ethicalabs/Research-Intent-Collab huggingface dataset:
Unspoken, Yet Lived: Reflections on Sexual and Reproductive Health and Rights Among Youth with Disabilities in Gulu, Northern Uganda

Background: Youth with disabilities remain among the most overlooked groups in global sexual and reproductive health and rights (SRHR) discourses, including in sub-Saharan Africa. Yet, their SRHR needs are often ignored. This reflexive article aims to illuminate and recenter the experiences and perspectives of youth with disabilities living in Gulu City and Gulu District, Northern Uganda, exploring what matters to them regarding SRHR and their broader life aspirations. Methods: We adopted a qualitative, reflexive and participatory approach. Data were collected among six Ugandan young co-researchers with different disabilities (physical, visual, hearing, and albinism), who interacted with two Ugandan research assistants and a Canadian researcher involved in a larger SRHR research project. They engaged in in-person and virtual WhatsApp and Microsoft Teams exchanges over weeks, with the support of three Ugandan Sign Language interpreters. We thematically analyzed data, informed by the Intersectionality-based Policy Analysis and Structural Health Vulnerabilities and Agency frameworks. Results: Our analysis revealed four main findings: (1) the persistent feeling of social discrimination, stigma, and exclusion, including from parents, (2) inaccessible SRHR information and services, and knowledge gaps, (3) gender- and disability-based violence, and (4) youth with disabilities’ aspirations for SRHR and in life. Conclusions: The voices of youth with disabilities in Gulu underscore the value of disability equity-focused research. They reminded us that they are intelligent, capable, and thoughtful citizens with agency whose SRHR and broader well-being must be acknowledged and respected. Their perspectives carry critical implications for SRHR programming, policy, and research.
Comparative metagenomic analysis of the vaginal microbiome in healthy women

The composition of these vaginal microbiome has a significant impact on women's health. However, few studies have characterized the vaginal microbiome of healthy Chinese women using metagenomic sequencing. Here, we carried out a comparative metagenomic analysis to survey taxonomic, functional levels, and microbial communities' genome content in healthy women's vaginal microbiome. Overall, we observed a total of 111 species, including all dominant vaginal Lactobacillus species, such as L. iners, L. crispatus, L. gasseri, and L. jensenii. Unlike microbial taxa, several pathways were ubiquitous and prevalent across individuals, including adenosine ribonucleotides de novo biosynthesis and pyruvate fermentation to acetate and lactate II. Notably, our diversity analysis confirmed a significant difference in healthy women from different ethnic groups. Moreover, we binned vaginal assemblies into 62 high-quality genomes, including 9 L. iners, 7 A. vaginae, 5 L. jensenii, and 5 L. crispatus. We identified the pan and core genomes of L. iners and A. vaginae and revealed the genetic diversity. Primary differences between strains were the hypothetical genes and mobile element-like genes. Our results provide a framework for understanding the implications of the female reproductive tract's composition and functional potential and highlight the importance of genome-resolved metagenomic analysis to further understand the human vaginal microbiome.
Ethics : The business case - corporate social responsibility meets electronics manufacturing

Le business case de l’approche éthique des affaires : quand la responsabilité sociale d’entreprise se confronte aux conditions de production de l’industrie électronique                 L'objectif de cette recherche est d'analyser pourquoi et comment les institutions qui composent le secteur de l'industrie électronique ont structurellement intégré une politique de responsabilité sociale des entreprises (RSE). Ensuite, d'examiner le rôle et les effets de cette évolution sur la mondialisation par le biais des chaînes d'approvisionnement internationales du secteur. Dans une première étape, via la théorie culturelle, et dans le contexte de la société du risque et de la modernité récente, la RSE se révèle une réponse institutionnelle défensive face aux risques de réputation et aux atteintes probables à la légitimité. Ensuite, la théorie culturelle nous permet d'analyser la RSE dans le secteur choisi en tant que processus socio-dynamique exerçant une pression sur les entreprises pour élargir leur culture organisationnelle tout en les orientant plus vers des valeurs égalitaires. Plusieurs effets sectoriels de ce processus sont analysés : le rôle de l'activité RSE dans les pratiques concurrentielles à travers l'isomorphisme, la façon dont les systèmes de classement éthique améliorent l'homogénéité de l'activité RSE, et l'impact de la réactivité des consommateurs en matière de RSE. Après avoir exploré l'intégration de la RSE dans une organisation, puis ses effets sur l'environnement sectoriel, on se focalise sur l'impact que la RSE peut avoir sur la mondialisation et le développement. Ainsi, le troisième volet de cette étude s’intéresse à l'impact que la RSE peut avoir en pénétrant les chaînes d'approvisionnement les plus intensément liées aux abus éthiques. Cela invite à réévaluer les processus de mondialisation, et leurs effets sur le développement. Grâce aux travaux d'Amartya Sen, Jean Tirole et d'autres, l'impact de la RSE sur les chaînes d'approvisionnement en électronique est évalué de manière critique en montrant comment une intervention structurelle dans les sociétés en développement pourrait être envisagée. Le travail de terrain pour cette enquête empirique a consisté en des visites d'usines en Chine et des entretiens avec la direction et les employés ; aussi, en des entretiens avec des cadres de multinationales, des contrôleurs et consultants en RSE et des militants d'associations syndicales internationales. Ce travail est complété par la participation à plusieurs réunions des parties prenantes du secteur et par l'analyse de documents produits par ces parties ; aussi, par de rapports, et des diverses formes de couverture médiatique, y compris de documentaires.
FinPT: Financial Risk Prediction with Profile Tuning on Pretrained Foundation Models

Financial risk prediction plays a crucial role in the financial sector. Machine learning methods have been widely applied for automatically detecting potential risks and thus saving the cost of labor. However, the development in this field is lagging behind in recent years by the following two facts: 1) the algorithms used are somewhat outdated, especially in the context of the fast advance of generative AI and large language models (LLMs); 2) the lack of a unified and open-sourced financial benchmark has impeded the related research for years. To tackle these issues, we propose FinPT and FinBench: the former is a novel approach for financial risk prediction that conduct Profile Tuning on large pretrained foundation models, and the latter is a set of high-quality datasets on financial risks such as default, fraud, and churn. In FinPT, we fill the financial tabular data into the pre-defined instruction template, obtain natural-language customer profiles by prompting LLMs, and fine-tune large foundation models with the profile text to make predictions. We demonstrate the effectiveness of the proposed FinPT by experimenting with a range of representative strong baselines on FinBench. The analytical studies further deepen the understanding of LLMs for financial risk prediction.
Movie Recommendation System Based on Collaborative Filtering

With the explosively growing of the technologies and services of the Internet, the information data world increases rapidly. Recommendation systems have acted an important role in many ways, including movies, books, friends, shopping on net and music. Especially like today, people are surrounded by mass of information. People try to find their preferred movies. It has become difficult when facing so many kinds of movies. People may dizzied by plenty of items on the net, they don't know how to make a choices. In order to find their preferred movies, they need to spend lots of time on seeking. To help people find their preferred movies quickly, a good personalized recommendation system would be useful for users to choose their preferences. Recommendation technology is one of important applications of Information Filtering, which has been applied broadly in E-commerce. Collaborative filtering is the core technology of personality recommendation, and it is the most widely used and successful technology in recommendation system.In this article, we mainly care about the research on characteristic recommendation system. We elaborate and discuss its content, structure, information and recommend technology, and the challenge. In this paper, we did detailed analyses on collaborative filtering technology and also some relative algorithms. Then we made some comparisons with traditional method. At last, we generated a module of recommendation system which contains three important points for people: generate users’ preference to do recommendation; use the movies own tags to cluster movies; and calculate the similarity between movies and users. People could obtain the users’ description from SNS (twitter). These methods have helped people to choose the movies compared with the traditional way.
Optimization of Manifold Learning Using Differential Geometry for 3D Reconstruction in Computer Vision

Manifold learning is a significant computer vision task used to describe high-dimensional visual data in lower-dimensional manifolds without sacrificing the intrinsic structural properties required for 3D reconstruction. Isomap, Locally Linear Embedding (LLE), Laplacian Eigenmaps, and t-SNE are helpful in data topology preservation but are typically indifferent to the intrinsic differential geometric characteristics of the manifolds, thus leading to deformation of spatial relations and reconstruction accuracy loss. This research proposes an Optimization of Manifold Learning using Differential Geometry Framework (OML-DGF) to overcome the drawbacks of current manifold learning techniques in 3D reconstruction. The framework employs intrinsic geometric properties—like curvature preservation, geodesic coherence, and local–global structure correspondence—to produce structurally correct and topologically consistent low-dimensional embeddings. The model utilizes a Riemannian metric-based neighborhood graph, approximations of geodesic distances with shortest path algorithms, and curvature-sensitive embedding from second-order derivatives in local tangent spaces. A curvature-regularized objective function is derived to steer the embedding toward facilitating improved geometric coherence. Principal Component Analysis (PCA) reduces initial dimensionality and modifies LLE with curvature weighting. Experiments on the ModelNet40 dataset show an impressive improvement in reconstruction quality, with accuracy gains of up to 17% and better structure preservation than traditional methods. These findings confirm the advantage of employing intrinsic geometry as an embedding to improve the accuracy of 3D reconstruction. The suggested approach is computationally light and scalable and can be utilized in real-time contexts such as robotic navigation, medical image diagnosis, digital heritage reconstruction, and augmented/virtual reality systems in which strong 3D modeling is a critical need.
Implementation and protection of the rights of the Roma national minority in Ukraine

The purpose of the article is to study the current state of implementation and legal protection of the rights of the Roma ethnic minority in Ukraine.  It is noted that the Roma lag far behind the main part of the population in terms of education, employment, housing and health care, and are almost completely unrepresented in political institutions. In this regard, a large number of Roma have limited opportunities to improve their quality of life and integrate with the majority of Ukrainian society.  It was concluded that the causes of prejudice against Roma and existing restrictions on the realization of their civil rights include: segregation, traditional features of the internal social structure of Roma communities, and the lack of constructive dialogue between Roma communities, local communities, local authorities, and state authorities. An important role in solving these problems belongs to the international foundation «Renaissance», which is one of the largest Ukrainian charitable foundations and non-governmental organization.  In order to create conditions for the realization and protection of Roma rights in Ukraine in various spheres of public life, the Council of Europe project «Strengthening the protection of national minorities, including Roma, and minority languages in Ukraine» was launched in 2018, based on the recommendations of two monitoring bodies of the Framework Convention Council of Europe on the Protection of National Minorities and the European Charter of Regional or Minority Languages.  The results of sociological research on the current problems of legal protection of the rights of the Roma population are presented.  It is emphasized that the State Service of Ukraine for Ethnopolitics and Freedom of Conscience and the Secretariat of the Commissioner of the Verkhovna Rada of Ukraine for Human Rights deal with the issues of implementation and protection of Roma rights.  It is concluded that the main directions for improving the legal protection of the rights of the Roma population are: carrying out educational work; provision of free legal aid to Roma; strengthening the legal opportunities of Roma; development of bodies of self-organization of the Roma population; establishment of communication between Roma and residents of cities and towns; integration of Roma into Ukrainian society.
Mental health literacy and suicidal ideation among Chinese college students: The mediating role of depressive symptoms and anxiety symptoms

Mental health literacy (MHL) is essential to mental health. Symptoms of depression and anxiety are significant antecedents and closely related to suicide among college students. Few studies have explored the mediating role of depressive and anxiety symptoms between MHL and suicidal ideation.5578 college students were included in the analysis. The online Wenjuanxing platform was used to collect data from November 2020 to March 2021. The bootstrapping method was used to test the mediating role of depressive and anxiety symptoms in the links between MHL and suicidal ideation.Approximately 18.8 % of Chinese college students in our study reported having suicidal ideation. MHL exhibited a significant and negative correlation with depressive symptoms, anxiety symptoms, and suicidal ideation, whereas depressive and anxiety symptoms correlated significantly and positively with suicidal ideation. Compared with the lowest MHL quartile, the 3rd and 4th quartiles of MHL were associated with a significantly lower risk of suicidal ideation after adjusting for various confounding factors. Depressive and anxiety symptoms partially mediated the relationship between MHL and suicidal ideation, and the mediating effect of depressive symptoms was significantly greater than that of anxiety symptoms.This study was a cross-sectional survey. Future longitudinal studies on this relation are needed.Depressive and anxiety symptoms mediate the relationship between MHL and suicidal ideation. Comprehensive school-based specific psychological education programs are needed to improve college students' MHL and change their attitudes toward mental health services.
Corporate Social Responsibility in Malaysian Apparel Manufacturing Industry: A Study on Corporate Social Responsibility Website Reporting

ABSTRACT:A well planned and implemented Corporate Social Responsibility (CSR) programs could give any company a competitive advantage over its competitors. However, the way it is communicated to its stakeholders will be one of the deciding factors. This study examines how the WRAP certified apparel manufacturers in Malaysia communicate their CSR programs on their company website. This study identifies the dimensions of CSR they focus while they communicate their CSR initiatives to their stakeholders and how companies use their company website to communicate their CSR related activities. The study employed the content analysis technique and descriptive statistics using percentages to analyse the company websites. The companies CSR activities were divided into 5 dimensions namely employee relations, product quality, community relations, environmental issues and diversity issues. Findings suggest that the Malaysian apparel companies understand the importance of CSR and consider it as one of the factors which can give the companies an edge over their competitors. However the companies can still improve in their communication by using more pictures and giving some specifics about the product quality and diversity dimension. Furthermore, the remaining 40% of the companies have to understand the importance of CSR and communicate their CSR related activities on their company website.
On Cooperative Patrolling: Optimal Trajectories, Complexity Analysis, and Approximation Algorithms

The subject of this work is the patrolling of an environment with the aid of a team of autonomous agents. We consider both the design of open-loop trajectories with optimal properties, and of distributed control laws converging to optimal trajectories. As performance criteria, the refresh time and the latency are considered, i.e., respectively, time gap between any two visits of the same region, and the time necessary to inform every agent about an event occurred in the environment. We associate a graph with the environment, and we study separately the case of a chain, tree, and cyclic graph. For the case of chain graph, we first describe a minimum refresh time and latency team trajectory, and we propose a polynomial time algorithm for its computation. Then, we describe a distributed procedure that steers the robots toward an optimal trajectory. For the case of tree graph, a polynomial time algorithm is developed for the minimum refresh time problem, under the technical assumption of a constant number of robots involved in the patrolling task. Finally, we show that the design of a minimum refresh time trajectory for a cyclic graph is NP-hard, and we develop a constant factor approximation algorithm.
Audio-visual speech modeling for continuous speech recognition

This paper describes a speech recognition system that uses both acoustic and visual speech information to improve recognition performance in noisy environments. The system consists of three components: a visual module; an acoustic module; and a sensor fusion module. The visual module locates and tracks the lip movements of a given speaker and extracts relevant speech features. This task is performed with an appearance-based lip model that is learned from example images. Visual speech features are represented by contour information of the lips and grey-level information of the mouth area. The acoustic module extracts noise-robust features from the audio signal. Finally the sensor fusion module is responsible for the joint temporal modeling of the acoustic and visual feature streams and is realized using multistream hidden Markov models (HMMs). The multistream method allows the definition of different temporal topologies and levels of stream integration and hence enables the modeling of temporal dependencies more accurately than traditional approaches. We present two different methods to learn the asynchrony between the two modalities and how to incorporate them in the multistream models. The superior performance for the proposed system is demonstrated on a large multispeaker database of continuously spoken digits. On a recognition task at 15 dB acoustic signal-to-noise ratio (SNR), acoustic perceptual linear prediction (PLP) features lead to 56% error rate, noise robust RASTA-PLP (relative spectra) acoustic features to 7.2% error rate and combined noise robust acoustic features and visual features to 2.5% error rate.
Evolution-Guided Policy Gradient in Reinforcement Learning

Deep Reinforcement Learning (DRL) algorithms have been successfully applied to a range of challenging control tasks. However, these methods typically suffer from three core difficulties: temporal credit assignment with sparse rewards, lack of effective exploration, and brittle convergence properties that are extremely sensitive to hyperparameters. Collectively, these challenges severely limit the applicability of these approaches to real-world problems. Evolutionary Algorithms (EAs), a class of black box optimization techniques inspired by natural evolution, are well suited to address each of these three challenges. However, EAs typically suffer from high sample complexity and struggle to solve problems that require optimization of a large number of parameters. In this paper, we introduce Evolutionary Reinforcement Learning (ERL), a hybrid algorithm that leverages the population of an EA to provide diversified data to train an RL agent, and reinserts the RL agent into the EA population periodically to inject gradient information into the EA. ERL inherits EA's ability of temporal credit assignment with a fitness metric, effective exploration with a diverse set of policies, and stability of a population-based approach and complements it with off-policy DRL's ability to leverage gradients for higher sample efficiency and faster learning. Experiments in a range of challenging continuous control benchmarks demonstrate that ERL significantly outperforms prior DRL and EA methods.
ADDITIVE MANUFACTURING (3D PRINTING) APPLICATIONS IN AUTOMOTIVE SECTOR

DergiPark: 498000
Integrating pesticides with biotic and biological control for arthropod pest management

Insecticides and acaricides are used commonly for pest suppression in agriculture, forestry and public health. The National Research Council (2000) and others have documented their value in protecting crops, livestock and humans from injury by insects and other arthropods. However, adverse effects of pesticide use can include the killing of non-target organisms, contamination of water supplies and persistence of unwanted residues on foods and animal feed. The chronic health effects of even extremely low concentrations of pesticides in food and water remain under debate today just as they were when the National Research Council (1993) reported on pesticides in children's diets in the early 1990s. Resistance to one or more pesticides has evolved in populations of over 500 insect and mite species (Clark & Yamaguchi, 2002), rendering many of those pesticides ineffective against the resistant populations. For these and other reasons, supplementing or replacing pesticides with non-chemical control tactics, including biological control, is a goal in many crop and livestock production systems.  As biological control programs that rely on parasites, predators and pathogens are developed, they rarely are so robust as to provide all the pest suppression needed in an entire cropping system for the lifespan of the crop. Even if such robust biological control is attainable over time in specific crops or situations, initial efforts that target only one or a few pests often leave a need for pesticides to manage other species if their populations exceed economic thresholds.