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Psychometric validation of the French version of the Supportive Care Needs Survey for Partners and Caregivers of cancer patients
No full textInternational audienceThe objective of this study was to assess the psychometric properties of the French version of the Supportive Care Needs Survey for Partners and Caregivers (SCNS-P&C-F). The SCNS-P&C-F, the Hospital Anxiety and Depression Scale (HADS) and the CareGiver Oncology Quality of Life questionnaire (CarGOQoL) were completed by 327 caregivers at the baseline. The SCNS-P&C-F was completed a second time by 121 participants within 30 days. Four factors were retained with a good explanation of variance (82.65%) and acceptable internal consistencies (α: 0.70 to 0.94): 1) Health Care Service and Information Needs, 2) Emotional and Psychological Needs, 3) Work and Social Security Needs and 4) Communication and Family Support Needs. Overall, convergent and divergent validities were confirmed. The caregiver's gender, age, professional status and level of anxiety and depression, as well as the type of relationship with the patient and cancer, showed an effect on some caregivers’ unmet supportive care needs. Lastly, the test–retest reliability was acceptable (> 0.70), except for the communication and family support dimension. The scale is appropriate for clinical and research use (e.g. good reliability and validity)
WEAK FUNCTORIALITY OF COHEN-MACAULAY ALGEBRAS
No full textInternational audienceWe prove the weak functoriality of (big) Cohen-Macaulay algebras, which controls the whole skein of "homological conjectures" in commutative algebra [10][13]; namely, for any local homomorphism R → R of complete local domains, there exists a compatible homomorphism between some Cohen-Macaulay R-algebra and some Cohen-Macaulay R-algebra. When R contains a field, this is already known [13, 3.9]. When R is of mixed characteristic , our strategy of proof is reminiscent of G. Dietz's refined treatment [7] of weak functoriality of Cohen-Macaulay algebras in characteristic p; in fact, developing a "tilt-ing argument" due to K. Shimomoto, we combine the perfectoid techniques of [1][2] with Dietz's result
TOFLIT18, le retour
No full textInternational audiencePrésenté dans le Dialogue n°43 de juillet 2016, l’objectif du projet TOFLIT18 est d’ouvrir de nouvelles voies de recherche sur l’histoire économique française à la veille de la révolution industrielle grâce aux données des archives du Bureau de la Balance du Commerce (L. Charles et G. Daudin, 2011) portant sur plus de 500 000 flux du commerce extérieur français. Trois ans plus tard, nous exposons ici un bref aperçu de l’évolution du projet et de sa situation actuelle. Pour plus de détails, les lecteurs intéressés ou ceux entreprenant des projets similaires pourront consulter le site https://toflit18.hypotheses.org
Contribution of chronic diseases to educational disparity in disability in France: results from the cross-sectional “disability-health” survey
No full textInternational audienceBackground: This study aimed 1) to assess whether the contribution of chronic conditions to disability varies according to the educational attainment, 2) to disentangle the contributions of the prevalence and of the disabling impact of chronic conditions to educational disparities.Methods: Data of the 2008-09 Disability Health Survey were examined (N = 23,348). The disability indicator was the Global Activity Limitation Indicator (GALI). The attribution method based on an additive hazard model was used to estimate educational differences in disabling impacts and in the contributions of diseases to disability. Counterfactual analyses were used to disentangle the contribution of differences in disease prevalence vs. disabling impact.Results: In men, the main contributors to educational difference in disability prevalence were arthritis (contribution to disability prevalence: 5.7% (95% CI 5.4-6.0) for low-educated vs. 3.3% (3.0-3.9) for high-educated men), spine disorders (back/neck pain, deformity) (3.8% (3.6-4.0) vs. 1.9% (1.8-2.1)), chronic obstructive pulmonary diseases (2.4% (2.3-2.6) vs. 0.6% (0.5-0.7)) and ischemic heart /peripheral artery diseases (4.1% (3.9-4.3) vs. 2.4% (2.2-3.0)). In women, arthritis (9.5% (9.1-9.9) vs. 4.5%, (4.1-5.2)), spine disorders (4.5% (4.3-4.7) vs. 2.1% 1.9-2.3) and psychiatric diseases (3.1% (3.0-3.3) vs. 1.1% (1.0-1.3)) contributed most to education gap in disability. The educational differences were equally explained by differences in the disease prevalence and in their disabling impact.Conclusions: Public health policies aiming to reduce existing socioeconomic disparities in disability should focus on musculoskeletal, pulmonary, psychiatric and ischemic heart diseases, reducing their prevalence as well as their disabling impact in lower socioeconomic groups
« Le Chevalier hypocondriaque de Gilbert Saulnier Du Verdier (1632) ou la nostalgie du roman de chevalerie ».
No full textInternational audienc
Dynamic compartmental models for algorithm analysis and population size estimation
No full textInternational audienceDynamic Compartmental Models (DCM) can be used to study the population dynamics of Multi- and Many-objective Optimization Evolutionary Algorithms (MOEAs). These models track the composition of the instantaneous population by grouping them in compartments and capture their behavior in a set of values, creating a compact representation for analysis and comparison of algorithms. Furthermore, the use of DCMs is not limited to analysis, by creating models of the same algorithm with different configurations is possible to extract new models by interpolation, and use them to explore fine-grained configurations lying between the ones used as a base. We illustrate the use of the model on some Multi- and Many-objective algorithms, run on enumerable MNK-Landscapes instances with 6 objectives for the analysis, and 5 objectives when used as a tool to do configuration
La représentation des frontières dans les discours de Marine Le Pen et de Viktor Orbán
No full textInternational audienceThis research confronts how Marine Le Pen and Viktor Orbán use border theme in the context of the arrival of migrants in Europe in their discourse. The analysis shows two populist visions of border security: the restoration and control of national borders versus the closure of the external borders of the Schengen Area. These narratives project two conceptions of national sovereignty: France withdrawn into itself and a Fortress Europe. They reflect the representation of the borders as symbols of identity in terms of the protection of territory and the assertion of power.L’objectif de cette recherche est de confronter la représentation des frontières dans les discours de deux leaders très médiatisés dans l’espace public national et européen Marine Le Pen et Viktor Orbán, à partir du contexte de l’arrivée des migrants en Europe. Dans les récits élaborés la frontière se trouve au centre du discours populiste, mais son utilisation ne fait sens que par rapport à un symbolisme identitaire situé à plusieurs échelles : par rapport à l’opposition entre les étrangers (Européens/migrants) et le pouvoir de l’étranger (Bruxelles) versus le pouvoir du peuple incarné par les leaders. L’analyse montre deux visions populistes de sécurisations du territoire : le rétablissement et le contrôle des frontières nationales ou la fermeture des frontières de l’Espace Schengen. Les discours des deux leaders populistes traduisent la représentation symbolique et identitaire des frontières sous l’angle de la protection du territoire et de l’affirmation du pouvoir, mais ils projettent deux conceptions opposées de la souveraineté nationale : une France repliée sur soi et une Europe forteress
Sorting and Transforming Program Repair Ingredients via Deep Learning Code Similarities
No full textInternational audienceIn the field of automated program repair, the redundancy assumption claims large programs contain the seeds of their own repair. However, most redundancy-based program repair techniques do not reason about the repair ingredients---the code that is reused to craft a patch. We aim to reason about the repair ingredients by using code similarities to prioritize and transform statements in a codebase for patch generation. Our approach, DeepRepair, relies on deep learning to reason about code similarities. Code fragments at well-defined levels of granularity in a codebase can be sorted according to their similarity to suspicious elements (i.e., code elements that contain suspicious statements) and statements can be transformed by mapping out-of-scope identifiers to similar identifiers in scope. We examined these new search strategies for patch generation with respect to effectiveness from the viewpoint of a software maintainer. Our comparative experiments were executed on six open-source Java projects including 374 buggy program revisions and consisted of 19,949 trials spanning 2,616 days of computation time. DeepRepair's search strategy using code similarities generally found compilable ingredients faster than the baseline, jGenProg, but this improvement neither yielded test-adequate patches in fewer attempts (on average) nor found significantly more patches than the baseline. Although the patch counts were not statistically different, there were notable differences between the nature of DeepRepair patches and baseline patches. The results demonstrate that our learning-based approach finds patches that cannot be found by existing redundancy-based repair techniques
Bears: An Extensible Java Bug Benchmark for Automatic Program Repair Studies
No full textProceedings of the 26th IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER '19)International audienceBenchmarks of bugs are essential to empirically evaluate automatic program repair tools. In this paper, we present Bears, a project for collecting and storing bugs into an extensible bug benchmark for automatic repair studies in Java. The collection of bugs relies on commit building state from Continuous Integration (CI) to find potential pairs of buggy and patched program versions from open-source projects hosted on GitHub. Each pair of program versions passes through a pipeline where an attempt of reproducing a bug and its patch is performed. The core step of the reproduction pipeline is the execution of the test suite of the program on both program versions. If a test failure is found in the buggy program version candidate and no test failure is found in its patched program version candidate, a bug and its patch were successfully reproduced. The uniqueness of Bears is the usage of CI (builds) to identify buggy and patched program version candidates, which has been widely adopted in the last years in open-source projects. This approach allows us to collect bugs from a diversity of projects beyond mature projects that use bug tracking systems. Moreover, Bears was designed to be publicly available and to be easily extensible by the research community through automatic creation of branches with bugs in a given GitHub repository, which can be used for pull requests in the Bears repository. We present in this paper the approach employed by Bears, and we deliver the version 1.0 of Bears, which contains 251 reproducible bugs collected from 72 projects that use the Travis CI and Maven build environment