ethicalabs/Research-Intent-Collab huggingface dataset:
Trends in Disparities in Low-Income Children's Health Insurance Coverage and Access to Care by Family Immigration Status

To examine time trends in disparities in low-income children's health insurance coverage and access to care by family immigration status.We used data from the National Survey of Children's Health in 2003 to 2011-2012, including 83,612 children aged 0 to 17 years with family incomes <200% of the federal poverty level. We examined 3 immigration status categories: citizen children with nonimmigrant parents; citizen children with immigrant parents; and immigrant children. We used multivariable regression analyses to obtain adjusted trends in health insurance coverage and access to care.All low-income children experienced gains in health insurance coverage and access to care from 2003 to 2011-2012, regardless of family immigration status. Relative to citizen children with nonimmigrant parents, citizen children with immigrant parents had a 5 percentage point greater increase in health insurance coverage (P = .06), a 9 percentage point greater increase in having a personal doctor or nurse (P < .01), and an 11 percentage point greater increase in having no unmet medical need (P < .01). Immigrant children had significantly lower health insurance coverage than other groups. However, the group had a 14 percentage point greater increase in having a personal doctor or nurse (P < .01) and a 26 percentage point greater increase in having no unmet medical need (P < .01) relative to citizen children with nonimmigrant parents.Some disparities in access to care related to family immigration status have lessened over time among children in low-income families, although large disparities still exist. Policy efforts are needed to ensure that children of immigrant parents and immigrant children are able to access health insurance and health care.
Zonally opposing shifts of the intertropical convergence zone in response to climate change

Future changes in the location of the intertropical convergence zone (ITCZ) due to climate change are of high interest since they could substantially alter precipitation patterns in the tropics and subtropics. Although models predict a future narrowing of the ITCZ during the 21st century in response to climate warming, uncertainties remain large regarding its future position, with most past work focusing on the zonal-mean ITCZ shifts. Here we use projections from 27 state-of-the-art climate models (CMIP6) to investigate future changes in ITCZ location as a function of longitude and season, in response to climate warming. We document a robust zonally opposing response of the ITCZ, with a northward shift over eastern Africa and the Indian Ocean, and a southward shift in the eastern Pacific and Atlantic Ocean by 2100, for the SSP3-7.0 scenario. Using a two-dimensional energetics framework, we find that the revealed ITCZ response is consistent with future changes in the divergent atmospheric energy transport over the tropics, and sector-mean shifts of the energy flux equator (EFE). The changes in the EFE appear to be the result of zonally opposing imbalances in the hemispheric atmospheric heating over the two sectors, consisting of increases in atmospheric heating over Eurasia and cooling over the Southern Ocean, which contrast with atmospheric cooling over the North Atlantic Ocean due to a model-projected weakening of the Atlantic meridional overturning circulation.
PhotoAgent: Agentic Photo Editing with Exploratory Visual Aesthetic Planning

With the recent fast development of generative models, instruction-based image editing has shown great potential in generating high-quality images. However, the quality of editing highly depends on carefully designed instructions, placing the burden of task decomposition and sequencing entirely on the user. To achieve autonomous image editing, we present PhotoAgent, a system that advances image editing through explicit aesthetic planning. Specifically, PhotoAgent formulates autonomous image editing as a long-horizon decision-making problem. It reasons over user aesthetic intent, plans multi-step editing actions via tree search, and iteratively refines results through closed-loop execution with memory and visual feedback, without requiring step-by-step user prompts. To support reliable evaluation in real-world scenarios, we introduce UGC-Edit, an aesthetic evaluation benchmark consisting of 7,000 photos and a learned aesthetic reward model. We also construct a test set containing 1,017 photos to systematically assess autonomous photo editing performance. Extensive experiments demonstrate that PhotoAgent consistently improves both instruction adherence and visual quality compared with baseline methods. The project page is https://mdyao.github.io/PhotoAgent/.
Old age as risk indicator for poor end-of-life care quality – A population-based study of cancer deaths from the Swedish Register of Palliative Care

If patient age affects the quality of end-of-life care in cancer is unknown. Using data from a population-based register of palliative care in Sweden, we addressed this question.This nation-wide study focused on the last week of life of adults dying from cancer in 2011-2012, based on data reported to a national quality register for end-of-life care (N=26,976). We specifically investigated if age-dependent differences were present with respect to thirteen indicators of palliative care quality. Patients were categorised in one out of five pre-defined age groups. Odds ratios (OR) with 95% confidence intervals (CIs), adjusted for type of end-of-life care unit, were calculated using logistic regression, with the oldest group as reference.Age-dependent differences in implementation rate were detected for ten out of thirteen end-of-life care quality indicators, most of which were progressively less well met with each increment in age group. Compared to elderly cancer patients, young patients were more often informed about imminent death, (OR, 3.9; 95% CI 2.5-5.9, p<0.001), were more often systematically assessed for the presence and severity of pain (OR, 1.6; 95% CI 1.2-2.1, p<0.001) or other symptoms (OR, 1.4; 95% CI 1.0-1.9, p=0.044), were more likely to be assessed by palliative care consultation services (OR, 4.3; 95% CI 3.3-5.7, p<0.001) and to have injections prescribed as needed against pain (OR, 3.4; 95% CI 1.3-9.4, p=0.016), anxiety (OR, 3.8; 95% CI 2.0-7.1, p<0.001) or nausea (OR, 3.6; 95% CI 2.3-5.7, p<0.001). The families of young patients were more likely to be informed about imminent death (OR, 2.6; 95% CI 1.5-4.3, p=0.001) and to be offered bereavement support (OR, 4.6; 95% CI 2.7-7.8, p<0.001).Old age is a risk indicator for poor end-of-life care quality among cancer patients in Sweden.The executive committee of the National Quality Registries in Sweden.
First Pharmacoepigenomics in Personalized Medicine: CpG-PGx SNPs as New Candidates for a Systematic Insight into Genomic-Epigenomic-Phenomic-Pharmacogenomics (G-E-Ph-PGx) Axis

Background: There are important gaps in describing the associations between variants found by GWAS and various phenotypes. Prior reports suggested that SNPs in regulatory regions should be more investigated to uncover these associations. Thus, this study initiated a novel method along with Pharmacoepigenomics suggesting a new coined term “CpG-PGx SNP”. Methods: The rationale behind our analysis strategy was based on the impact of SNPs playing dual roles both in the CpG site disruption/formation and having PGx associations. Thus, we employed GeneCards (relevance score), PharmGKB (significant p-value), and GWAS catalog data for each gene (p&amp;lt;E-8). Following obtaining the 25 best-scored genes of four major epigenetic processes (methylation, demethylation, acetylation, and deacetylation), we generated two lists of candidate genes including potential CpG-PGx SNPs 2 of 22 and possible CpG-PGx SNPs. Results: Among 2,900 significant PGx annotations, we found 99 potential CpG-PGx SNPs related to 16 genes. CYP2B6, CYP2C19, CYP2D6, and COMT genes were the top genes. Additionally, we found 1,230 significant GWAS-based SNPs, among them 329 CpG-SNPs related to 48 genes with at least one CpG site disruption/formation. The top gene with the highest CpG-SNPs was TET2, followed by JMJD1C, and HDAC9. Importantly, we detected some synonymous variants in Epigenetically Modifiable Accessible Region (EMAR) which can open new insights into undiscovered roles of these SNPs. We identified 173 CpG-Disruptive SNPs, 155 CpG-Forming SNPs, and just 1 CpG SNP with both impacts. Conclusion: In conclusion, here we introduced CpG-PGx SNP for the first time, suggested 3 major genes playing crucial roles in Pharmacoepigenomics (PEpGx), CYP2D6 as the heart of PEpGx, and TET2 with the highest possibility of having CPG-PGx SNPs. We believe that his novel technological advance potentially will help the scientific community to utilize “CpG-PGx SNP” to unravel complex disease driven genetic and epigenetic interactions yielding therapeutic opportunities.
Learning Representations from Dendrograms

We propose unsupervised representation learning and feature extraction from dendrograms. The commonly used Minimax distance measures correspond to building a dendrogram with single linkage criterion, with defining specific forms of a level function and a distance function over that. Therefore, we extend this method to arbitrary dendrograms. We develop a generalized framework wherein different distance measures and representations can be inferred from different types of dendrograms, level functions and distance functions. Via an appropriate embedding, we compute a vector-based representation of the inferred distances, in order to enable many numerical machine learning algorithms to employ such distances. Then, to address the model selection problem, we study the aggregation of different dendrogram-based distances respectively in solution space and in representation space in the spirit of deep representations. In the first approach, for example for the clustering problem, we build a graph with positive and negative edge weights according to the consistency of the clustering labels of different objects among different solutions, in the context of ensemble methods. Then, we use an efficient variant of correlation clustering to produce the final clusters. In the second approach, we investigate the combination of different distances and features sequentially in the spirit of multi-layered architectures to obtain the final features. Finally, we demonstrate the effectiveness of our approach via several numerical studies.
CIGR Handbook of Agricultural Engineering, Volume I Land and Water Engineering, Chapter 5 Irrigation and Drainage, Part 5.8 Water Quality in Agriculture

First paragraph: Water that is intended for agricultural uses but in some way endangers agricultural activity can be defined as “unsuitable” water. Natural waters are defined as “polluted” when they become unsuitable following the addition of substances other than those normally present. The use of water of less than optimal quality for irrigation introduces various kinds of risk (agronomic, sanitary, and environmental) and can produce damage of direct and indirect types, depending on the form of pollution involved (see Fig. 5.76; [1–3]).
A unified graph-based approach for protein function prediction using AlphaFold structures and sequence features

Predicting protein function is a key challenge in computational biology with broad implications for understanding biological systems and disease mechanisms. Traditional deep learning approaches rely heavily on protein sequence data and protein-protein interaction (PPI) networks, often neglecting structural information due to limited availability of experimentally resolved protein structures. The advent of AlphaFold, which predicts protein structures with near-atomic accuracy, provides an opportunity to integrate structural context into function prediction. In this study, we propose StructSeq2GO, a novel hybrid model that combines structural and sequence information. StructSeq2GO employs graph representation learning to extract structural features from AlphaFold-predicted protein structures and integrates them with sequence embeddings derived from the ProteinBERT language model to predict Gene Ontology (GO) labels. Experimental evaluations demonstrate that StructSeq2GO achieves state-of-the-art performance across three GO domains, with Fmax scores of 0.485, 0.681, and 0.663, AUC scores of 0.764, 0.939, and 0.891, and AUPR scores of 0.688, 0.763, and 0.702 for the Biological Process (BPO), Cellular Component (CCO), and Molecular Function (MFO) ontologies, respectively. These results highlight the critical importance of structural information and the efficacy of ProteinBERT in enhancing protein function prediction, as structure provides spatial and biochemical context not captured by sequence alone. The model's performance is influenced by the quality of AlphaFold structural predictions and may benefit from future improvements in structure confidence modeling. Additionally, extending StructSeq2GO to predict pathway-level or disease-related annotations could broaden its biological utility.
Occupational Safety and Health in the Digital Age: Investigating the impact of digital technologies on workplace safety and health

This study investigates how digital technologies reshape occupational safety and health (OSH) across highhazard and service settings. Using a mixed-methods, multi-site, longitudinal design (42 worksites; 30 months), we evaluated three technology classes—exposure detection (wearables/computer vision), hazard reduction (collaborative and autonomous systems, drones), and workflow control (algorithmic scheduling/productivity dashboards). A staggered rollout enabled difference-in-differences, multilevel, and time-to-event analyses, complemented by 120 interviews, 24 focus groups, and implementation artefacts. Exposure detection was associated with 18–21% lower recordable and lost-time injury rates, a 24–31% decline in hazardous exposure minutes, and higher near-miss detection. Hazard-reduction automation produced smaller but significant improvements, including reduced musculoskeletal symptoms. By contrast, workflow control tools did not reduce injuries on average and increased psychosocial demands and reduced perceived control unless participatory guardrails (autonomy windows, break enforcement, fatigue flags) were embedded. Implementation quality— calibrated alerts, closed-loop response, and transparent, non-punitive data governance—significantly amplified benefits and neutralised adverse psychosocial effects. Findings support a sociotechnical view: digitalisation improves safety when paired with work redesign, human-automation teaming, and governance aligned to ISO 45001/45003 principles. Recommendations prioritise hierarchy-of-controls digitalisation, AI assurance, integrated leading indicators, and SME-friendly toolkits. The study reframes “digital safety” from gadget adoption to system-level, participatory risk reduction.
Communication spectrum of corporate social responsibility reporting

The prevalent application of reports on Corporate Social Responsibility (CSR) significantly changed the way companies communicate with their stakeholders. Contents of these reports focus on the company’s Triple Bottom Line (TBL) as a model that obtains the balance between financial, environmental and social performances of business. By achieving this balance, companies successfully respond to striving demands of sustainable development. Significant governmental and non- governmental initiatives and organizations around the world have already recognized the importance of mandatory CSR reporting, and therefore advocate its standardization process. This is a proper response to the growing demands of managers and stakeholders for prompt and transparent information’s regarding the company triple bottom line. The contents and the process of creating and publishing a CSR report require development of such databases that can provide integral analysis of company financial, environmental and social impacts. Adequate reporting process can be implemented only thru continuous communication of a company with its internal and external stakeholders. In this paper, authors determine the scientific aspects of CSR communication spectrum between a company and its stakeholders. Therefore, the aim of their research is to promote CSR reporting as a relevant mean of stakeholder management and evaluation of business sustainability.
Improving the use of modelling for projections of climate change impacts on crops and pastures

Projections of climate change impacts on global food supply are largely based on crop and pasture modelling. The consistency of these models with experimental data and their ability to simulate the effects of elevated CO(2) and of increased climate variability has been debated. The effects of high temperatures, of increased climate variability and of several limiting factors which interact with elevated CO(2) such as soil nutrients, pests and weeds are neither fully understood nor well implemented in leading models. Targeted model developments will be required based on experimental data concerning: (i) the role of extreme climatic events, (ii) the interactions between abiotic factors and elevated CO(2), (iii) the genetic variability in plant CO(2) and temperature responses, (iv) the interactions with biotic factors, and (v) the effects on harvest quality. To help make better use of the available knowledge, it is envisioned that future crop and pasture modelling studies will need to use a risk assessment approach by combining an ensemble of greenhouse gas emission (or stabilization) scenarios, of regional climate models and of crop and pasture models, as well as an ensemble of adaptation options concerning both management practices and species/varieties.
Revisiting China’s Principle of Mutual Respect for Sovereignty and Territorial Integrity in Bosnia and Herzegovina. The Construction of a New Paradox?

This article aims to assess China’s adherence to principles of mutual respect and territorial integrity in Bosnia and Herzegovina by analyzing its increasing presence in the country through the use of soft power in politics, economy, and culture. It focuses on China’s involvement in the Serb-majority entity, Republika Srpska, and evaluates whether this aligns with China’s principle of mutual respect for sovereignty and territorial integrity. In this regard, the study also examines to potential imbalances and tensions within the country due to China’s presence. The main objective is to investigate whether China’s actions in Bosnia and Herzegovina represent a new paradox in its foreign policy.
Validity evidence for the use of the Pediatric Quality of Life Inventory, the Revised Children’s Anxiety and Depression Scale-25, and the Columbia-Suicide Severity Rating Scale in measurement-based care in intensive outpatient child and adolescent mental health care

We sought to evaluate the validity of the interpretations made on the scores from three patient-reported outcome measures (PROMs), the Pediatric Quality of Life Inventory (PedsQL), the Revised Children's Anxiety and Depression Scale-25 (RCADS-25), and Columbia-Suicide Severity Rating Scale-short form (C-SSRS), for use in measurement-based care (MBC) in intensive outpatient child and adolescent mental health services.A mixed-methods, secondary analysis of interview and survey data from an MBC implementation evaluation, as well as PROMs data collected through MBC in routine clinical practice, was performed. The setting was intensive outpatient mental health services for children 6-18 years of age. The Standards for Educational and Psychological Testing argument-based approach to validation was used combining qualitative and quantitative data to evaluate validity.The PROMs appear to comprehensively cover key domains relevant to child and adolescent mental health intensive outpatient treatment. There is preliminary evidence that youth scores accurately reflect their symptoms and functioning and pick up change in these constructs, however, potential issues with response processes were identified with the C-SSRS, the school domain of PedsQL, and for caregiver proxy-reports on the PedsQL and RCADS-25, which warrant further investigation.There is evidence to support the use of these PROMs for MBC in child and adolescent mental health. However, further investigation is needed into response processes, internal structure, and to establish clinically meaningful thresholds to improve interpretability, and ensure the validity of their use.
A framework for collaborative filtering recommender systems

As the use of recommender systems becomes more consolidated on the Net, an increasing need arises to develop some kind of evaluation framework for collaborative filtering measures and methods which is capable of not only testing the prediction and recommendation results, but also of other purposes which until now were considered secondary, such as novelty in the recommendations and the users? trust in these. This paper provides: (a) measures to evaluate the novelty of the users? recommendations and trust in their neighborhoods, (b) equations that formalize and unify the collaborative filtering process and its evaluation, (c) a framework based on the above-mentioned elements that enables the evaluation of the quality results of any collaborative filtering applied to the desired recommender systems, using four graphs: quality of the predictions, the recommendations, the novelty and the trust.
HELIOSPHERE DIMENSION AND COSMIC RAY MODULATION

To appear on the Proceedings of the 13th ICATPP Conference on Astroparticle, Particle, Space Physics and Detectors for Physics Applications, Villa Olmo (Como, Italy), 3-7 October, 2011, to be published by World Scientific, Singapore (2012)
Integrating Green Human Resource Management Practices (GHRMPs) with Human Resource Information Systems (HRIS) for sustainable organizational growth

In the contemporary business landscape, sustainability has become an imperative rather than a choice. Organizations are increasingly recognizing the need to incorporate environmentally friendly policies into their operations. One of the key domains where sustainability can be effectively embedded is human resource management (HRM). The concept of Green HRM, which integrates environmental management principles into HRM practices, is gaining traction across industries. Simultaneously, the adoption of Human Resource Information Systems (HRIS) has revolutionized HR functions by digitizing processes, improving efficiency, and enhancing data management. The integration of Green HRM practices with HRIS offers organizations a strategic pathway to achieve sustainable growth by fostering an eco-conscious workforce, reducing resource consumption, and ensuring compliance with environmental regulations. The study explores the synergy between Green HRM and HRIS, highlighting how HRIS facilitates paperless HR operations, sustainable recruitment, eco-friendly training, remote work, and energy-efficient workforce management. It also discusses how HRIS supports sustainability metrics in performance appraisals and regulatory compliance. Despite challenges such as initial investment costs, change management, and data security concerns, the benefits of integrating Green HRM with HRIS far outweigh the hurdles. Organizations that adopt this integration will enhance their sustainability efforts, boost employee engagement, and gain a competitive edge in the evolving corporate landscape.