ethicalabs/Research-Intent-Collab huggingface dataset:
Equivariant graph neural networks in drug discovery: from property prediction to molecule generation

Advancements in machine learning have revolutionized various aspects of drug discovery, from molecular property prediction to de novo design. This thesis presents a comprehensive exploration of equivariant graph neural networks (EGNNs) and their applications in critical areas of computational drug discovery, specifically focusing on property prediction, molecular representation learning, and structure-based de novo ligand design. Toxicity prediction is a critical early-stage filter in drug development. Traditional methods often rely on text-based or 2D representations or simplified 3D models, potentially missing crucial structural information. We hypothesized that full 3D molecular structures in form of ensembles of high-quality conformers could significantly improve toxicity predictions. Next, we explored the de novo molecule generation resulting in the development of an diffusion-based equivariant graph neural network, EQGAT-diff. This framework represents a significant advancement in molecular generation, incorporating both Gaussian and discrete state space diffusion techniques. A key innovation in EQGAT-diff is its timestep-dependent loss weighting scheme, which dramatically improves both training and inference efficiency. Building on the insights and capabilities of EQGAT-diff, we tackled the challenge of structure-based drug design. The result is PILOT, an equivariant diffusion model for de novo 3D ligand generation conditioned on protein pockets. Its multi-objective trajectory-based importance sampling allows for the simultaneous optimization of multiple properties, including binding affinity, synthetic accessibility or toxicity. Finally, we propose PoliGenX, a model based on EQGAT-diff that is conditioned not only on a protein's pocket, but also on parallely learned latent embeddings of seed molecules. We envision the usage of PoliGenX in hit expansion campaigns. We show that it successfully preserves shape similarity with seed molecules, while still being able to chemically diversify them in a de novo fashion.
Comparative Cost-effectiveness of Robot-assisted and Standard Laparoscopic Prostatectomy as Alternatives to Open Radical Prostatectomy for Treatment of Men with Localised Prostate Cancer: A Health Technology Assessment from the Perspective of the UK National Health Service

Robot-assisted laparoscopic prostatectomy is increasingly used compared with a standard laparoscopic technique, but it remains uncertain whether potential benefits offset higher costs.To determine the cost-effectiveness of robotic prostatectomy.We conducted a care pathway description and model-based cost-utility analysis. We studied men with localised prostate cancer able to undergo either robotic or laparoscopic prostatectomy for cure. We used data from a meta-analysis, other published literature, and costs from the UK National Health Service and commercial sources.Care received by men for 10 yr following radical prostatectomy was modelled. Clinical events, their effect on quality of life, and associated costs were synthesised assuming 200 procedures were performed annually.Over 10 yr, robotic prostatectomy was on average (95% confidence interval [CI]) £1412 (€1595) (£1304 [€1473] to £1516 [€1713]) more costly than laparoscopic prostatectomy but more effective with mean (95% CI) gain in quality-adjusted life-years (QALYs) of 0.08 (0.01-0.15). The incremental cost-effectiveness ratio (ICER) was £18 329 (€20 708) with an 80% probability that robotic prostatectomy was cost effective at a threshold of £30 000 (€33 894)/QALY. The ICER was sensitive to the throughput of cases and the relative positive margin rate favouring robotic prostatectomy.Higher costs of robotic prostatectomy may be offset by modest health gain resulting from lower risk of early harms and positive margin, provided >150 cases are performed each year. Considerable uncertainty persists in the absence of directly comparative randomised data.
Conservation and management of biodiversity in Pakistan through the establishment of marine protected areas

Marine protected area (MPA) is an area in the coastal zone of land or sea specially dedicated to protection and maintenance of biological diversity and of natural and associated cultural resources, and managed through legal or other effective means. In this paper a need for designating MPAs in Pakistan is presented on the basis of case studies on mangroves and its ecosystem, corals and coral reef fishes, marine turtles, whales and dolphins, and planktons and pelagic environment. This paper reflects that there are a number of species and habitat that require conservation and for this purpose designation of marine protected areas along the coast of Pakistan is inevitable. MPAs would ensure better management of marine ecosystem and environment. This is also linked with the economic and social stability provided by the sustainable use of resources. The need is also in line with commitment of the Government of Pakistan under the International Biodiversity Convention to establish MPAs in Pakistan. At least nine sites are identified as potential candidates for MPAs. Some of which have more than one important commodity that needs to be preserved. Three main sites suggested for immediate designation of MPA are Indus Delta, Astola Island and Miani Hor (Sonmiani Bay).
Tabletop Roleplaying Games as Procedural Content Generators

Tabletop roleplaying games (TTRPGs) and procedural content generators can both be understood as systems of rules for producing content. In this paper, we argue that TTRPG design can usefully be viewed as procedural content generator design. We present several case studies linking key concepts from PCG research -- including possibility spaces, expressive range analysis, and generative pipelines -- to key concepts in TTRPG design. We then discuss the implications of these relationships and suggest directions for future work uniting research in TTRPGs and PCG.
Comparison of Protein Force Fields for Molecular Dynamics Simulations

In the context of molecular dynamics simulations of proteins, the term "force field" refers to the combination of a mathematical formula and associated parameters that are used to describe the energy of the protein as a function of its atomic coordinates. In this review, we describe the functional forms and parameterization protocols of the widely used biomolecular force fields Amber, CHARMM, GROMOS, and OPLS-AA. We also summarize the ability of various readily available noncommercial molecular dynamics packages to perform simulations using these force fields, as well as to use modern methods for the generation of constant-temperature, constant-pressure ensembles and to treat long-range interactions. Finally, we finish with a discussion of the ability of these force fields to support the modeling of proteins in conjunction with nucleic acids, lipids, carbohydrates, and/or small molecules.
Regenerative Medicine/Cardiac Cell Therapy: Pluripotent Stem Cells

AbstractFor more than 20 years, tremendous efforts have been made to develop cell-based therapies for treatment of heart failure. However, the results of clinical trials using somatic, nonpluripotent stem or progenitor cells have been largely disappointing in both cardiology and cardiac surgery scenarios. Surgical groups were among the pioneers of experimental and clinical myocyte transplantation (“cellular cardiomyoplasty”), but little translational progress was made prior to the development of cellular reprogramming for creation of induced pluripotent stem cells (iPSC). Ever since, protocols have been developed which allow for the derivation of large numbers of autologous cardiomyocytes (CMs) from patient-specific iPSC, moving translational research closer toward clinical pilot trials. However, compared with somatic cell therapy, the technology required for safe and efficacious pluripotent stem cell (PSC)-based therapies is extremely complex and requires tremendous resources and close interactions between basic scientists and clinicians. This review summarizes PSC sources, strategies to derive CMs, current cardiac tissue engineering approaches, concerns regarding immunogenicity and cellular maturity, and highlights the contributions made by surgical groups.
High Quality Designing Of Sinter Based Additively Manufactured (3D Printing) Degradable Magnesium-Gadolinium Scaffolds For Biomedical Implant Applications

The integration of 3D printing and Mg-5Gd alloys is revolutionizing biomedical applications, particularly in scaffolds for bone implants. Scaffolds facilitate bone growth and repair, requiring precise fabrication to achieve a balanced degradation rate that aligns with bone regeneration while maintaining mechanical support during healing. This study optimizes 3D printing parameters for Mg-5Gd alloy feedstock (40 vol.% binder loading) to produce high-quality magnesium structures with controlled degradation rates. Key parameters, including printing speed, extrusion rate, layer thickness, and post-processing techniques, were refined to achieve dense discs and scaffolds with pore sizes of 700–1250 µm, matching cortical bone structure. Using a 0.3 mm nozzle and printing speeds of 10–20 mm|s, structures with densities up to 97% and degradation rates below 1 mm|year were achieved. Results demonstrate that scaffold degradation rates can be tailored by adjusting geometry, pore size, and wall thickness, showcasing AM potential to advance regenerative medicine and biomedical implants.
IMPLEMENTING THE INTERNATIONAL “RESPONSIBILITY TO PROTECT”: A SOCIOLOGICAL CASE STUDY OF THE INSTITUTIONAL PRACTICES OF THE UNITED STATES DEPARTMENT OF DEFENSE TOWARD OPERATIONALIZING HUMANITARIAN INTERVENTION

The concept of Responsibility to Protect (R2P) was promulgated by the United Nations in 2001 to address the issue of military intervention in the case of gross and systematic violations of human rights by a state to prevent large scale loss of life. This issue reflects a greater international focus on protection of civilians to prevent future atrocities. My research examines how the key departments in the executive branch, specifically, the Department of State (DOS), US Agency for International Development (USAID) and the Department of Defense (DOD), have changed policy doctrine and procedures to incorporate these R2P related norms into United States Government (USG) practices between 2001 and 2016. In assessing the extent to which these norms have become institutionally embedded, I address the following questions: (1) What is the institutional environment in which the USG negotiates its mandates regarding the implementation of R2P? (2) How do the distinct institutional cultures of DOS, USAID and particularly the DOD, shape and influence positions on military intervention into humanitarian crises? (3) What is the relationship between the DOD (and its various offices) and the other US departments and agencies as well as civil society with which it works to implement R2P? (4) What processes, procedures and action has the USG implemented to help operationalize R2P? (5) How has the USG institutional action and thinking (focused primarily on DOD and DOS) changed over time, from the emergence of R2P through two US administrations?
Efficient surrogate models for materials science simulations: Machine learning-based prediction of microstructure properties

Determining, understanding, and predicting the so-called structure-property relation is an important task in many scientific disciplines, such as chemistry, biology, meteorology, physics, engineering, and materials science. Structure refers to the spatial distribution of, e.g., substances, material, or matter in general, while property is a resulting characteristic that usually depends in a non-trivial way on spatial details of the structure. Traditionally, forward simulations models have been used for such tasks. Recently, several machine learning algorithms have been applied in these scientific fields to enhance and accelerate simulation models or as surrogate models. In this work, we develop and investigate the applications of six machine learning techniques based on two different datasets from the domain of materials science: data from a two-dimensional Ising model for predicting the formation of magnetic domains and data representing the evolution of dual-phase microstructures from the Cahn-Hilliard model. We analyze the accuracy and robustness of all models and elucidate the reasons for the differences in their performances. The impact of including domain knowledge through tailored features is studied, and general recommendations based on the availability and quality of training data are derived from this.
A directed persistent homology theory for dissimilarity functions

We develop a theory of persistent homology for directed simplicial complexes which detects persistent directed cycles in odd dimensions. We relate directed persistent homology to classical persistent homology, prove some stability results, and discuss the computational challenges of our approach. Our directed persistent homology theory is motivated by homology with semiring coefficients: by explicitly removing additive inverses, we are able to detect directed cycles algebraically.
Nurses’ Shift Length and Overtime Working in 12 European Countries

Despite concerns as to whether nurses can perform reliably and effectively when working longer shifts, a pattern of two 12- to 13-hour shifts per day is becoming common in many hospitals to reduce shift to shift handovers, staffing overlap, and hence costs.To describe shift patterns of European nurses and investigate whether shift length and working beyond contracted hours (overtime) is associated with nurse-reported care quality, safety, and care left undone.Cross-sectional survey of 31,627 registered nurses in general medical/surgical units within 488 hospitals across 12 European countries.A total of 50% of nurses worked shifts of ≤ 8 hours, but 15% worked ≥ 12 hours. Typical shift length varied between countries and within some countries. Nurses working for ≥ 12 hours were more likely to report poor or failing patient safety [odds ratio (OR)=1.41; 95% confidence interval (CI), 1.13-1.76], poor/fair quality of care (OR=1.30; 95% CI, 1.10-1.53), and more care activities left undone (RR=1.13; 95% CI, 1.09-1.16). Working overtime was also associated with reports of poor or failing patient safety (OR=1.67; 95% CI, 1.51-1.86), poor/fair quality of care (OR=1.32; 95% CI, 1.23-1.42), and more care left undone (RR=1.29; 95% CI, 1.27-1.31).European registered nurses working shifts of ≥ 12 hours and those working overtime report lower quality and safety and more care left undone. Policies to adopt a 12-hour nursing shift pattern should proceed with caution. Use of overtime working to mitigate staffing shortages or increase flexibility may also incur additional risk to quality.
Pharmacological Prescription at the End of Life: Quality Assessment in the Transition of Care to a Community Palliative Care Support Team

Appropriate pharmacological management is a cornerstone of quality in palliative care (PC), focusing on comfort and quality of life. Therapeutic review is crucial in PC, aiming to optimize symptom relief, reduce adverse effects, and manage drug interactions. This study aims to delve into the real-world pharmacological prescription practices within a Community Palliative Care Support Team (CPCST) in the northern region of Portugal, comparing practices at admission and at the last consultation before death. It is an observational, cross-sectional, retrospective study without intervention involving patients admitted to a CPCST in 2021. Data were obtained from clinical records, and the statistical analysis included descriptive and inferential measures. Sixty-four patients were included, with an average age of 77.34 years, referred mainly by a specialized Hospital Palliative Care Support Team (65.63%). Polypharmacy was present, with a significant increase in opioids, antipsychotics, prokinetics, antiemetics, antispasmodics, and local corticosteroids, and a reduction in drugs for peptic ulcer and gastroesophageal reflux treatment, antithrombotics, hypolipidemics, antihypertensives, and antidiabetics, among others. The oral route was preferred, decreasing between the two analyzed moments (85.5% versus 49.1%). Pro re nata (PRN) medications increased significantly (p ≤ 0.001). The prescription profile reflects a focus on symptom relief. The deprescription of drugs for chronic comorbidities suggests adaptation to care goals. At the end of life, PRN medications increase significantly (1.34 versus 3.26, p ≤ 0.001), administered as needed to soothe fluctuating symptoms. The pharmacological classes that have significantly increased are relevant in alleviating common symptoms in PC. The use of alternative routes for medication administration increases as instability of the oral route occurs, leading to a reduction in orally administered medications. Among these alternatives, the subcutaneous route shows the largest increase. The findings underscore the importance of flexible and responsive medication strategies in end-of-life care.
DATA MESH ARCHITECTURE: DECENTRALIZED DOMAIN OWNERSHIP AND FEDERATED GOVERNANCE AS A SOLUTION TO ENTERPRISE DATA PLATFORM SCALABILITY

Enterprise data platforms have reached a fundamental scalability ceiling under centralized architectures. Asorganizations accumulate data across dozens of business domains, the traditional paradigm of a central dataengineering team managing a monolithic data warehouse or data lake creates an irreducible bottleneck: deliveryvelocity slows, data quality degrades, and domain context is systematically lost in translation between subjectmatter experts and data engineers. This paper presents a rigorous technical examination of Data Mesh - asociotechnical architecture introduced by Zhamak Dehghani - as a first-principles solution to enterprise dataplatform scalability. We analyze its four foundational pillars:1) Domain-oriented decentralized data ownership,2) Data as a product,3) Self-serve data infrastructure, and4) Federated computational governance.We examine reference implementation patterns using Apache Kafka, Apache Spark, DBT, and cloud-native objectstorage; evaluate governance mechanisms balancing local autonomy with global compliance requirements(GDPR, CCPA); and present a comparative performance analysis between monolithic and Data Meshdeployments across five enterprise scalability dimensions. Our findings demonstrate that organizations adoptingData Mesh principles report 60–80% reductions in data product delivery time, 45% improvements in data qualityscores, and near-linear scaling of data platform capacity relative to organizational growth. We conclude that DataMesh represents not merely an architectural pattern but a fundamental paradigm shifts in how enterprisesconceptualize data ownership, accountability, and scalability.
Sparse Signal Representation, Sampling, and Recovery in Compressive Sensing Frameworks

يسمح الاستشعار الانضغاطي بإعادة بناء الإشارات الأصلية من عدد أقل بكثير من العينات مقارنة بمعدل أخذ العينات في نيكويست. حفزت فعالية الاستشعار الانضغاطي الباحثين لنشرها في مجموعة متنوعة من مجالات التطبيق. يحسن استخدام مصفوفة أخذ العينات الفعالة لخوارزميات الاسترداد عالية الأداء أداء إطار الاستشعار الانضغاطي بشكل كبير. تعرض هذه الورقة المفاهيم الأساسية للاستشعار الانضغاطي بالإضافة إلى العمل السابق المنجز في المجالات المستهدفة وفقًا لمجالات التطبيق المختلفة. ولتطوير الآفاق ضمن الكتل الوظيفية المتاحة لأطر الاستشعار الانضغاطي، يتم التحقيق في مجموعة متنوعة من مجالات التطبيق. تتم مراجعة العناصر الأساسية الثلاثة لإطار الاستشعار الانضغاطي (تباين الإشارات، وأخذ العينات الفرعية، وإعادة البناء) بدقة في هذا العمل من خلال التعرف على الفجوات البحثية الرئيسية التي حددها مجتمع البحث سابقًا. وبالمثل، يتم استخدام الصيغة الرياضية الأساسية لتحديد بعض مقاييس تقييم الأداء الأولية للاستشعار الانضغاطي 1D و 2D.
One world, one health

From the point of view that all organisms and the environment share one health, expending effort to address the needs of animals and ecosystems might pay better dividends for human health in the longer term.
OPTIMIZING WORKPLACE SAFETY: THE VITAL ROLE OF OCCUPATIONAL HEALTH AND SAFETY COMMITTEES IN PREVENTING AND REDUCING WORK-RELATED ACCIDENTS AND ILLNESSES IN KOTA BUKIT INDAH INDUSTRIAL ESTATE PURWAKARTA, INDONESIA

Abstract  Currently, the industrial sector in Indonesia is developing very rapidly in line with advances in science and technology. The use of technology in the industrial world also varies greatly from simple technology to complex technology. However, even though a culture of occupational safety and health has been promoted since half a century ago, work accidents in Indonesia are still relatively high. Recognizing that the involvement of workers in the workplace can be achieved, among others, through having representatives of the workforce in implementing occupational safety and health and establishing an Occupational Safety and Health organization. So, the Government issued Minister of Manpower Regulation number 4 of 1987 concerning Occupational Safety and Health Advisory Committee and Procedures for Appointing Work Safety Experts, Article 1 (d) explained that what is meant by the Occupational Safety and Health Advisory Committee, hereinafter referred to as Occupational Safety and Health Advisory Committee. The Occupational Safety and Health Advisory Committee is an auxiliary body in the workplace which is a forum for cooperation between employers and workers to develop cooperative mutual understanding and effective participation in the implementation of occupational safety and health. However, until now in the implementation of occupational safety and health, a competency system has not been developed that includes the roles and duties of each Occupational Safety and Health Advisory Committee team, including the Chair of Occupational Safety and Health Advisory Committee and members of Occupational Safety and Health Advisory Committee. Even though the competency system is needed so that the implementation of an occupational safety and health management system can be carried out quickly and effectively to minimize the impact of work accidents that may occur in the company.
Would You Like to be a Prosumer? Information Revelation, Personalization and Price Discrimination in Electronic Markets

Abstract Electronic commerce and flexible manufacturing allow personalization of initially standardized products at low cost. Will customers provide the information necessary for personalization? Assuming that a consumer can control the amount of information revealed, we analyze how her decision interacts with the pricing strategy of a monopolist who may abuse the information to obtain a larger share of total surplus. We consider two scenarios, one where consumers have different tastes but identical willingness to pay and another with high and low valuation customers. In both cases full revelation may only result if the monopolist can commit to a maximum price before consumers decide about disclosure.
A sample treatment of Langevin-type stochastic differential equations

AbstractA sample treatment of stochastic differential equations of the Langevin type is presented. It is shown that the formal mean square solutions of these equations are, in a certain sense, consistent with the solutions obtained based upon a sample theoretic approach. The procedure adopted in this development is to first construct an explicit sequence of Gaussian processes which approach in the limit the Brownian motion process. With derivatives of these processes as inputs to linear differential equations, we show that these equations possess solutions in the sample sense. These solutions are then shown to converge to the formal mean square solution of a differential equation having as input the white noise or the formal derivative of the Brownian motion process.