ethicalabs/Research-Intent-Collab huggingface dataset:
Human Resources Information System (HRIS): A Theoretical Perspective

HRIS is one of the major modern HR tools. In developed countries, it became popular since the be-ginning of this century. In Bangladesh, corporate organizations have started to implement HRIS in last 5 years. But still its implementation is limited within the big corporate houses. Small corporate houses and public organizations have failed to realize the benefits of HRIS and taken hardly any initiative to implement the system. The major barrier to success of HRIS is the lack of management commitment. The major limitation is the high cost. But the benefits of the HRIS are more than the limitations. Once it is implemented in any organization, employees and management have accepted and realized the benefits. But to get it implemented is a challenge. This study is an attempt to provide a theoretical analysis of the HRIS implementation with analysis of benefits, limitations and barriers. A case study was prepared to provide a better understanding of the topic in a real life context.
Benchmarking Ploidy Estimation Methods for Bulk and Single‐Cell Whole Genome Sequencing

Abstract                   Maintaining cellular ploidy is critical for normal physiological processes, although gains in ploidy are frequently observed during development, tissue regeneration, and metabolism, and potentially contribute to aneuploidy, thereby promoting tumor evolution. Although numerous computational tools have been developed to estimate cellular ploidy from whole‐genome sequencing (WGS) data at bulk or single‐cell resolution, to the knowledge, no systematic comparison of their performance has been conducted. Here, a benchmarking study is presented of 11 methods for bulk WGS and 8 methods for single‐cell WGS data, utilizing both experimental and simulated datasets derived from diploid cells mixed with aneuploid or polyploid cells. For bulk WGS tools, their performance is evaluated in estimating tumor purity and ploidy, as well as the influence of preprocessing steps, somatic mutation callers, purity, sequencing platforms, and depths. It is found that PURPLE outperforms other methods when tumor purity exceeded 30%, regardless of sequencing coverage or platform. However, all existing tools performed poorly applied to euploid samples or long‐read sequencing data. For single‐cell WGS tools, their ploidy detection accuracy is assessed, and SeCNV is identified as the top‐performing method. These findings provide valuable guidance for future research on ploidy analysis and ongoing improvements in computational tools for single‐cell sequencing data.
Evaluation of the Implementation Effectiveness of Digital Scenario-based Teaching in University-level English Conversation Instruction: A Study Based on Artificial Intelligence Generated Content (AIGC)

Abstract         In recent years, the rapid development of artificial intelligence (AI) technology has highlighted the growing potential of Artificial Intelligence Generated Content (AIGC) in the field of education. In university-level English instruction, traditional teaching models often fail to meet the increasing demand for oral practice and contextual communication skills among students. This study, grounded in the theoretical framework of digital scenario-based teaching and leveraging AIGC technology, designed and implemented a teaching model tailored for English conversation instruction in higher education. Through an empirical investigation into teaching outcomes—including dimensions such as student learning performance, communicative competence improvement, and instructional satisfaction—the findings demonstrate that AIGC-driven digital scenario-based teaching significantly enhances students' comprehensive language application skills while stimulating their interest and active engagement in learning. Moreover, this study identifies technical bottlenecks and pedagogical challenges encountered during implementation, proposing optimization strategies and providing valuable insights for the intelligent evolution of university English teaching.
A Practical Guide to Interpret a Randomized Controlled Trial

The most dangerous error in clinical trial interpretation is equating p > 0.05 with no effect. This review provides a practical, algorithm-based framework for classifying randomized controlled trial (RCT) results into six distinct categories positive, imprecise (+), neutral, inconclusive, negative, and harmful using confidence interval (CI) position relative to the minimal clinically important difference (MCID) as the primary tool, augmented by Bayesian posterior probabilities. We demonstrate that the same p > 0.05 result can represent three fundamentally different conclusions (inconclusive, negative, or neutral), show how Bayesian reanalysis can rescue benefit signals missed by frequentist thresholds, and illustrate the framework with real-world examples from critical care and cardiology trials. The framework synthesizes guidance from Altman, Harrell, Pocock, Zampieri, the ASA, and ICH E9 into a single coherent decision algorithm.
SS34-02 WORKPLACE HEALTH WITHOUT BORDERS’ VIRTUAL OCCUPATIONAL HEALTH AND SAFETY TRAINING USING SYNCHRONOUS AND ASYNCHRONOUS METHODS

Abstract                                   Introduction                   Training is a focus area of Workplace Health Without Borders (WHWB). There are 3,4 billion workers in the world. Nearly two-thirds of them work in unhealthy and unsafe conditions. Worldwide, there are about 8,000 certified / registered occupational hygienists and only 16 countries with professional accreditation programs. The global need is great for more trained occupational health / hygiene professionals who understand how to protect workers from workplace injury and disease.                                                   Materials and Methods                   This presentation will share our methods and platform for instruction. We will discuss how we pivoted during the COVID-19 pandemic to a combination of synchronous / asynchronous training, and how this solved several important issues for our students and tutors and overcame other barriers to in-person training. We will present the outcomes of student evaluations and how we measure and deliver successful training.                                                   Results                   The impact of our training will be presented. Our training leads to mentoring which leads to networking for the students and global professionals responsible for worker wellbeing. We engage in-country tutors for instruction and facilitation so that networking and mentoring are more easily attained.                                                   Conclusions                   Students and professionals in low- or middle-income countries (LMICs) lack access to occupational health / hygiene training. There is often a lack of regulations in these countries, so that prevention of exposure and protection of worker health is not addressed. However, knowledge of breaking the routes of exposure that cause disease can be used anywhere when it is understood.
Quantum Sensing for High Energy Physics

Report of the first workshop to identify approaches and techniques in the domain of quantum sensing that can be utilized by future High Energy Physics applications to further the scientific goals of High Energy Physics.
Hausdorff Distances Between Distributions Using Optimal Transport and Mathematical Morphology

In this paper we address the question of defining and computing Hausdorff distances between distributions in a general sense. We exhibit some links between Prokhorov-Levy distances and dilation-based distances. In particular, mathematical morphology provides an elegant way to deal with periodic distributions. The case of possibility distributions is addressed using fuzzy mathematical morphology. As an illustration, the proposed approaches are applied to the comparison of spatial relations between objects in an image or a video sequence, when these relations are represented as distributions.
Monitoring and assessment of potentially hazardous particles in high-risk workplaces in the production of Ni-Cd batteries

Abstract                   The manufacture of Ni-Cd batteries involves the risk of contact with and inhalation of dust particles containing heavy metals, including potential carcinogens. Three workplaces were selected that appeared to pose the greatest risk to workers in terms of exposure to heavy metal (nickel and cadmium) dust generated during the production and handling of nickel-cadmium plates. Although the limits for dust and carcinogens and mutagens are very strict, they are gradually being tightened. Therefore, the main motivation was to find the source of the highest amounts of respirable particles, determine the size of the particles, the composition of the fraction and evaluated potential toxicity of particles captured on the filters. This will help to propose additional measures to minimise concentrations of potentially carcinogenic particles in the working environment. The chemical analysis, particle size distribution, metal content and cytotoxicity of the particles trapped on the filters were investigated. While the concentration of heavy metals was well below the permissible exposure limits, the extracts obtained from the sampled filters had a significant effect on cytotoxicity, particularly those containing lower concentrations of particles.
bioETH-Beacon: A Confidential On-Chain Genomic Beacon with Encrypted Counts, Filters, and Bounded Noise over a Fully Homomorphic EVM

The Global Alliance for Genomics and Health (GA4GH) Beacon protocol lets researchers ask whether a genomic variant has been observed in a participating cohort and receive aggregate variant-level counts. As Beacon networks grow, two privacy risks remain: host institutions can see plaintext queries, and repeated rare-variant queries can support membership-inference attacks. We present bioETH-Beacon, a smart-contract prototype that runs the Beacon "aggregate count" query over encrypted data on a fully homomorphic Ethereum Virtual Machine (fhEVM). Hospitals upload encrypted marker-count entries, authorized researchers submit encrypted marker queries, and the contract returns an encrypted answer that is released, via an off-chain key-management service, only to the requester named in the contract's on-chain ACL. The design is organized as a 3x4 tier-by-query-family grid spanning genotype, sex, age, and phenotype queries, with tiers that trade stronger confidentiality for lower query cost. For genotype paths, the prototype can add bounded on-chain noise to mitigate probing attacks. Experiments on synthetic panels derived from a Polygenic Score (PGS) catalog show the expected scaling behavior and demonstrate that pre-aggregation can substantially reduce query gas when public marker presence is an acceptable trade-off. Overall, bioETH-Beacon provides a research prototype for confidential Beacon-style genomic querying without a trusted compute evaluator.
MagicBathyNet: A Multimodal Remote Sensing Dataset for Bathymetry Prediction and Pixel-based Classification in Shallow Waters

Accurate, detailed, and high-frequent bathymetry, coupled with complex semantic content, is crucial for the undermapped shallow seabed areas facing intense climatological and anthropogenic pressures. Current methods exploiting remote sensing images to derive bathymetry or seabed classes mainly exploit non-open data. This lack of openly accessible benchmark archives prevents the wider use of deep learning methods in such applications. To address this issue, in this paper we present the MagicBathyNet, which is a benchmark dataset made up of image patches of Sentinel2, SPOT-6 and aerial imagery, bathymetry in raster format and annotations of seabed classes. MagicBathyNet is then exploited to benchmark state-of-the-art methods in learning-based bathymetry and pixel-based classification. Dataset, pre-trained weights, and code are publicly available at www.magicbathy.eu/magicbathynet.html.
Special Topics in Probabilistic Safety Assessments (PSA) Level 1

The special topics presented in this chapter are related to the in Probabilistic Safety Assessments (PSA) level 1, which is evaluating the risk impact considering that the reactor is damaged. The tasks are presented in the approach mentioned in the introduction and in the order of their flow path during the performance of such a study, i.e.: (a) How the input to the PSA model is prepared and which are the main challenges? (b) The screening of the hazards and the evaluation of the considered challenges to the NPP (Initiating Events), possibly leading to risk increase; (c) The development of the databases for failures of components and frequencies of the initiators; (d) Description of the plant reaction to the challenges by modeling it in a series of event trees for the chosen list of initiators in the previous tasks; (e) Description of plant barriers to the challenges identified in the event trees; (f) Integration and quantification general approach and special aspects of this task for internal/area or external events in NPP unitary models. Uncertainty and sensitivity analyses of PSA level 1, as basic information for further use of results in the decision-making process.
Cost-Effectiveness Analysis of CT-Based Finite Element Modeling for Osteoporosis Screening in Secondary Fracture Prevention: An Early Health Technology Assessment in the Netherlands

Objective. To conduct cost-utility analyses for Computed Tomography To Strength (CT2S), a novel osteoporosis screening service, compared with dual-energy X-ray absorptiometry (DXA), treat all without screening, and no screening methods for Dutch postmenopausal women referred to fracture liaison service (FLS). CT2S uses CT scans to generate femur models and simulate sideways fall scenarios for bone strength assessment. Methods. Early health technology assessment (HTA) was adopted to evaluate CT2S as a novel osteoporosis screening tool for secondary fracture prevention. We constructed a 2-dimensional simulation model considering 4 strategies (no screening, treat all without screening, DXA, CT2S) together with screening intervals (5 y, 2 y), treatments (oral alendronate, zoledronic acid), and discount rate scenarios among Dutch women in 3 age groups (60s, 70s, and 80s). Strategy comparisons were based on incremental cost-effectiveness ratios (ICERs), considering an ICER below €20,000 per QALY gained as cost-effective in the Netherlands. Results. Under the base-case scenario, CT2S versus DXA had estimated ICERs of €41,200 and €14,083 per QALY gained for the 60s and 70s age groups, respectively. For the 80s age group, CT2S was more effective and less costly than DXA. Changing treatment from weekly oral alendronate to annual zoledronic acid substantially decreased CT2S versus DXA ICERs across all age groups. Setting the screening interval to 2 y increased CT2S versus DXA ICERs to €100,333, €55,571, and €15,750 per QALY gained for the 60s, 70s, and 80s age groups, respectively. In all simulated populations and scenarios, CT2S was cost-effective (in some cases dominant) compared with the treat all strategy and cost-saving (more effective and less costly) compared with no screening. Conclusion. CT2S was estimated to be potentially cost-effective in the 70s and 80s age groups considering the willingness-to-pay threshold of the Netherlands. This early HTA suggests CT2S as a potential novel osteoporosis screening tool for secondary fracture prevention. Highlights For postmenopausal Dutch women who have been referred to the FLS, direct access to CT2S may be cost-effective compared with DXA for age groups 70s and 80s, when considering the ICER threshold of the Netherlands. This study positions CT2S as a potential novel osteoporosis-screening tool for secondary fracture prevention in the clinical setting. A shorter screening interval of 2 y increases the effectiveness of both screening strategies, but the ICER of CT2S compared with DXA also increased substantially, which made CT2S no longer cost-effective for the 70s age group; however, it remains cost-effective for individuals in their 80s. Annual zoledronic acid treatment with better adherence may contribute to a lower cost-effectiveness ratio when comparing CT2S to DXA screening and the treat all strategies for all age groups.
Quantum error correction with the toric code

Quantum computing platforms based on arrays of tweezer-confined neutral atoms have recently emerged as a competitive modality thanks to a direct path toward high qubit count, rapidly advancing operation fidelities, and their ability to execute circuits with arbitrary qubit connectivity. These features will enable the use of efficient error correction schemes with high encoding-rates, time-efficient decoding, and resource-efficient architectures based on transversal gates. With these goals in mind, recent state of the art neutral atom demonstrations focus on the transition from the use of physical qubits to error-corrected logical qubits, but to date there has been no demonstration of repeated error correction scalable to arbitrary depth. Here, we demonstrate many cycles of syndrome extraction in a toric quantum error correcting code, using mid-circuit measurement and replacement of lost qubits, including reloading of a qubit reservoir for indefinite coherent operation. We characterize the logical error rate after up to 90 cycles, showing that logical information can be preserved through multiple rounds of qubit reloading. Comparing two distances of the code up to 8 rounds of syndrome extraction shows a lower absolute logical error rate for the larger distance code.
Investigating the Utility of Explainable Artificial Intelligence for Neuroimaging‐Based Dementia Diagnosis and Prognosis

ABSTRACT                   Artificial intelligence and neuroimaging enable accurate dementia prediction but often involve ‘black box’ models that can be difficult to trust. Explainable artificial intelligence (XAI) aims to provide insights into the model's decisions; however, choosing the most appropriate method is non‐trivial and often context‐specific. We used T1‐weighted MRI to train models on two tasks: Alzheimer's disease (AD) classification (diagnosis) and predicting conversion from mild‐cognitive impairment (MCI) to all‐cause dementia (prognosis). We applied eleven XAI methods across two popular image classification architectures, producing visualisations of the most salient regions. We also propose a framework for interpreting explanations produced by different XAI methods and predictive models. Models achieved balanced accuracies of 81% and 67% for diagnosis and prognosis. XAI outputs highlighted brain regions relevant to AD with strong convergence across gradient‐based techniques. LIME produced explanations that were most similar across architectures. Mean saliency enhanced MCI prognosis prediction when included as an additional input feature. XAI can be used to verify that models are utilising relevant features and to generate valuable measures for further analysis.
Palestine in The Hague: Justice, Geopolitics, and the International Criminal Court

Palestine's request that the International Criminal Court investigate crimes allegedly committed by Israel on its territory presents the court with a major investigative and institutional challenge. To this point, the ICC has generally avoided situations where major powers strongly oppose court involvement. The prosecution's cautious selection of situations has in turn allowed for an accommodation between skeptical major powers and the court. An investigation in Palestine, which the United States and other major powers would oppose, could unsettle that fragile truce. This article considers how the situation in Palestine came before the court and analyzes several options available to the ICC prosecutor.
Application State And Trend Of Artificial Intelligence Generated Content In Design And Art

This study provides a comprehensive bibliometric review of Artificial Intelligence Generated Content (AIGC) applications in design and art, analysing publication trends from 2022 to 2024. Using data from the SCOPUS database, the study examines 472 publications, identifying key themes such as generative models, large language processing, and educational applications. The findings reveal a sharp increase in research interest, with prominent contributions from the United States and China. Major journals in this field include Documentation, Information &amp; Knowledge and Computers and Education: Artificial Intelligence. This review highlights current research trajectories and underscores the need for ethical guidelines and improved models to ensure responsible integration of AIGC in creative industries. The insights gained here aim to inform future research directions, contributing to the sustainable and innovative application of AIGC in design and art.
Intertemporal pricing and price discrimination: a semiparametric hedonic analysis of the personal computer market

AbstractWe apply a smooth coefficient semiparametric model to a unique high‐frequency data set to examine the intertemporal pricing of personal computers. Furthermore, we test whether firms charge differential component prices for their top performance personal computers and whether premium firms charge both a premium for all their computers and a premium for their top performance ones. We find nonlinear effects in the pricing of personal computer components. We also find that firms in general do not charge differential prices for the components of their top performance computers. In addition, high‐quality firms charge higher premia only for their most advanced products. Copyright © 2006 John Wiley &amp; Sons, Ltd.
The Chapter VII Powers of the United Nations Security Council

Bibliografía: p. [387]-407 ; Indice
Impact Assessment of Biological Control-Based Integrated Pest Management in Rice and Maize in the Greater Mekong Subregion

The impact and sustainability of two interventions that have been formulated to introduce integrated pest management (IPM) into rice and maize crops in Southwestern China, Laos, and Myanmar between 2011 and 2016, and were assessed at the end of 2017. From 22 Trichogramma rearing facilities established during the interventions, 11 were still producing substantial quantities of biocontrol agents 1.5 years after project support had ended, while seven had stopped operations completely, and four were doing stock rearing only. Through the implementation of biological control-based IPM, slightly higher yields were achieved in maize and rice (4–10%), when compared to control farmers, but the difference was not statistically significant. However, the use of pesticides nearly halved when farmers started using Trichogramma egg-cards as a biological control agent. Support from either public or private institutions was found to be important for ensuring the sustainability of Trichogramma rearing facilities. Many of the suggested IPM measures were not adopted by smallholder farmers, indicating that the positive impacts of the interventions mostly resulted from the application of Trichogramma biological control agents. The following assessment suggests that further promotion of IPM adoption among farmers is needed to upscale the already positive effects of interventions that facilitate reductions in synthetic pesticide use, and the effects on sustainable agricultural production of rice and maize in the target area more generally.