ethicalabs/Research-Intent-Collab huggingface dataset:
Speech acoustics, phonetics, and phonology unified by an optimal dynamic model of sound communication

A book by us (Speech: A dynamic Process, de Gruyter, 2017) presents an optimal communication model for the production of sounds through dynamic deformation of a simple tube using the criterion that a maximum contrast between consecutive sounds must be achieved by expending a minimum effort. Its output corresponds well to fundamental articulatory speech data (places of articulation, F1-F2-F3 trajectories). When driven by a periodic source, the model generates natural-sounding vowels and, through constricting the tube at distinctive regions, also stop consonants. From this model’s viewpoint, phonetic systems of vowels and consonants arise as the direct consequence of production dynamics capable of producing essentially any vowel or stop consonant. The good correspondence between characteristics of the model and those of speech leads us to conclude that (1) the model is explanatory, (2) because it is acoustically optimal so must be speech production, and (3) an acoustically anchored phonology will derive from it. Based on acoustics, the model thus identifies a natural link between phonetics, and phonology. Propositions of our approach have also been tested in perceptual studies.
Modeling Merging Galaxies using MINGA - Improving Restricted N-body by Dynamical Friction

Modeling interacting galaxies to reproduce observed systems is still a challenge due to the extended parameter space (among other problems). Orbit and basic galaxy parameters can be tackled by fast simulation techniques like the restricted N-body method, applied in the fundamental work by Toomre & Toomre (1972). This approach allows today for the study of millions of models in a short time. One difficulty for the classical restricted N-body method is the missing orbital decay, not allowing for galaxy mergers. Here we present an extension of the restricted N-body method including dynamical friction. This treatment has been developed by a quantitative comparison with a set of self-consistent merger simulations. By varying the dynamical friction (formalism, strength and direction), we selected the best-fitting parameters for a set of more than 250000 simulations. We show that our treatment reliably reproduces the orbital decay and tidal features of merging disk galaxies for mass ratios up to q=1/3 between host and satellite. We implemented this technique into our genetic algorithm based modeling code MINGA and present first results.
Adolescent Sexual and Reproductive Health and Rights in Urban Slums, Bangladesh: A Structural Analysis of Demographic and Health Surveys Between 2014 and 2022

&lt;p&gt;&lt;span&gt;Adolescent sexual and reproductive health and rights (ASRHR) constitute global health priorities, yet adolescents living in structurally vulnerable contexts—like urban slums—experience a disproportionate burden of adverse outcomes. In Dhaka (Bangladesh), 40% of the 23 million population live in 5,000 slums. While the country is experiencing high rates of child marriages and teen pregnancies and low contraception use, ASRHR challenges remain insufficiently documented in urban slums. To better inform interventions, it is essential to explore societal structures (cultural, social, economic, political) shaping complex ASRHR outcomes. To identify societal structures associated with child marriage, teen pregnancy and contraception use, Bangladesh Demographic and Health surveys (2014-2018-2022) were analyzed using Poisson regression, reporting adjusted prevalence ratios with 95% confidence intervals (APRs (95%CI)). Over the three surveys, there were 15,502 girl participants aged 15-24, with a fair distribution across wealth index quintiles and Bangladesh regions. Child marriage varied from 70.4% (2014) to 62.3% (2022) at the national level but remained stable in slums (73.4%-74.3%). For child marriage, girls’ higher education was protective at the national level (2014: 0.80 (0.76-0.84), 2018: 0.83 (0.80-0.97), 2022: 0.79 (0.75-0.83)) and in slums (2014: 0.65 (0.54-0.80), 2018: 0.78 (0.70-0.87)). As a societal structure, child marriage was associated with increased risks of teen pregnancy for all years at the national level and in slums, with the highest APRs in 2022 (1.45 (1.42-1.48) and 1.57 (1.44-1.71) respectively). Lower contraception use was associated with having a woman as the head of the household at the national level (0.84 (0.81-0.88) in 2014, 0.93 (0.83-1.04) in 2018, 0.86 (0.83-0.89) in 2022) and in slums (0.86 (0.78-0.96) in 2014, 0.92 (0.89-0.95) in 2018, 0.89 (0.79-1.00) in 2022). Our findings suggest complex interconnection between ASRHR outcomes and a large influence of social and cultural structures, like family dynamics, gender norms, and community norms.&lt;/span&gt;&lt;/p&gt;
The synchrotron foreground and the cosmic microwave background temperature-polarization cross-correlation power spectrum from the first-year <i>WMAP</i> data

Abstract                We analyse the temperature–polarization cross-correlation in the Galactic synchrotron template that we have recently developed, and between the template and cosmic microwave background (CMB) temperature maps derived from WMAP data. Since the polarized synchrotron template itself uses WMAP data, we can estimate residual synchrotron contamination in the CMB CTEℓ angular spectrum. While CTE2 appears to be contaminated by synchrotron, no evidence for contamination is found in the multipole range which is most relevant for the fit of the cosmological optical depth.
VARCO-VISION: Expanding Frontiers in Korean Vision-Language Models

In this paper, we introduce an open-source Korean-English vision-language model (VLM), VARCO-VISION. We incorporate a step-by-step training strategy that allows a model learn both linguistic and visual information while preserving the backbone model's knowledge. Our model demonstrates outstanding performance in diverse settings requiring bilingual image-text understanding and generation abilities compared to models of similar size. VARCO-VISION is also capable of grounding, referring, and OCR, expanding its usage and potential applications for real-world scenarios. In addition to the model, we release five Korean evaluation datasets, including four closed-set and one openset benchmarks. We anticipate that our milestone will broaden the opportunities for AI researchers aiming to train VLMs. VARCO-VISION is available at https://huggingface.co/NCSOFT/VARCO-VISION-14B.
The ICTY's Conditionality Dilemma - On the Interaction of Influences of the European Union's Conditionality Policy and the International Criminal Tribunal for the Former Yugoslavia on the Development of Rule of Law in Serbia

The European Union has made cooperation with the International Criminal Tribunal for the former Yugoslavia a crucial condition to furthering relations with Serbia. This approach, known as "icty conditionality", stems from the conviction that the Tribunal is a key factor in rebuilding the rule of law in the Western Balkans. In contrast to the existing literature on eu conditionality in general or on icty conditionality in specific, this article emphasizes the relevance of all involved actors: it examines the interaction of icty conditionality, domestic factors and the icty’s judicial performance influencing the development of the rule of law in Serbia. The article concludes that the goal of using the icty as a tool to establish the rule of law in Serbia has failed due to a lack of norm diffusion, although all icty conditionality requirements have eventually formally been fulfilled. This was not only due to inconsistent application of icty conditionality on the eu’s side, but also on account of deficiencies in the legal operation of the Tribunal. Lastly, neither the eu’s demands nor the icty’s work fell on fruitful domestic grounds.
Bill tightens law against genetic discrimination by health insurers

washington A new Republican backed bill will prohibit health insurers from using genetic information to set premium costs, or deny insurance policies to people who have not been previously or recently insured.
Digital biomarkers and digital phenotyping in mental health care and prevention

Abstract                Biomarkers are physiologic or pathologic characteristics that can be objectively measured and evaluated as indicators of biologic processes, or biological responses to therapeutic interventions. Traditionally, psychiatry has suffered from a relative paucity of these, with no lab tests or medical devices available for the diagnosis or monitoring of mental health disorders. The widespread adoption of personal digital devices including smartphones and wearables allow to retrieve, record and store large amounts of user-generated data that have been hypothesized to play as “digital biomarkers” - intended as a new type of medical information that can produce actionable insights into the biological state of individuals, just as “normal” biomarkers, but collected through digital tools.                As well described by Onnela in 2015, digital biomarkers can define a digital phenotyping characterized by a “moment-by-moment quantification of the individual-level human phenotype in situ using data from personal digital devices,” in particular smartphones and mobile devices. Simpler said, digital biomarkers, can provide a comprehensive representation of people and patients' functioning. Their use in health research, prevention and practice is particularly relevant in the field of mental health being mental disorders highly heterogeneous in nature and over time. In the next years these novel ways of measuring mental health status will provide observations and perspectives into disease that were unavailable before and which will fruitfully inform personalized prevention and care. The presentation will introduce the concept of digital biomarkers and digital phenotyping, it will provide the state of the art on their identification and use in the field of mental health and will discuss the way forward to ensure their potential is exploited through effective collaboration between clinicians, public health researchers and the tech world in a joint effort to promote population well-being.
Aligning Human Resource Information Systems (HRIS) with the Imperatives of Society 5.0: A Strategic Framework for Digital Talent Management in the Indonesian Banking Sector

The rapid acceleration of digital transformation, spurred by the global pandemic and new economic demands, has placed the Indonesian banking sector at a critical juncture. Amidst this disruption, the Society 5.0 paradigm has emerged as a human-centric vision, proposing a deep integration of technology and society to enhance the quality of life. However, the success of this transformation hinges on its most vital asset: digital talent. A significant gap currently exists between the strategic capabilities of modern Human Resource Information Systems (HRIS) and the imperative to effectively manage digital talent in alignment with Society 5.0. This research aims to bridge this gap by developing a comprehensive conceptual framework, titled "Strategic Talent Alignment for a Resilient Human-centric Information System" (STAR-HRIS). Employing a systematic literature review, this study synthesizes findings from diverse sources, including academic journals, industry reports, and policy documents from regulatory bodies such as the Indonesian Financial Services Authority (OJK). The results present the STAR-HRIS framework, which is composed of three layers: (1) The Foundation of Governance &amp; Digital Infrastructure, encompassing the technology stack, data governance, and digital ethics; (2) The Pillars of Intelligent Talent Management, which include intelligent talent acquisition, adaptive talent development, and dynamic, AI-powered engagement and retention; and (3) The Organizational Enablers, which highlight the crucial roles of digital leadership, an innovative culture, and change management. The discussion interprets how the STAR-HRIS framework can serve as a roadmap for banking leaders and HR practitioners in Indonesia to evolve their HRIS from an administrative system into a dynamic talent ecosystem. This framework not only offers a practical solution to the digital talent gap but also emphasizes the importance of ethical considerations in AI implementation, consistent with the human-centric philosophy of Society 5.0. This research contributes an actionable strategic model for aligning technology, people, and strategy to navigate the future of the banking sector.
Monitoring Disability Policies and Legislation towards Effective Exercise of Rights to Equality and Inclusive Access for Persons with Disabilities: The Case of the Quebec Model

Quebec’s government established a mechanism to monitor its progress towards achieving the right to equality for people with disabilities. With the goal of strengthening the accountability of public actors, this mechanism is based on legal provisions and inclusive political guidelines. In 2009, the provincial government adopted a policy entitled “Equals in Every Respect: Because Rights Are Meant to Be Exercised” along with other legal dispositions aimed at significantly increasing the social participation of people with disabilities. The Disability Creation Process, a conceptual reference model also known as the Quebec Model, proposes that public actors should be able to identify and act upon environmental obstacles within their respective competences to transform them into facilitators. The challenge facing inclusive policy-monitoring mechanisms is to acquire quantitative and qualitative information-collecting tools and strategies that link the quality of access of the components of the physical and social environment to the quality of the social participation for the various segments of the population with or without disabilities.
Adaptive AI Tutoring in Education: Leveraging Large Language Models and Reinforcement Learning to Transform Personalized Learning at Scale

Educational institutions face mounting pressure to deliver personalized learning experiences that sustain student engagement while accommodating diverse learning speeds and backgrounds. While generative AI chatbots have attracted considerable attention as tutoring tools, emerging evidence suggests that reactive question-answering alone may be insufficient to optimize learning outcomes. This article examines how tightly integrating large language model (LLM)-guided reinforcement learning with AI tutoring platforms can substantially improve educational outcomes. Drawing on a five-month randomized controlled trial involving 770 high school students across ten schools in Taipei, we demonstrate that adaptive problem sequencing—informed by rich behavioral signals from student-chatbot interactions and code-editing patterns—increased final exam performance by 0.15 standard deviations compared to fixed sequencing. Mediation analysis revealed that these gains operated primarily through sustained student engagement rather than increased practice volume or uniformly harder content. The findings suggest that organizations implementing AI-assisted learning systems should prioritize proactive guidance mechanisms alongside conversational interfaces, with particular attention to extracting actionable intelligence from learner-system interactions. This evidence-based approach offers a scalable framework for workforce development, digital literacy initiatives, and educational equity efforts.
53 GENETIC DISCRIMINATION BY INSURERS AS A RESULT OF GENETIC RESEARCH AND TESTING: A COMPARISON OF NATIONAL POLICIES

Purpose  Fear of discrimination by health and life insurers has been shown to deter individuals from participating in genetic research and testing. We aimed to construct a comparison of genetic discrimination policies in Canada, Australia, the United Kingdom, and the United States providing useful lessons regarding the management of genetic discrimination public policy.  Methods  MEDLINE and the HumGen database were searched for items related to genetic discrimination and health and/or life insurance.  Results  The Canadian, Australian, and UK health systems cover all citizens regardless of disease risk. However, life insurance applicants are not protected. In 2004, the Canadian Genetics and Life Insurance Task Force released a “Points to Consider Document” highlighting the importance of having a Canadian debate on the necessity of adopting a moratorium on the use of genetic test results for life insurance. In 2003, the Australian Law Reform Commission and the Australian Health Ethics Committee of the National Health and Medical Research Council recommended the adoption of a system consisting of a regulatory review aimed at ensuring that genetic information would be used in a scientifically reliable and actuarially sound manner. The Association of British Insurers9 Code of Practice, in 1999, mandated a “5-year moratorium on the use of genetic test results by insurers” up to a certain policy amount on life, long-term care and disability insurance. In 2001, the moratorium was strengthened and extended for an additional 5 years. As of 2004, 48 states and the District of Columbia had passed some form of legislation prohibiting genetic discrimination in health insurance decisions. At the federal level, The Genetic Information Non-discrimination Act (S. 1053) prohibits discrimination on the basis of genetic information regarding health insurance. It is now in the House of Representatives, where its outcome is uncertain.  Conclusions  The public9s concern about their own insurability necessitates action to ensure the successful conduct of future genetic epidemiological studies and testing. We argue that the adoption of a voluntary moratorium on genetic test results by the insurance industry appears to be the best option to answer both public anxiety and to provide a minimal amount of protection to insurance applicants.
A survey on security and privacy of federated learning

Abstract   Federated learning (FL) is a new breed of Artificial Intelligence (AI) that builds upon decentralized data and training that brings learning to the edge or directly on-device. FL is a new research area often referred to as a new dawn in AI, is in its infancy, and has not yet gained much trust in the community, mainly because of its (unknown) security and privacy implications. To advance the state of the research in this area and to realize extensive utilization of the FL approach and its mass adoption, its security and privacy concerns must be first identified, evaluated, and documented. FL is preferred in use-cases where security and privacy are the key concerns and having a clear view and understanding of risk factors enable an implementer/adopter of FL to successfully build a secure environment and gives researchers a clear vision on possible research areas. This paper aims to provide a comprehensive study concerning FL’s security and privacy aspects that can help bridge the gap between the current state of federated AI and a future in which mass adoption is possible. We present an illustrative description of approaches and various implementation styles with an examination of the current challenges in FL and establish a detailed review of security and privacy concerns that need to be considered in a thorough and clear context. Findings from our study suggest that overall there are fewer privacy-specific threats associated with FL compared to security threats. The most specific security threats currently are communication bottlenecks, poisoning, and backdoor attacks while inference-based attacks are the most critical to the privacy of FL. We conclude the paper with much needed future research directions to make FL adaptable in realistic scenarios.
Exploring the use of serverless functions for compute-intensive efforts

In der heutigen Softwareentwicklung hat sich Cloud Computing als dominierende Lösung für das Hosting von Anwendungen etabliert, die wachsenden Anforderungen an Skalierbarkeit, Datenspeicherung und Sicherheit gerecht werden müssen. Diese Arbeit untersucht serverloses Computing, ein schnell wachsendes Cloud-Service-Modell, das Anwendungen ermöglicht, mühelos zu skalieren, wobei das Infrastrukturmanagement vollständig von Cloud-Anbietern übernommen wird. Serverloses Computing, auch als Function as a Service (FaaS) bekannt, ist insbesondere für ereignisgesteuerte Anwendungen und kurzlebige Aufgaben vorteilhaft und bietet Vorteile wie einfache Bereitstellung, automatische Skalierung und Abrechnung auf Basis der Ressourcennutzung. Diese Arbeit stellt flexi--serverless vor, eine C++-Bibliothek, die eine nahtlose Funktionsaufrufmöglichkeit sowohl auf serverlosen Plattformen als auch in lokalen Umgebungen bietet. Das Framework unterstützt Cloud-Anbieter wie AWS Lambda und Google Cloud Functions und ermöglicht Entwicklern, Anwendungen in beiden Umgebungen zu testen und zu evaluieren, insbesondere bei rechenintensiven und parallelen Aufgaben. Anhand von drei Anwendungsszenarien zeigt die Bibliothek ihren Nutzen bei der Vereinfachung von Übergängen zwischen lokalem und serverlosem Computing, wodurch serverlose Lösungen zugänglicher und effizienter werden. Zudem bietet die Arbeit eine vergleichende Analyse von serverlosen und traditionellen Rechenmodellen und hebt dabei Faktoren wie Kosten, Leistung und Skalierbarkeit hervor. Dieses Forschungsvorhaben trägt zur Optimierung von Cloud-Computing-Strategien bei, indem es Herausforderungen bei der Einführung serverloser Architekturen adressiert und Entwicklern ein vielseitiges Werkzeug zur Verfügung stellt.
Three Tools for Practical Differential Privacy

Differentially private learning on real-world data poses challenges for standard machine learning practice: privacy guarantees are difficult to interpret, hyperparameter tuning on private data reduces the privacy budget, and ad-hoc privacy attacks are often required to test model privacy. We introduce three tools to make differentially private machine learning more practical: (1) simple sanity checks which can be carried out in a centralized manner before training, (2) an adaptive clipping bound to reduce the effective number of tuneable privacy parameters, and (3) we show that large-batch training improves model performance.
Nuclear interactions of low-energy cosmic rays with the interstellar medium

Cosmic rays of kinetic energies below ~1 GeV per nucleon are thought to play a key role in the chemistry and dynamics of the interstellar medium. They are also thought to be responsible for nucleosynthesis of the light elements Li, Be, and B. However, very little is known about the flux and composition of low-energy cosmic rays since the solar modulation effect makes impossible a direct detection of these particles near Earth. We first discuss the information that the light elements have brought to cosmic-ray studies. We then discuss the prospects for detection of nuclear gamma-ray line emission produced by interaction of low-energy cosmic rays with interstellar nuclei.
An Adapted Similarity Kernel and Generalized Convex Hull for Molecular Crystal Structure Prediction

We adapted an existing approach to identifying stabilizable crystal structures from prediction setsthe Generalized Convex Hull (GCH)to improve its application to molecular crystal structures. This was achieved by modifying the Smooth Overlap of Atomic Positions (SOAP) kernel to define the similarity of molecular crystal structures in a more physically motivated way. The use of the adapted similarity kernel was assessed for several organic molecular crystal landscapes, demonstrating improved interpretability of the resulting machine-learned descriptors. We also demonstrate that the adapted kernel results in improved performance in predicting lattice energies using Gaussian process regression. Our overall findings highlight a sensitivity of similarity kernel-based landscape analysis methods to kernel construction, which should be considered when applying these methods.