ethicalabs/Research-Intent-Collab huggingface dataset:
Increasing the number of adults on a palliative care end‑of‑life register: a quality improvement project

Background/Aims Identifying patients at the end of life can facilitate easier access to support and reduce unnecessary emergency care admissions. This study aimed to increase the number of adults on the palliative and end-of-life care register by at least 10% in 20% of primary care practices in an English integrated care system. Methods A quality improvement project was carried out, using the Model for Improvement, with plan-do-study-act cycles. A hospice within a UK integrated care system added standard wording and system codes to letters sent to patients’ primary care provider. The number of patients on the palliative and end-of-life care register was monitored monthly between September 2022 and April 2023. Results By the end of the study period, the number of patients on the palliative and end-of-life care register had increased by &gt;10% in 20% of practices. Conclusions Adding a recommendation to add a patient to palliative and end-of-life care registers on letters sent to primary care providers can lead to an increase in the number of patients being identified to be in the last year of their life.
Data Localization, AI Governance, and Digital Sovereignty in Emerging Economies

This chapter addresses that analytical fragmentation by developing a comparative framework through which localization rules, AI governance instruments, and sovereignty claims are examined as mutually conditioning layers of digital statecraft rather than as isolated legal categories. A structured review of an uploaded Scopus corpus, which contained 139 records, was combined with a comparative analysis of India, Indonesia, Kenya, and Brazil, alongside official instruments issued by the African Union, UNESCO, the OECD, and NIST. The analysis demonstrates that broad territorial restrictions on data do not by themselves produce operational digital sovereignty; durable sovereignty is achieved when selective localization is aligned with data classification, compute and cloud capacity, risk-based AI governance, and interoperable cross-border transfer mechanisms.
Cosmological Magnetic Fields from Primordial Helicity

Primordial magnetic fields may account for all or part of the fields observed in galaxies. We consider the evolution of the magnetic fields created by pseudoscalar effects in the early universe. Such processes can create force-free fields of maximal helicity; we show that for such a field magnetic energy inverse cascades to larger scales than it would have solely by flux freezing and cosmic expansion. For fields generated at the electroweak phase transition, we find that the predicted wavelength today can in principle be as large as 10 kpc, and the field strength can be as large as 10^{-10} G.
Rationing of nursing care : associations with patient safety and quality of hospital care

On the basis of nurse reports indicating the occurrence of implicit rationing of nursing care in Swiss hospitals, the Swiss Federal Office of Public Health asked the Institute of Nursing Science of the University of Basel to conduct the Rationing of Nursing Care in Switzerland Study (RICH Nursing Study). The resulting study is an extension of the International Hospital Outcomes Study (IHOS), an international study of the organization of nursing care in hospitals and its impact on patient outcomes [1-3]. The IHOS study is led by the Center for Health Outcomes and Policy Research at the University of Pennsylvania (USA). The RICH Nursing study, and with it the research program of this dissertation, extended the IHOS research protocol by developing a new empirical measure of implicit rationing of nursing care. This thesis is comprised of ten chapters. Chapters 3 and 5-9 have been published or submitted as individual articles. Therefore, some repetition in the description of the background and methodology could not be avoided. The first three chapters describe the thesis’ background, its aims, and the available evidence on effects of cost saving strategies and changes in staffing levels and skill mixes on patient and nurse outcomes. • Chapter 1 gives a literature based overview of relevant developments in the healthcare system, including cost saving strategies, reductions of nursing resources, and their effects on patient and nurse outcomes • Chapter 2 describes the aims of this research program • Chapter 3 is a literature review and analysis, examining the available evidence on the effects of cost saving strategies and changes in staffing levels and skill mix in the inpatient care setting on selected patient and nurse outcomes. Chapters 4 and 5 explore the first two aims of this research program – to develop a conceptual framework of implicit rationing of nursing care, as well as an instrument to measure it as an empirical factor, and to evaluate the psychometric properties of the newly developed instrument. • ...
Unbiased orbit determination for the next generation asteroid/comet surveys

In the next generation surveys, the discovery of moving objects can be successful only if an observation strategy and the identication/orbit determination procedure are appropriate for the diverse apparent motions of the target sub-populations. The observations must accurately measure the displacement over a short interval of time; observations believed to belong to the same object have to be connected into tracklets. Information contained in tracklets is in most cases not sucien t to compute an orbit: two or more of them must be identie d to provide an orbit. We have developed a method for recursive identication of tracklets allowing an unbiased orbit determination for all sub-populations and ecien t enough to cope with the data o w expected from the next generation surveys. The success of the new algorithms can be easily measured only in a simulation, by consulting a posteriori some \ground truth". We present here the results of a simulation of the orbit determination for one month of oper- ations of the future Pan-STARRS survey, based upon a Solar System Model with a downsized population of Main Belt asteroids and a full size populations of Trojans, NEO, Centaurs, Comets and TNO. The results indicate that the method already developed and tested to nd identi- cations of NEO and Main Belt asteroids are directly applicable to Trojans. The more distant objects often require modied algorithms, tting orbits with only 4 parameters in a coordinate system specially adapted to handle very short arcs of observations. These orbits are mostly used as intermediate results, allowing to nd full solutions as more tracklets are identied. When the number density of detections is as large as expected from the next generation surveys, both joining observations into tracklets and identifying tracklets can produce some false results. The only reliable way to remove them is a procedure of tracklet/identication management. It compares the tracklets and the identications with a complex logic, allowing to discard almost all the false tracklets and all the false identications. However, the distant objects still present a challenge for orbit determination: they require three tracklets in separate nights. If this requirement is met we have found no problem in achieving an unbiased orbit determination for all populations. Further work will lead to more advanced simulations, in particular by introducing a realistic model for astrometric and photometric errors.
ImDrug: A Benchmark for Deep Imbalanced Learning in AI-aided Drug Discovery

The last decade has witnessed a prosperous development of computational methods and dataset curation for AI-aided drug discovery (AIDD). However, real-world pharmaceutical datasets often exhibit highly imbalanced distribution, which is overlooked by the current literature but may severely compromise the fairness and generalization of machine learning applications. Motivated by this observation, we introduce ImDrug, a comprehensive benchmark with an open-source Python library which consists of 4 imbalance settings, 11 AI-ready datasets, 54 learning tasks and 16 baseline algorithms tailored for imbalanced learning. It provides an accessible and customizable testbed for problems and solutions spanning a broad spectrum of the drug discovery pipeline such as molecular modeling, drug-target interaction and retrosynthesis. We conduct extensive empirical studies with novel evaluation metrics, to demonstrate that the existing algorithms fall short of solving medicinal and pharmaceutical challenges in the data imbalance scenario. We believe that ImDrug opens up avenues for future research and development, on real-world challenges at the intersection of AIDD and deep imbalanced learning.
Developing a Geographical Information System Database and Spatial Analysis for a Forest Biomass Resource Assessment

Abstract                This study was done to determine the volume, type, and distribution of forest biomass generated in Larimer County, Colorado. The data were compiled within ArcGISTm, a Geographical Information System (GIS) program to graphically display where they exist. Presenting the data using a GIS format created a clear visual representation of wood supply distribution for Larimer County. The GIS database was developed from many sources, including data provided by the U.S. Forest Service and Colorado State Forest Service, and data from IRS tax records (Agricultural tax credit records). The database summarizes forest biomass generation in terms of harvested acres, volumes, and product type removed. Products were typically in the form of fuelwood, chips, posts, and small saw logs. Data were converted into a format compatible with ArcGISTM, thus contained in one easily understood database.
Density functional theory and quantum chemistry: Metals and metal oxides

Abstract   The LCGTO-MCP-LSD (linear combination of Gaussian type orbitals - model core potential - local spin density) method has already been tested in a wide range of applications, including transition metals, transition-metal clusters, transition-metal oxide molecules and clusters. In this contribution a very brief overview of the density functional methodology, some remarks on the program deMon, developed in our laboratory, and a survey on recent applications aimed at delimiting the possibilities and limitations are given. The most recent applications of DFT to transition-metal oxide diatomics are discussed focusing on the usefulness of the methodology in theoretical spectroscopy as well as in describing metal-oxygen bonding.
Constitutional Validity of Surveillance Technologies in Pakistan: Reconciling National Security with Individual Privacy Rights in the Digital Age

This paper critically examines the constitutional validity of modern surveillance technologies in Pakistan, focusing on the tension between national security imperatives and the fundamental right to privacy enshrined in Article 14 of the 1973 Constitution. Drawing on recent jurisprudence, statutory frameworks, and international legal obligations, the study argues that Pakistan’s current surveillance regime—exemplified by the Lawful Intercept Management System (LIMS) and expanded powers under Section 54 of the Pakistan Telecommunication Act—operates in a legal grey zone, lacking judicial oversight and proportionality safeguards. Through an analysis of landmark cases such as Mohtarma Benazir Bhutto v. Federation of Pakistan and Justice Qazi Faez Isa v. President of Pakistan, the paper highlights systemic constitutional violations, including breaches of dignity (Article 14), freedom of speech (Article 19), and due process (Article 4). The study concludes with recommendations for a rights-respecting surveillance framework aligned with international standards, emphasizing judicial warrants, independent oversight, and data protection legislation.
Dark Atoms and Puzzles of Dark Matter Searches

The nonbaryonic dark matter of the Universe is assumed to consist of new stable forms of matter. Their stability reflects symmetry of micro world and particle candidates for cosmological dark matter are the lightest particles that bear new conserved quantum numbers. Dark matter candidates can appear in the new families of quarks and leptons and the existence of new stable charged leptons and quarks is possible, if they are hidden in elusive "dark atoms". Such possibility, strongly restricted by the constraints on anomalous isotopes of light elements, is not excluded in scenarios that predict stable double charged particles. The excessive -2 charged particles are bound in these scenarios with primordial helium in O-helium atoms, maintaining specific nuclear-interacting form of the dark matter, which may provide an interesting solution for the puzzles of the direct dark matter searches.
A Partition Theorem for a Randomly Selected Large Population

We state and prove a theorem on the partitioning of a randomly selected large population into stationary and non-stationary components by using a property of stationary population identity. Applications of this theorem for practical purposes is summarized at the end.
Surgical Science–Simbionix Robotic Hysterectomy Simulator: Validating a New Tool

To gather validity evidence for and determine acceptability of Surgical Science-Simbionix Hysterectomy Modules for the DaVinci Xi console simulation system (software; 3D Systems by Simbionix [now Surgical Science-Simbionix], Littleton, CO, and hardware; Intuitive Surgical, Inc., Sunnyvale, CA) and evaluate performance benchmarks between novice and experienced or expert surgeons.Prospective education study (Messick validity framework).Multicenter, academic medical institutions.Residents, fellows, and faculty in obstetrics and gynecology were invited to participate at 3 institutions. Participants were categorized by experience level: fewer than 10 hysterectomies (novice), 10 to 50 hysterectomies (experienced), and more than 50 hysterectomies (expert). A total of 10 novice, 10 experienced, and 14 expert surgeons were included.Participants completed 4 simulator modules (ureter identification, bladder flap development, colpotomy, complete hysterectomy) and a qualitative survey. Simulator recordings were reviewed in duplicate by educators in minimally invasive gynecologic surgery using the Modified Global Evaluative Assessment of Robotic Skills (GEARS) rating scale.Most participants felt that the simulator realistically simulated robotic hysterectomy (64.7%) and that feedback provided by the simulator was as or more helpful than feedback from previous simulators (88.2%) but less helpful than feedback provided in the operating room (73.5%). Participants felt that this simulator would be helpful for teaching junior residents. Simulator-generated metrics correlated with GEARS performance for the bladder flap and ureter identification modules in multiple domains including total movements and total time for completion. GEARS performance for the bladder flap module correlated with experience level (novice vs experienced/expert) in the domains of interest and total score but did not consistently correlate for the other procedural modules. Performance benchmarks were evaluated for the bladder flap module for each GEARS domain and total score.The modules were well received by participants of all experience levels. Individual simulation modules appear to better discriminate between novice and experienced/expert users than overall simulator performance. Based on these data and participant feedback, the use of individual modules in early residency education may be helpful for providing feedback and may ultimately serve as 1 component of determining readiness to perform robotic hysterectomy.
Analyzing Risk Communication, Trust, Risk Perception, Negative Emotions, and Behavioral Coping Strategies During the COVID-19 Pandemic in China Using a Structural Equation Model

ObjectiveRisk communication and the degree of trust are major factors that affect the public's behavioral coping strategies and play an important role in emergency risk management. However, the internal formation mechanism involved in the public's psychological behavior remains unclear. This study aimed to investigate the association among risk communication, trust, risk perception, negative emotions, and behavioral coping strategies during the coronavirus disease 2019 (COVID-19) pandemic, and to identify and quantify the factors that influence public behavior.MethodsWe launched an online survey through social media from April to July 2020 in China. Relevant data were elicited using a self-designed questionnaire that mainly examined respondent characteristics, risk communication, trust, risk perception, negative emotions, protective coping behavior, and excessive coping behavior in the context of the COVID-19 pandemic. A total of 735 valid responses were obtained. A structural equation model was then used to explore relationship pathways among the components.ResultsThe higher the degree of risk communication (β = −0.10, p &amp;lt; 0.05) and trust (β = −0.22, p &amp;lt; 0.001), the lower the public risk perception. Risk communication and trust had a direct effect on public behavioral coping strategies during the COVID-19 pandemic. The higher the level of risk communication (β = 0.14, p &amp;lt; 0.001) or trust (β = 0.48, p &amp;lt; 0.001), the more likely it was that this would encourage the public to adopt protective coping behaviors, while the public was less likely to engage in excessive coping behaviors as the degree of trust increased (β = −0.12, p &amp;lt; 0.01). Risk perception influenced by poor risk communication and trust generated negative emotions (β = 0.31, p &amp;lt; 0.001), and such negative emotions further positively influenced public behavioral coping strategies (whether protective [β = 0.09, p &amp;lt; 0.05] or excessive [β = 0.24, p &amp;lt; 0.001] behaviors).ConclusionRisk communication, trust, risk perception, and negative emotions were significantly directly or indirectly related to public behavior. The findings provide useful information for emergency risk management and a theoretical basis for follow-up research on public coping behavior during the COVID-19 pandemic.
Epigenetic regulation and chromatin remodeling in learning and memory

Understanding the underlying mechanisms of memory formation and maintenance has been a major goal in the field of neuroscience. Memory formation and maintenance are tightly controlled complex processes. Among the various processes occurring at different levels, gene expression regulation is especially crucial for proper memory processing, as some genes need to be activated while some genes must be suppressed. Epigenetic regulation of the genome involves processes such as DNA methylation and histone post-translational modifications. These processes edit genomic properties or the interactions between the genome and histone cores. They then induce structural changes in the chromatin and lead to transcriptional changes of different genes. Recent studies have focused on the concept of chromatin remodeling, which consists of 3D structural changes in chromatin in relation to gene regulation, and is an important process in learning and memory. In this review, we will introduce three major epigenetic processes involved in memory regulation: DNA methylation, histone methylation and histone acetylation. We will also discuss general mechanisms of long-term memory storage and relate the epigenetic control of learning and memory to chromatin remodeling. Finally, we will discuss how epigenetic mechanisms can contribute to the pathologies of neurological disorders and cause memory-related symptoms.
International Humanitarian Law and International Criminal Tribunals

International humanitarian law is the branch of customary and treaty-based international positive law whose purposes are to limit the methods and means of warfare and to protect the victims of armed conflicts. Grave breaches of its rules constitute war crimes for which individuals may be held directly accountable and which it is up to the sovereign states to prosecute. However, should a state not wish to, or not be in a position to prosecute, the crimes can be tried by international criminal tribunals instituted by treaty or by binding decision of the United Nations Security Council. This brief description of the current legal and political situation reflects the state of the law at the dawn of the twenty-first century. It does not, however, describe the work of a single day or the fruit of a single endeavor. Quite the contrary, it is the outcome of the international community’s growing awareness, in the face of the horrors of war and the indescribable suffering inflicted on humanity throughout the ages, that there must be limits to violence and that those limits must be established by the law and those responsible punished so as to discourage future perpetrators from exceeding them.
When to announce the queueing information for bounded rationality customers: a discrete-event–based simulation model

In queueing systems where queues are invisible, it is critical for companies to make decisions about the timing of announcing the anticipated delay to customers. In this paper, a simulation model is built to simulate an invisible queueing system, and several queueing scenarios are considered, including different system congestion and different company goals, to explore the impact of different announcement timings. In the modeling of customer behavior, we argue that it is difficult for companies to announce perfectly accurate delay and rarely have customers fully trust the announcement, so the quantal-response model is included to model customers’ probabilistic choice behavior due to the bounded rationality. Meanwhile, we consider customer heterogeneity, assign customers different initial patience and, as an extension, also assume that patience will be updated. We perform simulation experiments and analyze the experimental data to dissect the underlying reasons, and then give sound management suggestions. The experiments show that the optimal announcement timing is different for different scenarios, which shows that in practical decisions, companies should adopt different announcement strategies for different scenarios. What’s more, in some scenarios, delayed announcement at specific time is better than on-arrival announcement, which suggests that when we judge the value of announcement, we should add the definite word of specific timing to the announcement. The breakthrough point of this paper is to consider customers’ bounded rationality and the dynamic patience; meanwhile, it fills the gap of announcement timing research and explores the value of additional announcements after the initial announcement.
TRANSPORTATION OPTIMIZATION MODEL USING THE DISTANCE MATRIX: A CASE OF CEMENT DISTRIBUTION FROM SELECTED COMPANIES TO DISTRIBUTION CENTERS IN EBONYI STATE

Ascertaining an optimal cement distribution plan for cement companies in Nigeria has remained a challenge. The absence or fluctuation of data for estimating the cost of transporting cement from each source to each distribution center is a big stumbling block whenever modeling attempts are being made via transportation algorithms. This work has succeeded in removing these challenges by providing a Transportation Optimization Model for cement distribution using transportation Distance Matrix instead of transportation Cost Matrix. This research seeks to improve supply in the Nigerian cement industry. Three selected factories (Gboko, Port-Harcourt and Calabar) and four major distribution centers (Abakaliki, Onueke, Ohaozara and Afikpo) in Ebonyi state were considered for this work. The result of the findings using the Vogel Approximation Method, minimized the total transportation distance and by implication the total transportation costs.