ethicalabs/Research-Intent-Collab huggingface dataset:
Reforming the United Nations Security Council: Making it more Democratic in the Post-Westphalian Legal Order

The Security Council has sometimes failed to perform its main duty, which is the maintenance of international peace and security. The Council’s responsibilities in this regard have grown as new international challenges have emerged. These challenges include global environmental issues, refugee flows and mass migration across borders, the rapid spread of infectious diseases, civil war that threatens international peace and security, global terrorism, transnational crime and illegal stocks of nuclear, biological and chemical weapons. The Security Council has thus become the subject of both severe criticism and calls for its structural reform. A variety of reform proposals have been offered by scholars and politicians, almost all of which have focused solely on state-based solutions. The current study considers that reforming the Council through such means would not alter its current state to any significant extent. International law no longer reflects the state-based system of the Westphalian World Order. The international legal order does not involve only nationstates, and state-based systems are not able autonomously to deal with problems such as these in the post-Westphalian era. It is widely acknowledged that there are many non-state actors that could contribute to enhancing the Council’s representativeness, effectiveness and accountability. It is thus concluded that a reform proposal for the Security Council must consider these factors and produce a non-state based solution. It is proposed that the Council must consider granting formal access to Non-Governmental Organizations (NGOs) that have, as non-state actors, been active in the international legal order, and that have already made significant contributions to the above-mentioned issues.
Quantum Error Correction in Quaternionic Hilbert Spaces

We propose quaternion-based strategies for quantum error correction by extending quantum mechanics into quaternionic Hilbert spaces. Building on the properties of quaternionic quantum states, we define quaternionic analogues of Pauli operators and quantum gates, ensuring inner product preservation and Hilbert space conditions. A simple encoding scheme maps logical qubits into quaternionic systems, introducing natural redundancy and enhanced resilience against noise. We construct a quaternionic extension of the five-qubit code, introducing a framework of 15 syndrome measurements to detect quaternionic errors, including quaternionically rotated error components. Numerical estimates show that the quaternionic five-qubit code achieves a logical error threshold of approximately $p_{th} \approx 0.015$, demonstrating improved performance compared to the standard complex-valued code. These results suggest a new pathway for quantum error correction in high-noise environments, leveraging the richer structure of quaternionic quantum mechanics to improve fault tolerance.
Contrasting continuous quality improvement, Six Sigma, and lean management for enhanced outcomes in US hospitals

PurposeRapidly rising healthcare costs, partially due to preventable medical errors, have led hospitals to redouble their process improvement (PI) efforts. The purpose of this paper is to examine how PI initiatives mediate the effect of medical error sources to enhance three hospital outcomes (patient safety, operational effectiveness, and competitiveness).Design/methodology/approachDrawing from Dynamic Capabilities Theory, the authors develop a framework to explore three PI initiatives: Continuous Quality Improvement (CQI), Six Sigma Initiatives (SSI), and Lean Management Initiatives (LMI). Hierarchical regression analysis is employed to test the proposed model, using data from a nationwide survey of 210 US hospitals.FindingsFor enhancing patient safety outcomes, it was found that CQI and LMI were significant in mediating hospital error sources; however, SSI was not significant after accounting for the other two PI types. For improving organizational effectiveness, CQI and SSI were significant; whereas LMI was not significant over and above the other two PI types. Finally, only SSI was significant for superior sustainable competitive advantage.Research limitations/implicationsThe paper provides insight into which PI initiatives were most effective for various hospital outcomes. The findings can benefit healthcare practitioners as they select among different PI programs for enhancing healthcare results. Limitations of the study include the use of perceptual measures, relatively small sample size, and potential alternate relationships relevant to the outcome variables.Originality/valueThis is the first study to explore the mediating effects of three PI programs for the impact of medical errors on each of three hospital outcomes.
Impact of Adolescent Social Media Use on Body Image, Mental Health and Eating Disorders: A Review

Adolescents are considered vulnerable to negative influences on social media because their use of the medium expands at a time when they are in a transition period in their lives dealing with many other issues such as puberty, exam stress and anxiety about their future. This review focuses on primary research articles exploring the impact of social media on adolescents’ mental health, body image and eating disorder related issues. This review also includes articles regarding how social media can be used to deliver positive messages, recruit vulnerable subjects for early intervention and explore the effectiveness of new treatment strategies. Based on the reviewed articles, it seems  that girls, boys and transgender persons are similarly at-risk from negative social media influence. Going ahead, there is a need to focus on the nature of social media activity rather than just  time spent to identify vulnerable young persons. It is possible that in some cases social media usage can drive a vicious cycle that amplifies negative psychological attitudes  initiated due to social and personal context. Further research is required to explore the role parents and social media platforms can play in maintaining positive attitudes and effecting early intervention programs.
Movie Recommendation Systems Based on Collaborative Filtering: A Case Study on Netflix

Filmler, şarkılar ve alışveriş ürünleri gibi ögelerin kullanıcı değerlendirmeleri Öneri Sistemleri (ÖS) tarafından henüz değerlendirilmemiş ürünleri tahmin etmek için kullanılır. ÖS kullanıcılara çeşitli alanlarda öneri vermek için geliştirilmiştir ve ÖS uygulama alanlarından birisi de film önerisidir. Bu alanda üç genel algoritma kullanılmaktadır; kullanıcılar arası benzerliğe dayanarak tavsiye veren İşbirlikçi Filtreleme, kullanıcı-eşya eşleştirilmesindeki ilişkiden beslenen İçerik Tabanlı Filtreleme ve bu iki algoritmayı birleştiren Hibrit Filtreleme. Bu çalışmamızda İşbirlikçi Filtreleme çerçevesinde hangi metotların daha etkili çalıştığı incelenmiştir. Analizimizde Netflix Ödül veri seti kullanılmış ve iyi bilinen İşbirlikçi Filtreleme metotları olan Tekil Değer Ayrışımı, Tekil Değer Ayrışımı++, K En Yakın Komşu ve Eş Kümeleme kıyaslanmıştır. Her metodun hatası Ortalama Hata Kare Kökü kullanılarak ölçülmüştür. Son olarak, K En Yakın Komşu metodunun veri setimizde daha başarılı olduğu sonuçlanmıştır.
Accessing sexual and reproductive health services during climate change-related environmental disruptions in coastal Ghana: a privilege or human right for young women with disabilities?

Introduction                     Climate change is increasingly recognized as a threat to global health, yet its influence on the Sexual, reproductive health and rights (SRHR) of young women with disabilities (WwD) remains poorly documented in Ghana. Human rights advocates contend that categorizing SRHR services for WwD as privileges diminishes essential entitlements and promotes inequality.                                                           Methods                     In this study we examined the lived experiences of WwD in accessing SRHR services during climate change-related environmental disruptions in a coastal Ghanaian community to inform policy. A qualitative exploratory design was used. Semi-structured interviews were conducted between March and May 2025 with ten young WwD who accessed SRH services in the community. Interviews were conducted in English or a local language, audio recorded, transcribed, and analyzed using Framework Analysis. The analytic process was guided by the study objectives and informed by the behavioral assumptions of the Theory of Reasoned Action and the Theory of Planned Behavior.                                                           Results                     Climate change-related flooding and erosion, along with inadequate sanitation facilities, negatively impact the SRHR of young WwD by restricting access to services, hindering mobility and communication, and increasing risks related to menstrual hygiene and infections. Women with disabilities faced unique challenges during flooding, including dependence on others, navigating unsafe areas, and limited access to SRH information. Their vulnerabilities were exacerbated by the intersections of gender, disability, poverty, and coastal geography. Participants used improvised coping strategies, revealing gaps in disability-inclusive climate change and health planning.                                                           Discussion                     Climate change exacerbates existing inequalities, putting young WwD at increased risk of exclusion from SRH information and services. Young WwD in Coastal Ghana accessing SRHR services during climate change-related disruptions is a human rights issue. There is a pressing need to improve climate change adaptation for them, enhance infrastructure accessibility, and include them in community planning. Further research is suggested to guide national policy. include them in community planning. Further research is suggested to guide national policy.
Integrating Site Reliability Engineering SRE Principles into Enterprise Architecture for Predictive Resilience

Modern enterprises increasingly depend on complex distributed software systems where small faults can cascade into large customer impact. Site Reliability Engineering provides a disciplined approach to reliability through explicit service level objectives, error budgets, automation, incident response and continuous learning. Enterprise Architecture provides an enterprise-wide design view that connects business capabilities, information flows and technology platforms. This paper proposes an integrated framework that makes reliability a first-class architecture concern and that links architecture decisions to runtime evidence. The framework introduces an artifact mapping between Enterprise Architecture models and SRE primitives such as service level indicators, service level objectives and error budgets. It also defines a predictive resilience loop that combines observability telemetry with architecture context and change signals to anticipate degradation risk before user impact occurs. The paper synthesizes related work on resilience, observability, trace and log anomaly detection and interpretable root cause analysis then proposes implementation patterns for SLO hierarchies, drift detection, policy driven release governance and chaos experiments. Finally, it defines evaluation metrics and an illustrative enterprise scenario that demonstrates how predictive signals can trigger targeted governance actions and architecture updates.
Privacy-preserving federated learning with differential privacy for healthcare AI: a convergence and utility analysis

Federated Learning (FL) enables collaborative model training across distributed healthcare institutions without sharing raw patient data, offering a paradigm shift for privacy-sensitive medical AI. However, FL remains vulnerable to gradient inversion attacks and model poisoning, necessitating formal privacy guarantees. This paper presents a comprehensive analysis of Differential Privacy (DP)-augmented Federated Learning for healthcare AI applications, specifically Electronic Health Record (EHR) classification. We evaluate three aggregation strategies FedAvg, FedProx, and the proposed FedNova-DP across simulated environments with 10, 25, and 50 heterogeneous clients under both IID and non-IID data distributions. The proposed FedNova-DP framework achieves 93.8% accuracy on the MIMIC-III-derived benchmark dataset under non-IID conditions with a differential privacy budget of ε = 0.5, representing a 4.4% improvement over FedAvg-DP (89.4%) under equivalent conditions. Convergence analysis demonstrates that FedNova-DP reaches target accuracy 31% faster (in communication rounds) than FedAvg. A detailed privacy-utility trade-off analysis across ε ∈ [0.1, 10] reveals that the proposed framework maintains competitive utility at strong privacy regimes (ε = 0.5, accuracy = 89.3%) compared to non-private centralized training (97.4%). These findings establish FedNova-DP as a practical, deployable solution for privacy-preserving healthcare AI at scale.
Visual Expressions in Corporate Social Responsibility Reports: The Role of Minority Investors' Online Information Demand

ABSTRACT                   Corporate social responsibility (CSR) reports hold significant importance for firms to communicate with stakeholders. Previous studies have primarily emphasized the implications of verbal characteristics present in CSR reports, yet there exists a limited understanding on the distinct features of visual information in these reports. The paper integrates stakeholder salience theory and elaboration likelihood model to examine whether online information demand of minority investors in the unique online interactive platforms can prompt corporate visual expressions in their CSR reports. Additionally, we contend that the relationship between online information demand and visual expressions in CSR reports is accentuated when minority investors play a prominent role in a firm, yet attenuated when a firm provides more comprehensible and transparent information. Employing a hand‐collected dataset of 1998 observations from publicly listed Chinese firms from 2009 to 2017, our empirical findings strongly support these arguments. Taken together, this research enhances our understandings of how and when firms respond to the increased collective salience of minority investors resulting from their online information demand by disclosing more visually oriented CSR reports.
Improving power posterior estimation of statistical evidence

The statistical evidence (or marginal likelihood) is a key quantity in Bayesian statistics, allowing one to assess the probability of the data given the model under investigation. This paper focuses on refining the power posterior approach to improve estimation of the evidence. The power posterior method involves transitioning from the prior to the posterior by powering the likelihood by an inverse temperature. In common with other tempering algorithms, the power posterior involves some degree of tuning. The main contributions of this article are twofold -- we present a result from the numerical analysis literature which can reduce the bias in the estimate of the evidence by addressing the error arising from numerically integrating across the inverse temperatures. We also tackle the selection of the inverse temperature ladder, applying this approach additionally to the Stepping Stone sampler estimation of evidence.
Presenting information through a dashboard for Smart Video evaluations : The process of developing a design for a marketing dashboard

Using the internet for watching videos or online shopping keeps growing, along with video advertisement to increase online sales. To know if the video actually increases the online sales, the owner of a video ad wants to do follow ups on how the video is doing, and get statistics. A different solution from the original video ads is Smart Video. It is an interactive video player with a clickable slideshow of products. This video can get even more types of statistics than a normal video, and today that statistic is not accessible for the Smart Video clients, without the help of someone from the Smart Video team that can create a report for them. The purpose of this thesis was to relieve the workload of the Smart Video team and to create a dashboard that shows all information that the clients find relevant about their videos. This paper is about the process of developing a design for a marketing dashboard, that follows the guidelines of information dashboard design by Stephen Few. The process included interviews, multiple designs, prototypes, and evaluations, before ending up with a prototype of a desktop solution that follows the aesthetics of Smart Video and can be realizable with the current technology.
Government Appointment Discretion and Judicial Independence: Preference and Opportunistic Effects on Brazilian Courts

The prolific literature on de facto judicial independence misses a key variable to explain political bias: the government’s discretion over the appointment of Supreme Court Justices. In this paper, we explore a distinct feature of the Brazilian judiciary system to assess political bias due to government appointment discretion. As there are two courts, the STF (Supreme Federal Court) and the STJ (Superior Court of Justice), that deal with similar matters and have different restrictions on the appointment of their members, it is possible to compare the degree of political influence to which they are subject. We test (1) whether there are differences in the degree of political influence depending on the president’s discretion over the nomination of a justice, and (2) whether the justices actively benefit the party of the president who has appointed them. We find evidence of the first effect, but little of the second.
Limitations of standard cost-effectiveness methods for health technology assessment of treatments for rare, chronic diseases: a case study of treatment for cystic fibrosis

Cost-effectiveness analysis (CEA) is useful to assess the value of health care interventions based on clinical effectiveness and costs. However, standard CEA methods make important assumptions that may significantly increase the incremental cost-effectiveness ratio (ICER) for lifelong treatments for rare, chronic diseases. We used the cost-effectiveness of elexacaftor/tezacaftor/ivacaftor and ivacaftor (ELX/TEZ/IVA) for the treatment of cystic fibrosis as a case study to explore how alternative assumptions for (1) discounting, (2) utility measures, (3) disease management costs, and (4) static drug pricing impact cost-effectiveness outcomes. Cost-effectiveness of ELX/TEZ/IVA was evaluated using base-case inputs and assumptions reflecting standard CEA methods and was then compared with cost-effectiveness estimates obtained with alternate assumptions: (1) applying a lower discount rate to health benefits (1.5%) than costs (3%); (2) including a treatment-specific utility increment; (3) excluding disease management costs incurred during the period of extended survival attributable to ELX/TEZ/IVA treatment; and (4) decreasing the price of ELX/TEZ/IVA following loss of exclusivity. Modifying assumptions for these four factors together reduced the ICER by 75% from the base case, with the largest reduction (45%) occurring when the price trajectory was modified to allow for generic entry. Differential discounting, use of a treatment-specific utility increment, and exclusion of additional disease management costs each individually reduced the ICER by 36%, 14%, and 10%, respectively, from the base case. This study illustrates the impact that modifications to standard CEA methods may have on measures of cost-effectiveness for rare, chronic diseases.
Materials design and fundamental understanding of tellurium-based electrochemistry for rechargeable batteries

Abstract   Rechargeable tellurium (Te)-based batteries are emerging as energy storage devices with high volumetric energy density due to tellurium's superior electronic conductivity and high specific volumetric capacity. However, Te-based batteries are quite new, raising fundamental questions regarding the electrochemistry of Te-based cathodes and holistic aspects of full-cell performance. This review begins with a critical discussion on Li-Te electrochemistry in carbonate and ether electrolytes, followed by a comprehensive review on material design, cell architectures, and the working mechanism of Te-based cathodes in Li-Te-based batteries. The primary focus is to develop a fundamental understanding of the Te structure's role, carbon host chemistry and porosity, and the use of electrolytes to address Te pulverization and parasitic polytellurides shuttle effects and to establish reversible Te and Li2Te phase transitions. In addition, liquid and solid-state electrolytes for Li-Te batteries showing promise of enabling a stable solid electrolyte interphase (SEI) and reversible Te cathode reactions are presented. The following section exemplifies other novel metal-Te based batteries, including Na-Te, K-Te, Mg-Te, Zn-Te, and Al-Te systems, highlighting their respective cathode and electrolyte selection. Then, the comparison of quantitative performance data of various metal-Te-based batteries across Li-ion and Li-S batteries is revealed to provide a landscape of current research. In closing, this work identifies unanswered scientific and technological questions, discusses promising research directions, and highlights the experimental and simulation-based studies needed to discover the unknown of rechargeable Te-based batteries.