The Issue of Enforcement in International Law: A Case Study of the War in Ukraine

This thesis seeks to outline ways to enforce international law more effectively. Through the analysis of the current international legal framework and the different mechanisms created to enforce international law, it identifies why they are insufficient to enforce international law effectively, and it gives recommendations to ameliorate the way international law is currently enforced. This research focuses on the ongoing war in Ukraine as a case study, and provides specific examples of ways international law was grossly violated by Russia, a U.N. permanent Security Council member, in order to identify patterns in the non-enforcement of international law. To bridge the gap in the literature regarding the conflict in Ukraine, this thesis looks at information from social media, as well as testimonies from people in Ukraine. It identifies the impunity gap and the lack of corporate accountability as the two main areas of focus for the enforcement of international law. The research suggests the implementation of a shared governance model, the creation of more regional organizations, and more cooperation and transparency between national and international legal/judicial systems to strengthen the effective enforcement of international law. Moreover, it proposes to include corporations into the international legal framework to address corporate impunity

Locating leak detecting sensors in a water distribution network by solving prize-collecting Steiner arborescence problems

We consider the problem of optimizing a novel acoustic leakage detection system for urban water distribution networks. The system is composed of a number of detectors and transponders to be placed in a choice of hydrants such as to provide a desired coverage under given budget restrictions. The problem is modeled as a particular Prize-Collecting Steiner Arborescence Problem. We present a branch-and-cut-and-bound approach taking advantage of the special structure at hand which performs well when compared to other approaches. Furthermore, using a suitable stopping criterion, we obtain approximations of provably excellent quality (in most cases actually optimal solutions). The test bed includes the real water distribution network from the Lausanne region, as well as carefully randomly generated realistic instance

An Effective Branch-and-cut algorithm in Order to Solve the Mixed Integer Bi-level Programming

[EN] In this paper, a new branch-and-cut algorithm for mixed integer bi-level programming is proposed. For achieving this purpose, a historical perspective of the development of enumeration methods in the field of bi-level linear programming is considered. Then, we present some obstacles for using branch and bound method based on them, and an algorithm is developed to solve for mixed integer bi-level problem. Finally, we use a preference function to determine the choice of branching and specialized cuts in a branch and cut tree. Computational results are reported and compared favorably to those of previous methods and then implications discussed. The results show that not only the proposed algorithm can find high quality solutions for solving a number of the problems, but also it is competitive with other famous published algorithms.Rahmani, A.; Yousefikhoshbakht, M. (2017). An Effective Branch-and-cut algorithm in Order to Solve the Mixed Integer Bi-level Programming. International Journal of Production Management and Engineering. 5(1):1-10. doi:10.4995/ijpme.2017.6512SWORD1105

Emergence of antibiotic resistance in immunocompromised host populations: A case study of emerging antibiotic resistant tuberculosis in AIDS patients

Objective The evolution of antibiotic resistance is far outpacing the development of new antibiotics, causing global public health concern about infections that will increasingly be unresponsive to antimicrobials. This risk of emerging antibiotic resistance may be meaningfully altered in highly AIDS-immunocompromised populations. Such populations fundamentally alter the bacterial evolutionary landscape in two ways, which we seek to model and analyze. First, widespread, population-level immunoincompetence creates a novel host environment with disrupted selective pressures. Second, within AIDS-prevalent populations, the recommendation that antibiotics be taken to treat and prevent opportunistic infection raises the risk of selection for drug-resistant pathogens. Design To determine the impact of HIV/AIDS on the emergence of antibiotic resistance–specifically in the developing world where high prevalence and economic challenges complicate disease management. Methods We present an SEIR epidemiological model of bacterial infection, and parametrize it to capture HIV/AIDS-attributable emergence of resistance under conditions of both high and low HIV/AIDS prevalence. Results We demonstrate that HIV/AIDS-immunocompromised hosts can be responsible for a disproportionately greater contribution to emergence of resistance than would be expected based on population-wide HIV/AIDS prevalence alone. As such, the AIDS-immunocompromised have the potential become wellsprings of novel, resistant, opportunistic pathogen strains that can propagate into the broader global community. We discuss how public health policies for HIV/AIDS management can shape the evolutionary environment for opportunistic bacterial infections

Locating leak detecting sensors in a water distribution network by solving prize-collecting Steiner arborescence problems

We consider the problem of optimizing a novel acoustic leakage detection system for urban water distribution networks. The system is composed of a number of detectors and transponders to be placed in a choice of hydrants such as to provide a desired coverage under given budget restrictions. The problem is modeled as a particular Prize-Collecting Steiner Arborescence Problem. We present a branch-and-cut-and-bound approach taking advantage of the special structure at hand which performs well when compared to other approaches. Furthermore, using a suitable stopping criterion, we obtain approximations of provably excellent quality (in most cases actually optimal solutions). The test bed includes the real water distribution network from the Lausanne region, as well as carefully randomly generated realistic instances

Human and mouse essentiality screens as a resource for disease gene discovery.

The identification of causal variants in sequencing studies remains a considerable challenge that can be partially addressed by new gene-specific knowledge. Here, we integrate measures of how essential a gene is to supporting life, as inferred from viability and phenotyping screens performed on knockout mice by the International Mouse Phenotyping Consortium and essentiality screens carried out on human cell lines. We propose a cross-species gene classification across the Full Spectrum of Intolerance to Loss-of-function (FUSIL) and demonstrate that genes in five mutually exclusive FUSIL categories have differing biological properties. Most notably, Mendelian disease genes, particularly those associated with developmental disorders, are highly overrepresented among genes non-essential for cell survival but required for organism development. After screening developmental disorder cases from three independent disease sequencing consortia, we identify potentially pathogenic variants in genes not previously associated with rare diseases. We therefore propose FUSIL as an efficient approach for disease gene discovery