The crime of abortion between Islamic law and Algerian law

يسعى هذا البحث الى توضيح مفهوم جريمة الإجهاض، وشرح أركانها و شروطها و بيان ما يترتب عليها من عقوبات، فالإجهاض هو إنهاء متعمد وبلا ضرورة لحالة الحمل، قبل الموعد الطبيعي للولادة، وهو جناية يحرمها الاسلام لما فيها من انتهاك لحرمات الله تعالى، كما تجرمها القوانين الوضعية ومنها القانون الجزائري لأنها تشكل اعتداء على مصلحة الجنين والأم والمجتمع الانساني، ويوقع النظام الجنائي الإسلامي عقوبات عادلة على مقترف هذه الجناية، من غرة وكفارة وتعزير وحرمان من الميراث، وغيرها، عند توفر أركانها وتحقق شروطها، ويخلص هذا البحث الى اهم أوجه الشبه والاتفاق بين الفقه الاسلامي والقانون الجزائري في مجال تجريم الإجهاض وتحديد صوره وحالات اباحتهThis research seeks to clarify the concept of the crime of abortion, to explain its elements and conditions and to clarify the consequential judicial penalties, for abortion is an intentional and unnecessary termination of the state of pregnancy, before the natural date of birth, and it is a crime that Islam prohibits because of its violation of God’s prohibitions, as Criminal laws, including Algerian law, criminalize them because they constitute an attack on the interests of the fetus, the mother, and the human community, And the Islamic criminal system imposes fair penalties on the perpetrator of this crime, from surprise, atonement, ta'zir, deprivation of inheritance, and others, when its pillars are available and it’s conditions are fulfilled. And this research concludes with the most important similarities and agreement between Islamic jurisprudence and Algerian law in the field of criminalizing abortion and specifying its forms and cases of legalization. &nbsp

Analyse de la diversité génétique et symbiotique des populations naturelles tunisiennes de Medicago truncatula et recherche de QTL liés au stress salin

TOULOUSE3-BU Sciences (315552104) / SudocSudocFranceF

Solving combinatorial bi-level optimization problems using multiple populations and migration schemes

In many decision making cases, we may have a hierarchical situation between different optimization tasks. For instance, in production scheduling, the evaluation of the tasks assignment to a machine requires the determination of their optimal sequencing on this machine. Such situation is usually modeled as a Bi-Level Optimization Problem (BLOP). The latter consists in optimizing an upper-level (a leader) task, while having a lower-level (a follower) optimization task as a constraint. In this way, the evaluation of any upper-level solution requires finding its corresponding lower-level (near) optimal solution, which makes BLOP resolution very computationally costly. Evolutionary Algorithms (EAs) have proven their strength in solving BLOPs due to their insensitivity to the mathematical features of the objective functions such as non-linearity, non-differentiability, and high dimensionality. Moreover, EAs that are based on approximation techniques have proven their strength in solving BLOPs. Nevertheless, their application has been restricted to the continuous case as most approaches are based on approximating the lower-level optimum using classical mathematical programming and machine learning techniques. Motivated by this observation, we tackle in this paper the discrete case by proposing a Co-Evolutionary Migration-Based Algorithm, called CEMBA, that uses two populations in each level and a migration scheme; with the aim to considerably minimize the number of Function Evaluations (FEs) while ensuring good convergence towards the global optimum of the upper-level. CEMBA has been validated on a set of bi-level combinatorial production-distribution planning benchmark instances. The statistical analysis of the obtained results shows the effectiveness and efficiency of CEMBA when compared to existing state-of-the-art combinatorial bi-level EAs

Fusion de préférences pour la détection de communautés dans les réseaux sociaux

National audienceThis article addresses the issue of preference fusion in the context of social networks. The aim of this work is to compute the collective preferences of a user group belonging to a given community from the individual preferences of each of them. In particular, we are interested here in the representation of individual preferences taking into account the uncertainty phenomenon. The uncertainty representing a source of complexity in decision making, we propose an effective preference fusion method based on belief function theory. This method allows to qualify some user communities by analyzing the collective preferences obtained during the fusion process. Specifically, it allows the characterization of communities sharing the same collective preferences. Experiments on generated data highlight the interest of the proposed solution.Cet article aborde la problématique de la fusion de préférences dans le contexte des réseaux sociaux. L'ob-jectif de ce travail est de déterminer les préférences " collectives " d'un groupe d'utilisateurs appartenant a une communauté donnéè a partir des préférences indivi-duelles de chacun d'entre eux. En particulier, nous nous intéressons icì a la représentation des préférences des individus en tenant compte de leurs incertitudes. L'in-certitude représentant une source de complexité dans la prise de décision , nous proposons une méthode efficace de fusion de préférences fondée sur la théorie des fonc-tions de croyance. Cette méthode permet de qualifier des communautés d'utilisateurs par l'analyse des préférences collectives obtenues a l'issue de l'´ etape de fusion. Plus précisément , elle permet la caractérisation des commu-nautés partageant les mêmes préférences collectives. Des expérimentations sur des jeux de données générées sou-lignent l' interêt de la solution proposée. Mots-clés : Réseaux sociaux, fusion de préférences , fonctions de croyances

Supplemental Material - Understanding the nature of social embeddedness in police recruitment in England and Wales

Supplemental Material for Understanding the nature of social embeddedness in police recruitment in England and Wales by Gareth Stubbs, Elarbi Ben Ayed Elkaroui and Irianto Harny in The Police Journal.</p

A new decomposition-based NSGA-II for many-objective optimization

Multiobjective evolutionary algorithms (MOEAs) have proven their effectiveness and efficiency in solving problems with two or three objectives. However, recent studies show that MOEAs face many difficulties when tackling problems involving a larger number of objectives as their behavior becomes similar to a random walk in the search space since most individuals are nondominated with respect to each other. Motivated by the interesting results of decomposition-based approaches and preference-based ones, we propose in this paper a new decomposition-based dominance relation to deal with many-objective optimization problems and a new diversity factor based on the penalty-based boundary intersection method. Our reference point-based dominance (RP-dominance), has the ability to create a strict partial order on the set of nondominated solutions using a set of well-distributed reference points. The RP-dominance is subsequently used to substitute the Pareto dominance in nondominated sorting genetic algorithm-II (NSGA-II). The augmented MOEA, labeled as RP-dominance-based NSGA-II, has been statistically demonstrated to provide competitive and oftentimes better results when compared against four recently proposed decomposition-based MOEAs on commonly-used benchmark problems involving up to 20 objectives. In addition, the efficacy of the algorithm on a realistic water management problem is showcased

Cynodon dactylon L. extract as an eco-friendly corrosion inhibitor of mild steel in saline solution

Corrosion-induced loss of metal integrity is a serious industrial concern. One of the most reliable and cost-effective corrosion reduction solutions is corrosion inhibitor innovation. The aim of this investigation therefore, is to study the corrosion inhibition of Cynodon dactylon L (Bermuda grass) extract on mild steel in a 3.5% NaCl solution. The plant was extracted with 80% ethanol and different concentrations were tested at a temperature range of 30 to 60OC and for various immersion time ranging from 4 to 72 hours using gravimetric (Weight Loss) method. The results showed that Cynodon dactylon extract exhibited strong corrosion inhibition efficiency (97.78%.). The inhibition efficiency of the Cynodon dactylon extract increased with an increase of extract concentration and through the immersion periods but decreased with an increase of the temperature. The inhibitive effect could be attributed to the presence of some phytochemical compounds in the plant which were adsorbed on the surface of the mild steel

Code smell detection and identification in imbalanced environments: .

International audienceContext: Code smells are sub-optimal design choices that could lower software maintainability.Objective: Previous literature did not consider an important characteristic of the smell detection problem,namely data imbalance. When considering a high number of code smell types, the number of smelly classesis likely to largely exceed the number of non-smelly ones, and vice versa. Moreover, most studies did address the smell identification problem, which is more likely to present a higher imbalance as the number of smellyclasses is relatively much less than the number of non-smelly ones. Furthermore, an additional research gap in the literature consists in the fact that the number of smell type identification methods is very small comparedto the detection ones

Agrobacterium strains isolated from root nodules of common bean specifically reduce nodulation by Rhizobium gallicum

Publication Inra prise en compte dans l'analyse bibliométrique des publications scientifiques mondiales sur les Fruits, les Légumes et la Pomme de terre. Période 2000-2012. http://prodinra.inra.fr/record/256699International audienceIn a previous work, we showed that non-nodulating agrobacteria strains were able to colonize root nodules of common bean. Both rhizobia and agrobacteria co-existed in the infected nodules. No impact on symbiosis was found in laboratory conditions when using sterile gravel as a support for growth. In this study, soil samples originating from different geographic and agronomic regions in Tunisia were inoculated with a mixture of agrobacteria strains isolated previously from root nodules of common bean. A significant effect on nodulation and vegetal growth of common bean was observed. Characterization of nodulating rhizobia and comparison with non-inoculated controls showed a biased genetic structure. It seemed that Rhizobium gallicum was highly inhibited, whereas nodulation by Sinorhizobium medicae was favored. Co-inoculation of non-sterile soils with R. gallicum and agrobacteria confirmed these findings. In vitro antibiosis assays indicated that agrobacteria exercised a significant antagonism against R. gallicum