ethicalabs/Research-Intent-Collab huggingface dataset:
RL-Calibrated Chaos Engineering: A Constrained MDP Approach to Network Resilience Testing

Chaos engineering tests production network resilience by injecting controlled failures; the central open problem is calibration: how much failure injection is sufficient to expose latent resilience defects without degrading quality of service (QoS) experienced by end users? In practice, the inability to systematically calibrate failure injection has limited chaos engineering adoption in production environments, particularly in systems where reliability, cost, and user experience are tightly coupled. As AI-driven infrastructure and autonomous systems proliferate, this problem becomes critical-improper experimentation either misses failure modes or introduces unacceptable operational risk. The chaos-level engine of U.S. Patent No. 12,242,370 B2 (Cisco Technology, Inc., 2025) automates chaos-level derivation from network telemetry and refines it through a linear parameter adjustment loop, but provides no formal optimality guarantee, no mathematically rigorous safety constraint, and no sample-complexity characterization. This paper introduces a principled framework that resolves these limitations by casting chaos-level calibration as a Constrained Markov Decision Process (CMDP) and training a reinforcement-learning (RL) agent to select chaos levels maximizing cumulative resilience-discovery yield per unit of QoS risk, subject to a hard probabilistic constraint on production-disabling events. Three theorems establish the theoretical foundation: Theorem 1 (Safe Action Set Existence) proves a non-empty set of QoS-safe chaos actions always exists, guaranteeing CMDP feasibility; Theorem 2 (Bellman Optimality) establishes the resilience-per-risk reward satisfies the Bellman contraction, guaranteeing a globally optimal deterministic policy exists; Theorem 3 (PAC-Convergence) gives an explicit sample complexity bound O(|S|²|A|ε⁻² log |S||A|/δ) for reaching an ε-optimal safe policy with probability 1-δ. A Lagrangian primal-dual policy-gradient algorithm enforces the safety constraint at exact probabilistic semantics without penalty approximation. Empirical evaluation in a 150-node SD-WAN simulation-instantiating the patent's reference architecture-demonstrates the RL agent discovers 41.3 ± 3.8% more latent resilience defects than the patent's heuristic baseline, reduces unnecessary production disruptions by 58.7%, and achieves zero hard-constraint violations across 500 evaluation episodes, converging in 34 training episodes versus non-convergence of the heuristic baseline within 200 episodes.
IMPLEMENTATION AND OPTIMIZATION OF ANTIMICROBIAL STEWARDSHIP PROGRAMS: STRATEGIES FOR RESPONSIBLE ANTIMICROBIAL USE AND RESISTANCE PREVENTION

The implementation and optimization of antimicrobial stewardship programs represent a pivotal and proactive approach in the ongoing battle against antimicrobial resistance, a global health crisis of growing concern. These programs are essential strategies aimed at promoting responsible antimicrobial use, preserving the effectiveness of existing drugs, and curbing the emergence of antimicrobial-resistant pathogens. Antimicrobial agents, including antibiotics, are cornerstone tools in modern medicine, indispensable for treating infections and ensuring successful medical procedures. However, their overuse and misuse have led to a concerning rise in antimicrobial resistance, rendering many once-effective treatments ineffective. This alarming trend threatens to erode the very foundation of healthcare, making routine medical interventions riskier and potentially life-threatening. In this context, antimicrobial stewardship programs assume a central role in safeguarding the efficacy of these vital medications. Their objectives encompass a range of practices, from optimizing prescribing patterns and dosages to minimizing unnecessary antimicrobial use. These programs unite healthcare professionals, institutions, and policymakers in a concerted effort to ensure that these essential drugs remain effective for future generations.
Pengembangan  Human  Resource  Information  System (HRIS)  untuk  Optimalisasi  Manajemen  Sumber  Daya  Manusia  di  Perguruan Tinggi

Manajemen sumber daya manusia di Perguruan Tinggi yang menggunakan aplikasi &lt;br /&gt;perangkat lunak  akan  dapat  meningkatkan  efektifitas  dan efisiensi. Tanpa  bantuan  aplikasi &lt;br /&gt;Human  Resource  Information  System  (HRIS)  maka  kinerja  manajemen  operasional  tidak &lt;br /&gt;akan optimal. Data SDM yang dimiliki perguruan tinggi menjadi tidak terpusat sehingga ada &lt;br /&gt;kemungkinan  terjadi  redundancy  data.  Selain  itu  pengolahan  data  dan  penyajian  data &lt;br /&gt;membutuhkan  waktu  yang  lama.  Penelitian  ini  bertujuan  untuk  mengembangkan  aplikasi &lt;br /&gt;manajemen SDM. Aplikasi tersebut akan diimplimentasikan di Perguruan Tinggi, HRIS akan &lt;br /&gt;dikembangkan  dengan  studi  kasus  di  Universitas  Islam  Raden  Rahmat  (UNIRA)  Malang. &lt;br /&gt;Dengan  aplikasi  tersebut  diharapkan  HRIS  diharapkan  kinerja  manajemen  operasional &lt;br /&gt;menjadi  lebih  optimal.  Metode  yang  digunakan  pada  penelitian  ini  adalah  metode  terapan &lt;br /&gt;(action  research).  Pendekatan  pengembangan  sistem  menggunakan  metode  prototyping. &lt;br /&gt;Sedangkan metode perancangan yang digunakan yaitu perancangan sistem dan perancangan &lt;br /&gt;rinci, yang meliputi perancangan objek. Alat yang digunakan untuk mengukur implementasi &lt;br /&gt;sistem yang dibangun menggunakan metode kuisioner. Validitas yang dipergunakan dalam &lt;br /&gt;alat  ukur  penelitian  ini  adalah  validitas  isi  (content  validity).  Hasil  penelitian  ini  disajikan &lt;br /&gt;secara deskriptif dengan rincian sebagai berikut sistem ini sangat baik (45%) dimana sistem &lt;br /&gt;memiliki  kemudahan  di  dalam  penggunaannya  (65%  menyatakan  sangat  baik  dan  35% &lt;br /&gt;menyatakan  baik),  disamping  itu  56%  menyatakan  sangat  baik  terhadap  desain  interface, &lt;br /&gt;keakuaratan  informasi  yang  diberikan  dalam  sistem  dinyatakan  72%  baik,  bahasa  yang &lt;br /&gt;digunakan dalam aplikasi 55% sangat baik dan 45% baik, dan terakhir mengenai tentang error &lt;br /&gt;handling sebanyak 32% menyatakan sangat baik, 68% yang menyatakan baik.
Analysis of the European Union's performance as an international mediator in the South Caucasus with respect to peace building in the region - ENP and conflict resolution in the South Caucasus

von George Danielidze
Pierre Auger Observatory and Telescope Array: Joint Contributions to the 33rd International Cosmic Ray Conference (ICRC 2013)

Joint contributions of the Pierre Auger and Telescope Array Collaborations to the 33rd International Cosmic Ray Conference, Rio de Janeiro, Brazil, July 2013: cross-calibration of the fluorescence telescopes, large scale anisotropies and mass composition.
ADAPTING AND EXPANDING THE RISK-DRIVEN METHODOLOGY OF CRITICAL ENTITIES PROTECTION TO CRITICAL INFRASTRUCTURE RESILIENCE MANAGEMENT

Background. The ongoing study is aimed at developing methods and information technologies for monitoring and assessing the resilience of critical entities and infrastructures to improve the efficiency of situational management of these complex dynamic systems. The urgency of this study is due to the need to design and integrate adaptive control systems to maintain the safety and stability of critical infrastructures under destructive impact of negative factors on their constituent elements, and the increased need for methodological, information and analytical support of the current control tasks at all phases of the resilience management life-cycle of critical entities. Materials and methods. The theoretical foundations of the study are the general theory of risk and fundamentals of safety analysis, the stateof- the-art resilience concept and the recent methodology of organizational systems management. The methodological approach to solving the problem of enhancing the stability of critical infrastructures is based on the conjugation of security risk-driven auditing and adaptive resilience management methods. Results and conclusions. The expansion of the range of application of the methodological apparatus for an integrated assessment of the security violation risk factors of critical entities, designed at the Institute of Systems Analysis of the Russian Academy of Sciences, in terms of its adaptation to critical infrastructure resilience management, has been proposed. An adapted approach based on a multilevel analysis of the potential threats model, vulnerabilities and the performance of countermeasures provides an aggregated assessment of the resilience level and a reasonable choice of recovery and adaptation profiles for maintaining and protecting the critical system functions for a given type of actuating threats. In practice, such a risk-driven approach can be used for information and analytical support of the critical infrastructure operators’ activities as a tool for preventive analytics and situational control of the critical entities resilience.
Interactions Between Dark Matter and Dark Energy: Simulations and Cosmological Implications .

Understanding the evolution of the universe is deeply rooted in ex-  ploring the intricate interplay between dark matter and vacuum energy.  While traditional cosmology treats these components as independent, new  frameworks propose dynamic interactions that transcend the standard  CDM paradigm. This idea is compelling because it challenges the no-  tion of a static vacuum energy and introduces a fluid, evolving picture  of the cosmos, where energy exchange between dark matter and vacuum  energy influences cosmic transitions, structure formation, and expansion  dynamics.  This approach is significant for several reasons. First, it provides a  unifying perspective that links the universe’s accelerating expansion with  the growth of large-scale structures, bridging two seemingly disparate phe-  nomena under a single theoretical framework. Second, by incorporating  interactions, we can address persistent tensions in cosmology, such as dis-  crepancies in the Hubble constant, which traditional models struggle to  resolve. Finally, this theory opens a new avenue for testing cosmological  predictions through observational data, including gravitational lensing,  fast radio bursts, and galaxy clustering.  The abstract nature of this idea is its strength it invites a reconsid-  eration of the fundamental forces shaping the cosmos, positioning dark  matter and vacuum energy not as isolated entities but as dynamic, in-  terdependent agents. By embracing this conceptual shift, we not only  refine our understanding of the universe’s past and future but also create  a fertile ground for theoretical and observational breakthroughs.
Trends in Workplace Wearable Technologies and Connected‐Worker Solutions for Next‐Generation Occupational Safety, Health, and Productivity

The workplace influences the safety, health, and productivity of workers at multiple levels. To protect and promote total worker health, smart hardware, and software tools have emerged for the identification, elimination, substitution, and control of occupational hazards. Wearable devices enable constant monitoring of individual workers and the environment, whereas connected worker solutions provide contextual information and decision support. Here, the recent trends in commercial workplace technologies to monitor and manage occupational risks, injuries, accidents, and diseases are reviewed. Workplace safety wearables for safe lifting, ergonomics, hazard identification, sleep monitoring, fatigue management, and heat and cold stress are discussed. Examples of workplace productivity wearables for asset tracking, augmented reality, gesture and motion control, brain wave sensing, and work stress management are given. Workplace health wearables designed for work‐related musculoskeletal disorders, functional movement disorders, respiratory hazards, cardiovascular health, outdoor sun exposure, and continuous glucose monitoring are shown. Connected worker platforms are discussed with information about the architecture, system modules, intelligent operations, and industry applications. Predictive analytics provide contextual information about occupational safety risks, resource allocation, equipment failure, and predictive maintenance. Altogether, these examples highlight the ground‐level benefits of real‐time visibility about frontline workers, work environment, distributed assets, workforce efficiency, and safety compliance.
The Extent of Knowledge Among Faculty Members at Jordanian Universities Regarding Principles of AI Ethics in Scientific Research and Its Guidelines

Objectives: Objectives: This study aims to explore the extent of knowledge among faculty members at Jordanian universities regarding the principles of AI ethics in scientific research and its regulatory guidelines, in alignment with SDG 4: Quality Education to promote inclusive and equitable education and lifelong learning opportunities.   Theoretical Framework: The study is based on the ethical principles of artificial intelligence, emphasizing key dimensions such as data reliability and integrity, privacy and security, human and socio-cultural benefits, and the ethics of integrity, fairness, justice, responsibility, and transparency. These dimensions were used as the basis for designing the study instrument.   Method: A descriptive survey methodology was employed. The researchers developed a questionnaire consisting of 40 items, distributed across four domains: (1) data reliability and integrity, (2) privacy, security, and protection, (3) human and socio-cultural benefits, and (4) ethics of integrity, fairness, justice, responsibility, and transparency. The instrument was administered to a randomly selected sample of 245 faculty members across various Jordanian universities.   Results and Discussion: The results revealed a high level of knowledge among faculty members regarding the principles and guidelines of AI ethics in scientific research. Moreover, no statistically significant differences were found in participants' responses based on variables such as college affiliation, teaching experience, academic rank, or source of academic degree. The discussion elaborates on these findings, emphasizing their significance in enhancing ethical research practices involving AI.   Research Implications: The study highlights the importance of incorporating AI ethics education into faculty development programs and strengthening institutional guidelines to uphold ethical standards in scientific research.   Originality/Value: This research fills a gap in understanding the level of AI ethics knowledge among faculty members at Jordanian universities, providing actionable insights to advance ethical AI use in academic research.
What future for environmental and climate litigation?

The book provides in-depth analysis and innovative insights on the prospects of climate and environmental litigation, namely by exploring the ability of judicial remedies and sanctions to affect public and private decision-making in every context where natural resources, climate as well as human health are at stake. The chapters reproduce, with additional elaborations, the papers presented at the international workshop that gives the volume its title, held at the University of Milan on 16 September 2022. The underlying question is whether and to what extent, in the face of unsatisfactory and unreasonable political choices on the balance between the different interests at stake, resorting to national and supernational courts represents a valid alternative for a more sustainable future. The relevant contexts covered by the book include, for instance, industrial development, exploitation of natural resources, agricultural production, manufacturing techniques, as well as policies on energy, public and private transport, and urban development. The book is composed of three parts, each one addressing, from multiple perspectives, a specific category of judicial remedies in a certain area of legal studies: I) international human rights law; II) private international law and international trade law; II) domestic and international criminal law.
The Digital Transformation in Health: How AI Can Improve the Performance of Health Systems

Mobile health has the potential to revolutionize health care delivery and patient engagement. In this work, we discuss how integrating Artificial Intelligence into digital health applications-focused on supply chain, patient management, and capacity building, among other use cases-can improve the health system and public health performance. We present an Artificial Intelligence and Reinforcement Learning platform that allows the delivery of adaptive interventions whose impact can be optimized through experimentation and real-time monitoring. The system can integrate multiple data sources and digital health applications. The flexibility of this platform to connect to various mobile health applications and digital devices and send personalized recommendations based on past data and predictions can significantly improve the impact of digital tools on health system outcomes. The potential for resource-poor settings, where the impact of this approach on health outcomes could be more decisive, is discussed specifically. This framework is, however, similarly applicable to improving efficiency in health systems where scarcity is not an issue.
Appointed Courts, Elected Courts, and Public Utility Regulation: Judicial Independence and the Energy Crisis

This paper investigates the importance of variations in judicial institutions after a ‘shock’ has unraveled a regulatory status quo. State court decisions involving utility regulation are examined. Appointed state courts are generally agreed to be more independent than elected state courts. Before 1970, the primary participants in the process of utility regulation (and thus its largest beneficiaries) were the regulated firms and their commercial customers; afterwards, utility regulation increasingly accommodated consumer groups as well. Certain scholars have proposed that independent courts help keep administrative agencies from deviating from the original wishes of their political principals, and thus might be expected to slow down such changes in regulatory approach (which occurred with few alterations to the governing statutes). Other scholars have proposed instead that independent courts can decide as discretion dictates, and may thus lead such changes. The results of this analysis provide support for the latter view: controlling for other factors (such as partisan affiliation), more independent appointed courts sided more often with consumer groups while less independent elected courts sided more often with regulated firms and their large commercial customers.
Reducing Uncertainty: The Need to Clarify the Key Elements of the Precautionary Principle

Consilience, No 1 (2009): Issue One: 2009
Genetic testing, insurance discrimination and medical research: what the United States can learn from peer countries

While genetic testing may be the gateway to the future of medicine, it also poses challenges for individuals, especially in terms of differentiated treatments on the basis of their genetic characteristics. The fear of unwanted disclosure to insurers and the possibility of genetic discrimination can hamper the recruitment of individuals for clinical research that involves genetic testing. Precision medicine initiatives, such as All of Us, are proliferating in the United States. In order to succeed, however, they must ensure that the millions of Americans recruited to share their genetic data are not penalized with regard to life, disability and long-term insurance coverage. In this Perspective, we discuss several initiatives adopted by countries around the world, such as the United Kingdom and France, that better balance the interests of insurers and research subjects, and explain how the United States might learn from them. We call for regulatory and industry leadership to come together to establish a voluntary moratorium on insurance pricing with the aim of protecting research participants.
Correlation length scalings in fusion edge plasma turbulence computations

The effect of changes in plasma parameters, that are characteristic near or at an L-H transition in fusion edge plasmas, on fluctuation correlation lengths are analysed by means of drift-Alfven turbulence computations. Scalings by density gradient length, collisionality, plasma beta, and by an imposed shear flow are considered. It is found that strongly sheared flows lead to the appearence of long-range correlations in electrostatic potential fluctuations parallel and perpendicular to the magnetic field.
Applicantion Model of Transparency and Accountability of Regional Government Financial Reporting: It’s Influence on the Level of Regional Government Corruption in Indonesia

This research aims to empirically analyze the influence of transparency and accountability of local government financial reports (LKPD) on the level of local government corruption. It is important to carry out this research to see that the unqualified opinion (WTP) given by the Financial Audit Agency (BPK) has increased which shows that the presentation of regional government financial reports (LKPD) is getting better, but cases of corruption in government institutions continue to increase every year. The population used in this research is the City/Regency Governments throughout Riau. The type of data used in this research is secondary data. The City Government (Pemkot) that was the sample in this study was selected based on certain criteria (purposive sampling) with the aim of obtaining a sample that met the specified criteria. There are 15 city/district governments in Riau that can be used as samples in this research. The methods used in analyzing this research data are descriptive statistical analysis and inferential statistical analysis. Data processing was carried out using the IBM Statistical Package for Social Science (SPSS) version 25 and Warp PLS application programs. The research results prove that accountability influences the regional corruption index; Transparency influences the regional corruption index. Increasing accountability and transparency in government governance is an important step in efforts to reduce corruption and improve the quality of government in the regions. Concrete actions such as improving financial reporting, strengthening supervision, and increasing public access to government information must be taken to achieve this goal.