ethicalabs/Research-Intent-Collab huggingface dataset:
Towards Goal-Oriented Semantic Signal Processing: Applications and Future Challenges

Advances in machine learning technology have enabled real-time extraction of semantic information in signals which can revolutionize signal processing techniques and improve their performance significantly for the next generation of applications. With the objective of a concrete representation and efficient processing of the semantic information, we propose and demonstrate a formal graph-based semantic language and a goal filtering method that enables goal-oriented signal processing. The proposed semantic signal processing framework can easily be tailored for specific applications and goals in a diverse range of signal processing applications. To illustrate its wide range of applicability, we investigate several use cases and provide details on how the proposed goal-oriented semantic signal processing framework can be customized. We also investigate and propose techniques for communications where sensor data is semantically processed and semantic information is exchanged across a sensor network.
Total Variation Distance for Product Distributions is $\#\mathsf{P}$-Complete

We show that computing the total variation distance between two product distributions is $\#\mathsf{P}$-complete. This is in stark contrast with other distance measures such as Kullback-Leibler, Chi-square, and Hellinger, which tensorize over the marginals leading to efficient algorithms.
Dissecting Catastrophic Forgetting in Continual Learning by Deep Visualization

8 pages, 6 figures, 3 tables
TimeSeriesExam: A time series understanding exam

Large Language Models (LLMs) have recently demonstrated a remarkable ability to model time series data. These capabilities can be partly explained if LLMs understand basic time series concepts. However, our knowledge of what these models understand about time series data remains relatively limited. To address this gap, we introduce TimeSeriesExam, a configurable and scalable multiple-choice question exam designed to assess LLMs across five core time series understanding categories: pattern recognition, noise understanding, similarity analysis, anomaly detection, and causality analysis. TimeSeriesExam comprises of over 700 questions, procedurally generated using 104 carefully curated templates and iteratively refined to balance difficulty and their ability to discriminate good from bad models. We test 7 state-of-the-art LLMs on the TimeSeriesExam and provide the first comprehensive evaluation of their time series understanding abilities. Our results suggest that closed-source models such as GPT-4 and Gemini understand simple time series concepts significantly better than their open-source counterparts, while all models struggle with complex concepts such as causality analysis. We believe that the ability to programatically generate questions is fundamental to assessing and improving LLM's ability to understand and reason about time series data.
GALACTIC COSMIC-RAY MODULATION IN A REALISTIC GLOBAL MAGNETOHYDRODYNAMIC HELIOSPHERE

To understand the behavior of cosmic-ray modulation seen by the two Voyager spacecraft in the region near the termination shock (TS) and in the heliosheath at a distance of >100 AU, a realistic magnetohydrodynamic global heliosphere model is incorporated into our cosmic-ray transport code, so that the detailed effects of the heliospheric boundaries and their plasma/magnetic geometry can be revealed. A number of simulations of cosmic-ray modulation performed with this code result in the following conclusions. (1) Diffusive shock acceleration by the TS can significantly affect the level of cosmic-ray flux and, in particular, its radial gradient profile in the region near the TS and in the inner heliosheath. (2) The radial profile of cosmic-ray flux strongly depends on longitude. There is a slight north-south asymmetry due to an asymmetric TS, but the larger difference in the radial profiles comes from longitudinal variation. Voyager 1 and 2 are separated by similar to 40 degrees in longitude. Simulations in these two directions show a large difference in the radial profile of cosmic-ray flux. Thus, it is not appropriate to determine the cosmic-ray radial gradient by directly using the two-point Voyager measurements. Various other simulations are also performed to show how sensitively the modulation level depends on latitude, cosmic-ray energy, and interstellar spectrum.
Rule of Law, Effective Protection of Rights and Independence of the Judicial System

This chapter focuses on the interpenetration that exists between the principle of judicial independence and that of the effective protection of rights, underlined by the ongoing rulings of both the CJEU and the ECtHR. Indeed, the renewed importance attributed to the guarantee of this principle has emerged today in the light of a series of internal events in some Member States characterized by marked interventions in the reform of their judicial systems. The effects of the newly introduced disciplines are such that they are resulting in what is now being called a real ‘crisis of the rule of law’ as a core value of the EU. So disruptive is the scope of these reforms as a backslide of the integration process that it is even being traced back to the political features of ‘illiberal democracies’ or forms of ‘democratic regression’.
PENGEMBANGAN SISTEM HRIS (HUMAN RESOURCE INFORMATION SYSTEM) MANAJEMEN KARYAWAN MENGGUNAKAN METODE WATERFALL DI CV. SOLUSI MITRA CONSULTING

Salah satu elemen yang penting dalam menunjang aktivitas operasional perusahaan yaitu pengelolaan sumber daya manusia. Tetapi, banyak perusahaan yang masih menggunakan metode konvensional dalam proses administrasi cuti, lembur, dan penggajian karyawan yang dapat menimbulkan masalah seperti telatnya proses persetujuan, kesalahan dalam rekap data, dan kurangnya transparansi informasi. Penelitian ini bertujuan untuk mengembangkan sistem HRIS ( Human Resource Information System) berbasis website menggunakan metode Waterfall untuk meningkatkan efisiensi dan efektivitas manajemen karyawan. Digunakannya Metode Waterfall pada penelitian ini karena memiliki tahapan yang terstruktur dimulai dari analisis kebutuhan, desain sistem, implementasi, pengujian, sampai pemeliharaan sistem. Sistem HRIS yang dikembangkan ini memiliki fitur presensi karyawan, pengajuan cuti, dan lembur secara online dan integrasi notifikasi menggunakan aplikasi pihak ketiga yaitu Slack, approval oleh manajer, serta pengelolaan dan export data penggajian dalam format PDF. Hasil dari implementasi sistem ini menunjukkan peningkatan dalam efisiensi administrasi yang sebelumnya ketika pengajuan cuti atau lembur memerlukan waktu 2 hingga 4 hari kerja menjadi kurang dari 1 hari kerja, serta pengurangan penggunaan kertas hingga 80% dalam proses pengajuan cuti atau lembur dan peningkatan akurasi data penggajian dengan tingkat kesalahan yang menurun dari sebelumnya. Maka dari itu, penerapan sistem HRIS ini memberikan dampak positif dalam pengelolaan sumber daya manusia secara keseluruhan di CV, Solusi Mitra Consulting.
Supplementary Table S4 from Blood-Based Genomic Alteration Signature for Predicting Progression-Free Survival in &lt;i&gt;De Novo&lt;/i&gt; Metastatic Hormone-Sensitive Prostate Cancer: A Real-World Study

&lt;p&gt;Multivariate Analysis of Prognostic Factors Based on ctDNA&lt;/p&gt;
Can simulation improve the traditional method of root cause analysis: A preliminary investigation

The Joint Commission on Accreditation of Healthcare Organizations recommendations for conducting root cause analysis (RCA) include identifying "root causes" and "common-cause variation" rather than "proximate causes" and "special-cause variation" to create interventions. Simulation for health care RCA is a novel technique but has not been compared with traditional RCA methods.All of the RCAs of adverse events conducted at Tulane Hospital between September 2010 and September 2011 were reviewed. A case of missed postprocedural, preoperative hemorrhage resulting in death was chosen. Hospital records were analyzed to identify the presumed root causes. A simulation of the event was developed and conducted. Six test subjects (preoperative and postanesthesia care unit nurses) participated in the simulation. Root causes identified by simulation analysis were compared with those identified by traditional RCA.In 2 of 6 simulations, the adverse event was duplicated. The root cause identified by standard RCA technique was inattention to signs of bleeding in the patient/ lack of appropriate monitoring of the patient by nursing staff ("special-cause variation"). Simulation-based RCA revealed that the root cause was not only inadequate monitoring, but also the lack of physical presence of physicians in the care environment ("common-cause variation"). Simulation-based RCA identified root causes more amenable to intervention.This study demonstrates that simulation-based RCA can identify additional root causes amenable to making health care interventions when compared with traditional RCA.
Navigating intersectional expectations: a computational multimodal analysis of the effects of identities and communication styles on public engagement with science on TikTok

Communication research has long established the impact of the communicator's social identity on persuasion. However, few communication studies have applied an intersectional lens to examine identities or systematically examined how the effectiveness of communication styles has been evaluated through identity-based expectations. Focusing on digital science communication, we used a unique multimodal dataset of 10,800 videos and 448,002 comments to explore how people's engagement and commenting behaviors were influenced by a communicator's gender, race, and their interaction with communication styles. Our results show that women of color, particularly Latina/Hispanic women, often faced dual role incongruity when communicating science online, receiving significantly lower engagement than those with a single marginalized identity. Audiences showed more engagement with online communicators who adopted role-congruent communication styles to communicate science (i.e., favoring affective tone from women and aggressiveness from men). This study sheds light on how identity-related heuristics increasingly shape engagement behaviors in visual-oriented platforms.
JUDICIAL REVIEW OF CONSTITUTIONAL COURT DECISION NO. 90/PUU-XXI/2023 CONCERNING AGE LIMITS FOR PRESIDENTIAL AND VICE-PRESIDENTIAL CANDIDATES

The Constitutional Court is an organization of legal power which, in view of the constitution, has a legal capability to maintain regulation and equity. Regulation Number 24 of 2003 makes sense of that the obligations and elements of the Constitutional Court are to deal with established matters in regards to specific protected matters to shield the constitution so it is carried out dependably as per the desire of individuals and majority rule beliefs. In protecting the constitution, obviously, sacred appointed authorities are required who have information and skill in state organization as well as a promise to executing and managing state life as per the passages of the constitution, so every choice gave by the Constitutional Court is a legitimate item that doesn't go external the passageways of the constitution, so the actual constitution is naturally kept up with. This examination is spurred by the significant job of the Constitutional Court in giving over choices since it is as per Article 10 of Regulation No. 24 of 2003 concerning the Constitutional Court, the choice of the Constitutional Court is conclusive and has restricting legitimate power. The overall population, state directors, and all parts of the country trust that the Constitutional Court judges will really complete their capabilities, obligations and commands as per the Constitution, so through Constitutional Appointed authorities who have a statesmanlike soul, the Constitutional Court can create choices that can give a feeling of equity. in the midst of society. Keywords: Equity, Judge's Choice, Constitutional Court.
Helpful, harmless, honest? Sociotechnical limits of AI alignment and safety through Reinforcement Learning from Human Feedback

Abstract           This paper critically evaluates the attempts to align Artificial Intelligence (AI) systems, especially Large Language Models (LLMs), with human values and intentions through Reinforcement Learning from Feedback methods, involving either human feedback (RLHF) or AI feedback (RLAIF). Specifically, we show the shortcomings of the broadly pursued alignment goals of honesty, harmlessness, and helpfulness. Through a multidisciplinary sociotechnical critique, we examine both the theoretical underpinnings and practical implementations of RLHF techniques, revealing significant limitations in their approach to capturing the complexities of human ethics, and contributing to AI safety. We highlight tensions inherent in the goals of RLHF, as captured in the HHH principle (helpful, harmless and honest). In addition, we discuss ethically-relevant issues that tend to be neglected in discussions about alignment and RLHF, among which the trade-offs between user-friendliness and deception, flexibility and interpretability, and system safety. We offer an alternative vision for AI safety and ethics which positions RLHF approaches within a broader context of comprehensive design across institutions, processes and technological systems, and suggest the establishment of AI safety as a sociotechnical discipline that is open to the normative and political dimensions of artificial intelligence.
Leveraging learning systems to improve quality and patient safety in allergen immunotherapy

Adverse events occur in all fields of medicine, including allergy-immunology, in which allergen immunotherapy medical errors can cause significant harm. Although difficult to experience, such errors constitute opportunities for improvement. Identifying system vulnerabilities can allow resolution of latent errors before they become active problems. We review key aspects and frameworks of the medical error response, acknowledging the fundamental responsibility of clinical teams to learn from harm. Adverse event response comprises 4 major phases: (1) event recognition and reporting, (2) investigation (for which root cause analysis can be helpful), (3) improvement (inclusive of the plan-do-study-act cycle), and (4) communication and resolution. Throughout the process, clinician wellness must be maintained. Adverse event prevention should be prioritized, and a human factors engineering approach can be useful. Quality improvement tools and approaches complement one another and together offer a meaningful avenue for error recovery and prevention.
EXTREMAL PROBLEMS IN GRAPH THEORY: A COMBINATORIAL OPTIMIZATION PERSPECTIVE

The extremal theory of graphs considers the study of how large or small a graph invariant may be, according to certain constraints. The field crosses the overlying with combinatorial optimization, in which optimal configurations are studied under discrete conditions. Paper discusses the extremal problems in the idiom of optimization theory, where analytically driven approaches and computational methods are introduced, that complement the insights on how graph structures tend to act under the extremal conditions. We discuss some classical results like Turán type theorems, Mantel theorems and the Erdős Stone theorems and state their formulations in optimization terms. With integer programming and greedy algorithms, we find solutions to some extremal problems and compute their complexity and compare theoretical predictions and experimental results. This was done in our research, proving the possibility that optimization strategies be incorporated into the extremal graph theory and a foundation towards the further development of the algorithm in the subject.
Transparency and methodological quality of the development, quality of recommendations and completeness of reporting of CPG in palliative and end of life care of adult patients by using AGREE-II, AGREE-REX and RIGHT

Evidence Synthesis Protocol
Adapting to Climate Risks through Cross-Border Investments: Industrial Vulnerability and Smart City Resilience

Abstract         Climate change entails potential risks for investors, and its effects on investment has spread beyond physical borders. This study investigates how multinational corporations (MNCs) incorporate climate risks into their decisions regarding foreign direct investments (FDIs). We find that large differences in the climate risks of home and host cities discourages FDI by increasing cross-border adaptation costs. Such impacts are particularly pronounced among environmentally sensitive industries that are more exposed to climate risks. Further analysis reveals that city-based smartness factors mitigate the negative impacts of climate risk differences on FDI by reducing adaptation costs and engendering new business opportunities. This study provides new evidence on the profound effects of climate risks on FDI and how smart cities can increase their resilience to climate risks in the context of international business.
Judicial Independence And The Rule Of Law: Exploring The European Experience

Judicial Independence is here analysed on a theoretical and empirical basis, with a comparative view. The macro - micro nexus is also investigated relying on the research data referring to a cluster of European countries which differ in terms of culture of JI and institutional legacy.
Conceptual development of an early warning system for glacial lake outburst floods in central Asia: Pilot site modelling for disaster risk reduction

Glacial lake outburst floods (GLOFs) are a common and dangerous glacial hazard which threatens millions of people in high mountainous regions worldwide. The availability of an early warning system (EWS) for GLOFs can alleviate the impact in case of an event. In Central Asia, devastating GLOF events caused fatalities and infrastructure damage in the past. This thesis aims to develop a conceptual EWS for GLOFs at the pilot site of the Aksay and Ala-Archa valleys in Kyrgyzstan, Central Asia. Utilizing an internationally recognized four-component framework for EWSs—risk knowledge, monitoring and warning, dissemination and communication, and response capability—the study offers a multi-faceted approach to Disaster Risk Reduction (DRR) in the region. Based on the possibility of a moraine-dam breach, different worst-case scenarios are developed with peak discharges between 300 m3/s and 900 m3/s that are used in a steady flow simulation within the hydrological modelling tool HEC-RAS to simulate the flooding extent of a GLOF. The study identifies GLOF hotspots and assesses the exposure and vulnerability of infrastructure and residential areas, estimating the GLOF danger of 251 to 407 residents along the Ala-Archa river channel. Based on the risk assessments, the study proposes an EWS including monitoring of the glacial lake and a detection and warning system. The system emphasizes redundancy, cost-effectiveness, includes suggestions for two types of detection sensors and the use of air and electrical horns for warnings. The study further proposes practical dissemination and communication strategies, and outlines response capability necessities including an emergency response plan. The thesis concludes by highlighting areas for future research, including community involvement, technical implementation, and dam vulnerability assessments, to further refine and possibly implement the conceptual EWS.
The United Kingdom Glaucoma Treatment Study: a multicenter, randomized, placebo-controlled clinical trial: design and methodology.

Elevated intraocular pressure (IOP) is a major risk factor for the deterioration of open-angle glaucoma (OAG); medical IOP reduction is the standard treatment, yet no randomized placebo-controlled study of medical IOP reduction has been undertaken previously. The United Kingdom Glaucoma Treatment Study (UKGTS) tests the hypothesis that treatment with a topical prostaglandin analog, compared with placebo, reduces the frequency of visual field (VF) deterioration events in OAG patients by 50% over a 2-year period.The UKGTS is a randomized, double-masked, placebo-controlled, multicenter treatment trial for OAG.Five hundred sixteen newly diagnosed (previously untreated) patients with OAG were recruited prospectively at 10 centers between 2007 and 2010.Patients were assigned by concealed telephone allocation to treatment with a prostaglandin analog (latanoprost 0.005%) or placebo. The observation period was 2 years, with subjects monitored by VF testing, quantitative imaging, optic disc photography, and tonometry at 11 visits. Data were acquired according to novel protocols optimized for the analysis of deterioration velocity. The sample size was determined for a 2-sided error of α=0.05 to detect the difference between 24% and 11% in incident deterioration over a 24-month follow-up at 90% power and assuming a 25% attrition rate.The primary outcome was time to VF deterioration within 24 months. Secondary outcomes included the deterioration velocity of VF and quantitative imaging measures and the relationship between these velocities and risk factors for deterioration.The study design enabled a short trial with a 2-year observation period and provided data that can be used to assess the feasibility of further shortening trial duration with the progression velocity of VF and structural imaging measurements as outcomes.The UKGTS is the first randomized, placebo-controlled trial to evaluate the efficacy of medical treatment in reducing VF deterioration in OAG. The measurement of deterioration velocity and inclusion of quantitative imaging has the potential to reduce the number of patients and duration required for subsequent clinical trials. This trial also will quantify risk factors for deterioration, enabling more precise risk profiling of patients and the development of patient management protocols.The author(s) have no proprietary or commercial interest in any materials discussed in this article.
Edge Computing in 5G and IoT Enhancing Data Processing Real-Time Analytics and Reducing Latency for Critical Applications

The integration of 5G networks, edge computing, and Internet of Things (IoT) was transforming the landscape of modern digital systems, enabling more efficient, scalable, and responsive applications across various sectors. This chapter explores the synergies between these technologies, focusing on their role in enhancing real-time data processing, reducing latency, and optimizing bandwidth for critical applications. The convergence of 5G and edge computing plays a pivotal role in addressing the limitations of traditional cloud-based systems by enabling localized data processing, which was crucial for applications in smart cities, healthcare, precision agriculture, and autonomous systems. By enabling ultra-low latency communication and supporting massive device connectivity, these technologies ensure seamless interaction between edge devices and IoT networks, paving the way for advanced real-time analytics and decisionmaking. However, challenges related to infrastructure deployment, security, and scalability remain key areas of ongoing research. This chapter also outlines future directions for the continued evolution of these technologies, highlighting their potential in emerging fields such as augmented reality (AR), virtual reality (VR), and smart manufacturing. The insights provided are crucial for understanding the transformative impact of 5G and edge computing on critical applications in a data-driven world.