ethicalabs/Research-Intent-Collab huggingface dataset:
Optimization of the transport and logistics system to simplify movement of population in rural areas

The purpose of the article is to examine existing data for the selection of survey areas, data collection for the mobile network at the level of travel chains, and analysis of travel patterns. Travel demand in three rural areas with different population densities is considered, and requirements for new mobility solutions based on demand and people's travel habits are established.  Public transport plays a decisive role in the logistics of territorial communities of Ukraine. However, inadequate provision and implementation of technological advances have left rural areas behind and heavily dependent on private cars. This article describes how to improve the availability of transport services in rural areas, where the demand for travel is often underestimated. The demand for travel in three rural areas with different population densities was analyzed, and the requirements for new mobility solutions based on demand and people's travel habits were determined.  There is a need to access a higher level of subsidies if on-demand mobility services cannot attract an adequate level of demand so that rural and semi-rural communities have access to the same level of services and opportunities available to urban areas. Most of these services are deployed in urban settings with high travel demand and population density. Research on regions with low demand is rarely considered.  Many on-demand services are community-based, where demand is determined based on local knowledge and specific needs. Those mobility services that are more commercially oriented use qualitative market research to determine demand for specific population segments and specific locations.  Social isolation is exacerbated by lack of accessibility, roads and public transport, but is also linked to socio-demographic factors.  It is suggested that consideration be given to removing barriers to commercially viable new mobility services in rural areas by: using data-driven approaches to understand typical daily travel patterns; identifying new mobility services that can be deployed for commercial purposes and those that will require ongoing financial support to provide socially necessary services.
Relevance of learning analytics to measure and support students' learning in adaptive educational technologies

In this poster, we describe the aim and current activities of the EARLI-Centre for Innovative Research (E-CIR) "Measuring and Supporting Student's Self-Regulated Learning in Adaptive Educational Technologies" which is funded by the European Association for Research on Learning and Instruction (EARLI) from 2015 to 2019. The aim is to develop our understanding of multimodal data that unobtrusively capture cognitive, meta-cognitive, affective and motivational states of learners over time. This demands for a concerted interdisciplinary dialogue combining findings from psychology and educational sciences with advances in computer sciences and artificial intelligence. The participants in this E-CIR are leading international researchers who have articulated different emerging perspectives and methodologies to measure cognition, metacognition, motivation, and emotions during learning. The participants recognize the need for intensive collaboration to accelerate progress with new interdisciplinary methods including learning analytics to develop more powerful adaptive educational technologies.
Gateway API v1.0 as Mesh-Lite Traffic Management

Modern distributed architectures call for traffic management strategies that are scalable yet do not weigh down the system with unnecessary overhead. Such strategies should also facilitate observability, enforcement of policies, and intelligent routing, importantly, without the accounts of full service meshes. The paper positions Gateway API v1.0 as a mesh-lite model that serves as a bridge between straightforward ingress controllers on one side and complex service mesh infrastructures on the other. In effect, Gateway API introduces the use of Kubernetes resources as a standard for routing, resilience, and security policies thus gaining in modularity, extensibility, and in the same time operational simplicity. The assessment was carried out by the installation of Gateway API in multi-cluster and edge-cloud setups, and performance metrics such as latency, throughput, and configuration complexity were measured and compared with Istio and Envoy-based meshes. The results show that Gateway API is capable of providing observability and traffic governance at almost mesh levels while it reduces the resource consumption by 40–60%, which in turn facilitates lifecycle management and integration. Case studies highlight its feasibility for the hybrid and edge scenarios where the full mesh cannot be efficiently used. In essence, findings represent Gateway API v1.0 as a cloud-native networking tool that has undergone a practical evolutionary process, thus enabling scalable service orchestration and adaptive traffic control that is in harmony with Kubernetes’ declarative model. Consequently, this has been traffic management redefined for the modern distributed and edge-native ecosystems.
Effectiveness of antimicrobial stewardship programs in reducing antibiotic resistance in intensive care units: a systematic review

Abstract                        Background:             Antimicrobial resistance (AMR) poses a significant global threat, with intensive care units (ICUs) being key hotspots due to the extensive use of antibiotics. While antimicrobial stewardship (AMS) programs (ASPs) aim to optimize antibiotic use, their impact on AMR in ICUs remains unclear. This review assesses the current evidence on the effectiveness of ASPs in influencing resistance patterns and antibiotic use in ICU settings.                                   Materials and Methods:             A systematic review was conducted by Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, utilizing PubMed and Google Scholar. Included studies were peer-reviewed, written in English, described specific AMS interventions, and reported outcomes related to AMR in ICU populations. Data on study design, intervention type, resistance trends, and antibiotic use were extracted. The risk of bias was assessed using validated tools to ensure the study’s quality and reliability.                                   Results:             Of the 100 studies initially identified, 25 met the inclusion criteria and were included in the qualitative analysis. The findings suggest that ASPs, particularly those involving multidisciplinary collaboration, real-time antimicrobial monitoring, and adherence to evidence-based guidelines, are associated with significant reductions in AMR rates and overall antibiotic use in ICUs. However, variability in implementation strategies, resource allocation, and compliance levels contributed to differences in outcomes across studies. ASPs are vital in fighting AMR in ICUs. Nonetheless, inconsistent implementation limits their impact. Standardized, evidence-based approaches, along with further research on long-term outcomes, cost-effectiveness, and advanced diagnostics, are needed to enhance their effectiveness.                                   Conclusion:             ASPs play a crucial role in combating antimicrobial resistance in ICUs. However, inconsistent implementation limits their impact. Standardized, evidence-based approaches, along with further research on long-term outcomes, cost-effectiveness, and advanced diagnostics, are needed to strengthen their effectiveness.
Second order error correction in quantum computing

Error correction codes are necessary for the development of reliable quantum computers. Such codes can prevent the lost of information from decoherence caused by external perturbations. This thesis evaluates a five qubit code for correcting second order bit-flip errors. The code consists of encoding, decoherence, decoding, and error correction steps. This work analyzes the proposed code using geometric algebra methods and examines the state of the system after each step in the process.
Types of application of artificial intelligence in the diagnosis and prognosis of osteoporosis; a narrative review

Introduction: The rising impact of osteoporosis and fragility fractures highlights the need for advanced management strategies. Integrating digital health interventions, especially artificial intelligence (AI) algorithms, is essential. Osteoporosis, a major contributor to elderly disability, demands AI to minimize diagnostic errors. This review targets stakeholders interested in employing AI for osteoporosis management. Methods: We examined 16 articles from PubMed, Google Scholar, and Medline (January 1, 2015, to January 1, 2023) using keywords like AI, osteoporosis, fragility fracture, and machine learning. After excluding redundancies, 15 articles were selected, covering five key aspects of osteoporosis management: Bone mineral densitometry (BMD) predictive variables (n=1), diagnosis, screening, and classification of osteoporosis (n=5), diagnosis and screening of fractures (n=4), fracture risk forecast (n=2), and automated image segmentation (n=3). Results: Recent machine learning (ML) advances empower AI in assessing bone health beyond X-rays. Techniques, including AI-driven analysis with multi-detector computed tomography scans, extend beyond X-ray imaging. Convolutional neural networks (CNNs) excel in fracture diagnosis, surpassing medical professionals. Enhanced CNN performance is achieved through data augmentation and generative networks. Conclusion: Initial ML applications in osteoporosis research focus on the macroscopic scale, leaving a gap in microscale exploration. Establishing a robust system for bone micro-damage initiation detection is crucial for future applications in bone micromechanics. Ongoing development is essential to assess effectiveness and affordability through controlled studies.
Assessing the Effectiveness of Mediation and Arbitration as an Alternative Dispute Resolution in Resolving Interfaith Disputes among Muslims and Christians in Kaduna State

This study assesses the use and effectiveness of mediation and arbitration as an Alternative Dispute Resolution (ADR) mechanism for resolving conflicts among Muslims and Christians in Kaduna State, Northwest Nigeria. Using a mixed-methods convergent parallel design, quantitative data were collected through a structured questionnaire administered to 384 respondents (192 Muslims and 192 Christians), while qualitative data were generated via 20 in-depth interviews with religious leaders and ADR/legal practitioners. Findings show a high level of ADR awareness (88.5%) and significant utilization (personal use 54.7%; witnessed only 28.6%). Mediation is largely facilitated by religious leaders (Imams/Pastors) rather than court-connected mediators. Respondents generally perceive mediation as effective due to faster settlement, lower cost, and improved relationship preservation, though major challenges include religious bias and enforcement gaps. The study concludes that mediation especially faith-anchored mediation plays a critical role in maintaining inter-community peace, but requires improved legitimacy, procedural safeguards, and stronger linkage with enforceable mechanisms.&nbsp;
STATISTICAL MECHANICS OF EQUILIBRIUM AND NONEQUILIBRIUM PHASE TRANSITIONS: THE YANG–LEE FORMALISM

Showing that the location of the zeros of the partition function can be used to study phase transitions, Yang and Lee initiated an ambitious and very fruitful approach. We give an overview of the results obtained using this approach. After an elementary introduction to the Yang–Lee formalism, we summarize results concerning equilibrium phase transitions. We also describe recent attempts and breakthroughs in extending this theory to nonequilibrium phase transitions.
Non-Gaussian sampling effects on the estimation of the cosmic microwave background power spectrum

We introduce a non-Gaussian model of structure formation, and show how it produces surprising sampling effects on the estimation of the CMB power spectrum. Estimates of the average power spectrum based on small sky patches produce qualitatively different results from patch to patch, and vary also with the patch size. For instance a system of secondary Doppler peaks is observed in small enough patches, but at different positions in different patches. However, no secondary Doppler peaks are observed in large sky patches. These effects question usual methods of power spectrum estimation, and techniques like bootstrapping. The non-Gaussianity of this model fails to be detected by standard tests.
Accessibility Politics: A Study of Disability Rights and the Political Struggles for Inclusive Societies

Politics of disability rights and accessibility activism are now at the forefront of international movements toward inclusive societies. Years of disability rights activism have not translated into laws, let alone the creation of international guidelines compelling equality, but people with disabilities remain subjected to long-term forms of exclusion and marginalization. Figures regarding work, for instance, place in context acute following disparities between the non-disabled and the disabled which indicate widespread economic disparities. This study looks at the politics of accessibility by examining how legislation, policy architecture, social movements, and emerging technologies all contribute to the daily experience of people with disabilities. While there have been significant advances legislatively—regional accessibility laws as well as international agreements—implementation remains sporadic and more often than not in the absence of the enforcement provisions required to effect significant change. Virtual spaces, in particular, pose new barriers, with most sites and apps remaining inaccessible even when standards do exist. Moreover, the disability experience is not typically monolithic. Instead, it is shaped by intersecting identities such as gender, race, and geography and therefore is vastly intersectional in character. The COVID-19 pandemic further shed light on these disparities by disrupting access to vital services and exacerbating structural inequities. Technological innovation, like artificial intelligence, has introduced new dangers, particularly in computerized hiring systems that inadvertently exclude disabled applicants. The dominant theoretical model—the social model of disability—has been instrumental in shifting attitudes from a concern with individual impairment to societal barriers. There is growing recognition, however, of the need for a more comprehensive model that takes into account medical, cultural, and structural factors as well. This study contends that accessibility must be conceived not merely as a technical or legal issue, but as a broader political and ethical commitment. Disability must be seen as an intrinsic and enriching aspect of human difference, worthy of being fully included and actively participating in all areas of life.
The role of the united nations security council in protecting human rights

The international protection of human rights has been the origin of an international legal order called the international human rights law.This new branch emerged from many multi-lateral conventions defining the various individual and collective rights human beings deserve. The realization of these rights required the active contribution of the united nations and its organs. The security council may partipated actively in respecting human rights when dealing with situation threatening peace and security through ;united nations sanctions, strong peace missions and even the criminal prosecution
Knowledge on Antimicrobial Resistance and Stewardship in Undergraduate Nursing Students: A Cross-sectional study

Background: Antimicrobial resistance (AMR) is a global health threat, causing increased morbidity, mortality, and healthcare costs. Effective antimicrobial stewardship (AMS) is crucial to limit its spread. Nurses play a critical role in addressing AMR, but knowledge deficiency among undergraduate nursing students can hinder their preparedness for stewardship responsibilities. This study aims to determine the knowledge level of undergraduate nursing students about antibiotics, AMR, and AMS, addressing the challenge of knowledge deficiency among these students. Methods: A cross-sectional study was conducted on 140 undergraduate nursing students, using a self-administered questionnaire to collect demographic data and knowledge about antibiotics, antimicrobial resistance, and antimicrobial stewardship. Statistical analyses were performed using SPSS version 20.0, with descriptive statistics providing an overview of participants' knowledge and chi-square tests investigating associations between factors like age, gender, semester, and residence with knowledge. Results: Participants had the mean knowledge score of 7 ± 2.067, and none of the participants had adequate knowledge, 40.7% had moderately adequate knowledge, and 59.3% had inadequate knowledge. Semester of study was the only factor that had significant relations with knowledge on antimicrobial resistance and stewardship (p = 0.010). Conclusion: The study reveals significant gaps in undergraduate nursing students' understanding of antibiotics, antimicrobial resistance, and stewardship, highlighting the need for comprehensive curricular reform and innovative educational strategies to prepare future nurses for addressing antimicrobial resistance and strengthening healthcare systems.
Wireless sensor networks in the internet of things: review, techniques, challenges, and future directions

Wireless sensor networks (WSN) are an emerging multidisciplinary intersection of cutting-edge research fields, and their advantages in terms of freedom of formation, high signal-to-noise ratio, high strength, and unattended, which makes WSN have good prospects for application in the field of internet of things (IoT). Considering all the benefits that WSN offer, this paper reviews the development history of wireless sensor networks internet of things (WSN-IoT), analyses the technologies used by sensors in the IoT, and illustrates the future developing patterns and remaining challenges, in conjunction with the main technologies in the perception layer of the current network of things industry.
Genetic Discrimination: The Use of Genetically Based Diagnostic and Prognostic Tests by Employers and Insurers

Genetic discrimination is detrimental to public health programs, as well as to society generally. Advances in genetic testing and screening, accelerated and prompted by the Human Genome Initiative, increase society's ability to detect and monitor chromosomal differences. These technologies and their resulting genomic data will enhance medical science, but may also encourage discrimination. Although few employers or insurers currently utilize genetic screening, testing or data, rising employee benefit costs and market forces create powerful incentives for usage.Current municipal, state and federal laws, including the Americans with Disabilities Act (ADA), may not sufficiently protect employees and insureds from genetic discrimination. While municipal and state protections should not be overlooked, the ADA's sweeping scope may currently provide the most comprehensive safeguard. Federal laws banning discrimination on the basis of race or sex might also successfully redress some forms of genetic discrimination. Genetic technologies’ advent necessitates efforts to rectify state and federal statutory coverage gaps, strictly regulate employers and produce comprehensive guidelines regarding its use.
The effect of human resource information systems (HRIS) on staff retention: a study of recruitment and selection in a UK based hospitality organisation

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University London.
A Coupon-Collector Model of Machine-Aided Discovery

Empirical studies of scientific discovery---so-called Eurekometrics---have indicated that the output of exploration proceeds as a logistic growth curve. Although logistic functions are prevalent in explaining population growth that is resource-limited to a given carrying capacity, their derivation do not apply to discovery processes. This paper develops a generative model for logistic \emph{knowledge discovery} using a novel extension of coupon collection, where an explorer interested in discovering all unknown elements of a set is supported by technology that can respond to queries. This discovery process is parameterized by the novelty and quality of the set of discovered elements at every time step, and randomness is demonstrated to improve performance. Simulation results provide further intuition on the discovery process.
Statistical Insights and Exploratory Data Analysis for E-commerce Sales Data: A Collaborative Filtering and Recency-Based Recommendation System

Nowadays, recommendation systems are crucial in e-commerce. They deliver timely and relevant product suggestions to users. A well-crafted recommendation system can increase sales and create value for both buyers and sellers. In this research, we examine a large dataset containing sales data, product information, and customer contacts to gather statistical insights. We then introduce a collaborative filtering approach enhanced with data based on recency. Exploratory data analysis (EDA) techniques help identify relationships among variables, using key statistical tools and measures. To better understand consumer behavior, we generate grouped statistics such as purchasing trends by product category and customer age. The results of this research support the development of a collaborative filtering recommendation engine that incorporates recency weighting to improve product suggestions for online retail&amp;nbsp;platforms.
Analysis of chemical reaction systems by means of network thermodynamics

The simple network thermodynamics approach is applied to chemical reaction systems, whereby chemical reactions can be studied avoiding complex mathematical treatment. Steady state reaction rates are obtained for two chemical reaction systems, viz. the decomposition of ozone and the reaction of hydrogen with bromine. The rate equations so obtained agree with those derived from the chemical kinetics concept.