Business Ethics, the Environment &Responsibility, EarlyView.

Deux des auteurs d'Esthétique du film, publié dans la collection Nathan Université, Jacques Aumont et Michel Marie, se sont à nouveau associés pour présenter un bilan clair et synthétique des analyses de films publiées depuis 1970, principalement en France et aux Etats-Unis. Sans prétendre apporter une méthode universelle permettant d'analyser n'importe quel film, les auteurs se sont efforcés de décrire et de commenter les meilleures analyses et d'en retenir les acquis méthodologiques. Après avoir défini l'activité analytique, l'ouvrage aborde l'analyse dite (...) " textuelle ", l'analyse narratologique appliquée au film, l'analyse de l'image et du son ; il étudie les rapports entre analyse et histoire et pose la question des fondements de ce type de recherche. (shrink)

After satisfying their quantitative and qualitative needs as regards nutrition, consumers in developed countries are becoming more involved in the ethical aspects of food production, especially when it relates to animal products. Social demands for respecting animal welfare in housing systems are increasing rapidly, as is social awareness of human responsibility towards farm animals. Many studies have been conducted on animal welfare measurement in different production systems, but the available information for small ruminants remains insufficient. In this study, a 75 (...) criteria-evaluation tool has been set up on the basis of the five freedoms concept. Animal welfare considerations have been analyzed in 25 documents, including labeling schemes, regulations, and recommendations from different European countries. The results show many differences between regular and organic small ruminant farming standards. Emergency measures are generally lacking. A weak representation of psychological aspects of animal welfare, especially by the current European legislation, is highlighted. (shrink)

Virtual screening is the most critical process in drug discovery, and it relies on machine learning to facilitate the screening process. It enables the discovery of molecules that bind to a specific protein to form a drug. Despite its benefits, virtual screening generates enormous data and suffers from drawbacks such as high dimensions and imbalance. This paper tackles data imbalance and aims to improve virtual screening accuracy, especially for a minority dataset. For a dataset identified without considering the data’s imbalanced (...) nature, most classification methods tend to have high predictive accuracy for the majority category. However, the accuracy was significantly poor for the minority category. The paper proposes a K-mean algorithm coupled with Synthetic Minority Oversampling Technique to overcome the problem of imbalanced datasets. The proposed algorithm is named as KSMOTE. Using KSMOTE, minority data can be identified at high accuracy and can be detected at high precision. A large set of experiments were implemented on Apache Spark using numeric PaDEL and fingerprint descriptors. The proposed solution was compared to both no-sampling method and SMOTE on the same datasets. Experimental results showed that the proposed solution outperformed other methods. (shrink)