diversité de l'ensemble des données.Nous avons proposé de développer notre propre méthode de réseaux antagonistes génératifs (GAN) pour construire notre modèle de synthèse d'images contrôlées. Nous avons intégré des descripteurs de texture (radiomics) dans un modèle GAN, pour permettre le contrôle de la texture. Nous avons testé notre modèle, le ConText-GAN, pour la génération d'IRM musculaires des membres inférieurs. Le modèle a permis d'utiliser une combinaison de méthodes de DL et d'outils de texture radiomics, une combinaison intéressante pour augmenter la précision et l'explicabilité des modèles de DL. En outre, les images générées ont été utilisées pour enrichir un ensemble de données pour une tâche de segmentation musculaire.The large family of Neuromuscular Diseases (NMD) includes over 200 diseases affecting the peripheral nervous system. In this case, muscle would not contract properly, leading to muscle weakness and even loss of motor function. The main challenge associated with these diseases is to find robust characterization measures, or biomarkers.One of the main symptoms, common to all NMD, is fatty infiltration. This phenomenon consists of the progressive replacement of muscle by fat, leading to a gradual loss of muscle function.Using quantitative Magnetic Resonance Imaging (qMRI), it is possible to quantify the Fat Fraction (FF), which a popular biomarker for assessing the fat infiltration evolution. However, the large volume of data associated with qMRI requires the development of image processing methods to enable automatic measurement of biomarkers.More specifically, it is necessary to locate the Regions of Interest (ROI), i.e., the muscle tissues on the MRI scans. This step, known as segmentation, can be carried out automatically using Deep Learning (DL) models based on Convolutional Neural Networks (CNN).Yet, there is a lack of investigation into this topic in NMD. We therefore propose to evaluate 5 state-of-the-art CNNs-based geometric and clinical criteria.We determined nnUNet as the best automatic CNN segmentation method for muscle MRI segmentation, thanks to its hyperparameter optimization properties. This method drastically reduces segmentation time, with a high reliability rate.Once the Regions of Interests (ROI) have been located, the value of the biomarker is determined in this region on the qMRI maps. The conventional value of the biomarker is then the average of the intensities of the qMRI map over this given region. However, there are many ways of describing the distribution of fat infiltration in a region, by exploiting its textural feature.We propose to use textures features, namely radiomics, and assess their potential as new biomarkers of NMD, in comparison with the previous biomarkers.Our results shown that these texture-based biomarkers provide a more complete description of texture, and help to follow the evolution of the disease involvement, making them a sensitive and relevant biomarker for NMD.Finally, there is a crucial need for data in NMD MRI. Image processing methods using DL require large training datasets to be rained. Furthermore, these datasets should be as diverse as possible, to help the network improve its generalization abilities.Existing solutions imply creating synthetic data to expand, or complete, the training data set of DL models.To be sure of the diversity of the images produced, it is essential to control the texture present on them. Specifically, for NMD MRI, we need to be able to synthesize images of patients at different stages of pathology to ensure dataset diversity.We proposed to develop our own Generative Adversarial Networks (GAN) method to build our controlled image synthesis model.We integrated texture descriptors (radiomics) into a GAN model, to enable texture control. We tested our model, the ConText-GAN, for the generation of muscle MRIs of lower limbs.This model enabled the creation of realistic images that could resemble those of NMD patients. The model made it possible to use a combination of DL methods and radiomics texture tools, an interesting combination for increasing the accuracy and explainability of DL models.Furthermore, the generated images were used to help enrich a dataset for a muscle segmentation task
Populism, populists, european democracies and European Union. The Italian case
No full textIn this chapter, the author starts by a necessary clarification of some notions as populism and fascism because there is a lot of confusion in the public debate but also a lot of academic controversies. The debate has been immediately re-launched in September 2022, after the victory at the general elections of Giorgia Meloni’s head of Brothers of Italy, a party who has a neo-fascist legacy, and after her nomination as chief of the Italian government. Marc Lazar concludes this first part of the chapter by giving what he calls an operative definition of populism, populist and fascism. In a second part, the author analyses Meloni’s party Brothers of Italy and proposes a characterisation of this party which is evolving. In a third part of the chapter, Marc Lazar reflects on what does Meloni and her party on Italian democracy and on the European Union but also what the Italian democracy and the European Union do to Meloni and Brothers of Italy. For the author, the Italian democracy and the European Union demonstrate a high capacity of resilience to the populist challenge and a propension of acculturation of the populists’ leader and party. He concludes pointing out that is a working progress, the end of which is unknown
Managing Technology Risks Through Technological Proficiency: Guidance for Local Governments
No full textLike most organizations, local governments face challenges managing technology, the critical resource to meet evolving public service expectations. But benefits associated with adapting the latest technology come with risks, some more apparent than others.
This report details the problems facing municipal officials as they try to maximize the benefits of technology for their communities and constituents in the face of cybersecurity, legal, operational, financial, reputational and societal risks.
The report concludes that top municipal officials must create and maintain an environment of “technological proficiency.” That includes creating a process for making technology decisions, developing an annually reviewed technology plan that is tied to the budget, instituting a “cyber hygiene” training program for all employees in proper computer security practices, and making sure that agency technology is competently managed.
The report is supplemented by a "Best Practices and Resources Guide" that organizations can use to achieve technology proficiency. It provides best practices based on an organization's technology profile.Report and Supplement were prepared for the Municipal Excess Liability Fund, a joint insurance fund of over 600 New Jersey local government agencies
MARC 数据与图书馆
No full textThis article describes impacts of application of MARC on libraries .At First,the paper think application of MARC will bring some changes of library workflow , regroup of organization and exchangement of staff.Secondly,application of MARC may move the work centre to information services and re-collocate the library resoures .Finally ,the author think that application of MARC will help to reform documents guarantee system
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