Les déterminants de la baisse de la fécondité en Algérie

وصلت الخصوبة، التي تشكل عنصر أساسي للحركة الديمغرافية، إلى مستويات لم تعهدها الجزائر من قبل. فلقد كان معدل عدد الأطفال لكل امرأة، وهوالمؤشر الذي يعبر أحسن تعبير على الخصوبة، يقارب خلال السبعينيات الثماني أطفال (08) لكل امرأة. يعتبر هذا "الانفجار السكاني" الذي حدث في الجزائر بعيد الاستقلال نتيجة تضافر عوامل متعددة اجتماعية، ديمغرافية وتاريخية.شرعت، منذ الثمانينيات، نسبة الخصوبة في التدني المستمر حسب والسريع أدى في النهاية إلى انخفاض عدد الأطفال النهائي لكل امرأة الذي تراجع بدوره  من حوالي ثماني أطفال لكل امرأة في السبعينيات إلى قرابة طفلين فقط في السنوات الأخيرة.يفسر الانخفاض الهام للخصوبة بعدة عوامل أهمها تراجع سن زواج الإناث بسبب تمديد فترة الدراسة خاصة وانتشار ممارسة تباعد الولادات نتيجة ارتفاع المستوى الثقافي للأمهات La fécondité qui constitue une composante essentielle de la dynamique démographique a atteint des niveaux jamais égalés en Algérie. En effet, le nombre moyen d’enfants par femme qui illustre le mieux le niveau de la fécondité, avoisinait les 8 enfants par femme dans les années 1970. Cette « explosion démographique » post indépendance observée en Algérie est le résultat d’une association de plusieurs facteurs aussi bien d’ordre social, démographique, qu’historique. A partir des années 1980 s’enclenche un mouvement de baisse de la fécondité qui se poursuivra à un rythme de plus en plus rapide et qui se traduira par une chute de la descendance par femme qui passe d’un peu plus de 8 enfants à environ 2 enfants de nos jours. La réduction importante de la fécondité est attribuée à plusieurs facteurs dont les plus déterminants sont le recul de l’âge au mariage, particulièrement féminin, notamment grâce à l’allongement de la durée des études et au développement de la pratique contraceptive

LE REEQUILIBRAGE DU CONTRAT INTERNATIONAL SUITE A DES CIRCONSTANCES IMPREVISIBLES

L’environnement politique et économique en constante évolution génère des répercutions sur l’économie et l’équilibre de plusieurs contrats internationaux. Le contrat étant à la fois un outil de prévision ainsi qu’un véhicule de circulation de richesses, peut prévoir la possibilité de maintenir son équilibre économique et le réadapter à toute circonstance nouvelle dite imprévisible. Ce rééquilibrage se fait à travers la renégociation ou carrément la résiliation du contrat international, c’est qu’on appelle la clause hardship.De plus, en l’absence de stipulations contractuelles, le droit international à travers les conventions internationales et la lex mercatoria ainsi que plusieurs législations nationales admettent la révision du contrat suite à l’avènement de circonstances imprévisibles en dépassant le principe de la force obligatoire du contrat ainsi que son intangibilité dans le cadre de la théorie d’imprévision

DeePromoter: Robust Promoter Predictor Using Deep Learning

The promoter region is located near the transcription start sites and regulates transcription initiation of the gene by controlling the binding of RNA polymerase. Thus, promoter region recognition is an important area of interest in the field of bioinformatics. Numerous tools for promoter prediction were proposed. However, the reliability of these tools still needs to be improved. In this work, we propose a robust deep learning model, called DeePromoter, to analyze the characteristics of the short eukaryotic promoter sequences, and accurately recognize the human and mouse promoter sequences. DeePromoter combines a convolutional neural network (CNN) and a long short-term memory (LSTM). Additionally, instead of using non-promoter regions of the genome as a negative set, we derive a more challenging negative set from the promoter sequences. The proposed negative set reconstruction method improves the discrimination ability and significantly reduces the number of false positive predictions. Consequently, DeePromoter outperforms the previously proposed promoter prediction tools. In addition, a web-server for promoter prediction is developed based on the proposed methods and made available at https://home.jbnu.ac.kr/NSCL/deepromoter.htm

Towards Controlling the Acceptance Factors for a Collaborative Platform in Engineering Design

International audienceThis paper might serve as a guide to take step towards a better acceptance of computer-based Knowledge management (KM) tools in institutional setting. At first time, it investigates a set of factors with different origins which are proved to have an effect on usage decision. Secondly, we set a list of candidate factor which are supposed to influence future users of a collaborative KM platform (Dimocode). At the end, we develop a methodology to take into account the selected factors and master their positive or negative impacts. The contents of this paper would be an appropriate framework in the way of Knowledge management systems (KMS) deployment

From protein-protein to isoform-isoform interactions: the toolkit to map alternative splicing to interactome

Alternative splicing (AS) can impact protein structure and lead to protein-protein interaction (PPI) rewiring. Available PPI networks neglect alternative splicing isoforms: as interactions might happen only between a subset of isoforms, the PPI network contains both false-positive and false-negative interactions. Since it is not feasible to validate all isoform-isoform interactions experimentally, we present a set of tools to investigate AS on a network level: DIGGER to map splicing to the PPI network, as well as NEASE and Spycone to evaluate the functional consequences of network rewiring. DIGGER (https://exbio.wzw.tum.de/digger) integrates PPIs, domain-domain, and residuelevel interactions - the structures that might be spliced in or out and result in interaction gain or loss. Users can explore possible rewiring for an isoform or exon of interest and extract relevant subnetworks. NEASE (https://github.com/louadi/NEASE) identifies pathways that are significantly affected by network rewiring. NEASE extends classic gene set enrichment analysis by considering isoform-specific interactions affecting pathways. Spycone (https://github.com/yollct/spycone) addresses the time-course changes in AS. It searches for isoforms that demonstrate similar temporal splicing patterns and reflect the splicing co-regulation. Spycone further integrates gene set, network, and splicing-aware NEASE enrichment. Overall, we offer a splicing-focused network analysis toolkit that allows for studying the mechanistic consequences of AS.Book of abstract: 4th Belgrade Bioinformatics Conference, June 19-23, 202

A Dynamic Knowledge Management Framework for the High Value Manufacturing Industry

Dynamic Knowledge Management (KM) is a combination of cultural and technological factors, including the cultural factors of people and their motivations, technological factors of content and infrastructure and, where these both come together, interface factors. In this paper a Dynamic KM framework is described in the context of employees being motivated to create profit for their company through product development in high value manufacturing. It is reported how the framework was discussed during a meeting of the collaborating company’s (BAE Systems) project stakeholders. Participants agreed the framework would have most benefit at the start of the product lifecycle before key decisions were made. The framework has been designed to support organisational learning and to reward employees that improve the position of the company in the market place

Factors influencing AIS effectiveness among manufacturing SMEs: Evidence from Malaysia

This study examines accounting information systems (AIS) effectiveness and its influence factors in the specific context of small and medium manufacturing enterprises (SMEs) in Malaysia. The proposed model examines the impact of AIS sophistication, manager participation in AIS implementation, manager AIS knowledge, manager accounting knowledge, and effectiveness of external experts such as vendors, consultants, government agencies, and accounting firms on AIS effectiveness. We included 232 SMEs registered with the Federation of Malaysian Manufacturers (FMM) in testing the model. The results show that manager accounting knowledge, and the effectiveness of vendors and accounting firms significantly contributed to AIS effectiveness. Overall, this study suggests that managers of SMEs need to acquire sufficient accounting knowledge to better understand business information requirements. Second, SMEs should engage qualified vendors who have experience and understand unique characteristics of SME to overcome their lack of AIS knowledge. SMEs should also exploit their good relationship with accounting firms to help them implement effective AIS. Finally, it is important for SMEs to learn from AIS implementation so that opportunities can be recognized and priority can be given to those initiatives that support their information needs

The AIMe registry for artificial intelligence in biomedical research

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