ethicalabs/Research-Intent-Collab huggingface dataset:
Judicial Review and Constitutional Court Authority: Comparative Analysis of Indonesia's Constitutional Court and International Best Practices

Constitutional courts serve as guardians of constitutional supremacy through judicial review mechanisms. This study examines the authority and practices of Indonesia's Constitutional Court in comparative perspective with international best practices. Using comparative legal analysis, this research evaluates judicial review systems in Germany, South Korea, South Africa, and the United States to identify effective governance models. The study reveals that while Indonesia's Constitutional Court possesses comprehensive constitutional review authority, challenges remain in enforcement mechanisms, case backlog management, and institutional independence. International best practices demonstrate the importance of clear jurisdictional boundaries, efficient case processing, and robust enforcement powers. The research concludes that Indonesia can strengthen its constitutional court system by adopting selective best practices including streamlined procedures, enhanced enforcement mechanisms, and improved institutional safeguards while maintaining its unique constitutional framework.
Athletic Enhancement, Human Nature and Ethics – Threats and Opportunities of Doping Technologies

The book provides an in-depth discussion on the human nature concept from different perspectives and from different disciplines, analyzing its use in the doping debate and researching its normative overtones. The relation between natural talent and enhanced abilities is scrutinized within a proper conceptual and theoretical framework: is doping to be seen as a factor of the athlete's dehumanization or is it a tool to fulfill his/her aspirations to go faster, higher and stronger? Which characteristics make sports such a peculiar subject of ethical discussion and what are the, both intrinsic and extrinsic, moral dangers and opportunities involved in athletic enhancement? This volume combines fundamental philosophical anthropological reflection with applied ethics and socio-cultural and empirical approaches. Furthermore it presents guidelines to decision- and policy-makers on local, national and international levels.
Novel Kinetic 3D MHD Algorithm for High Performance Parallel Computing Systems

The impressive progress of the kinetic schemes in the solution of gas dynamics problems and the development of effective parallel algorithms for modern high performance parallel computing systems led to the development of advanced methods for the solution of the magnetohydrodynamics problem in the important area of plasma physics. The novel feature of the method is the formulation of the complex Boltzmann-like distribution function of kinetic method with the implementation of electromagnetic interaction terms. The numerical method is based on the explicit schemes. Due to logical simplicity and its efficiency, the algorithm is easily adapted to modern high performance parallel computer systems including hybrid computing systems with graphic processors.
Requirements for a product information management (PIM) infrastructure to support partner programs

Thesis (S.M.)--Massachusetts Institute of Technology, System Design & Management Program, 2000. ; Includes bibliographical references (leaves 148-151). ; by Manu Vedapudi. ; S.M.
A Picard-type Iteration for Backward Stochastic Differential Equations : Convergence and Importance Sampling

published
A study into the mental health of PhD students in Australia: investigating the determinants of depression, anxiety, and suicidality

PhD students are particularly vulnerable to experiencing poor mental health. Mental health concerns that arise during their studies can not only affect their study progress but also have long-lasting impacts on their mental health after their studies. Extensive research has been conducted on the mental health of university students, but few studies have focused on PhD students and even fewer on PhD students in Australia. The present study investigated demographic, occupational, psychological, social, and relational determinants of mental health symptoms (depression, anxiety, and suicidality) in PhD students in Australia. PhD students enrolled in Australian universities were invited to complete an online survey. Results from regression analyses identified key determinants of mental health symptoms in our sample of PhD students (N = 302). In particular, higher levels of imposter thoughts, perfectionism discrepancy, and loneliness were strong predictors of depression, anxiety, and suicidality. These findings contribute to our understanding of the mental health of PhD students in Australia. Importantly, these findings inform areas of focus where potential strategies can be implemented to better protect the mental health of this population. For example, strategies that mitigate loneliness or foster effective, collaborative student-supervisor relationships.
The power of precedents: using the case law of the ad hoc international criminal tribunals and hybrid courts in adjudicating sexual violence and gender-based crimes at the ICC

(2012). The power of precedents: using the case law of the ad hoc international criminal tribunals and hybrid courts in adjudicating sexual violence and gender-based crimes at the ICC. Australian Journal of Human Rights: Vol. 18, No. 2, pp. 75-108.
Hurricane Forecasting: A Novel Multimodal Machine Learning Framework

This paper describes a novel machine learning (ML) framework for tropical cyclone intensity and track forecasting, combining multiple ML techniques and utilizing diverse data sources. Our multimodal framework, called Hurricast, efficiently combines spatial-temporal data with statistical data by extracting features with deep-learning encoder-decoder architectures and predicting with gradient-boosted trees. We evaluate our models in the North Atlantic and Eastern Pacific basins on 2016-2019 for 24-hour lead time track and intensity forecasts and show they achieve comparable mean absolute error and skill to current operational forecast models while computing in seconds. Furthermore, the inclusion of Hurricast into an operational forecast consensus model could improve over the National Hurricane Center's official forecast, thus highlighting the complementary properties with existing approaches. In summary, our work demonstrates that utilizing machine learning techniques to combine different data sources can lead to new opportunities in tropical cyclone forecasting.
Computations of optimal transport distance with Fisher information regularization

We propose a fast algorithm to approximate the optimal transport distance. The main idea is to add a Fisher information regularization into the dynamical setting of the problem, originated by Benamou and Brenier. The regularized problem is shown to be smooth and strictly convex, thus many classical fast algorithms are available. In this paper, we adopt Newton's method, which converges to the minimizer with a quadratic rate. Several numerical examples are provided.
Self-Supervised Visual Representations Learning by Contrastive Mask Prediction

Accepted to ICCV 2021
Role of Pharmacists and Public Health in Antimicrobial Stewardship: Addressing Prescribing Patterns and Resistance in Elderly Populations and Patients with Decompensated Liver Cirrhosis

Background: Antimicrobial resistance (AMR) is a global health threat, which is particularly devastating in the elderly as a result of multisource chronic diseases, immune senescence, and intense exposure to antibiotics. Antimicrobial stewardship (AMS) is crucial to address inappropriate prescribing and resultant adverse events but it is restricted in older people's care. The purpose of this article was to consider the contributions to AMS and the tools for driving next steps toward the optimized use, and minimized resistance, and best patient outcomes given the role of the pharmacist and a public health framework, especially regarding our older adults.  Methods: A narrative synthesis approach to review of published information and international guidelines was undertaken, with specific attention to how to prescribe in older patients, antibiotic related toxicities, stewardship strategies across typical infections, the role of the pharmacist, and wider public health in AMS.  Results: Investigators assessed the difficulty of prescribing of aging adult by identifying comorbidities, poly-medications, and changed pharmacokinetics along with the most common adverse reactions, including gastrointestinal, neurologic, renal, hepatic, cardiovascular, and hematologic toxicities. AMS strategies, including biomarker inclusive initiation, compliance with guidelines, de-escalation, intravenous substitution and shorter duration were uniformly associated with favorable outcomes. Pharmacists are also central to the continuation of safe, evidence-based prescribing and medication education, pharmacotherapy management, and hospital drug reconciliation, andwork in concert with public health measures to support stewardship through surveillance, infection prevention, and public awareness efforts. Taken together these initiatives form a comprehensive approach for addressing the misuse and resistance to antibiotics.  Conclusion: Integrating pharmacists’ clinical expertise with public health stewardship frameworks is paramount for combating AMR in elderly patients. Collaborative, patient-based AMS strategies focussing on elderly care are effective in decreasing bad events, preserving the effect of antibiotics and promoting individual and societal health.
A review: Malay speech recognition and audio visual speech recognition

Automatic speech recognition (ASR) is an area of research which deals with the recognition of speech by machine in several conditions. ASR performs well under restricted conditions (quiet environment), but performance degrades in noisy environments. This paper presents a brief survey on Automatic Speech Recognition on Malays Corpus and multi-modal speech recognition on others Corpus. The audio only speech recognition has been done by many researchers few decades. After years of research and development the performance of automatic speech recognition remains one of the important research challenges (eg., variations of the context, database, and environment). The criteria for designing Speech Recognition system are pre-processing filter, end-point detection, feature extraction techniques, speech classifiers, database, and performance evaluation. The existing problems that are in Automatic Speech Recognition (ASR)-noise environments and the various techniques to solve these problems had constructed. The objective of this review paper is to summarize and compare some of the well know methods used by previous researcher.
Interpretations of Directed Information in Portfolio Theory, Data Compression, and Hypothesis Testing

We investigate the role of Massey's directed information in portfolio theory, data compression, and statistics with causality constraints. In particular, we show that directed information is an upper bound on the increment in growth rates of optimal portfolios in a stock market due to {causal} side information. This upper bound is tight for gambling in a horse race, which is an extreme case of stock markets. Directed information also characterizes the value of {causal} side information in instantaneous compression and quantifies the benefit of {causal} inference in joint compression of two stochastic processes. In hypothesis testing, directed information evaluates the best error exponent for testing whether a random process $Y$ {causally} influences another process $X$ or not. These results give a natural interpretation of directed information $I(Y^n \to X^n)$ as the amount of information that a random sequence $Y^n = (Y_1,Y_2,..., Y_n)$ {causally} provides about another random sequence $X^n = (X_1,X_2,...,X_n)$. A new measure, {\em directed lautum information}, is also introduced and interpreted in portfolio theory, data compression, and hypothesis testing.
การประเมินพื้นที่เกษตรในเมืองระดับชุมชนเพื่อความมั่นคงทางอาหาร :  กรณีศึกษาสวนดาดฟ้าอาคารพักอาศัยแปลง G ชุมชนดินแดง (Assessment of urban agricultural areas for food security:  A case study of the rooftop gardens of a residential building, Plot G,  Din Daeng community)

จากการพัฒนาเมืองแบบแยกการใช้ประโยชน์ที่ดินของกรุงเทพมหานคร ทำให้พื้นที่เกษตรกรรมถูกแยกออกจากพื้นที่เมือง และถูกกำหนดให้อยู่ในพื้นที่ชานเมืองที่ห่างไกล หากเกิดวิกฤตที่ส่งผลกระทบต่อการขนส่ง เมืองอาจเสี่ยงที่จะขาดความมั่นคงทางอาหารได้ ปัญหาดังกล่าวส่งผลให้เกษตรในเมืองจึงมีความสำคัญต่อความมั่นคงทางอาหารของเมือง ซึ่งงานวิจัยครั้งนี้ มีวัตถุประสงค์เพื่อประเมินพื้นที่เกษตรกรรมในเมืองระดับชุมชน กรณีศึกษา สวนดาดฟ้าอาคารพักอาศัยแปลง G ชุมชนดินแดง โดยใช้วิธีการเก็บข้อมูลจากแบบสอบถามกลุ่มผู้อยู่อาศัยในโครงการฯ รวมจำนวน 286 ชุด และเก็บข้อมูลจากการสัมภาษณ์กลุ่มผู้ดูแลสวนผักชั้นดาดฟ้า จำนวน 5 ราย เจ้าหน้าที่การเคหะแห่งชาติ ผู้ดูแลโครงการฟื้นฟูเมืองชุมชนดินแดง จำนวน 1 ราย รวมถึงนำเสนอผลการวิเคราะห์ข้อมูลแบบสอบถามด้วยวิธีการทางสถิติ ได้แก่ ค่าร้อยละ ค่าเฉลี่ย และค่าคะแนนการประเมินความมั่นคงทางอาหารของผู้อยู่อาศัยในโครงการฯ รวมทั้งวิเคราะห์ข้อมูลแบบสัมภาษณ์ด้วยวิธีสรุปความ ซึ่งผลการวิจัย พบว่า การจัดให้มีสวนผักชั้นดาดฟ้าอาคารพักอาศัยแปลง G ไม่สามารถยกระดับความมั่นคงทางอาหารของกลุ่มตัวอย่าง ผู้อยู่อาศัยในโครงการฯ ได้ โดยได้คะแนนการประเมินอยู่ในเกณฑ์ปานกลางเกือบทุกมิติ และได้คะแนนการประเมินปัจจัยย่อยด้านการเข้าถึงพื้นที่สวนผักชั้นดาดฟ้า ด้านความหลากหลายทางอาหาร และด้านความปลอดภัยทางอาหาร อยู่ในเกณฑ์ควรปรับปรุง ทั้งนี้ ผลการวิจัยที่ได้สามารถใช้เป็นข้อมูลประกอบการพิจารณาประยุกต์ใช้ในการจัดให้มีพื้นที่เกษตรกรรมชุมชนหรือพื้นที่สีเขียวประเภทกินได้ในโครงการฟื้นฟูเมืองชุมชนดินแดงและชุมชนอื่น ๆ ต่อไป Urban development with land-use segregation in Bangkok has led to the separation of agricultural areas from urban zones, relegating them to the peripheral zones. In the event of a crisis affecting transportation, the city may face risks of food insecurity. This issue highlights the importance of urban agriculture in ensuring food security within the city. This research aims to assess urban agricultural areas at the community level, focusing on the case study of the rooftop gardens in the residential building, Plot G, of Din Daeng community. Data collection was conducted through questionnaires from 286 residents. Additionally, interviews were conducted with five rooftop vegetable garden caretakers and a project manager of the National Housing Authority. The questionnaire data were analyzed using statistical methods, including percentages, means, and food security assessment scores of the residents. The findings indicate that the rooftop gardens in the residential building, Plot G, did not significantly enhance food security among residents, with most scores falling within the moderate range. Sub-factors such as access to rooftop gardens, food diversity, and food safety were identified as areas requiring improvement. The findings from both the questionnaires and interviews provide valuable insights for guiding implementation of urban agricultural spaces or edible green areas in future urban renewal projects and other communities.
Whole Slide Preview Image Segmentation and Setup for Digital Pathology Scanners

Abstract                 The problem of tissue finding is of special interest in automating WSI scanners where it decomposes the preview image of tissue glass slides into a simplified and abstract level of localization and identification to setup WSI scanner for high-resolution scan. Prior to such scanning, a preview image is captured to calibrate the scanner’s parameters. Scan parameters such as focus depth and scan region are determined using a tissue finding software package. This paper introduces a series of pipelines (e.g. binary mask segmentation, tissue/artifact classification, region-of-interest allocation) to automate tissue preview segmentation in both brightfield and darkfield microscopy.
Aligning Language Models Using Follow-up Likelihood as Reward Signal

In natural human-to-human conversations, participants often receive feedback signals from one another based on their follow-up reactions. These reactions can include verbal responses, facial expressions, changes in emotional state, and other non-verbal cues. Similarly, in human-machine interactions, the machine can leverage the user's follow-up utterances as feedback signals to assess whether it has appropriately addressed the user's request. Therefore, we propose using the likelihood of follow-up utterances as rewards to differentiate preferred responses from less favored ones, without relying on human or commercial LLM-based preference annotations. Our proposed reward mechanism, ``Follow-up Likelihood as Reward" (FLR), matches the performance of strong reward models trained on large-scale human or GPT-4 annotated data on 8 pairwise-preference and 4 rating-based benchmarks. Building upon the FLR mechanism, we propose to automatically mine preference data from the online generations of a base policy model. The preference data are subsequently used to boost the helpfulness of the base model through direct alignment from preference (DAP) methods, such as direct preference optimization (DPO). Lastly, we demonstrate that fine-tuning the language model that provides follow-up likelihood with natural language feedback significantly enhances FLR's performance on reward modeling benchmarks and effectiveness in aligning the base policy model's helpfulness.
VLS: Steering Pretrained Robot Policies via Vision-Language Models

Why do pretrained diffusion or flow-matching policies fail when the same task is performed near an obstacle, on a shifted support surface, or amid mild clutter? Such failures rarely reflect missing motor skills; instead, they expose a limitation of imitation learning under train-test shifts, where action generation is tightly coupled to training-specific spatial configurations and task specifications. Retraining or fine-tuning to address these failures is costly and conceptually misaligned, as the required behaviors already exist but cannot be selectively adapted at test time. We propose Vision-Language Steering (VLS), a training-free framework for inference-time adaptation of frozen generative robot policies. VLS treats adaptation as an inference-time control problem, steering the sampling process of a pretrained diffusion or flow-matching policy in response to out-of-distribution observation-language inputs without modifying policy parameters. By leveraging vision-language models to synthesize trajectory-differentiable reward functions, VLS guides denoising toward action trajectories that satisfy test-time spatial and task requirements. Across simulation and real-world evaluations, VLS consistently outperforms prior steering methods, achieving a 31% improvement on CALVIN and a 13% gain on LIBERO-PRO. Real-world deployment on a Franka robot further demonstrates robust inference-time adaptation under test-time spatial and semantic shifts. Project page: https://vision-language-steering.github.io/webpage/
Pharmacoepigenomics in Personalized Medicine: A Hypothesis-Generating Approach to Introduce CpG-PGx SNPs as New Candidates for a Systematic Insight into Genomic-Epigenomic-Phenomic-Pharmacogenomics (G-E-Ph-PGx) Axis

Background: There are important gaps in describing the associations between variants found by GWAS and various phenotypes. Prior reports suggest that SNPs in regulatory regions should be further investigated to uncover these associations. Thus, this study involved a novel approach, along with Pharmacoepigenomics, prompting a new coined term “CpG-PGx SNP”. Methods: The rationale behind our analysis strategy was based on the impact of SNPs playing dual roles both in the CpG site disruption/formation and having PGx associations. Thus, we employed GeneCards (relevance score), PharmGKB (significant p-value), and GWAS catalog data for each gene (p &lt; 5 × 10−8). Following the obtainment of the 25 best-scored genes of four major epigenetic processes (methylation, demethylation, acetylation, and deacetylation), we generated two lists of candidate genes, including potential CpG-PGx SNPs and possible CpG-PGx SNPs. Results: Among 2900 significant PGx annotations, we found 99 potential CpG-PGx SNPs related to 16 genes. CYP2B6, CYP2C19, CYP2D6, and COMT genes were the top genes. Additionally, we found 1230 significant GWAS-based SNPs, among them 329 CpG-SNPs related to 48 genes with at least one CpG site disruption/formation. The top gene with the highest CpG-SNPs was TET2, followed by JMJD1C and HDAC9. Importantly, we detected some synonymous variants in the Epigenetically Modifiable Accessible Region (EMAR), which can provide insights into undiscovered roles of these SNPs. We identified 173 CpG-Disruptive SNPs, 155 CpG-Forming SNPs, and just 1 CpG SNP with both impacts. Conclusions: In conclusion, here we introduce CpG-PGx SNP for the first time and suggest three major genes playing crucial roles in Pharmacoepigenomics (PEpGx), CYP2D6 as the heart of PEpGx, and TET2 with the highest possibility of having CPG-PGx SNPs. We believe that this approach will help the scientific community to utilize “CpG-PGx SNP” to unravel complex disease-driven genetic and epigenetic interactions, yielding therapeutic opportunities.
A study to identify leadership style of nurse managers and influence of leadership style on patient safety culture, organizational citizenship behavior, and job satisfaction so as to suggest an evidence based feed forward for preparing guidelines for training of nurse managers working in a superspecialty tertiary health care teaching institute in Northern India

Introduction:             The safety of patients in health-care systems has long been a concern, but despite many positive changes in practice, health systems, and regulations, the desired level of safety remains unachieved. The competency of health-care leaders to create positive work environments and manage constant change is essential to the success of teams and organizations. The need for great leadership in health care has always been imperative; however, throughout the industry's recent transformation, it has been vital. Faced with enormous amounts of change, today's leaders must be capable of serving their teams while adapting to the evolving landscape and leading us into the future.                                   Aim:             The aim of this study was to identify the leadership style of nurse managers and ascertain the influence of leadership style on patient safety culture, organizational citizenship behavior, and job satisfaction so as to suggest an evidence-based feed forward for preparing guidelines for training of nurse managers working in a superspecialty tertiary health-care teaching institute in Northern India.                                   Objectives:             The objectives of this study were as follows – (1) to identify the leadership style of nurse managers based on full-range leadership model using the prevalidated tool, (2) to ascertain the influence of leadership style on patient safety culture using the prevalidated tool, (3) to assess the influence of leadership style on organizational citizenship behavior and job satisfaction using the prevalidated tool, and (4) to suggest an evidence-based feed forward for preparing guidelines for training of nurse managers working in a superspecialty health-care teaching institute in India using analysis of data thus obtained.                                   Methodology:             This was an analytical study.                                   Results:             (1) In the study, it was thus found that as transformational and transactional leadership behavior increases, patient safety culture, organizational citizenship behavior, and job satisfaction also increase; (2) on the other hand, patient safety culture, organizational citizenship behavior, and job satisfaction decrease as laissez-faire leadership behavior increases.                                   Conclusion:             Staff nurse under the leadership of their managers provides exemplary care and shares professional knowledge as well as provides direction and support to practice best patient care through policy development.