281 research outputs found
Yenan, China, T. A. Bisson Speaking at Meeting
No full textAn image scanned from a black and white photograph with a handwritten caption on the back that reads, Yenan Meeting (3) author speaking. One in a series of photographs documenting a trip taken by Thomas Arthur Bisson and related to his subsequent publication, Yenan in June 1937: Talks with the Communist Leaders.https://digitalcommons.library.umaine.edu/spec_photos/3462/thumbnail.jp
Free Movement in the EU: Harmonisation of Mobile Citizens’ Social Rights
No full textThe author focuses on the current stagnation in negotiating process on the further improvement of supranational regulation on coordination of social security systems in the European Union. The article examines the basic principles of the free movement of workers in the EU and notes that the 2004/2007 EU enlargement has had a significant impact on the scale and direction of labour mobility within the Community. The analysis of the main indicators and characteristics of workers' mobility reveals the existing disparities between the Member States. The author points out that the divergence of national social security regimes, as well as diverging interests of individual EU Member States, such as protecting the rights of their own mobile citizens, or combating “social dumping”, play a key role in hindering the harmonization of social security rules in the context of freedom of movement. The concept of “failing forward” used for the study allowed to comprehend how social integration can be promoted when challenged by contradictions. The need to comply with the rules of the common internal market, on the one hand, and the interests of individual EU member states and their citizens, on the other, in a situation where the current legislation does not meet the challenges of the time, and the development of new legislation is constantly blocked, leads the EU institutions to intensify intergovernmental cooperation and resort to complementary mechanisms. The author concludes that the use of nonbinding regulatory instruments such as electronic data exchange serves as an intermediate link in the process of deepening integration in the area and may become an impetus for restarting negotiations and help finalise the text of the new legislation
Docteur! Comédie en un acte.
No full text"Représentée pour la première fois, à Paris, sur le théâtre du Gymnase, le 24 août 1900."At head of title: Alexandre Bisson & Georges Thurner.Mode of access: Internet
Comestible Edible : L'aliment comme matériau = Edible : Food as Material
No full text"Diane Bisson presents her first book, a colourful and textured reflection on cooking and our dietary habits. In face of the proliferation of disposable containers and over-packaging, the author invites us to take up the challenge of transforming food into genuine design material. Flatware made of quinoa, plates for desert, biscuit drinking straws, 100% edible lunches: such are the author's objectives. Edible, Food as material presents the results of this playful yet scientific journey with a collection of magnificent photographs and over thirty food samples designed and developed by the author. Her research rests on a vision resolutely linked with sustainable development as it explores the concept of the edible plate as both cultural model and viable material for the reduction of waste. Edible, Food as material fuses art with science to present the possible scope of a future series of edible plates and containers." - Publisher's website
GLP-1 receptor agonists and cardiovascular events in metabolically healthy or unhealthy obesity
No full textAims: The associations of glucagon-like peptide-1 receptor agonists (GLP-1RAs) and outcomes among patients with obesity according to the presence of cardiovascular risk factors (metabolically healthy obesity (MHO) or metabolically unhealthy obesity (MUHO)) remain unclear. We examined the associations of GLP-1RAs with mortality and adverse cardiovascular events in patients with MHO and MUHO. Methods: The TriNetX network was utilized to select a cohort of patients with MHO or MUHO, and use or non-use of GLP-1RAs with propensity score matching (1:1). Cardiovascular events were identified during follow-up. Results: A total of 2 983 151 patients with obesity (512 434 with MHO and 2 470 717 with MUHO) were included in the study. Among these, 416 713 (13.9%) were GLP-1RA users. After propensity score matching, GLP-1RA use in MUHO was associated with a significantly lower risk of mortality (HR 0.580 [95% CI, 0.566-0.595]), ischemic stroke (HR 0.921 [0.890-0.953]), AF (HR 0.913 [0.888-0.938]) and hospitalization for HF (HR 0.925 [0.900-0.949]) during follow-up compared with non-use of GLP-1RA. Patients with MHO had a markedly lower risk of clinical events than those with MUHO. A trend towards a lower risk of cardiovascular events associated with GLP-1RA was seen among patients with MHO. There was no statistical interaction in the risk of cardiovascular outcomes with GLP-1RA use for MHO and MUHO patients. Conclusions: The use of GLP-1RAs was associated with lower rates of cardiovascular events than no use in patients with MUHO. Similar but non-statistically significant trends were seen in patients with MHO
Éthique du devenir sujet femme : le sacré aux frontières de la jouissance
No full textThèse numérisée par la Direction des bibliothèques de l'Université de Montréal
Essai d'opérationnalisation de l'axe de participation (Groupe optimal)
No full textLe but du présent travail était une première critique d'un tel système de catégories et l'étude comparative de trois modalités d'observation à l'aide de ce système de catégories: méthodes continue, rotative et oscillatoire
Essai d'opérationnalisation de l'axe de participation (Groupe optimal)
No full textLe but du présent travail était une première critique d'un tel système de catégories et l'étude comparative de trois modalités d'observation à l'aide de ce système de catégories: méthodes continue, rotative et oscillatoire
The LOTUS Initiative for Open Natural Products Research: TMAP
No full textTMAP of the compounds present on Wikidata curated in the frame of the LOTUS Initiative: https://doi.org/10.7554/eLife.7078
Prediction of early death after atrial fibrillation diagnosis using a machine learning approach: A French nationwide cohort study
No full textAimsAtrial fibrillation is associated with important mortality but the usual clinical risk factor based scores only modestly predict mortality. This study aimed to develop machine learning models for the prediction of death occurrence within the year following atrial fibrillation diagnosis and compare predictive ability against usual clinical risk scores.Methods and resultsWe used a nationwide cohort of 2,435,541 newly diagnosed atrial fibrillation patients seen in French hospitals from 2011 to 2019. Three machine learning models were trained to predict mortality within the first year using a training set (70% of the cohort). The best model was selected to be evaluate and compared with previously published scores on the validation set (30% of the cohort). Discrimination of the best model was evaluated using the C index. Within the first year following atrial fibrillation diagnosis, 342,005 patients (14.4%) died after a period of 83 (SD 98) days (median 37 [10-129]). The best machine learning model selected was a deep neural network with a C index of 0.785 (95% CI, 0.781-0.789) on the validation set. Compared to clinical risk scores, the selected model was superior to the CHA2DS2-VASc and HAS-BLED risk scores and superior to dedicated scores such as Charlson Comorbidity Index and Hospital Frailty Risk Score to predict death within the year following atrial fibrillation diagnosis (C indexes: 0.597; 0.562; 0.643; 0.626 respectively. PConclusionMachine learning algorithms predict early death after atrial fibrillation diagnosis and may help clinicians to better risk stratify atrial fibrillation patients at high risk of mortality.Translational perspectiveAtrial fibrillation is responsible for a substantial proportion of short-term mortality making futile, complex and expensive, cardiovascular procedures/devices or therapies that will not change overall prognosis due to competing risk between cardiovascular and non-cardiovascular death. Machine learning algorithms predict early mortality in atrial fibrillation patients with a better ability than previously developed traditional clinical risk scores. A Machine learning approach may help clinicians to better stratify atrial fibrillation patients at high risk of mortality and may assist physicians in decision-making when managing atrial fibrillation patients in a holistic and integrated care manner
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