ethicalabs/Research-Intent-Collab huggingface dataset:
Compact Toroid Theory Planning Workshop. A panel report to the Director, Division of Applied Plasma Physics, Office of Fusion Energy

The purpose of the Workshop was to identify the most important physics issues that need to be addressed in the near term in order to assure the optimal design and timely interpretation of Compact Toroid (CT) experiments. The Panel was also asked to assess the levels of effort required to obtain priority information on appropriate time scales compatible with DOE plans to design a CT proof-of-principle experiment. The fiscal year cost anticipated for the effort recommended by the Workshop Panel (excluding costs for computing) is estimated to be approximately $5.7M. CT theory is currently funded at a level of approximately $2.0M per year.
A social justice framing of climate change discourse and policy: Adaptation, resilience and vulnerability in a Jamaican agricultural landscape

Abstract   It is now widely recognized that climate change is likely to have detrimental impacts across the Caribbean region, with the burden likely to fall disproportionately on the most vulnerable segments of society. It is therefore an appropriate time to ask whether the frameworks that lie behind climate change discourse and policy are consistent with the demands of social and environmental justice. In this paper, we use climate justice as a lens for evaluating three prominent frameworks for addressing climate change, those of adaptation, resilience, and vulnerability. Each of these discursive frameworks, we argue, can contribute to our understanding of climate change, but they do not all incorporate justice concerns to the same degree. In order to illustrate this, we examine the justice implications of using each of the three frameworks to assess a case study of agricultural transformation in Southwestern Jamaica. Farmers in this region have adapted to changing climate conditions in a variety of ways, including the use of new agricultural technology. The ability of many farmers to take advantage of such innovations, however, is constrained by the underlying landscape of vulnerability within the region. After interpreting this example from the perspectives of adaptation, resilience and vulnerability, we conclude that all three paradigms are capable of calling attention to climate justice issues, but only in the vulnerability perspective are such issues intrinsic. We believe, therefore, that a greater attention to vulnerability within Caribbean climate policy holds the potential to advance the goals of climate justice within the region.
Avoiding, transforming, transitioning: pathways to sustainable low carbon passenger transport in developing countries

This review examines conditions affecting road passenger transport in developing countries that can be instrumental to building a pathway for reducing carbon emissions while concurrently meeting sustainable development goals. By contrasting present and future status of these conditions a vision emerges where non-OECD passenger travel increases of up to 200% can be accommodated via strong investments in transit and non-motorized modes and a recasting of informal transport services into self-organized systems, with lower levels of car ownership and avoidance of carbon emissions. Reductions in motorized travel are also necessary from OECD countries; the focus there is given to what level of pricing and regulatory interventions could change behavior. The articulation of detailed visions can help clarify and prioritize areas where policy efforts can have great impact. Strong actions are necessary from both regions.
Insight into the Trends in Research on the Impact of Social Media on Adolescent Mental Health

This study investigates the impact of social media on adolescent mental health through a bibliometric analysis of literature from 2004 to 2024 in the web of science database. With internet usage among adolescents exceeding 87% and instant messaging rates reaching 84.1%, platforms such as Facebook and Instagram significantly affect their mental well-being. The study identifies “anxiety,” “depression,” and “adolescents” as central themes, demonstrating a strong correlation between high-frequency social media use and mental health issues. Adolescents, the most affected group, face significant risks from prolonged social media exposure. The United Kingdom leads study collaborations in this field. The findings highlight the complexity of social media’s impact on mental health, influenced by various factors ranging from childhood experiences to specific psychological issues. Emphasizing adolescent mental health, the study calls for future study to explore the long-term effects of social media use and develop effective intervention measures and policy recommendations. This scientific evidence aims to guide policymakers, educators, and parents in promoting the comprehensive development and well-being of adolescents, helping them navigate the digital age healthily and safely.
Development and Validation of a Natural Language Processing Algorithm Using Electronic Health Record Data to Identify Breast Cancer Patients With Low Social Support

PURPOSE                     Social support is important in the management of breast cancer. We developed a series of structured variables or modules from electronic health record (EHR) data to form the basis for the development of EHRsupport, an EHR-based measure of social support.                                                           METHODS                     We built a natural language processing (NLP) algorithm from clinical notes in 7,989 women diagnosed from January 2006 to September 2021 with invasive breast cancer. Our team reviewed charts, developed a lexicon, manually crafted rules, applied the NLP algorithm to 565,258 EHR notes and 68,760 patient messages –1 to +3 months around diagnosis, combined terms into separate modules, and tuned (N = 40), updated, and tested (N = 100) these versus chart review. We further developed modules from structured data sources.                                                           RESULTS                     We identified and developed 11 modules from unstructured data: spouse/partner status, parenthood status (clinical) visit support, living situation (alone or with others), friend or other support, positive social support, negative (lack of) social support, deceased person, transportation issues, relationship conflict or stress, and social isolation. Module data availability ranged from 1.4% for social isolation to 92.0% for spouse/partner. Modules were accurate (0.81-0.95). The most highly available groups had moderate to excellent F1 scores (0.75-1.00), precision or positive predictive value (0.61-1.00), and recall or sensitivity (0.75-1.00). Recall and precision were more variable among rarer modules. Five percent of patients lacked an in-state emergency contact and 3% of patients had diagnostic codes for low support at any time point.                                                           CONCLUSION                     The EHRsupport algorithm accurately identified social support data, supporting the development of a clinical tool that can be used to identify patients with low social support.
Erratum to “Systematic versus on-demand early palliative care: A randomised clinical trial assessing quality of care and treatment aggressiveness near the end of life” [Eur J Cancer (2016) 69 (110–118)] (S095980491632487X)(10.1016/j.ejca.2016.10.004)

The publisher regrets that the collaborators for this paper were not listed as such within the author details of the published paper. The collaborators were published in the Acknowledgements and are as follows: Alberto Farolfi, Silvia Ruscelli, Martina Valgiusti, Sara Pini, Marina Faedi, Department of Medical Oncology, IRST IRCCS, Meldola; Angela Ragazzini, Unit of Biostatistics and Clinical Trials, IRST IRCCS, Meldola; Cristina Pittureri and Elena Amaducci, Palliative Care and Hospice Unit, AUSL Romagna, Cesena; Irene Guglieri, Psychooncology Service, Veneto Institute of Oncology IOV – IRCCS, Padua; Francesca Bergamo, Sara Lonardi, Department of Clinical and Experimental Oncology, Medical Oncology 1, Veneto Institute of Oncology IOV – IRCCS, Padua; Camilla Di Nunzio, Medical Oncology Unit, Oncology–Hematology Department, Guglielmo da Saliceto Hospital, Piacenza; Monica Bosco, Palliative Care Unit, Oncology–Hematology Department, Guglielmo da Saliceto Hospital, Piacenza; Barbara Bocci, Medical Oncology Unit, San Paolo Hospital, Milan; Alfina Bramanti and Chiara Gandini, Oncology Unit, Fondazione IRCCS Policlinico San Matteo, Pavia; Angela Buonadonna, Medical Oncology Unit, Aviano National Cancer Institute, Aviano; Alessandro Comandone, Medical Oncology Unit, Presidio Humanitas Gradenigo, Turin; Sonia Zoccali, Coordinamento Cure Palliative (supported by F.I.L.E., Leniterapia Italian Foundatio), Florence; Maria Simona Pino, Medical Oncology Unit, Oncology Department, S. Maria Annunziata Hospital, Florence; Davide Dalu, Palliative Care Unit, Oncology Department, L. Sacco Hospital, Milan; Pietro Sozzi, Oncology Unit, Ospedale degli Infermi, Ponderano; Alberto Gozza, Medical Oncology, Department of Medicine, E.O. Galliera Hospitals, Genoa; Monica Giordano and Carla Longhi, Oncology Unit, Sant'Anna Hospital, Como; Cristina Autelitano, Palliative Care Unit, Arcispedale S. Maria Nuova – IRCCS, Reggio Emilia; Teresa Gamucci, Oncology Unit, SS Trinità Hospital Sora, ASL Frosinone, Frosinone; Cataldo Mastromauro, Oncology Unit, ULSS 12 Veneziana, Venice; Rodolfo Scognamiglio, Hospice Nazareth, Mestre; Daniela Degiovanni, Palliative Care Unit, Casale Monferrato, ASL Alessandria; Federica Negri, Medical Oncology Unit, Istituti Ospitalieri, Cremona; Augusto Caraceni, Palliative Care, Pain Therapy and Rehabilitation Department, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan; and Luigi Montanari, Palliative Care Unit Ravenna, AUSL Romagna, Italy. The publisher would like to apologise for any inconvenience caused.
A probabilistic analysis of shotgun sequencing for metagenomics

Genome sequencing is the basis for many modern biological and medicinal studies. With recent technological advances, metagenomics has become a problem of interest. This problem entails the analysis and reconstruction of multiple DNA sequences from different sources. Shotgun genome sequencing works by breaking up long DNA sequences into shorter segments called reads. Given this collection of reads, one would like to reconstruct the original collection of DNA sequences. For experimental design in metagenomics, it is important to understand how the minimal read length necessary for reliable reconstruction depends on the number and characteristics of the genomes involved. Utilizing simple probabilistic models for each DNA sequence, we analyze the identifiability of collections of M genomes of length N in an asymptotic regime in which N tends to infinity and M may grow with N. Our first main result provides a threshold in terms of M and N so that if the read length exceeds the threshold, then a simple greedy algorithm successfully reconstructs the full collection of genomes with probability tending to one. Our second main result establishes a lower threshold in terms of M and N such that if the read length is shorter than the threshold, then reconstruction of the full collection of genomes is impossible with probability tending to one.
Terrorism and Banditry: Implications for Nigeria's Sovereignty and Territorial Integrity

Purpose: This research examines the implications of terrorism and banditry on Nigeria's sovereignty and territorial integrity.&#x0D; Methodology: Employing a content analysis approach and drawing from qualitative data from secondary sources, the study highlights the extensive ramifications of terrorism and banditry, encompassing loss of lives and property, displacement of people, economic disruption, damage to Nigeria's reputation, and political instability. The research underscores the urgency for the Nigerian government to take decisive action in addressing these challenges, fostering economic growth, rebuilding investor trust, and enhancing the country's image.&#x0D; Findings: The research findings hold practical implications for policymakers and security agencies, urging a unified and comprehensive approach in confronting terrorism and banditry in Nigeria. The research underscores the significance of addressing the psychological impact on affected individuals by providing essential mental health support, facilitating their recovery, and fostering social cohesion. The Realist theory guides the study, emphasizing the prioritization of state security and interests in an anarchic international system, offering valuable insights into comprehending the implications of terrorism and banditry on Nigeria's sovereignty and territorial integrity.&#x0D; Recommendations: To effectively combat terrorism and banditry, the study recommends reinforcing national security through increased funding, improved intelligence gathering and addressing socio-economic factors such as poverty, unemployment, and inequality through targeted policies. Emphasizing international cooperation and strengthening governance and accountability are identified as vital aspects in combating the cross-border nature of these threats. The recommended strategies offer a roadmap to effectively combat these security challenges, safeguarding Nigeria's stability, peace, and economic prosperity. By implementing these measures, practitioners can work towards restoring the nation's security, rebuilding confidence, and enhancing its position in the international community.
Computing Singularly Perturbed Differential Equations

A computational tool for coarse-graining nonlinear systems of ordinary differential equations in time is discussed. Three illustrative model examples are worked out that demonstrate the range of capability of the method. This includes the averaging of Hamiltonian as well as dissipative microscopic dynamics whose `slow' variables, defined in a precise sense, can often display mixed slow-fast response as in relaxation oscillations, and dependence on initial conditions of the fast variables. Also covered is the case where the quasi-static assumption in solid mechanics is violated. The computational tool is demonstrated to capture all of these behaviors in an accurate and robust manner, with significant savings in time. A practically useful strategy for initializing short bursts of microscopic runs for the accurate computation of the evolution of slow variables is also developed.
Optical Neural Network Based on Synthetic Nonlinear Photonic Lattices

We reveal that a synthetic photonic lattice based on coupled optical loops can be utilized as a neural network for processing of optical pulse sequences in time domain. As a proof-of-concept, we train the optical system to restore an initial shape of the pulse train from the signal distorted due to linear dispersion in a fiber-optic link. We also show efficient training of the optical network with an intrinsic Kerr-type nonlinearity for the realization of target nonlinear transmission functions and inference functionality for the discrimination of different pulse sequences. The theoretical modeling is performed under practical conditions and can guide future experimental realizations.
Global projections of storm surges using high-resolution CMIP6 climate models: validation, projected changes, and methodological challenges

In the coming decades, the frequency of coastal flooding will increase due to sea-level rise and changes in climate extremes. We force the Global Tide and Surge Model (GTSM) with a climate model ensemble from the CMIP6 High Resolution Model Intercomparison Project (HighResMIP) to produce global projections of extreme sea levels (defined as tides and storm surge) from 1950 to 2050. This is the first time that an ensemble of global ~25km resolution climate models is used for this purpose, which increases the credibility of projected storm surges. Here we validate the historical simulations (1985-2014) against the ERA5 climate reanalysis. The overall performance of the HighResMIP ensemble is good with mean bias smaller than 0.1 m. However, there is a strong large-scale spatial bias. Future projections for the high emission SSP5-8.5 scenario indicate changes up to 0.1 m or 20% in 10-year return period surge level from 1951-1980 to 2021-2050. Increases are seen in parts of the coastline of the Caribbean, Madagascar and Mozambique, Alaska, and northern Australia, whereas the Mediterranean region may see a decrease. The full dataset underlying this analysis, including timeseries and statistics, is openly available on the Climate Data Store and can be used to inform broad-scale assessment of coastal impacts under future climate change.
A novel view of the insulin signaling pathway based on prediction of protein structure by the AI platform AlphaFold

The predicted structures of major proteins involved in the insulin signaling pathway obtained from the AlphaFold Protein Structure Database.
Semantic Segmentation in Satellite Hyperspectral Imagery by Deep Learning

Satellites are increasingly adopting on-board AI to optimize operations and increase autonomy through in-orbit inference. The use of Deep Learning (DL) models for segmentation in hyperspectral imagery offers advantages for remote sensing applications. In this work, we train and test 20 models for multi-class segmentation in hyperspectral imagery, selected for their potential in future space deployment. These models include 1D and 2D Convolutional Neural Networks (CNNs) and the latest vision transformers (ViTs). We propose a lightweight 1D-CNN model, 1D-Justo-LiuNet, which outperforms state-of-the-art models in the hypespectral domain. 1D-Justo-LiuNet exceeds the performance of 2D-CNN UNets and outperforms Apple's lightweight vision transformers designed for mobile inference. 1D-Justo-LiuNet achieves the highest accuracy (0.93) with the smallest model size (4,563 parameters) among all tested models, while maintaining fast inference. Unlike 2D-CNNs and ViTs, which encode both spectral and spatial information, 1D-Justo-LiuNet focuses solely on the rich spectral features in hyperspectral data, benefitting from the high-dimensional feature space. Our findings are validated across various satellite datasets, with the HYPSO-1 mission serving as the primary case study for sea, land, and cloud segmentation. We further confirm our conclusions through generalization tests on other hyperspectral missions, such as NASA's EO-1. Based on its superior performance and compact size, we conclude that 1D-Justo-LiuNet is highly suitable for in-orbit deployment, providing an effective solution for optimizing and automating satellite operations at edge.
Constraints on the multi-lognormal magnetic fields from the observations of the cosmic microwave background and the matter power spectrum

10 pages, 6 figures. Accepted for publication in Physical Review D, published 26 November 2013
Effect of Microgravity  on Human T Lymphocyte Activation: Experiments in Spacelab and Sounding Rockets

Several physiological systems are altered by the environment of spaceflight.The results of an experiment carried out in Spacelab-1 have surprisingly shown that the mitogenic activation with Concanavalin A (Con A) of T lymphocytes is nearly completely inhibited (by more than 95%) in microgravity conditions [1].We have investigated the causes of the phenomenon in a series of studies performed in the last 15 years in 6 Spacelab missions (D-1 in 1985, SLS-1 in 1991, IML-1 in 1992, IML-2 in 1994 and dramatic STS-107 in 2003), in sounding rockets (6 missions) and in ground-based simulations in the clinostat. Immune cells have been chosen by us and several other research groups as an important model to study in vitro the influence of microgravity on cell differentiation and genetic expression following transduction of an external signal, on cell motility, formation of cell aggregates and cytoskeleton. [...]
Perceptions in the medical field towards persons with disabilities’ sexual and reproductive health and rights

BACKGROUND: People with disabilities, representing the largest minority in the world, are affected by conditions that negatively impact their daily activities. As any human being, they are entitled to have equal and non-discriminatory access to sexual and reproductive health and rights. This narrative review aims to analyse medical professionals and students’ behaviours and dynamics towards persons with disabilities regarding their sexual health and rights. METHODS: PubMed® database search and selection of relevant articles from 2013 to May 2023, resulting in the inclusion of 25 articles. RESULTS: Most studies allude to unfavourable behaviour and dynamics towards the sexuality of people with disabilities in the medical field. These include mainly discriminatory assumptions, sexuality seen as a taboo topic, lack of knowledge and training on persons with disabilities’ healthcare, and communicational and relational handicaps. Physical limitations, time constraints, and complex terms are also identified as barriers. Notwithstanding, positive aspects and experiences on sexual and reproductive healthcare provision are mentioned as well. CONCLUSIONS: Sexual and reproductive health and rights in persons with disabilities are perceived in the medical field with conflicting views, even though there is a tendency towards the negative side. This results in a poorer care provision to people with disabilities and incapacitate them to have their rights fulfilled. Training in PWD care should be prioritised in medical curricula to improve medical perceptions. Further studies should be conducted to better understand the results.
Optimal design and experimental validation of a simulated moving bed chromatography for continuous recovery of formic acid in a model mixture of three organic acids from Actinobacillus bacteria fermentation

The economically-efficient separation of formic acid from acetic acid and succinic acid has been a key issue in the production of formic acid with the Actinobacillus bacteria fermentation. To address this issue, an optimal three-zone simulated moving bed (SMB) chromatography for continuous separation of formic acid from acetic acid and succinic acid was developed in this study. As a first step for this task, the adsorption isotherm and mass-transfer parameters of each organic acid on the qualified adsorbent (Amberchrom-CG300C) were determined through a series of multiple frontal experiments. The determined parameters were then used in optimizing the SMB process for the considered separation. During such optimization, the additional investigation for selecting a proper SMB port configuration, which could be more advantageous for attaining better process performances, was carried out between two possible configurations. It was found that if the properly selected port configuration was adopted in the SMB of interest, the throughout and the formic-acid product concentration could be increased by 82% and 181% respectively. Finally, the optimized SMB process based on the properly selected port configuration was tested experimentally using a self-assembled SMB unit with three zones. The SMB experimental results and the relevant computer simulation verified that the developed process in this study was successful in continuous recovery of formic acid from a ternary organic-acid mixture of interest with high throughput, high purity, high yield, and high product concentration.