ethicalabs/Research-Intent-Collab huggingface dataset:
The power spectrum of cosmic microwave background polarization from cosmic string wakes

Nous calculons la contribution intégrée au spectre de puissance de la polarisation du fond diffus cosmique (CMB) grâce aux sillages des cordes cosmiques. Une introduction aux défauts topologique, cordes cosmiques, de polarisation du CMB, et aux champs spin–s est donnée. Nous utilisons ensuite ces outils pour calculer le spectre de puissance angulaire de la polarisation des modes E et B grâce aux des sillages des cordes cosmiques, dans la limite du ciel plat. Nous trouvons que les termes de corrélation croisée (EB, ET, BT) sont zero, tandis que les spectres de puissance pour EE et BB ont la même forme et grandeur. Ce résultat contraste le polarisation du mode B causée par les fluctuations Gaussiennes, qui disparaîssent. Cependant, nous trouvons que la forme du spectre de puissance causée par les sillages de cordes cosmiques est très similaire au spectre en mode B prédite par lentille gravitationnelle, mais avec une amplitude globale trés faible. Donc, le signal du sillage de corde cosmique est trop faible pour être measuré au-dessus l'indicatif du lentille. Aussi, les méthodes de soustraction du fond serait très difficile. Nous trouvons que l'amplitude maximum dans le spectre de puissance sqrt(l(l+1)C_l/2pi) est d'environ 10^(-4) pour l~400.Nous étudions brièvement le forme asymptotique du spectre de puissance, et nous trouvons que Cl est quasi–constant en l jusqu'à un tournant correspondant à la taille angulaire du sillage le plus important. Nous déterminons alors quel sillage donne la contribution dominante au spectre de puissance complet. Nous trouvons que les sillages dominants sont ceux qui ont été formés à l'epoque de l'égalité de matière et de rayonnement, et qui croisent notre cône de lumière passé à l'époque de recombinaison. Nous concluons que l'indicatif dans l'espace Fourier est trop faible pour être détecté. Donc, les recherches futures devraient se concentrer sur les caractéristiques l'espace spatial.
Land‐use strategies to balance livestock production, biodiversity conservation and carbon storage in Yucatán, Mexico

AbstractBalancing the production of food, particularly meat, with preserving biodiversity and maintaining ecosystem services is a major societal challenge. Research into the contrasting strategies of land sparing and land sharing has suggested that land sparing—combining high‐yield agriculture with the protection or restoration of natural habitats on nonfarmed land—will have lower environmental impacts than other strategies. Ecosystems with long histories of habitat disturbance, however, could be resilient to low‐yield agriculture and thus fare better under land sharing. Using a wider suite of species (birds, dung beetles and trees) and a wider range of livestock‐production systems than previous studies, we investigated the probable impacts of different land‐use strategies on biodiversity and aboveground carbon stocks in the Yucatán Peninsula, Mexico—a region with a long history of habitat disturbance. By modelling the production of multiple products from interdependent land uses, we found that land sparing would allow larger estimated populations of most species and larger carbon stocks to persist than would land sharing or any intermediate strategy. This result held across all agricultural production targets despite the history of disturbance and despite species richness in low‐ and medium‐yielding agriculture being not much lower than that in natural habitats. This highlights the importance, in evaluating the biodiversity impacts of land use, of measuring population densities of individual species, rather than simple species richness. The benefits of land sparing for both biodiversity and carbon storage suggest that safeguarding natural habitats for biodiversity protection and carbon storage alongside promoting areas of high‐yield cattle production would be desirable. However, delivering such landscapes will probably require the explicit linkage of livestock yield increases with habitat protection or restoration, as well as a deeper understanding of the long‐term sustainability of yields, and research into how other societal outcomes vary across land‐use strategies.
The problem of phase transitions in statistical mechanics

The first part of this review deals with the single-phase approach to the statistical theory of phase transitions. This approach is based on the assumption that a first-order phase transition is due to the loss of stability of the parent phase. We demonstrate that it is practically impossible to find the coordinates of the transition points using this criterion in the framework of the global Gibbs theory which describes the state of the entire macroscopic system. On the basis of the Ornstein?Zernike equation we formulate a local approach that analyzes the state of matter inside the correlation sphere of radius Rc ? 10 ?. This approach is proved to be as rigorous as the Gibbs theory. In the context of the local approach we formulate a criterion that allows finding the transition points without calculating the chemical potential and the pressure of the second conjugate phase. In the second part of the review we consider second-order phase transitions (critical phenomena). The Kadanoff?Wilson theory of critical phenomena is analyzed, based on the global Gibbs approach. Again we use the Ornstein?Zernike equation to formulate a local theory of critical phenomena. With regard to experimentally established quantities this theory yields precisely the same results as the Kadanoff?Wilson theory; secondly, the local approach allows the prediction of many previously unknown details of critical phenomena, and thirdly, the local approach paves the way for constructing a unified theory of liquids that will describe the behavior of matter not only in the regular domain of the phase diagram, but also at the critical point and in its vicinity.
Explainable Machine Learning for Public Policy: Use Cases, Gaps, and Research Directions

Explainability is highly-desired in Machine Learning (ML) systems supporting high-stakes policy decisions in areas such as health, criminal justice, education, and employment. While the field of explainable ML has expanded in recent years, much of this work has not taken real-world needs into account. A majority of proposed methods are designed with \textit{generic} explainability goals without well-defined use-cases or intended end-users and evaluated on simplified tasks, benchmark problems/datasets, or with proxy users (e.g., AMT). We argue that these simplified evaluation settings do not capture the nuances and complexities of real-world applications. As a result, the applicability and effectiveness of this large body of theoretical and methodological work in real-world applications are unclear. In this work, we take steps toward addressing this gap for the domain of public policy. First, we identify the primary use-cases of explainable ML within public policy problems. For each use case, we define the end-users of explanations and the specific goals the explanations have to fulfill. Finally, we map existing work in explainable ML to these use-cases, identify gaps in established capabilities, and propose research directions to fill those gaps to have a practical societal impact through ML. The contribution is 1) a methodology for explainable ML researchers to identify use cases and develop methods targeted at them and 2) using that methodology for the domain of public policy and giving an example for the researchers on developing explainable ML methods that result in real-world impact.
Smart Sanctions of the United Nations Security Council

This study deals with the topic of the United Nations Security Council’s smart sanctions. Although they are frequently applied (certainly more often than coercion with the use of armed force), considerably less attention is paid to them in domestic academic publications. Therefore, the aim of this scientific paper is to offer at least a basic overview of this type of collective sanctions in order to fill the gap. It is based on describing the so-called classical forms of sanctions and on introducing the humanitarian problems related to their application which paved the way to smart sanctions. Subsequently, a comparison of classical and smart sanctions follows. Beside legal characteristics, a comparative analysis of these two types of sanctions was one of the main research methods used in this paper. In the conclusion attention is paid to the question of effectiveness of smart sanctions; however, the study does not offer an exact answer of this specific and very difficult issue.
12$^{th}$ Carolus Magnus Summer School on Plasma and Fusion Energy Physics

The 12th edition of the Carolus Magnus Summer School on Plasma and Fusion EnergyPhysics is hosted by the Katholieke Universiteit Leuven. The Carolus Magnus Summer Schoolhas been organised once every 2 years since 1993. It is a joint initiative of the Laboratory forPlasma Physics of the Royal Military Academy in Brussels (Belgium), the Belgian NuclearResearch Centre (SCK/CEN) in Mol (Belgium), the Dutch Institute for Fundamental EnergyResearch (DIFFER) in Eindhoven (The Netherlands) and the Institute of Energy and ClimateResearch (IEK-4) of the Forschungszentrum Jülich (Germany). All institutes are members of theEUROfusion Consortium. For the 12th CMSS edition, the Centre for mathematical Plasma-Astrophysics (CmPA) of the KU Leuven joined the team. KU Leuven is the oldest university inthe Low Countries. It is internationally renowned for the high quality of its alumni, and ranksamong the top 10 European universities in terms of its scholarly output
Looking through glass: Knowledge discovery from materials science literature using natural language processing

17 pages, 5 figures
ROLE OF EDUCATION IN PEACE BUILDING, CONFLICT RESOLUTION AND SOCIAL COHESION IN NIGERIA

Nigeria comprises numerous multi-ethnic communities characterized by diverse ethnic groups, cultures, and religions. Ethnicity, culture, and religion significantly influence the behavior of individuals within these communities. Differences in these aspects often render certain actions unacceptable to others, resulting in violence and conflict. Education serves as a key mechanism for promoting understanding and tolerance among individuals in multi-ethnic settings. Accordingly, this article critically examines the role of education in peace building, conflict resolution, and social cohesion in Nigeria. The structure of the paper includes an introduction, a review of the concepts of education, peace building, conflict resolution, and social cohesion, followed by an analysis of education as a means of fostering these outcomes. Subsequently, the challenges facing education in fostering peace building, conflict resolution and social cohesion in contemporary Nigeria were discussed. Education contributes to cultural and religious tolerance, character development, acquisition of critical thinking skills, respect for fundamental rights and freedoms and addressing the root causes of grievances for promoting peace building, conflict resolution, and social cohesion. Challenges to education&rsquo;s role in fostering peace building, conflict resolution, and social cohesion in contemporary Nigeria include inadequate funding, infrastructural decay, insufficient staffing, corruption, low staff motivation, data shortages, and ethnic, cultural, and religious diversity. Recommendations include increasing budgetary allocations to the education sector and motivating staff through improved salaries and allowances to enhance the implementation of educational programmes that promote peace building, conflict resolution, and social cohesion.
Using system-theoretic process analysis and event tree analysis for creation of a fault tree of blackout in the diesel-electric propulsion system of a cruise ship

Diesel-Electric Propulsion (DEP) has been widely used for propulsion of LNG carriers, icebreakers, drilling units, warships and cruise ships. It is important that every blackout is prevented, especially on cruise ships, considering the possible consequences of such an event. In this work, hazard analysis of a simplified DEP system of a cruise ship is implemented to identify the hazardous scenarios leading to a blackout. This is achieved by combining System-Theoretic Process Analysis (STPA) and Event Tree Analysis (ETA). The STPA is used to identify the hazards and the possible control actions leading to hazards along with their causal factors, whilst the ETA is used to determine the propagation of hazards into the other hazards or accident. Next, the results of STPA and ETA are mapped into a Fault Tree for better representation of results. In this way, the relationship between accident, hazards and unsafe control actions is explicitly described and a more comprehensive picture of the potential accidental scenarios in the system is provided, rendering possible allocation of quantitative performance requirements as per IEC 61508.
Ethical Dilemmass and Regulations of Artificial Intelligence Under the Perspective of Nietzsche’s Superman Philosophy Based on the Alien: Romulus

The paper analyzes the ethical dilemmas and regulations of AI from five perspectives, grounded in Nietzsche's Übermensch philosophy. The aim is to provide theoretical support and multiple case studies for the establishment of an ethical order in AI. Firstly, it addresses kinship ethics dilemmas and regulations concerning AI within the context of dual ethics. This section examines the ethical challenges posed by AI through both human-centric and alien-centric lenses. It raises critical questions regarding whether kinship ethics should be predicated on a clear distinction between humans and animals. Secondly, it explores social ethics dilemmas and regulations related to AI against the backdrop of artificial ethics and professional standards. Ethical judgments alongside legal boundaries give rise to significant social ethical challenges associated with AI. The technology exacerbates social inequalities while undermining principles of equal opportunity. This segment poses essential inquiries about whether social ethics necessitate that AI assumes certain social responsibilities, as well as what specific forms these responsibilities should take. Should we redefine social ethics based on fairness when individual circumstances are similar, or justice when they differ? Thirdly, it delves into political ethics dilemmas and regulations pertaining to AI within contexts shaped by imagery suggestions and ethical reinforcements. Using Alien: Romulus as a case study, this section discusses how one might explore the moral imagination surrounding AI driven by its moral autonomy through visual representations. It raises pertinent questions about whether loyalty and integrity constitute political or ethical obligations that must be addressed by AI systems. Fourthly, national ethics dilemmas concerning regulation of AI are examined in light of digital transformation processes and advancements in technological security development. This part prompts reflection on whether a great power’s responsibilities represent a matter of national ethics for AI. Finally, the ethical dilemmas surrounding Earth and the regulation of AI within the framework of bioethics and ethical care are examined. This paper poses the question of whether concepts such as co-assistance, co-integration, co-sharing, and co-prosperity represent essential issues of Earth ethics that AI must address.
A neural networks approach for designing compact all-optical photonic crystal based AND logic gate

Abstract                   This paper introduces a new method for creating an all-optical AND gate by utilizing a two-dimensional photonic crystal configuration for the first time. This gate design is intended for applications in optical computing and all-optical logic, offering the potential for rapid computation and parallel processing. The described gate is characterized by its compact dimensions and comprises two inputs and a single output. The high and low logic states are defined based on power values, where logic 0 corresponds to low power and logic 1 corresponds to high power emitted from the light source. To enhance the design process, artificial neural networks (ANNs) are utilized. ANNs offer a powerful tool for optimizing and fine-tuning the photonic crystal structure parameters to achieve the desired logic functionality. With the help of the applied ANNs, the design process is eased and high performance is achieved for the proposed photonic crystal structure. By integrating ANNs into the design process, this research opens up new possibilities for advancing the field of photonic logic circuits. Combining photonic crystals and ANN optimization provides a powerful approach to designing complex and efficient optical computing systems. The results show that the obtained power values are high for 1 logic state and low for the 0 logic state, which verifies the AND gate accuracy table. The achieved accurate results verify the validity of the proposed approach for achieving precise and reliable all-optical logic operations.
Measuring the Quality of Palliative Care at End of Life: An Overview of                         Data Sources

Palliative care, and more specifically end-of-life (EOL) care, serves to address the physical, practical, psychosocial, and spiritual needs of dying patients and their families. The quality of this care is critical to reduce the burden of illness and moderate escalating health-care costs. Accordingly, assessing the quality of EOL care is a priority of many governments. This article is an overview of the three main types of data sources that can be used to indicate the quality of EOL care: population-based administrative data, clinical data, and patient-reported outcomes. Existing administrative data are relatively inexpensive to use and provide a whole picture of the health-care system. Clinical data are useful for benchmarking care provided against best practices. Patient-reported outcome measures capture quality as defined by the patient and directly represent impact of care. Understanding the capabilities of these data types is the basis for developing feasible quality assessments to inform program and policy development.
Uncovering the skillsets required in computer science jobs using social network analysis

The rapid growth of technology and computer science, which has led to a surge in demand for skilled professionals in this field. The skill set required for computer science jobs has evolved rapidly, creating challenges for those already in the workforce who need to adapt their skills quickly to meet industry demands. To stay ahead of the curve, it is essential to understand the hottest skills needed in the field. The article introduces a new method for analyzing job advertisements using social network analysis to identify the most critical skills required by employers in the market. In this research, to form the communication network of skills, first 5763 skills were collected from the LinkedIn social network, then the relationship between skills was collected and searched in 7777 computer science job advertisements, and finally, the balanced communication network of skills was formed. The study analyzes the formed communication network of skills in the computer science job market and identifies four distinct communities of skills: Generalists, Infrastructure and Security, Software Development, and Embedded Systems. The findings reveal that employers value both hard and soft skills, such as programming languages and teamwork. Communication skills were found to be the most important skill in the labor market. Additionally, certain skills were highlighted based on their centrality indices, including communication, English, SQL, Git, and business skills, among others. The study provides valuable insights into the current state of the computer science job market and can help guide individuals and organizations in making informed decisions about skills acquisition and hiring practices.
Antimicrobial Resistance and Stewardship Programs in Saudi Arabia: A Decade of Implementation and Outcomes

Background Saudi Arabia faces substantial antimicrobial resistance burdens with rapidly escalating antibiotic consumption. Following the 2014 national antimicrobial stewardship plan and 2018 prescription restriction policy, comprehensive evaluation of decade-long implementation remains absent. This systematic review synthesizes evidence on antimicrobial resistance patterns, stewardship program effectiveness, clinical outcomes, economic impact, and educational initiatives across Saudi Arabian healthcare settings from 2014–2025. Methods We systematically searched PubMed, MEDLINE, Embase, and Cochrane Library from July 2014 to June 2025, supplemented by grey literature and government reports. Studies examining antimicrobial resistance surveillance, stewardship program implementation, clinical effectiveness, economic outcomes, or educational interventions in Saudi Arabian healthcare settings were included. Two independent reviewers screened studies and extracted data following PRISMA guidelines. Quality assessment utilized Newcastle-Ottawa Scale and Cochrane Risk of Bias tools. Evidence certainty was graded using GRADE methodology. Results Systematic searches identified 1,847 records, with 42 studies meeting inclusion criteria. MRSA prevalence ranged from 8.6% to 47%, with a pooled estimate of 24.3% (95% CI: 19.7–29.4%) derived predominantly from cross-sectional and retrospective surveillance studies, with heterogeneity driven largely by differences in hospital type and specimen source. Following the 2018 prescription restriction policy, total antibiotic consumption decreased by 30%, though parenteral use paradoxically increased by 34%; these signals cannot establish causality and may reflect case mix shifts, coding changes, or supply channel changes rather than true clinical need. Stewardship programs demonstrated 15–40% reductions in inappropriate prescribing, 8–25% decreases in antimicrobial costs, and 12–35% reductions in hospital-acquired infections. Educational interventions improved healthcare provider knowledge scores by 25–45% and prescription appropriateness by 18–30%. Economic analyses revealed cost savings of $850–$3,200 per patient. Conclusions Saudi Arabia's decade-long antimicrobial stewardship initiatives demonstrate meaningful progress. However, rising ESBL and carbapenem resistance, implementation heterogeneity, and workforce constraints remain critical challenges requiring sustained investment.