ethicalabs/Research-Intent-Collab huggingface dataset:
A genetic algorithm for compressive sensing sparse recovery

The advent of compressive sensing (CS) theory opened the possibility of linking the sensing effort, that is, the volume of data being produced by the sensor, to the amount of information it conveys, rather than to the desired sensor bandwidth, as traditional sampling theory suggests. Consequently, in the typical CS scenario, one ends up with a set of few measurements and the challenge is to recover a signal whose dimensionality is much higher than the number of measurements, typically under the assumption of being sparse. One faces, therefore, a constrained l 0  minimization problem. Despite being ubiquitous in nature, finding the solution with lowest lo norm is known to be NP-hard. In this work we propose mimicking the nature to approach a solution. More specifically, we design a genetic algorithm (GA) that, despite being based on the rules of evolution of biological systems, is fully tailored to our specific problem. Adopting the terminology from genetics, our chromosomes are representations of different support configurations, with an associated restricted-support temporal solution. The fitness of each chromosome is measured in terms of reprojection error of the associated solution. We deal with the sparsity requirement by means of a generalized crossover strategy based on support set overlap, rather than explicitly adding an l 0  or l 1  regularizer to the fitness function. We show that the proposed algorithm outperforms the generic multiobjective GA NSGA-II for solving the CS constrained l 0  minimization in terms of l 2  reconstruction error, at no cost in execution time.
Examination of the role of international law in peace building and conflict resolution

International conventions, such as the United Nations Convention against Transnational Organized Crime1 and its protocols, provide comprehensive legal frameworks for addressing various aspects of transnational crime, including human trafficking, drug trafficking, and smuggling of migrants. Additionally, the United Nations Security Council has adopted several resolutions, such as Resolution 1373, which mandate States to enhance legal measures to prevent and suppress terrorist financing, recruitment, and operations. Regional agreements, like the African Union's Convention on the Prevention and Combating of Terrorism, also play a crucial role in coordinating efforts among neighbouring countries. At the national level, many States have enacted specific anti-terrorism and anti-transnational crime legislation, reinforcing criminal justice systems and enabling the prosecution of offenders, irrespective of where crimes occur. However, challenges remain in harmonizing laws across jurisdictions, ensuring effective cooperation in extradition, information sharing, and respecting human rights during law enforcement. The effectiveness of these legal frameworks depends on the political will of States, technical capacity, and the ability to balance security with civil liberties. Strengthening legal cooperation mechanisms and enhancing global partnerships remain essential for ensuring that these frameworks meet the evolving nature of transnational crime and terrorism. By doing so, the international community can address the root causes of these threats and create a more secure global environment. &nbsp;
Enterprise Management and Risk Assessment Analysis Practice

Finance is the core competitiveness of the country. Since the reform and opening up, China's financial industry has developed rapidly and made historic achievements, but there are still many contradictions and problems that make it difficult to meet the requirements of high-quality economic development. First, the debt problem: China's enterprises, local governments and household sectors are all facing considerable debt pressure. Some enterprises and local governments have hidden debts, and the debt of the household sector is also increasing. This poses a risk to the stability of the financial system.Second, financial institution risk: Some financial institutions have risks, including credit risk and liquidity risk. Some non-bank financial institutions have relatively low capital adequacy ratios and are potentially at risk of default.Third, financial chaos: some financial chaos problems still exist, such as illegal fund-raising, online financial fraud and so on. These issues challenge the effectiveness of financial regulation and public trust in the financial system.Fourth, structural problems in the financial system: there are some structural problems in China's financial system, such as insufficient interaction between the banking sector and the capital market, and relatively low efficiency of financial resource allocation. These problems constrain the development of the financial system and sustainable economic growth.
Impact and mitigation of Hamiltonian characterization errors in digital-analog quantum computation

6+8 pages, 5 figures
Quantitative Analysis of Dynamic Fault Trees by means of Monte Carlo Simulations: Event-Driven Simulation Approach

Abstract   The reliability analysis of complex and dynamic systems is often achieved by a quantitative analysis of dynamic fault trees (DFT), which model the system failure, i.e. a specific undesired event called top event, in terms of failures of the components of the system. Indeed, DFT takes into account the sequential relationships among events and their statistical dependencies. Given the failure probability of the components, the quantitative analysis aims at numerically evaluating, among other things, the failure probability of the top event. In this paper, we are interested in the Monte Carlo simulation which can consider any kind of failure distribution and is not limited in the DFT representation: it considers DFT with repeated events and shared events, takes into account all dynamic gates (PAND, SEQ, FDEP, and SPARE). However, Monte Carlo simulation encounters some disadvantages: an entirely new simulation must be executed every time a parameter changes and it may be time-consuming when the desired accuracy is high. To address these difficulties, this paper proposes a new dynamic fault tree simulation performed by an event-driven simulator. With this approach, gate simulations that produce no change in the output of a gate are eliminated augmenting the speed up of the simulation. The implementation of our approach uses an event queue data structure and an event-scheduler as alternative to the usual time-driven implementation which is characterized by an iterative loop. Thus, periods of inactivity are omitted. As results, computational efficiency is obtained and the speed-up performance of the Monte Carlo simulation program is improved.
Privacy and Hacking Powers: Is there an Implied Right to Privacy in the Use of Computer Surveillance Powers in Australia?

On 3 September 2021, Australia’s Commonwealth Parliament passed the Surveillance Legislation Amendment (Identify and Disrupt) Act 2021 (Cth). In doing so, it added to an already expansive regime of warrants and authorisations, enabling law enforcement and intelligence officers to break into, search, seize and even destroy computers, devices, or networks. These powers are largely untested in terms of judicial appeal and administrative review and are some of the most privacy-intrusive powers given by any legislation anywhere in the world. In examining the scope and interference enabled by these powers, we conclude that officers seeking warrants to hack into or damage computers, devices or networks in Australia have an implicit duty to consider the effect of their actions on the suspect’s privacy.
Pseudo-Rehearsal: Achieving Deep Reinforcement Learning without Catastrophic Forgetting

Neural networks can achieve excellent results in a wide variety of applications. However, when they attempt to sequentially learn, they tend to learn the new task while catastrophically forgetting previous ones. We propose a model that overcomes catastrophic forgetting in sequential reinforcement learning by combining ideas from continual learning in both the image classification domain and the reinforcement learning domain. This model features a dual memory system which separates continual learning from reinforcement learning and a pseudo-rehearsal system that recalls items representative of previous tasks via a deep generative network. Our model sequentially learns Atari 2600 games without demonstrating catastrophic forgetting and continues to perform above human level on all three games. This result is achieved without: demanding additional storage requirements as the number of tasks increases, storing raw data or revisiting past tasks. In comparison, previous state-of-the-art solutions are substantially more vulnerable to forgetting on these complex deep reinforcement learning tasks.
Joint PRISE - OIE training workshop on Basic Veterinary Epidemiology applied to the surveillance and research on animal diseases, in particular HPAI, Hanoi, Vietnam, 27th Novembre - 1st Decembre 2006

Cet atelier a été organisé conjointement par l'OIE et le CIRAD, en collaboration avec l'Université d'Agriculture de Hanoi, dans le cadre du Pôle de Compétence en Partenariat, PCP Prise (Pôle de recherche sur l'intensification des systèmes d'élevage) du CIRAD au Vietnam. L'objectif visé était de former des chercheurs et des agents des services vétérinaires vietnamiens aux concepts de base de l'épidémiologie appliquée à la recherche sur les maladies contagieuses et notamment la grippe aviaire ainsi qu'à l'utilisation d'outils statistiques simples. La formation reposait sur l'utilisation d'un outil d'apprentissage sur ordinateur, RANEMA (Remise à Niveau en Epidémiologie des Maladies Animales), qui a été développé par le CIRAD et l'Ecole Nationale Vétérinaire d'Alfort. L'atelier a rassemblé 26 participants de diverses institutions de recherche vietnamienne ainsi que des agents des services vétérinaires. Il a permis d'améliorer significativement les connaissances des participants en épidémiologie. La grande motivation des participants ainsi que leur participation active aux activités du cours ont contribué à la réussite de l'atelier. Il est prévu, dans le cadre des actions incitatives de la Délégation des Echanges Scientifique Internationaux du Cirad d'organiser d'autres ateliers dans le prolongement de celui-ci afin d'offrir aux partenaires vietnamiens la possibilité d'approfondir certains domaines de l'épidémiologie animales.
Sensor observation service for air quality management: a web application for suspended particulate matter pollution monitoring in urban Coimbatore, India

In Proceedings of the NSDI-2013, Annual NSDI Meeting, November 29-30, 2013, IIT Bombay, Mumbai, India
Abstract 10590: Detection of Cardiac Attr Amyloidosis in a Real-World Hf Population by Natural Language Processing Guided Automated Data Extraction From Electronic Health Records

Background:             As cardiac aTTR amyloidosis(aTTR-CM) is frequently underdiagnosed and missed, improved screening to enhance earlier diagnosis of the disease is essential. Recent observations have demonstrated that clinical clues related to the presence of aTTR-CM and additional predisposing or associated medical conditions derived from machine learning(ML) models may provide a systematic framework to increase the suspicion of aTTR-CM in heart failure(HF) pts.             Objectives:             The present study was set up to explore the use of a systematic framework to diagnose aTTR-CM in a real-world HF population.                                   Methods:             Between 2014 and 2018, 3035 HF pts (Age:74 ± 12 years; EF: 45 ± 19 %, male: 50 %) consecutively referred to a community HF clinic were assessed. Using targeted disease-specific electronic health record (EHR) models (Natural language processing/ LynxCare Inc., Leuven, Be) the prevalence and odds ratios for cardiac, non-cardiac, and combinations of both cardiac and non-cardiac phenotypes predictive for aTTR-CM were assessed.                                   Results:             101 pts((Age: 78.57 ± 9.17 years; EF 46 ±15 %, male: 40% ) were diagnosed with aTTR-CM. Besides HF and cardiomyopathy-related phenotypes, atrial fibrillation was the strongest cardiac predictor for aTTR-CM(prevalence:76 %, OR 2.95, 95% CI= 2.10, 4.14) whereas the strongest non-cardiac predictor was carpal tunnel syndrome(prevalence :21 %, OR 6.55, 95% CI= 7.21, 5.90). The combination of heart block, joint disorders, and combined systolic and diastolic HF was the highest combined phenotype in aTTR-CM(prevalence:16 %, ORR 2.63, 95% CI = 0.96, 3.28).                                   Conclusion:             On top of well-known diagnoses and phenotypes unique combinations of cardiac and non-cardiac phenotypes predict aTTR-CM In a real-world HF population. Therefore, if successfully employed in the EHR this strategy may identify aTTR-CM pts and lead to earlier detection of it by raising the suspicion of the diagnosis in HF pts.
Algorithmic Justice: The Legal Implications of AI in Criminal Sentencing and Risk Assessment

The increasing integration of artificial intelligence (AI) in criminal justice systems, particularly in sentencing and risk assessment, marks a significant shift in legal decision-making practices. While algorithmic tools such as COMPAS and HART are promoted for their potential to enhance consistency, efficiency, and objectivity, their use raises serious legal and ethical concerns. These systems often rely on biased historical data, leading to discriminatory outcomes—especially against ethnic minorities—by reinforcing systemic inequalities. Moreover, the opaque, proprietary nature of many algorithms undermines the transparency and accountability essential to a fair trial. This article examines the legal implications of algorithmic risk assessment tools, arguing that their uncritical application endangers fundamental rights such as the presumption of innocence, the right to a fair trial, and judicial discretion. Without meaningful reforms addressing bias, transparency, and due process, algorithmic justice risks replacing human judgment with flawed, unchallengeable predictions.
The Ascension Health Experience

Ascension Health is the largest Catholic and nonprofit health system in the United States, encompassing 70 acute care hospitals organized into 34 health ministries. Consistent with its distributed leadership model, Ascension Health has created a Chief Nursing Officer (CNO) Advisory Council to provide strategic direction and thought leadership on major system-level initiatives that impact quality, safety, operational performance, nursing leadership, and patient care delivery. The council fosters systemwide CNO engagement and dialogue through a unique structure of regional CNO work teams called "pods," each of which is chaired by a member of the council. This communication structure has facilitated consensus on major system initiatives at Ascension Health related to clinical goals, patient safety, nursing leadership, and systemwide capital investments. This article describes the history, structure, goals, processes, and successes of the CNO Advisory Council shared governance model.
The evolving law on sexual and reproductive health rights and the right to abortion in Kenya

Article 26(4) of the Constitution of Kenya guarantees the right to abortion in these circumstances: ‘where there is danger to the life of the mother; where there is danger to the health of the mother; if there is need for emergency treatment of any kind; and if allowed by any other written law.' Accordingly, this dissertation argues that the jurisprudence of international and regional human rights bodies demonstrates that the right to abortion is a justiciable human right. Therefore, it probes whether Kenya is honouring her state obligation to respect, promote and fulfil the right to abortion as a human right as guaranteed in the Constitution and international law obligations. Furthermore, it analyses Kenyan law and policy on the right to abortion and assesses whether Kenya's law on abortion is a barrier to the effective realization of the right to abortion. To investigate whether safe abortion is accessible to Kenyan women and a realizable human right in Kenya, the dissertation examines the Constitution, legislation and government policies on access to abortion vis-à-vis the reality and experiences of Kenyan women accessing safe abortion. The dissertation finds that the subsisting contradiction between the constitution and the penal code provisions on access to abortion reinforced by inconsistent policies from the government of Kenya continues to exacerbate unsafe abortion in Kenya thus hindering the effective realisation of the right to abortion in Kenya. The study compares how South Africa, has implemented its progressive law on the right to abortion and the insights that Kenya could draw from the South African experience.The study concludes by appealing to Kenya to ensure the effective realisation of the right to abortion by revoking the punitive clauses of the penal code, aligning laws and government policies with Article 26(4) of the Constitution, enacting the Reproductive Healthcare Bill that will expand access to abortion and educating Kenyans on the current permissive legal provisions on access to safe abortion.
Agroclimatic conditions in China under climate change scenarios projected from regional climate models

The recent warming trends have led to rising concerns on how the changing climate has been altering and will continue to alter agroclimatic conditions in China. In this study, high resolution climate scenarios from regional climate models (RCMs) are used as input to the agro-ecological zones (AEZ) model for China and to compute a comprehensive set of agroclimatic indicators. Uncertainties in the projected impacts of climate change on agroclimatic conditions are also discussed with respect to (1) RCM outputs for different emission scenarios, and (2) differences in projections obtained from two different RCMs under the same emission scenario. The results indicate a significant extension of the crop growing period in tandem with the rising temperatures during the crop growing season, which may lead to increase in multi-cropping opportunities at high latitudes and thus advance the total potential output per unit of cropland. However, the results show that the Southwest China will experience a significant reduction in the value of humidity index, implying severe challenges for future agricultural development in the region. Spatially explicit patterns of changes in future agroclimatic conditions, as revealed in this study, can be beneficial for policy-makers, farming communities and other stakeholders to assess risk factors, design adaptation and mitigation measures, and improve management practices at the local to regional scales.
Indigenous Conflict Resolution and Peace-Building among the Nabdam of Ghana

Harmonious living is an essential ingredient for the progress of every society. This requires that conflicts which are a natural part of human life are amicably resolved when they arise. Largely, people have the options of resorting to the statuary courts system or indigenous approaches which are rooted in the customs and traditions of societies for the resolution of conflicts. This study examined the indigenous conflict resolution, peace-building and human rights among the Nabdam of Ghana using the descriptive design within the qualitative research paradigm. It involved thirty persons from the area consisting chiefs, elders, and individuals who have employed the approach in resolving their disputes. The instruments of interview, focused group discussion, and observation were deployed to gather data for the respondents. It emerged from the study that the Nabdam indigenous approach to conflicts resolution has four stages which are structured and followed to achieve peace-building and the recognition of human rights of persons involved in the process. It was therefore considered important for the indigenous approach to be strengthened and promoted by the government of Ghana in all societies in the country so as to achieve peace-building. It also emerged from the study that the Nabdam indigenous conflict resolution approach has no formal place for the involvement of women in its administration even though they were found to be effective in managing disputes especially those involving women. It was therefore concluded that women should be formally involved in the application of the approach.
Transport and Logistics Planning and Optimization

This chapter aims to obtain the optimal routings for intermodal transport corridor from Turkey to the United Kingdom through a model based on the principles of 0-1 goal programming method, optimizing conflicting objectives such as minimizing transport costs, transit-time, and maximizing transit-time reliability. Cost and transit-time data in the study were obtained from a shipper company and used such an input for 0-1 goal programming model. The secondary aim in this study is to measure transit-time reliability with the transit-time data regarding conducted shipments. Thus, the Burr distribution (type XII) has been used to represent the observed transit-time data to measure the transit-time variability. The proposed model shows that transit-time reliability can play a more decisive role than transport cost and transit-time factor for competitiveness of intermodal transport routes.
How astrophysical mean field dynamos can circumvent existing quenching constraints

Mean field dynamo theory is a leading candidate to explain the observed large scale magnetic fields of galaxies and stars. However, controversy arises over the extent of premature quenching by the backreaction of the growing field. We distinguish between rapid mean field dynamo action, which is required by astrophysical systems, and resistively limited action. We show how the flow of magnetic helicity is important for rapid action. Existing numerical and analytic work suggesting that mean field dynamos are prematurely quenched and resistively limited include approximations or boundary conditions which suppress the magnetic helicity flow from the outset. Thus they do not unambiguously reveal whether real astrophysical mean field dynamos are dynamically suppressed when the helicity flow is allowed. An outflow of helicity also implies an outflow of magnetic energy and so active coronae or winds should accompany mean field dynamos. Open boundaries alone may not be sufficient for rapid dynamo action and the additional physics of buoyancy and outflows may be required. Possible simulation approaches to test some of the principles are briefly discussed. Some limitations of the ``Zeldovich relation'' are also addressed.