ethicalabs/Research-Intent-Collab huggingface dataset:
IMPROVING DIGITAL LITERACY AND ADOLESCENT MENTAL HEALTH IN THE SOCIAL MEDIA ERA

The rapid rise of social media usage among adolescents presents both opportunities and challenges, particularly concerning mental health and digital literacy. In the digital age, adolescents must navigate complex virtual environments while maintaining psychological well-being. This community service program aimed to enhance digital literacy and promote mental health awareness among school-aged adolescents in Aceh. The activity involved 25 participants aged 15–24, drawn from various schools and youth communities. Implemented over two days, the program employed a quasi-experimental design, combining interactive education, case discussions, and role-play simulations. Pre-test and post-test evaluations measured changes in participants' knowledge levels. The results indicated a significant improvement in understanding digital literacy and mental health concepts, as evidenced by a Wilcoxon test result of p = 0.010 (&lt; 0.05). These findings underscore the effectiveness of interdisciplinary educational interventions in equipping adolescents with critical digital skills and emotional resilience in the era of pervasive social media. The program highlights the importance of collaborative efforts among educators, families, and communities in fostering safe, informed, and mentally healthy digital engagement among youth.
China's application of the One Health approach in addressing public health threats at the human-animal-environment interface: Advances and challenges

Due to emerging issues such as global climate change and zoonotic disease pandemics, the One Health approach has gained more attention since the turn of the 21st century. Although One Health thinking has deep roots and early applications in Chinese history, significant gaps exist in China's real-world implementation at the complex interface of the human-animal-environment.We abstracted the data from the global One Health index study and analysed China's performance in selected fields based on Structure-Process-Outcome model. By comparing China to the Belt & Road and G20 countries, the advances and gaps in China's One Health performance were determined and analysed.For the selected scientific fields, China generally performs better in ensuring food security and controlling antimicrobial resistance and worse in addressing climate change. Based on the SPO model, the "structure" indicators have the highest proportion (80.00%) of high ranking and the "outcome" indicators have the highest proportion (20.00%) of low ranking. When compared with Belt and Road countries, China scores above the median in almost all indicators (16 out of 18) under the selected scientific fields. When compared with G20 countries, China ranks highest in food security (scores 72.56 and ranks 6th), and lowest in climate change (48.74, 11th).Our results indicate that while China has made significant efforts to enhance the application of the One Health approach in national policies, it still faces challenges in translating policies into practical measures. It is recommended that a holistic One Health action framework be established for China in accordance with diverse social and cultural contexts, with a particular emphasis on overcoming data barriers and mobilizing stakeholders both domestically and globally. Implementation mechanisms, with clarified stakeholder responsibilities and incentives, should be improved along with top-level design.
An interpretation of stochastic differential equations as ordinary differential equations which depend on the sample point

where ww(/) = Wt(cS). Usually, this approach is not followed because of the technical difficulties that appear when one tries to solve (det) for arbitrary continuous w. One is therefore forced to use other lines of attack, and to study (stoch) directly. This gives rise to at least two nonequivalent theories, namely, the one due to Ito, and that of Fisk and Stratonovich. The purpose of this note is to announce that the "obvious approach" described in the beginning of the preceding paragraph can actually be pursued all the way, leading to a simple construction of solutions of (stoch) for arbitrary processes W with continuous sample paths. When W is a Wiener process, our construction gives the same result as the ordinary solution in the sense of Stratonovich. First, let us define what is meant by a solution of (det) when w is only continuous. We say that a curve x: t —• x(t), a  C°([g, b], R), such that:
Hydrologic Model Selection for the CFCAS Project: Assessment of Water Resources Risk and Vulnerability to Changing Climatic Conditions

The main purpose of this report is to present an up-to-date summary and comparison of existing hydrologic models that are potentially suitable for achieving the goals set in the Canadian Foundation for Climatic and Atmospheric Sciences (CFCAS) funded project “Assessment of Water Resources Risk and Vulnerability to Changing Climatic Conditions” (“project” hereafter). The report is intended to provide the information necessary for choosing the “right” model; a model which would be the most appropriate hydrologic modeling tool for the project in terms of various criteria. A two-level selection approach is used to objectively determine the most suitable model. At the first level a large number of existing hydrologic models are reviewed according to four fundamental selection criteria, and a subset of 18 models is identified. The selected 18 models are then ranked according to several evaluation criteria reflecting different aspects of specific project’s requirements. At the second level, total ranks attributed to the 18 selected models serve as an objective measure for determining the most appropriate model(s). https://ir.lib.uwo.ca/wrrr/1008/thumbnail.jpg
A Spatio-Temporal Knowledge-Discovery Platform for Earth-Science Data

The GPlates Geographic Information System (GIS) is a well-established tool for visualising and interacting with multimodal geo-data reconstructed through space and geological time. It overcomes the complexity of changing spatial reference frames due to plate-tectonic processes. Combining vast datasets in this manner is increasing the analysis complexity, with traditional visualisation-based approaches becoming ineffective in extracting key information and discovering hidden associations. This paper discusses the nature of these complexities, followed by the presentation of an extension to GPlates, involving the addition of interactive quantitative data-mining tools and capabilities, better suited to coping with the inherent analysis complexities. A case-study is used to demonstrate the system's unique capabilities. The integrated software infrastructure has manifested itself as a powerful knowledge discovery platform, which has the potential to lead to new high-impact discoveries in the Earth Sciences.
A new calculation of the cosmic-ray antiproton spectrum in the Galaxy and heliospheric modulation effects on this spectrum using a drift plus wavy current sheet model

The expected interstellar antiproton spectrum arising from cosmic-ray interactions in the Galaxy is recalculated, and the modulation of both antiprotons and protons is calculated using a two-dimensional modulation model incorporating gradient and curvature drifts and a wavy current sheet as well as the usual diffusion, convection, and energy-loss effects. Significant differences in the antiproton/proton ratio for different solar magnetic field polarities are predicted as well as a 'low-energy' component for antiprotons below about 1 GeV.
WD40-protein-mediated crosstalk among three epigenetic marks regulates chromatin states and yield in rice

Although there is increasing understanding of the regulatory effects of particular epigenetic marks, much less is known about how crosstalk among multiple marks affects genetic regulation. Here, we show that Dwarf-related WD40 protein 1 (DRW1) is involved in DNA 6mA demethylation, H3K27 trimethylation, and RNA m5C methylation in rice through its respective recruitment of the DNA demethylase AlkB homolog 1 (OsALKBH1), the histone methyltransferase CURLY LEAF (OsCLF), and NOP2/Sun RNA methyltransferase family member 2 (OsNSUN2). Knockout of DRW1 significantly reduces the extent of chromatin occupancy by OsALKBH1, OsCLF, and OsNSUN2, resulting in increased chromatin accessibility and enhanced expression of genes associated with brassinosteroid biosynthesis and signaling. Gene editing at a CAAT-box (ATTGG→ATTGA) and a GATA motif (GATAGGG→GAT) in the DRW1 promoter leads to elevated DRW1 transcription and thereby enhanced rice grain yield and salt tolerance. In field trials, DRW1-overexpressing rice lines displayed yield increases of ∼30.2% (in both normal and saline soils), accompanied by decreases in DNA 6mA and increases in H3K27me3 and RNA m5C levels at target genes. Overall, our study uncovers DRW1-mediated crosstalk among three epigenetic marks (DNA 6mA, H3K27me3, and RNA m5C) and reveals how this crosstalk controls transcriptional and post-transcriptional regulation to affect rice yield and salt tolerance.
Defining Fundamental Frequency for Almost Harmonic Signals

In this work, we consider the modeling of signals that are almost, but not quite, harmonic, i.e., composed of sinusoids whose frequencies are close to being integer multiples of a common frequency. Typically, in applications, such signals are treated as perfectly harmonic, allowing for the estimation of their fundamental frequency, despite the signals not actually being periodic. Herein, we provide three different definitions of a concept of fundamental frequency for such inharmonic signals and study the implications of the different choices for modeling and estimation. We show that one of the definitions corresponds to a misspecified modeling scenario, and provides a theoretical benchmark for analyzing the behavior of estimators derived under a perfectly harmonic assumption. The second definition stems from optimal mass transport theory and yields a robust and easily interpretable concept of fundamental frequency based on the signals' spectral properties. The third definition interprets the inharmonic signal as an observation of a randomly perturbed harmonic signal. This allows for computing a hybrid information theoretical bound on estimation performance, as well as for finding an estimator attaining the bound. The theoretical findings are illustrated using numerical examples.
Systematic Identification of Caregivers of Patients Living With Dementia in the Electronic Health Record: Known Contacts and Natural Language Processing Cohort Study (Preprint)

BACKGROUND                         Systemically identifying caregivers in the electronic health record (EHR) is a critical step for delivering patient-centered care, enhancing care coordination, and advancing research and population health efforts in caregiving. Despite EHRs being effective in identifying patients through standardized data fields like demographics, laboratory results, medications, and diagnoses, identifying caregivers through the EHR is challenging in the absence of specific caregiver fields.                                                                       OBJECTIVE                         Recognizing the complexity of identifying caregiving networks of people living with dementia, this study aims to systematically capture caregiver information by combining EHR structured fields, unstructured notes, and free text.                                                                       METHODS                         Among a cohort of people living with dementia aged 60 years and older from Kaiser Permanente Colorado, caregiver names were identified by combining structured patient contact fields, that is, known contacts, with name-matching and natural language processing techniques of unstructured notes and patient portal messages containing caregiver terms.                                                                       RESULTS                         Among the cohort of 789 people living with dementia, 95% (n=749) had at least 1 caregiver name listed in structured fields (mean 2.1 SD 1.1). Over 95% of the cohort had caregiver terms mentioned near a known contact name in unstructured encounter notes, with 35% having a full name match in unstructured patient portal messages. The natural language processing model identified 7556 “new” names in the unstructured EHR text containing caregiver terms among 99% of the cohort with high accuracy and reliability (&lt;i&gt;F&lt;/i&gt;&lt;sub&gt;1&lt;/sub&gt;-score=.85; precision=.89; recall=.82). Overall, 87% of the cohort had a new name identified ≥2 near a caregiver term in their notes and portal messages.                                                                       CONCLUSIONS                         Patterns in caregiver-related information were distributed across structured and unstructured EHR fields, emphasizing the importance of integrating both data sources for a comprehensive understanding of caregiving networks. A framework was developed to systematically identify potential caregivers across caregiving networks using structured and unstructured EHR data. This approach has the potential to improve health services for people living with dementia and their caregivers.
Electromagnetic Modeling and Simulation: Challenges in Validation, Verification, and Calibration

Modeling and simulation in electromagnetic engineering are discussed. Fundamental terms and concepts, and challenges in model validation and verification and code calibration are reviewed. Time- and frequency-domain models are developed and calibrated. Typical calibration scenarios are presented where tests and comparisons against analytical as well as numerical models are done.
Internet of Things and Security Challenges in Wireless Sensor Network

Wireless sensor networks (WSNs) are gradually more acquisition impact in our daily lives. They are deciding a huge series of applications in different domain, include health-care, assist and improved-living scenarios, engineering and manufacture analysing, manage networks, and different fields. In future, WSNs are normal to be incorporated into the “Internet of Things”, where sensor nodes incorporate the Internet with dynamism, and use it to cooperate with each other and achieve their tasks. However, when WSNs become a part of the Internet, we must cautiously explore and analyze the issues concerned with this integration. In this paper, we evaluate different approaches to integrate WSNs into the Internet of things.
Illuminating Manipulative Design: from ‘Dark Patterns’ to Information Asymmetry and the Repression of Free Choice under the Unfair Commercial Practices Directive

Dark patterns' are defined as 'tricks used in websites and apps that make you do things that you didn't mean to, like buying or signing up for something.' The term describes 'deceptive' and 'manipulative' techniques implemented when designing an app, website, or platform to change a user's behaviour in a way that would not have happened without the dark pattern. Yet much of the academic scholarship on the regulation of manipulative design has focused on privacy and data protection legislation. This article identifies seventeen common types of 'dark patterns'. It facilitates critical, legal, and regulatory dialogue by proposing a new taxonomy consistent with the relative provisions of the Unfair Commercial Practices Directive (UCPD). Critical analysis of three respected dark patterns taxonomies provides the basis of analysis of the protections provided to consumers by the UCPD. This approach focuses on the category of dark patterns we refer to as relying on 'Information Asymmetry' and an analysis of practices we identify as causing 'Free Choice Repression.' The article closes with policy recommendations to improve the regulation of dark patterns for commercial purposes.
Dark Matter in the Coming Decade: Complementary Paths to Discovery and Beyond

In this report we summarize the many dark matter searches currently being pursued through four complementary approaches: direct detection, indirect detection, collider experiments, and astrophysical probes. The essential features of broad classes of experiments are described, each with their own strengths and weaknesses. The complementarity of the different dark matter searches is discussed qualitatively and illustrated quantitatively in two simple theoretical frameworks. Our primary conclusion is that the diversity of possible dark matter candidates requires a balanced program drawing from all four approaches.
Sarcopenia Mechanics and Mitochondrial Coherence: A Statistical Physics Framework for the 3D→2D Geometric Phase Transition in Skeletal Muscle

Skeletal muscle is a highly organized three-dimensional contractile system characterized by a precise helical arrangement of actomyosin filaments and strict sarcomere lattice spacing of 2.2 µm. Maintaining this volumetrically dense architecture against gravity and continuous external loading demands an uninterrupted supply of adenosine triphosphate (ATP) for protein synthesis and myofilament stability. We present a statistical physics and systems engineering framework identifying the progressive loss of skeletal muscle mass in aging — sarcopenia — as a deterministic geometric phase transition from a three-dimensional creation mode configuration to a two-dimensional maintenance mode configuration. When the mitochondrial Axial Coherence Factor (ACF) falls below the first-principles universal threshold, collective molecular torque catalysis collapses. The critical threshold ACF = 0.65 is derived geometrically from the 3D random close-packing percolation threshold (pc = 0.4120 [1,2]) and the Jacobi ellipsoid rotational stability limit (Rmin = 2/3 [3]), yielding ACF = (pc × Rmin)^(1/3) = 0.650033 (Δ = 0.0051%, z = 0.013σ) [4]. Ten alternative derivation paths tested and closed. The resulting bioenergetic deficit shifts the intracellular balance from volumetric muscle anabolism to catabolic cross-sectional thinning. The independent evidence base spans multi-ethnic convergent cohort studies across three continents (Singapore, United Kingdom, Jamaica) [5,6], anchored by Nobel Prize-confirmed ATP synthase rotary mechanism [7,8] and convergent mitochondrial dysfunction evidence from 16 independent research groups across 4 continents spanning 45+ years. All computations verified against NIST CODATA 2022 [13]. Fisher's combined probability method: MS37 biological domains alone σ = 5.27 (χ² = 44.22, df = 6, p = 1.26×10⁻⁷). Full series cumulative (df=50): σ = 10.23. Exercise is identified as the only universal intervention capable of elevating mitochondrial visitation frequency fv at both molecular and tissue scale simultaneously — the only mechanism proven effective for sarcopenia universally.
Public Budget Transparency and Accountability in Preventing Corruption and Inefficiency

Purpose: This study explores the role of public budget transparency and accountability in preventing corruption and inefficiency. It investigates how governance mechanisms and digital tools, such as e-governance and e-procurement systems, affect public trust in government institutions. Research Method: The study employs a systematic literature review, analyzing secondary data from various sources to examine the effectiveness of transparency and accountability across regions. The research focuses on regional differences between developed and developing countries and identifies critical factors such as institutional strength and citizen participation. Results and Discussion: The findings show that transparency mechanisms, particularly those supported by digital technologies, significantly reduce financial reporting errors and enhance public trust. However, transparency alone is not practical in regions with weak governance structures. Successful implementation requires strong accountability measures and active public involvement. Implications: The study suggests governments should combine digital tools with institutional reforms to ensure adequate public oversight and participation. Public administrators and policymakers must develop governance frameworks that encourage transparency and accountability. Future research should examine the influence of political, cultural, and social factors on the success of transparency initiatives.
A New Reactive Force Field for NOx-Water Interactions: Development, Evaluation, and Molecular Dynamics Simulation of Peroxynitrite

Reactive nitrogen species (RNS) are key contributors to plasma-liquid processes and play a critical role in the chemistry of plasma-activated water. Despite their importance, their molecular-level behavior in aqueous environments is still not well understood, largely due to the absence of reliable reactive force fields. In this study, a new ReaxFF parameter set, ReaxFFCHONx-2026, is developed and systematically assessed for modeling nitrogen- and oxygen-containing reactive species in both gas-phase and aqueous conditions relevant to plasma systems. The parameter set is optimized using density functional theory (DFT) reference data for representative NOx reaction pathways and integrated with an existing aqueous/biomolecular ReaxFF framework to enable reactive molecular dynamics simulations in water. Its performance is validated through a range of structural, thermodynamic, and dynamic properties, including radial distribution functions, potential energy profiles, and diffusion coefficients. The results demonstrate strong agreement with DFT calculations and previously reported data, particularly in describing N-O bond breaking and solvation behavior. As a case study, the interaction of peroxynitrite (ONOO⁻) with water is investigated using reactive molecular dynamics, where atomic charges are dynamically determined via the ReaxFF charge equilibration method. The simulations show protonation leading to ONOOH formation, pronounced site-specific solvation around oxygen atoms, and preferential cleavage of the peroxide O-O bond. Analysis of diffusion further indicates that the predicted transport properties of RNS are consistent with available data, supporting the reliability of the developed force field. Overall, ReaxFFCHONx-2026 offers a robust framework for large-scale atomistic simulations of plasma-activated water and reactive nitrogen chemistry.
Development and Application of Artificial Neural Network

Artificial neural network is a very important part in the new industry of artificial intelligence. In China, there are many researches on artificial neural network and artificial intelligence are developing rapidly. Therefore, this paper reviews and summarizes artificial neural network, and hopes that readers can get a deeper understanding of artificial neural network. This paper first reviews the development history of artificial neural network and its related theory, and introduces four major characteristics of artificial neural network, such as the non-linear, non-limitative, non-qualitative and non-convex. Then it emphatically analyzes its application in information, medicine, economy, control, transportation and psychology. Finally, the future development trend of artificial neural network is prospected and summarized.
Collective forces in scalar active matter

Large-scale collective behavior in suspensions of many particles can be understood from the balance of statistical forces emerging beyond the direct microscopic particle interactions. Here we review some aspects of the collective forces that can arise in suspensions of self-propelled active Brownian particles: wall forces under confinement, interfacial forces, and forces on immersed bodies mediated by the suspension. Even for non-aligning active particles, these forces are intimately related to a non-uniform polarization of particle orientations induced by walls and bodies, or inhomogeneous density profiles. We conclude by pointing out future directions and promising areas for the application of collective forces in synthetic active matter, as well as their role in living active matter.