ethicalabs/Research-Intent-Collab huggingface dataset:
PD08 Clinical And Cost Effectiveness Of Selected Diabetes Medicines In Ghana - An Adaptive Health Technology Assessment

IntroductionThere is a need to consider whether treatments included in essential medicine lists, standard treatment guidelines, and health benefits packages are cost effective, improve financial sustainability, and increase equitable access to health care. This assessment evaluated the cost effectiveness of selected antidiabetic medicines for inclusion on Ghana’s Essential Medicines List and updated standard treatment guidelines, and reimbursement by the National Health Insurance Authority.MethodsThis study was produced in line with the broad steps of the Ghana health technology assessment (HTA) process guideline using an adaptive HTA (aHTA) approach and following the process used by the National Cancer Grid of India. High quality HTA evidence was sourced from four HTA agencies based on the population (children aged two years or older and adults older than 18 years using antidiabetics), intervention, comparator, and outcomes framework using an adaptability checklist developed by the researchers. A price benchmarking analysis was conducted to generate context relevant evidence on medicine prices in terms of local value for money.ResultsThe study found that all medicines evaluated (sitagliptin, vildagliptin, saxagliptin, insulin detemir, insulin degludec, insulin glargine, insulin glusiline, insulin aspart, and insulin lispro) were efficacious. The price benchmark analysis showed that insulin detemir, glargine, and degludec had higher price ratios than their comparators, and an annual drug cost per patient that was approximately two to four times higher. Insulin lispro, aspart, and glulisine had price ratios of 0.22 to 0.44 and an estimated annual cost of GHS1,894 to GHS3,552 (USD163.3 to USD306.2), which was two to five times higher per patient than the comparators. The cost of saxagliptin and vildagliptin were four and three times lower than those in the benchmark country (the UK).ConclusionsThe study revealed that all medicines included are efficacious and potentially cost effective. The price benchmark analysis showed that, except for gliclazide 80 mg, Ghana is paying less for antidiabetic medications than the UK. Cost effectiveness may not be a sufficient basis to include or exclude medicines for reimbursement because they have a potentially significant budget impact for the payer.
Modified Characteristics of Hadronic Interactions in Ultra-High-Energy Cosmic-Ray Showers

Data from multiple experiments suggest that the current interaction models used in Monte Carlo simulations do not correctly reproduce the hadronic interactions in air showers produced by ultra-high-energy cosmic rays (UHECR), in particular – but not limited to – the production of muons during the showers. We have created a large library of UHECR simulations where the interactions at the highest energies are slightly modified in various ways – but always within the constraints of the accelerator data, without any abrupt changes with energy and without assuming any specific mechanism or dramatically new physics at the ultra-high energies. We will find that even when very different properties – cross section, elasticity, and multiplicity – of the interactions are modified, the resulting changes in some air-shower observables are still mutually correlated. Thus, not all possible combinations of changes of observables are easily reproduced by some combination of the modifications. Most prominently, the recent results of the Pierre Auger Observatory, which call for a change in the prediction of both the muon content at ground and the depth of the maximum of longitudinal development of the showers, are rather difficult to reproduce with such modifications, in particular when accounting for other cosmic-ray data. While some of these results are related to the assumptions we place on the modifications, the overall lessons are general and provide valuable insight into how the UHECR data can be interpreted from the point of view of hadronic physics.
The Effect of a Fisk-Type Heliospheric Magnetic Field on Cosmic-Ray Modulation

The Fisk model of the heliospheric magnetic field (HMF) has proved to be quite difficult to implement in three-dimensional numerical modulation codes. We have developed a divergence-free Fisk-Parker hybrid HMF that is easier to implement and that should be a reasonable approximation for the case when field lines open into the heliosphere both in the polar coronal holes and at low latitudes. To study the effects of this hybrid field on galactic cosmic rays, we solve the three-dimensional steady state Parker transport equation numerically, covering the entire model heliosphere. We find that latitudinal cosmic-ray gradients are reduced as expected, but only during epochs when particles are drifting from the polar regions of the heliosphere toward the ecliptic plane. We investigate 26 day recurrent variations of both protons and electrons and find that the amplitude of these variations are directly proportional to the latitudinal intensity gradient, independent of species, in agreement with observational studies. In the absence of drifts in the code, electrons and protons obey different but still linear relationships.
The Role of Business Ethics in Improving Corporate Social Responsibility

The inadequate integration of ethical principles into corporate social responsibility (CSR) practices remains a persistent challenge, undermining public trust and long-term business sustainability. This study aims to investigate how the implementation of business ethics can enhance the effectiveness of CSR within corporate settings. Employing a literature review methodology, the research analyzes academic publications, regulatory frameworks, and corporate reports related to business ethics and CSR. The findings demonstrate that the consistent application of ethical values enriches the meaning and impact of CSR initiatives, improves corporate reputation, and fosters stronger, more sustainable stakeholder relationships. However, challenges such as organizational cultural diversity and insufficient internalization of ethical principles within corporate systems and cultures continue to hinder progress. Consequently, strategic efforts are essential to move beyond treating business ethics as mere normative ideals toward fully embedding them as core values in CSR practices aimed at achieving social and environmental sustainability.
Mean field statistical mechanics of model Hamiltonian for hydrogen bonded phase transitions

AbstractRecently, a new prototype model has been proposed to explain structural phase transitions in single crystals of organic hydrogen bonded phenol–amine adducts. A variational calculation of the thermodynamic properties was able to explain the main features of the phase transition. We report an alternative statistical mechanical calculation which confirms the results of the earlier calculation even though self‐energy terms appear in the present calculation. The interpretation of the results within the pseudo spin representation is clarified further. (© 2009 WILEY‐VCH Verlag GmbH &amp; Co. KGaA, Weinheim)
Cartographies of the Present: ‘Contingent Sovereignty’ and Territorial Integrity

Sovereignty as territorial integrity has been recast by state legal advisors, diplomats and scholars, who employ terms and principles from international law while disregarding the content of the law. This chapter takes up the apparent permeability of borders in contemporary discourses and practices of military intervention. In spaces of alleged terrorist activity the relationship between state and territory has been called into question, and the global legal imaginary of sovereign states is separated de facto into actual sovereigns and ‘contingent’ sovereigns. The claim that ineffective internal sovereignty may justify intervention forms part of a broader reconfiguration of the relationship between sovereignty and territory. Drawing upon insights from political geography, this chapter uses ‘contingent sovereignty’ as a critical diagnosis. It focuses on contemporary practices of drone warfare and emerging justifications for intervention that are premised upon a state’s unwillingness or inability to confront internal threats. It argues that the international legal order is recast in these cartographic projections, where territory operates as a political technology for preserving certain populations.
Accretion in Radiative Equipartition (AiRE) Disks

Standard accretion disk theory (Shakura & Sunyaev 1973) predicts that the total pressure in disks at typical (sub-)Eddington accretion rates becomes radiation pressure dominated. However, radiation pressure dominated disks are thermally unstable. Since these disks are observed in approximate steady state over the instability time-scale, our accretion models in the radiation pressure dominated regime (i.e. inner disk) need to be modified. Here, we present a modification to the SS model, where radiation pressure is in equipartition with gas pressure in the inner region. We call these flows Accretion in Radiative Equipartition (AiRE) Disks. We introduce the basic features of AiRE disks and show how they modify disk properties such as the Toomre parameter and central temperature. We then show that the accretion rate of AiRE disks is limited from above and below, by Toomre and nodal sonic point instabilities, respectively. The former leads to a strict upper limit on the mass of supermassive black holes as a function of cosmic time (and spin), while the latter could explain the transition between hard and soft states of X-ray binaries.
Quantum Architecture Search with Unsupervised Representation Learning

Unsupervised representation learning presents new opportunities for advancing Quantum Architecture Search (QAS) on Noisy Intermediate-Scale Quantum (NISQ) devices. QAS is designed to optimize quantum circuits for Variational Quantum Algorithms (VQAs). Most QAS algorithms tightly couple the search space and search algorithm, typically requiring the evaluation of numerous quantum circuits, resulting in high computational costs and limiting scalability to larger quantum circuits. Predictor-based QAS algorithms mitigate this issue by estimating circuit performance based on structure or embedding. However, these methods often demand time-intensive labeling to optimize gate parameters across many circuits, which is crucial for training accurate predictors. Inspired by the classical neural architecture search algorithm Arch2vec, we investigate the potential of unsupervised representation learning for QAS without relying on predictors. Our framework decouples unsupervised architecture representation learning from the search process, enabling the learned representations to be applied across various downstream tasks. Additionally, it integrates an improved quantum circuit graph encoding scheme, addressing the limitations of existing representations and enhancing search efficiency. This predictor-free approach removes the need for large labeled datasets. During the search, we employ REINFORCE and Bayesian Optimization to explore the latent representation space and compare their performance against baseline methods. We further validate our approach by executing the best-discovered MaxCut circuits on IBM's ibm_sherbrooke quantum processor, confirming that the architectures retain optimal performance even under real hardware noise. Our results demonstrate that the framework efficiently identifies high-performing quantum circuits with fewer search iterations.
Demographics of young stars and their protoplanetary disks: lessons learned on disk evolution and its connection to planet formation

Since Protostars and Planets VI (PPVI), our knowledge of the global properties of protoplanetary and debris disks, as well as of young stars, has dramatically improved. At the time of PPVI, mm-observations and optical to near-infrared spectroscopic surveys were largely limited to the Taurus star-forming region, especially of its most massive disk and stellar population. Now, near-complete surveys of multiple star-forming regions cover both spectroscopy of young stars and mm interferometry of their protoplanetary disks. This provides an unprecedented statistical sample of stellar masses and mass accretion rates, as well as disk masses and radii, for almost 1000 young stellar objects within 300 pc from us, while also sampling different evolutionary stages, ages, and environments. At the same time, surveys of debris disks are revealing the bulk properties of this class of more evolved objects. This chapter reviews the statistics of these measured global star and disk properties and discusses their constraints on theoretical models describing global disk evolution. Our comparisons of observations to theoretical model predictions extends beyond the traditional viscous evolution framework to include analytical descriptions of magnetic wind effects. Finally, we discuss how recent observational results can provide a framework for models of planet population synthesis and planet formation.
ScVLM: Enhancing Vision-Language Model for Safety-Critical Event Understanding

Accurately identifying, understanding and describing traffic safety-critical events (SCEs), including crashes, tire strikes, and near-crashes, is crucial for advanced driver assistance systems, automated driving systems, and traffic safety. As SCEs are rare events, most general vision-language models (VLMs) have not been trained sufficiently to link SCE videos and narratives, which could lead to hallucinations and missing key safety characteristics. Here, we introduce ScVLM, a novel hybrid methodology that integrates supervised and contrastive learning techniques to classify the severity and types of SCEs, as well as to generate narrative descriptions of SCEs. This approach utilizes classification to enhance VLMs' comprehension of driving videos and improve the rationality of event descriptions. The proposed approach is trained on and evaluated by more than 8,600 SCEs from the Second Strategic Highway Research Program Naturalistic Driving Study dataset, the largest publicly accessible driving dataset with videos and SCE annotations. The results demonstrate the superiority of the proposed approach in generating contextually accurate event descriptions and mitigating VLM hallucinations. The code will be available at https://github.com/datadrivenwheels/ScVLM.
Dissemination and implementation of comparative effectiveness evidence: key informant interviews with Clinical and Translational Science Award institutions

Aim:             To identify ongoing practices and opportunities for improving national comparative effectiveness research (CER) translation through dissemination and implementation (D&amp;I) via NIH-funded Clinical and Translational Science Award (CTSA) institutions.             Materials &amp; methods:             Key informant interviews were conducted with 18 CTSA grantees sampled to represent a range of D&amp;I efforts.             Results &amp; conclusions:             The institutional representatives endorsed fostering CER translation nationally via the CTSA Consortium. However, five themes emerged from the interviews as barriers to CER D&amp;I: lack of institutional awareness, insufficient capacity, lack of established D&amp;I methods, confusion among stakeholders about what CER actually is and limited funding opportunities. Interviewees offered two key recommendations to improve CER translation: development of a centralized clearing house to facilitate the diffusion of CER D&amp;I resources and methods across CTSA institutions; and formalization of the national CTSA network to leverage existing community engagement relationships and resources for the purpose of adapting and disseminating robust CER evidence locally with providers, patients and healthcare systems.
Automatic jargon identifier for scientists engaging with the public and science communication educators

Scientists are required to communicate science and research not only to other experts in the field, but also to scientists and experts from other fields, as well as to the public and policymakers. One fundamental suggestion when communicating with non-experts is to avoid professional jargon. However, because they are trained to speak with highly specialized language, avoiding jargon is difficult for scientists, and there is no standard to guide scientists in adjusting their messages. In this research project, we present the development and validation of the data produced by an up-to-date, scientist-friendly program for identifying jargon in popular written texts, based on a corpus of over 90 million words published in the BBC site during the years 2012-2015. The validation of results by the jargon identifier, the De-jargonizer, involved three mini studies: (1) comparison and correlation with existing frequency word lists in the literature; (2) a comparison with previous research on spoken language jargon use in TED transcripts of non-science lectures, TED transcripts of science lectures and transcripts of academic science lectures; and (3) a test of 5,000 pairs of published research abstracts and lay reader summaries describing the same article from the journals PLOS Computational Biology and PLOS Genetics. Validation procedures showed that the data classification of the De-jargonizer significantly correlates with existing frequency word lists, replicates similar jargon differences in previous studies on scientific versus general lectures, and identifies significant differences in jargon use between abstracts and lay summaries. As expected, more jargon was found in the academic abstracts than lay summaries; however, the percentage of jargon in the lay summaries exceeded the amount recommended for the public to understand the text. Thus, the De-jargonizer can help scientists identify problematic jargon when communicating science to non-experts, and be implemented by science communication instructors when evaluating the effectiveness and jargon use of participants in science communication workshops and programs.
Quantum error mitigation for Fourier moment computation

Hamiltonian moments in Fourier space—expectation values of the unitary evolution operator under a Hamiltonian at different times—provide a convenient framework to understand quantum systems. They offer insights into the energy distribution, higher-order dynamics, response functions, correlation information, and physical properties. This paper focuses on the computation of Fourier moments within the context of a nuclear effective field theory on superconducting quantum hardware. The study integrates echo verification and noise renormalization into Hadamard tests using control reversal gates. These techniques, combined with purification and error suppression methods, effectively address quantum hardware decoherence. The analysis, conducted using noise models, reveals a significant reduction in noise strength by two orders of magnitude. Moreover, quantum circuits involving up to 266  gates over five qubits demonstrate high accuracy under these methodologies when run on IBM superconducting quantum devices.
Experimental and simulation studies of multivariable adaptive optimization of continuous bioreactors using bilevel forgetting factors

AbstractA multivariable on‐line adaptive optimization algorithm using a bilevel forgetting factor method was developed and applied to a continuous baker's yeast culture in simulation and experimental studies to maximize the cellular productivity by manipulating the dilution rate and the temperature. The algorithm showed a good optimization speed and a good adaptability and reoptimization capability. The algorithm was able to stably maintain the process around the optimum point for an extended period of time. Two cases were investigated: an unconstrained and a constrained optimization. In the constrained optimization the ethanol concentration was used as an index for the baking quality of yeast cells. An equality constraint with a quadratic penalty was imposed on the ethanol concentration to keep its level close to a hypothetical “optimum” value. The developed algorithm was experimentally applied to a baker's yeast culture to demonstrate its validity. Only unconstrained optimization was carried out experimentally. A set of tuning parameter values was suggested after evaluating the results from several experimental runs. With those tuning parameter values the optimization took 50–90 h. At the attained steady state the dilution rate was 0.310 h−1 the temperature 32.8°C, and the cellular productivity 1.50 g/L/h.
The intergenerational consequences of war: anxiety, depression, suicidality, and mental health among the children of war veterans

The long-term effects of military deployment on the mental health of war veterans have been investigated extensively, but few studies have examined the long-term impact of parental deployment on children's mental health.Using a retrospective, multigenerational survey and propensity score analysis to adjust for selection effects and endogeneity bias, we investigated the impact of parental deployment on the mental health of the adult children of Australian veterans of the Vietnam War. We analysed data from 1966 adult men (35%) and women (65%) whose fathers (N = 1418) were selected at random from the population of surviving men who served in the Australian army during the Vietnam War (1962-75). Mean age of respondents was 37. The main outcome measures were self-reported diagnosis or treatment for anxiety and depression (i.e. lifetime and previous 12 months), suicidality based on Psychiatric Symptom Frequency Scale, and current mental health as measured by the Mental Health Inventory of the SF-36. The key independent variable was whether their fathers were deployed to the Vietnam War.Almost 40 years after the war, the adult children of deployed veterans were more likely to have been diagnosed with anxiety [odds ratio (OR) = 1.54, confidence interval (CI) = 1.04, 2.28] and depression (OR = 1.77, CI = 1.03, 3.05), to have had thoughts of suicide and self-harm (OR = 2.39, CI = 1.57, 3.65) and to have made suicidal plans (OR = 3.52, CI = 1.40, 8.85) than the offspring of comparable, non-deployed army veterans. They also reported poorer current mental health (Coefficient = -5.08, CI = -6.60 - -3.56).The results imply that there are significant and enduring adverse effects of parental deployment on the mental health of children in military families, and provide some insight into the potential long-term impacts of recent military engagements in Afghanistan and Iraq.
Pre-training Tensor-Train Networks Facilitates Machine Learning with Variational Quantum Circuits

The paper has been accepted by ICASSP 2026