ethicalabs/Research-Intent-Collab huggingface dataset:
Use of social media by social science academics for scholarly communication

Purpose          The purpose of this study is to investigate social science academics’ use of social media for scholarly communication at Kuwait University.          Design/methodology/approach          Phase One data were collected through web-based and paper responses to questionnaires. Faculty members, teachers and teaching assistants in the social science faculty were invited to participate. Forty-six of the 100 invited participants responded. Phase Two comprised interviews with 10 respondents.          Findings          Social connection platforms, such as Twitter and Facebook, received the highest mean score for use (M = 4.35), followed by mobile apps, such as WhatsApp (M = 4.24), and multimedia platforms such as Instagram and YouTube (M = 3.59). Moderate to low use was recorded for academic social media. ResearchGate recorded the highest use (M = 3.09), followed by academia.edu (M = 2.93). “Keeping in touch” was the most frequently reported activity (M = 4.04). Two-thirds of respondents used social media for informal scholarly communication with people they knew. “Lack of university encouragement” received the highest score (M = 3.54) as a factor inhibiting use and almost half the respondents (47.2 per cent) cited “lack of time” as a barrier.          Practical implications          Improving academics’ understanding of the uses of social media might increase their visibility and improve their research and other scholarly activities. Study findings support the development of relevant training programs that include a focus on integrating social media into research activities and the dissemination of research findings.          Originality/value          This study contributes to the limited literature on this topic in Kuwait and the Arabian Gulf region.
THE ROLE OF HRIS (HUMAN RESOURCES INFORMATION SYSTEM) TECHNOLOGY IMPLEMENTATION IN MANAGING HUMAN RESOURCES IN PT. PEGADAIAN MEDAN

This study aims to find how the influence of compensation, discipline, and HRIS Development on HR Management at PT Pegadaian Medan Branch, the research method used is quantitative with a Multiple Regression Analysis approach. The number of samples taken was 52 respondents calculated using the Slovin formula. The problem to be studied is to find the right model of application of Compensation, Discipline, and development of HRIS applications that will affect HR management in general and specifically increase the business productivity of Medan branch pawnshop employees to provide the best, both for internal companies and in the wider community to help the process of pawning goods or gold. The results of this study indicate that a) The results obtained from research conducted on HRIS variables (X1), namely there is an influence between HRIS on HR Management at PT Pegadaian Medan Petisah. This means that one of the factors of HR management is influenced by the use of HRIS by employees. Employees who can operate IT properly will get optimal performance results, b) The results obtained from the Work Discipline variable influence HR Management. Where the greater the discipline received by employees both internal and external, the greater the management of HR at PT. Pegadaian, c) The results obtained prove that compensation influences HR Management. This means that the amount of compensation obtained for their work provides enthusiasm that gives birth to maximum HR management.
High Performance Nanotechnology Software (HPNS) for Parameter Characterization of Nanowire Fabrication and Nanochip System

This paper presents the high performance nanotechnology software (HPNS) to enable scientific researchers for predicting, visualizing and observing the temperature behavior and some parameters characteristics of nanochip system and nanowire fabrication. The analysis of scientific algorithms and high performance computing are searchable through a user friendly web-based system. This software will involve some mathematical modeling, numerical simulations and high performance computing technology to improve the accuracy of prediction, visualization quality and parallel performance indicators. The parameters involve on the thermal control process of nanowire fabrication are focuses on pressure, density, space, time control. The identification of the parameters influences the process of nanowire fabrication. The next focused are parameters characteristics of nanochip system. The parameters that involve are temperature, electromagnetic wave, space, time and other properties impact of the development of multilayer nanochip system. The implementations of parallel algorithms for solving the Partial Differential Equation of heat transfer and wave motion problems are based on large sparse parabolic and elliptic types. The discretization technique to obtain a large sparse linear system of equations is based on Finite Difference Method. The HPNS will support the supercomputing of numerical simulations and its repository using distributed memory architecture. The performance indicators will investigate the parallel programs using Parallel Virtual Machine (PVM) and C language on Linux operating system in terms of run time, accuracy, convergence, errors, speedup, efficiency and effectiveness. As a conclusion, HPNS will be an alternative software system to support huge computational complexity of the multilayer nanochip system and nanowire fabrication model.
Comparative Evaluation of Cloud-Native and VM-Based CI/CD Pipelines for Automated DevOps Deployments

The proliferation of DevOps methodologies has fundamentally reshaped the software development lifecycle, establishing Continuous Integration and Continuous Delivery/Deployment (CI/CD) as the central mechanism for achieving velocity and quality. This paradigm shift has given rise to two dominant architectural approaches for pipeline implementation: traditional, on-premise or IaaS-based Virtual Machine (VM) environments, and modern, fully managed cloud-native platforms. Each approach presents a distinct set of architectural, performance, economic, and security profiles that profoundly impact an organization's ability to deliver software effectively. This paper presents a comprehensive comparative analysis of these two paradigms. It introduces a quantitative framework for evaluation based on the industry-standard DevOps Research and Assessment (DORA) metrics and a detailed Total Cost of Ownership (TCO) model. Furthermore, it proposes a novel, weighted decision-making algorithm designed to guide practitioners and organizational leaders in selecting the optimal environment tailored to their specific strategic context, operational capabilities, and financial constraints. The analysis reveals a fundamental and recurring trade-off between the granular control, full-stack responsibility, and capital-intensive nature of VM-based environments versus the dynamic scalability, operational expenditure-driven model, and shared-responsibility security posture of the cloud. The findings indicate that while VM-based pipelines offer unparalleled customization, cloud-native architectures are more aligned with the core DevOps principles of speed, resilience, and elasticity, thereby enabling organizations to achieve elite levels of performance. This research provides a structured foundation for strategic decision-making in the critical domain of DevOps infrastructure.
Software Techniques to Mitigate Errors on Noisy Quantum Computers.

Quantum computers are domain-specific accelerators that can provide a large speedup for important problems. Quantum computers with few tens of qubits have already been demonstrated, and machines with 100+ qubits are expected soon. These machines face significant reliability and scalability challenges. The high hardware error rates limit quantum computers. To enable quantum speedup, it is essential to mitigate hardware errors. Our first work exploits the variability in the error rates of qubits to steer more operations towards qubits with lower error rates and avoid error-prone qubits. Our second work looks at executing different versions of the programs tuned to cause diverse mistakes so that the machine is less vulnerable to correlated errors, thereby making it easier to infer the correct answer. Our third work looks at exploiting the state-dependent bias in measurement errors (state 1 is more error-prone than state 0) and dynamically flips the state of the qubit to measure the stronger state. We perform our evaluations on real quantum machines from IBM and demonstrate significant improvement in the overall system reliability. ; Ph.D.
Environmental Rights for Administering Clean and Healthy Environment towards Sustainable Development in Malaysia: A Case Study

Malaysia is one of the environmentally rich and developing countries in the globe which is in fact, very attractiveand charming to all. But her bounty has been degrading gradually due to environmental pollution and therefore,the people’s rights are not maintained & ensured properly as guaranteed by their constitution which is also partof the environmental rights in the light of the international environmental laws. Meanwhile, the Government ofMalaysia passed some important environmental laws including ‘the Environmental Quality Act 1974; theEnvironmental Quality Regulations 1989 and the Environmental Quality Order 1989 etc; along with theinternational environmental laws in order to keep the clean and healthy environment but not yet been properlydone in compliance with the above laws. Consequently, sustainability may not be made possible. It may alsoaffect the biodiversities in flora and fauna. Moreover, it is observed that the existing legal mechanisms are notfriendly with the environment and development due to absence of environmental governance including theinsufficient environmental provisions, inadequate penal provisions, lack of political commitment, lack ofresources, unawareness, short term planning etc.
The Influence of Islamic Environmental Ethics on Business Decision-Making and Corporate Social Responsibility Practices

This study explores the influence of Islamic environmental ethics on Corporate Social Responsibility (CSR) and business decision-making, emphasizing how faith-based ethical frameworks guide sustainable practices in contemporary corporate environments. Grounded in the principles of stewardship (khalifah), justice (adl), and collective welfare (maslahah), Islamic ethics provide a holistic model for aligning profitability with moral and environmental responsibility. Using a mixed-method approach that combines survey research and content analysis, data were collected from 50 Shariah-compliant and ethically oriented companies across multiple industries. The survey measured the integration of ethical values into CSR initiatives, while content analysis of corporate reports evaluated transparency, environmental commitment, and ethical disclosures. The findings reveal that organizations adhering to Islamic ethical principles exhibit stronger environmental accountability, higher ethical compliance, and more sustainable long-term strategies compared to secular firms. These companies perceive environmental responsibility as a moral obligation rather than a regulatory requirement, integrating ethical governance into daily operations and strategic planning. The results also highlight that employee engagement and stakeholder trust improve significantly when CSR activities are guided by Islamic values. Furthermore, case studies of Islamic banks and small-to-medium enterprises (SMEs) in Muslim-majority regions demonstrate practical applications of these principles, including the use of zakat and waqf funds for environmental initiatives and community development programs. The study concludes that embedding Islamic ethics into business operations fosters a balance between economic growth, social welfare, and environmental stewardship. It also provides a pathway for strengthening corporate integrity and long-term competitiveness. Future research is recommended to examine the applicability of Islamic ethical principles across different industries and explore their intersection with emerging areas such as green innovation, artificial intelligence governance, and digital finance. Overall, this research underscores the potential of Islamic ethics as a foundation for sustainable business models that harmonize spiritual and economic objectives.
COVID-19 Information, Trust, and Risk Perception Across Diverse Communities in the United States: Initial Findings from a Multistate Community Engagement Alliance (CEAL)

Objectives. To provide initial findings from Community Engagement Alliance (CEAL), a multistate effort funded by the National Institutes of Health, to conduct urgent community-engaged research and outreach focused on COVID-19 awareness, education, and evidence-based response.  Methods. We collected survey data (November 2020–November 2022) from 21 CEAL teams from 29 state and regional CEAL sites spanning 19 US states, the District of Columbia, and Puerto Rico, which covered priority populations served and trusted sources of information about COVID-19, including prevention behaviors, vaccination, and clinical trials.  Results. A disproportionate number of respondents were Latino (45%) or Black (40%). There was considerable variability between CEAL sites regarding trusted sources of information, COVID-19 prevention, and COVID-19 vaccination. For example, more respondents (70%) reported health care providers as a trusted source of COVID-19 information than any other source (ranging from 6% to 87% by site).  Conclusions. CEAL rapidly developed novel infrastructure to engage academic, public health, and community organizations to address COVID-19’s impacts on underserved communities. CEAL provides an example of how to respond in future public health emergencies to quickly promote trustworthy, evidence-based information in ways that advance health equity. (Am J Public Health. 2024;114(S1):S112–S123. https://doi.org/10.2105/AJPH.2023.307504 )
Cyberbullying in the Age of Social Media: A Systematic Review of Mental Health Outcomes among Adolescents

Background: Cyberbullying via social media has emerged as a major public health concern among adolescents; however, evidence regarding its impact on mental health remains fragmented. This systematic review aimed to synthesize empirical evidence published between 2016 and 2025 on the association between social media–based cyberbullying and adolescent mental health outcomes. Methods: A systematic review was conducted using PubMed, ScienceDirect, Scilit, and PsycINFO in accordance with PRISMA 2020 guidelines. Studies were eligible if they included adolescents aged 10–19 years, explicitly examined cyberbullying within social media contexts, and assessed mental health outcomes using validated instruments. Risk of bias was evaluated using the Newcastle–Ottawa Scale (NOS) and Joanna Briggs Institute (JBI) appraisal tools. Results: Twenty-three studies involving more than 38,000 adolescents were included, comprising cross-sectional, longitudinal, and mixed-design studies. Reported prevalence of cyberbullying ranged from approximately 10% to 74.5%. Cybervictimization was consistently associated with increased risks of depression (OR ≈ 1.4–2.3), anxiety (OR ≈ 1.8–2.0), and suicidal behaviors (AOR = 2.62; 95% CI 1.73–3.98). Longitudinal evidence indicated that cybervictimization often preceded deterioration in mental health outcomes. Anxiety, peer relational stress, and sleep problems emerged as key mediating factors, while self-control and school connectedness appeared to serve as protective factors. Conclusions: Cyberbullying represents a significant and consistent risk factor for adverse mental health outcomes among adolescents. These findings highlight the need for comprehensive prevention strategies, including school-based interventions, digital literacy programs, and strengthened social media platform safeguards.
Identification of Anomalous Geospatial Trajectories via Persistent Homology

We present a novel method for analyzing geospatial trajectory data using topological data analysis (TDA) to identify a specific class of anomalies, commonly referred to as crop circles, in AIS data. This approach is the first of its kind to be applied to spatiotemporal data. By embedding $2+1$-dimensional spatiotemporal data into $\mathbb{R}^3$, we utilize persistent homology to detect loops within the trajectories in $\mathbb{R}^2$. Our research reveals that, under normal conditions, trajectory data embedded in $\mathbb{R}^3$ over time do not form loops. Consequently, we can effectively identify anomalies characterized by the presence of loops within the trajectories. This method is robust and capable of detecting loops that are invariant to small perturbations, variations in geometric shape, and local coordinate projections. Additionally, our approach provides a novel perspective on anomaly detection, offering enhanced sensitivity and specificity in identifying atypical patterns in geospatial data. This approach has significant implications for various applications, including maritime navigation, environmental monitoring, and surveillance.
Shallow Whole-Genome Sequencing from Plasma Identifies FGFR1 Amplified Breast Cancers and Predicts Overall Survival

Background: Focal amplification of fibroblast growth factor receptor 1 (FGFR1) defines a subgroup of breast cancers with poor prognosis and high risk of recurrence. We sought to demonstrate the potential of circulating cell-free DNA (cfDNA) analysis to evaluate FGFR1 copy numbers from a cohort of 100 metastatic breast cancer (mBC) patients. Methods: Formalin-fixed paraffin-embedded (FFPE) tissue samples were screened for FGFR1 amplification by FISH, and positive cases were confirmed with a microarray platform (OncoscanTM). Subsequently, cfDNA was evaluated by two approaches, i.e., mFAST-SeqS and shallow whole-genome sequencing (sWGS), to estimate the circulating tumor DNA (ctDNA) allele fraction (AF) and to evaluate the FGFR1 status. Results: Tissue-based analyses identified FGFR1 amplifications in 20/100 tumors. All cases with a ctDNA AF above 3% (n = 12) showed concordance for FGFR1 status between tissue and cfDNA. In one case, we were able to detect a high-level FGFR1 amplification, although the ctDNA AF was below 1%. Furthermore, high levels of ctDNA indicated an association with unfavorable prognosis based on overall survival. Conclusions: Screening for FGFR1 amplification in ctDNA might represent a viable strategy to identify patients eligible for treatment by FGFR inhibition, and mBC ctDNA levels might be used for the evaluation of prognosis in clinical drug trials.
Strong colour fields and cosmic ray showers at ultra-high energies

We argue that the increase of the ratio baryon/meson due to the presence of strong colour fields and percolation in ultra-high energy hadronic collisions, helps to explain some of the global features of ultra-high energy cosmic ray cascades at E&gt;10^18 eV and, in particular the observed excess in the number of muons with respect to current models of hadronic interactions. A reasonable agreement with the small value and slope of the average depth of shower maximum Xmax vs shower energy -- as seen in data collected at the Pierre Auger Observatory -- can be obtained with a fast increase of the p-Air production cross-section compatible with the Froissart bound.
Correction: Li et al. Analysis of Spatial and Temporal Characteristics of Citizens’ Mobility Based on E-Bike GPS Trajectory Data in Tengzhou City, China. Sustainability 2019, 11, 5003

The author would like to make the following corrections about the published paper [...]
Analysis of the determinants of workplace occupational safety and health practice in a selection of EU Member States

Incluye un resumen ejecutivo del informe en español ; En portada : European Agency for Safety and Health at Work ; Sumario: This report aims to provide insight into how the environment in which an establishment operates affects the way it manages workplace occupational safety and health (OSH)
Understanding the phase separation of N2/H2O and CO2/H2O binary systems through reactive force fields-based molecular dynamics simulations

Phase separation has a considerable effect on the detonation performances of explosives, but its mechanism has seldom been studied in terms of the interatomic interaction through molecular modeling. The binary mixtures of molecular N2, CO2, and H2O, which are the key components of detonation products of common explosives, with high density and at high temperature were investigated by using the reactive force fields-based molecular dynamics simulations. The mixing and demixing behaviors of N2/H2O and CO2/H2O systems were compared to distinguish the driven forces of phase separation. The N2/H2O mixtures with high density exhibit a remarkable phase separation at low temperature, while the CO2/H2O mixtures are mixing in a wide range of density and temperature. Similar changes in the repulsive van der Waals energy were found for all the studied systems. However, the corresponding changes in the attractive Coulomb energy are quite different for the mixing and demixing systems. Moreover, the polarization effect in dense systems contributes greatly to the Coulomb interaction. The Coulomb attraction is thus responsible for the phase separation of the dense systems under extreme conditions.
Sustainable Agriculture and Food Security in India: Challenges, Innovations, and Pathways for the Future

Abstract:   Sustainable agriculture is essential for ensuring food security in India, a country with a rapidly growing population and increasing environmental concerns. This paper explores the challenges hindering sustainable agricultural practices, including climate change, resource depletion, and socio-economic barriers. It also discusses innovative strategies such as precision farming, organic agriculture, and policy reforms that can lead to a more resilient agricultural sector. Using secondary data, the study analyzes trends in food production, resource utilization, and government interventions. The findings highlight the critical need for technological adoption, efficient resource management, and policy support to achieve long-term sustainability in Indian agriculture.
Learning in complex action spaces without policy gradients

While conventional wisdom holds that policy gradient methods are better suited to complex action spaces than action-value methods, foundational work has shown that the two paradigms are equivalent in small, finite action spaces (O'Donoghue et al., 2017; Schulman et al., 2017a). This raises the question of why their computational applicability and performance diverge as the complexity of the action space increases. We hypothesize that the apparent superiority of policy gradients in such settings stems not from intrinsic qualities of the paradigm but from universal principles that can also be applied to action-value methods, enabling similar functions. We identify three such principles and provide a framework for incorporating them into action-value methods. To support our hypothesis, we instantiate this framework in what we term QMLE, for Q-learning with maximum likelihood estimation. Our results show that QMLE can be applied to complex action spaces at a computational cost comparable to that of policy gradient methods, all without using policy gradients. Furthermore, QMLE exhibits strong performance on the DeepMind Control Suite, even when compared to state-of-the-art methods such as DMPO and D4PG.