ethicalabs/Research-Intent-Collab huggingface dataset:
Metagenomic Analysis Reveals the Transfer of Antibiotic Resistance from Manure-Fertilized Soil to Carrot Microbiome

we demonstrated the impacts of manure fertilization on the diversity and abundance of ARGs and the associated bacterial communities in agricultural soils and on carrots by shot-gun sequencing based metagenomics. Resistome alteration caused by manure application was profiled with the host populations and mobility as well as transfer of antibiotic resistance were identified with state-of-the-art metagenomic assembly approach. We found that manure application could enrich resistant microbes and associated ARGs via the soil-carrot system. Besides the overall enrichment being more evident in the soil, the plasmid-mediated ARGs also inclined to occur from manure to the soil rather than the carrot phyllosphere, reflecting that the soil rather than the carrot peel was influenced more significantly by the fertilization. The shared ARGs in the soil-carrot system transferring via bacterial endophytes and plasmid suggested a potential route for ARGs to transfer into human microbiome and pathogen via the food chain (e.g. vegetable, salad), and the possible bacterial ARG hosts migrated in the soil-carrot system with manure application included Yersiniaceae, Enterobacteriaceae, Erwiniaceae, Enterobacteriaceae, and Burkholderiaceae. With such, we concluded that antibiotic resistance transfer via raw carrot represents a risk to human health even after careful washing; therefore peeling is needed to ensure the safety usage of organically grown carrots. And in agricultural production, it is necessary to take appropriate agricultural measures to reduce the colonization of soil ARBs to roots, such as the use of rhizosphere beneficial microorganisms.
Probabilistic safety assessment (PSA) of a safety critical  system: a case study of a nuclear power plant

Probabilistic Safety Assessment approach has been successfully applied in engineering, economics, computer science and statistics to re-solve a wide range of safety-related problems. However, using Probabilistic Safety Assessment for quantifying safety of a safety critical system is a challenging task in Safety Engineering community. This method plays an essential role in analyzing safety of safety critical sys-tems and its various components. Therefore, in this paper, we present Probabilistic Safety Assessment framework which can be used to quantify the critical failures of a systems. The approach is well demonstrated on a Digital Feed Water Control System uses in a Nuclear Power Plant as safety critical system.
Andean terraced hills (a use of satellite imagery)

The aim of this paper is in stimulating the use of satellite imagery, in particular the free service of Google Maps, to investigate the distribution of the agricultural technique of terraced hills in Andean countries, near Titicaca Lake. In fact, satellite maps can give a clear view of the overall surface modified by human work, being then a precious help for on-site archaeological researches and for historical analysis. Satellite imagery is also able to give the distribution of burial and worship places. The paper discusses some examples near the Titicaca Lake.
Additional file 2 of Acupuncture for combat post-traumatic stress disorder: trial development and methodological approach for a randomized controlled clinical trial

Additional file 2. Ethical Approval Document 2 of 2. Data Monitoring Review Approval Letter.
The Slovak Presidency in the United Nations Security Council

The United Nations Security Council (hereinafter as the “UN Security Council”) has been the central body of the system of collective security which is a philosophical counterpart of the system of balance of power. In comparison with the Council of the League of Nations we can see various differences, especially in a way that the UN Security Council can adopt measures legally binding for every state of the world. This body has not just unprecedented competencies, but what is more vital is that it has various sanctions to its disposal by which it can enforce the international law. The UN Security Council is a collective body which has both permanent and elected members. Being a member of it is a great prestige, but also a great responsibility. The Slovak Republic has been an elected member of it only once in its short history, however, it was praised for the role it played during the two year’s term. The aim of this study is to introduce the most important moments of the Slovak presidency to which, unfortunately, smaller attention is being paid than it deserves.
The Consolidated (“terrorist”) List maintained by the United Nations Security Council : Assessing human rights and due process concerns

This paper analyses the procedures and working methods of the Security Council Sanctions Committee pursuant to Resolution 1267 (1999). The focus of the paper is the Consolidated List maintained by this Committee. The Consolidated List, also known as the “UN terrorist list”, forms a catalogue over individuals and entities belonging to or associated with Al-Qaida and the Taliban. Pursuant to Chapter VII of the United Nations Charter, listed individuals and entities are subjected to sanctions in which all Member States are obliged to implement. It falls within the scope of the thesis to describe and analyse the procedural rules of the Committee and the sanctions regime. While political and administrative in nature, the Committee’s procedures for including or removing names from this list poses legal challenges with respect to human rights norms.
GRACE: Global Repository of AI Consensus at Edyant — Principles, Policies, Guidelines and Best Practices for the Ethical Governance, Development and Use of AI

GRACE (Global Repository of AI Consensus at Edyant) is a living, multi-stakeholder consensus document defining principles, policies, guidelines, guardrails, and best practices for the ethical governance, development, and use of AI. It is synthesised from diverse inputs — academic research, institutional submissions, practitioner reports, open letters, and civil-society perspectives. This is version 1.1.0 (2026).
Effect of exercise immersion experience on health promotion and lifelong physical education of high school students in sports club activities

The purpose of this study was to investigate the impact of high school students' athletic commitment, health promotion education, and lifelong sports activities. To this end, the researcher searched for research subjects of 397 high school students residing in Seoul in 2019. As a result of the analysis, the following conclusions were drawn. First, the effect of exercise commitment on sports health promotion education was investigated. Looking at the activities of high school students, their commitment to behavior has had a profound impact on their health responsibilities and relationships. Second, the study also investigated the impact of athletic commitment to lifelong sports of sports activities in high school students and found that cognitive and behavioral commitment had a significant impact on lifelong sports. Finally, as a result of investigating the impact of health promotion education on lifelong sports of high school student sports activities, it was found that health responsibility and relationships have a great influence on lifelong sports.
Perancangan Aplikasi Human Resource Information System (HRIS)  Metode Prototyping (Studi Kasus CV. Pawit Mulyo)

Penelitian ini bertujuan untuk membuat perancangan aplikasi berbasis website Human Resources Information System (HRIS) dengan metode prototyping yang nantinya akan diterapkan pada CV. Pawit Mulyo. Data yang digunakan diperoleh dari studi pustaka, observasi, wawaancara, dan kuesioner untuk mendapatkan pemahaman langsung tentang bagaimana proses absensi dan pengajuan cuti dilakukan di CV. Pawit Mulyo. Metode yang digunakan pada penelitian ini adalah prototype, metode ini dipilih karena memungkinkan pengembang untuk membuat model awal dari sistem yang akan dibangun, sehingga dapat memperoleh umpan balik dari pengguna secara langsung. Pengolahan hasil kuesioner dengan menggunakan skala likert menunjukkan bahwa, aplikasi berbasis website HRIS yang dikembangkan dikategorikan sebagai “Sangat Layak” digunakan untuk memudahkan perusahaan berdasarkan rata-rata persentase yang diperoleh senilai 85,33%.
sj-docx-5-css-10.1177_24705470231169106 - Supplemental material for Mental Health Among People Presenting for Care of Physical Symptoms: The Factors Associated with Suicidality and Symptoms of Depression and Anxiety are Similar Across Specialties

Supplemental material, sj-docx-5-css-10.1177_24705470231169106 for Mental Health Among People Presenting for Care of Physical Symptoms: The Factors Associated with Suicidality and Symptoms of Depression and Anxiety are Similar Across Specialties by Sina Ramtin, Kathleen Carberry, Maria Correa, David Ring, Carol Alter and Donna Shanor in Chronic Stress
Categorical Foundations of Persistent Homology: Bridging Classical Topology and Topological Data Analysis with Applications

This paper introduces a novel categorical framework that unifies classical algebraic topology with modern topological data analysis through the lens of category theory. We develop the theory of persistence categories as a natural generalization of persistence modules, establishing functorial relationships between classical topological invariants and their persistent counterparts. Our approach reveals deep connections between sheaf cohomology, spectral sequences, and multi-parameter persistence, providing a rigorous mathematical foundation for understanding the stability and structure of topological features in data. We prove that persistent homology can be viewed as a particular instance of a more general categorical construction that encompasses both classical and computational topology. Furthermore, we establish new stability theorems for categorical persistence and demonstrate how classical results in algebraic topology can be lifted to the persistent setting through appropriate functorial constructions. We present practical applications in data science, computational biology, and machine learning, demonstrating the effectiveness of our theoretical framework through concrete implementations and computational experiments.
Fréchet ChemNet Distance: A Metric for Generative Models for Molecules in Drug Discovery

The new wave of successful generative models in machine learning has increased the interest in deep learning driven de novo drug design. However, assessing the performance of such generative models is notoriously difficult. Metrics that are typically used to assess the performance of such generative models are the percentage of chemically valid molecules or the similarity to real molecules in terms of particular descriptors, such as the partition coefficient (logP) or druglikeness. However, method comparison is difficult because of the inconsistent use of evaluation metrics, the necessity for multiple metrics, and the fact that some of these measures can easily be tricked by simple rule-based systems. We propose a novel distance measure between two sets of molecules, called Fréchet ChemNet distance (FCD), that can be used as an evaluation metric for generative models. The FCD is similar to a recently established performance metric for comparing image generation methods, the Fréchet Inception Distance (FID). Whereas the FID uses one of the hidden layers of InceptionNet, the FCD utilizes the penultimate layer of a deep neural network called ChemNet, which was trained to predict drug activities. Thus, the FCD metric takes into account chemically and biologically relevant information about molecules, and also measures the diversity of the set via the distribution of generated molecules. The FCD's advantage over previous metrics is that it can detect if generated molecules are a) diverse and have similar b) chemical and c) biological properties as real molecules. We further provide an easy-to-use implementation that only requires the SMILES representation of the generated molecules as input to calculate the FCD. Implementations are available at: https://www.github.com/bioinf-jku/FCD
<i>Gurraacha</i>                     : An Indigenous Inter-Ethnic Peace Building and Conflict Resolution Institution among the People of South Central Ethiopia

Abstract                                        This article deals with                     Gurraacha                     institution, which is very important in inter-ethnic peace building and resolving conflict among people of south-central Ethiopia. This institution was named after the Oromo term                     ‘Gurraacha’                     (literally meaning black) to indicate its power in inter-ethnic peace building and conflict resolution. It is one element of Oromo                     Gadaa                     system which was established time immemorial to sustain peace between Oromo and non-Oromo neighboring ethnic groups. The data for this study was collected through interview, observation and focus group discussions in 2014 and 2015. As revealed by this study,                     Gurraacha                     institution is a guarantee for sustaining peace among people of south-central Ethiopia by managing conflict over boundary, grazing land, looting of cattle and water points. Overall, the study concluded that                     Gurraacha                     institution has real significance in inter-ethnic peace-building, sustaining social harmony and inter-ethnic conflict resolution. In                     Gurraacha                     institution, people rebuild lost peace and order of                     Waaqa                     (God) by performing purification rituals. There is no corruption in                     Gurraacha                     institution since all activities are undertaken according to Waaqa’s law and order. There is no false oath in this institution because such act is believed to have negative consequences. The oath of                     Gurraacha                     institution which are made during reconciliation process transcend generations. This institution is the model of conflict transformation which is hardly found in today’s world. Therefore, using this indigenous institution for future policy formulation in the country as inter-ethnic peace building and conflict resolution model is important for the realization of sustainable peace and development.
Physics-based deep neural networks for beam dynamics in charged particle accelerators

This paper presents a novel approach for constructing neural networks which model charged particle beam dynamics. In our approach, the Taylor maps arising in the representation of dynamics are mapped onto the weights of a polynomial neural network. The resulting network approximates the dynamical system with perfect accuracy prior to training and provides a possibility to tune the network weights on additional experimental data. We propose a symplectic regularization approach for such polynomial neural networks that always restricts the trained model to Hamiltonian systems and significantly improves the training procedure. The proposed networks can be used for beam dynamics simulations or for fine-tuning of beam optics models with experimental data. The structure of the network allows for the modeling of large accelerators with a large number of magnets. We demonstrate our approach on the examples of the existing PETRA III and the planned PETRA IV storage rings at DESY.
Evaluating the Accuracy and Efficiency of AI-Generated Radiology Reports Based on Positive Findings—A Qualitative Assessment of AI in Radiology

With increasing imaging demands, radiologists face growing workload pressures, often resulting in delays and reduced diagnostic efficiency. Recent advances in artificial intelligence (AI) have introduced tools for automated report generation, particularly in simpler imaging modalities, such as X-rays. However, limited research has assessed AI performance in complex studies such as MRI and CT scans, where report accuracy and clinical interpretation are critical.To evaluate the performance of a semi-automated AI-based reporting platform in generating radiology reports for complex imaging studies, and to compare its accuracy, efficiency, and user confidence with the traditional dictation method.This study involved 100 imaging cases, including MRI knee (n=21), MRI lumbar spine (n=30), CT head (n=23), and CT Abdomen and Pelvis (n=26). Consultant musculoskeletal radiologists reported each case using both traditional dictation and the AI platform. The radiologist first identified and entered the key positive findings, based on which the AI system generated a full draft report. Reporting time was recorded, and both methods were evaluated on accuracy, user confidence, and overall reporting experience (rated on a scale of 1-5). Statistical analysis was conducted using two-tailed t-tests and 95% confidence intervals.AI-generated reports demonstrated significantly improved performance across all parameters. The mean reporting time reduced from 6.1 to 3.43 min (p<0.0001) with AI-assisted report generation. Accuracy improved from 3.81 to 4.65 (p<0.0001), confidence ratings increased from 3.91 to 4.67 (p<0.0001), and overall reporting experience favored using the AI platform for generating radiology reports (mean 4.7 vs. 3.69, p<0.0001). Minor formatting errors and occasional anatomical misinterpretations were observed in AI-generated reports, but could be easily corrected by the radiologist during review.The AI-assisted reporting platform significantly improved efficiency and radiologist confidence without compromising accuracy. Although the tool performs well when provided with key clinical findings, it still requires expert oversight, especially in anatomically complex reporting. These findings support the use of AI as a supportive tool in radiology practice, with a focus on data integrity, consistency, and human validation.
Intelligent Infrastructure as Code: GitOps, Resilience Engineering, and Automation Patterns for Scalable Big Data Platforms

Infrastructure as Code (IaC) has emerged as a foundational practice for automating infrastructure provisioning, configuration, and lifecycle management in modern distributed systems. As platforms evolve toward hybrid and multi-cloud deployments, traditional script-based automation approaches increasingly struggle to meet growing demands for scalability, resilience, security, and operational consistency challenges that are amplified for stateful Big Data platforms such as MongoDB, Apache Cassandra, and DataStax Enterprise, where data replication, consistency guarantees, node topology, and failure domains must be carefully managed. This article examines the evolution of IaC from early configuration management systems to declarative, GitOps-driven workflows and explores emerging automation patterns that enhance platform resilience for both stateless and data-intensive workloads. We analyze how intelligent automation combining declarative IaC, continuous delivery pipelines, observability, and early AI-assisted decision mechanisms enables reliable deployment, scaling, and recovery of complex cloud-native and Big Data platforms, including automated provisioning of MongoDB replica sets and sharded clusters, Cassandra and DataStax ring expansion, and policy-driven lifecycle management across regions. Using publicly available architectural diagrams and industry case studies, we highlight best practices for resilient infrastructure design, automated failure remediation, and scalable Big Data operations that reduce operational risk while supporting performance, availability, and data durability requirements.
Responsiveness and Uptake of Sexual Reproductive Health and Rights Education and Information Among Young People 10-24 Years Old: A Case Of ‘Get Up Speak Out’ (GUSO) Program Implementation Period in Western Kenya Region

Young people and girls suffer from some of the worst SRHR outcomes in Kenya such as sexual abuse and violence; STIs including HIV; unintended pregnancies; unsafe abortions; early and forced marriages; obstetric fistula; and maternal mortality. Some of the main causes to these poor outcomes include lack of correct and comprehensive information on key SRHR issues. The GUSO program was implemented in western region of Kenya from 2018-2020 with an aim of aim of increasing uptake of SRHR education and information among young people 10-24 years old through 3 strategies: Capacity development for information providers (SRHR curriculum based trainings); Direct access to SRHR information e.g. Electronic &amp; Media platforms (direct messaging and WhatsApp group discussions); and Community approach (table talks and clarification sessions).The findings show that the number of educators trained increased through the three years. There was incremental in number of young people reached with SRHR information and similarly incremental in program realization over targets, meaning increase in willingness among the young people to utilizing the deployed strategies of direct and indirect SRHR. This also means that the deployed strategy of training of trainers to enhance capacity for young people to access information was effective in creating demand for SRHR information. The findings imply that it is possible to realize desired targets on SRHR information access by young people through capacity building and adopting the correct strategies. This study has identified such approaches to include table talks, clarification sessions, and direct messaging. Therefore, the health sector can indeed, by adopting these strategies improve SRHR service utilization among young people that may have a reducing effect to the now high levels of teenage pregnancies and other related consequences. The study has tested and determined that it is feasible to improve access to SRHR education and information among young people through training of educators and adopting proper strategies through which young people access SRH information. Furthermore, the findings have proved that these approaches lead to improved knowledge level, attitude for and SRHR service seeking behaviour for young people.