ethicalabs/Research-Intent-Collab huggingface dataset:
Coherent view of crystal chemistry and ab initio analyses of Pb(II) and Bi(III) Lone Pair in square planar coordination

The stereochemistry of 6s2 (E) lone pair of divalent Pb and trivalent Bi (PbII and BiIII designated by M*) in structurally related PbO, PbFX (X= Cl, Br, I), BiOX (X= F, Cl, Br, I) and Bi2NbO5F is rationalized. The lone pair LP presence determined by its sphere of influence E, equal to those of oxygen or fluorine anions, was settled by its center then giving M*-E directions and distances. Detailed description of structural features of both elements in the title compounds characterized by [PbEO]n and [BiEO]n layers allowed to show the evolution of M*-E distance versus the changes with the square pyramidal SP coordination polyhedra. All are different, in red PbO one finds {PbEO4E4} square antiprism, a {[Bi.E]O4X4Xapical} monocapped square antiprism in PbFX and BiOX and {BiEO4F4}square antiprism in Bi2NbO5F. To analyze the crystal chemistry results, the electronic structures of these compounds were calculated within density functional theory DFT. Real space analyses of electron localization illustrate a full volume development of the lone pair on PbII within {PbEO4E4} in PbOE, {PbEF4X4} in PbFXE and Bi(III) within {BiEO4X4} square antiprisms, contrary to Bi(III) within {[Bi.E]O4F4Fapical} monocapped square antiprism. Larger hardness (larger bulk modules B0) and band gap characterize BiOF versus PbO due to the presence of F which brings antibonding Bi-F interactions oppositely to mainly bonding Bi-O. In PbFX and BiOX series there is a systematic decrease of B0 with the increasing volume following the nature and size of X which is decreasingly electronegative and increasingly large. The electronic densities of states mirror these effects through the relative energy position and relative electronegativities of F/X and O/X leading to decrease the band gap.
Using co-design to understand consumer’s health information-seeking behaviours and design preferences for a new digital clinical dashboard in aged care

Abstract                 Background                 Little is known about the information needs of older people and their family caregivers, particularly around medication management. This is largely because this population are infrequently consulted in research. Health technologies such as digital dashboards can present comprehensive and timely data summaries to improve knowledge and guide decision-making.                                Objectives                 The aim of this study was to understand current information seeking-behaviours of aged care service users and their families, and their preferences for the presentation of these types of information to support the co-design of a digital aged care dashboard.                                Methods                 Aged care clients (community and residential aged care) and their family members were invited to participate in semi-structured, one-on-one interviews conducted over the telephone. The interviews explored how participants sought health information, how this information supported their clinical decision-making, and how they would want this information to be presented via a digital dashboard. Interviews were audio-recorded, transcribed verbatim and independently analysed using an inductive content approach by three reviewers to identify prominent categories.                                Results                 Aged care clients and family members sought health information from healthcare providers, aged care facilities and the Internet. Information regarding medications, medical conditions and an overview for family members were of particular importance to participants. Participants saw the usefulness of a digital dashboard displaying relevant information, and provided suggestions regarding presentation of this information. This included the use of large text, representative colours, symbols and graphs. Participants recommended being able to tailor the dashboard to individual end-users.                                Conclusions                 By engaging aged care clients and their families in research, it was found that they had positive views about a digital dashboard that presented clinical information and was readily accessible. Such a dashboard could complement their current practices of information-seeking. However, for the dashboard to be effective for this population, several suggestions for its design were raised. Understanding the information-seeking behaviours of aged care clients and their families, together with knowledge of the information that is important to them, and then subsequent incorporation of this information into a digital dashboard that reflects their design preferences, could lead to more informed decision-making in this population.
Gene regulatory network inference: an introductory survey

Gene regulatory networks are powerful abstractions of biological systems. Since the advent of high-throughput measurement technologies in biology in the late 90s, reconstructing the structure of such networks has been a central computational problem in systems biology. While the problem is certainly not solved in its entirety, considerable progress has been made in the last two decades, with mature tools now available. This chapter aims to provide an introduction to the basic concepts underpinning network inference tools, attempting a categorisation which highlights commonalities and relative strengths. While the chapter is meant to be self-contained, the material presented should provide a useful background to the later, more specialised chapters of this book.
Pharmaceutical Innovations and Stewardship Programs in Combating Antimicrobial Resistance

This study evaluates the effectiveness of the UK’s AMR Strategy 2019-2024 in combating antimicrobial resistance (AMR), focusing on pharmaceutical innovations. By analyzing trends in human and veterinary antibiotic use alongside resistance rates, the research identifies improvements in reducing antibiotic consumption and resistance, with MRSA resistance declining from 10% in 2016 to 6% in 2023. Despite these positive trends, the research highlights ongoing challenges in the development and implementation of new antibiotics and alternative therapies. Semi-structured interviews with stakeholders, including policymakers and pharmaceutical experts, reveal barriers such as regulatory issues, slow innovation, and insufficient funding for new drug development. The study also examines case studies of pharmaceutical innovations, including β-lactamase inhibitors, bacteriophage therapies, and antimicrobial peptides, noting progress in some areas, but significant gaps in others. The research concludes that while the UK’s AMR Strategy has led to some positive outcomes, further efforts are needed to accelerate the development of novel therapies and address structural barriers in the pharmaceutical sector. Future research should focus on enhancing international collaboration, improving regulatory frameworks, and incentivizing innovation to combat AMR more effectively. Comparative analysis with other countries' strategies could also provide valuable insights for improving the UK’s response to the AMR crisis.
Economically Empowering Women as Sustainable Conflict Resolution: A Case Study on Building Peace in Uganda through Social Enterprise

Abstract                   The gendered consequences of war are often not fully realized, as women tend to carry the heavier burdens in post-conflict situations, yet at the same time can be left out of the formal peace process. Women can be part of the peace process informally through economic empowerment and sustainability. As most post-conflict situations are occurring in the developing world, one of the major issues in the peace process is the notion of a rescue narrative. Organizations from the developed world approach peacebuilding as a project that often disenfranchises and disempowers the people they are trying to help. Therefore, women must be empowered to contribute to their economic situations rather than becoming dependent on the help of outsiders. This amplifies the role of the follower by giving her the tools to be part of the solution and become self-sustainable.                   This chapter argues for the role of social enterprise in building sustainable peace by giving women agency and power in their communities. It will look at these phenomena through the lens of a non-governmental organization, 31 Bits, that offers a valuable case study in the post-conflict Northern Uganda town of Gulu where they employ 100 plus women in a five-year program that equips them to become fully self-sustainable through the creation of jewelry handmade from recycled paper. Their holistic approach moves beyond the nonprofit model of charity and survival for giving their beneficiaries the chance to thrive. In this way, it is not relief or rescue work but rather informal sustainable peace development. When women are economically empowered, their communities are closer to reaching gender equality and achieving positive peace.
A Review of Energy use and Carbon Footprint in Fishing with special reference to Life Cycle Assessment (LCA)

With over 4.1 million vessels operating worldwide the global fishing industry is critical for ensuring food security and supporting livelihoods. Asia leads in the total number of vessels globally with 2.68 million vessels which are operational, while India has about 0.166 million vessels (FAO, 2024). The fishing industry heavily depends on fossil fuels for fishing operations, which contributes significantly to greenhouse gas emissions. In 2011 alone, global fisheries consumed 40 billion litres of fuel, resulting in 179 million tonnes of CO2 emissions, which is about 4% of total emission from global food production (Parker et al., 2018). In Indian scenario fuel consumption and thus CO2 emissions per tonne of fish landed, have increased from 0.50 tonnes in 1961 to 1.52 tonnes in 2024. Mechanized and motorized vessels contributed the most to emissions, with trawlers emitting up to 1.43 tonnes of CO2 per tonne of fish. The economic challenges posed by rising fuel prices and inefficiencies in operations are highlighted in many fisheries, including India, where high fuel consumption and associated costs limits capacity utilization by up to 55% in many cases. This review examines strategies used for reducing energy use and emissions in fisheries and explores best strategies to minimize emissions from fishing fleet. Innovations in vessel design, fuel-efficient engines, and advanced gear technologies can be effective solutions for reducing energy use and emissions. Additionally, practices such as conducting energy audits, optimizing routes, and transitioning to alternative fuels like LNG and biogas can significantly improve sustainability. While traditional approaches based on fuel consumption provide a comparative understanding of energy use, Life Cycle Assessment (LCA) frameworks offer deeper insights into environmental impacts, making them valuable for shaping policies and practices that promote both economic and environmental sustainability in the fisheries sector.
A Comparative Study: Adaptive Fuzzy Inference Systems for Energy Prediction in Urban Buildings

This investigation aims to study different adaptive fuzzy inference algorithms capable of real-time sequential learning and prediction of time-series data. A brief qualitative description of these algorithms namely meta-cognitive fuzzy inference system (McFIS), sequential adaptive fuzzy inference system (SAFIS) and evolving Takagi-Sugeno (ETS) model provide a comprehensive comparison of their working principle, especially their unique characteristics are discussed. These algorithms are then simulated with dataset collected at one of the academic buildings at Nanyang Technological University, Singapore. The performance are compared by means of the root mean squared error (RMSE) and non-destructive error index (NDEI) of the predicted output. Analysis shows that McFIS shows promising results either with lower RMSE and NDEI or with lower architectural complexity over ETS and SAFIS. Statistical Analysis also reveals the significance of the outcome of these algorithms.
Deep Learning and Computational Physics (Lecture Notes)

These notes were compiled as lecture notes for a course developed and taught at the University of the Southern California. They should be accessible to a typical engineering graduate student with a strong background in Applied Mathematics.   The main objective of these notes is to introduce a student who is familiar with concepts in linear algebra and partial differential equations to select topics in deep learning. These lecture notes exploit the strong connections between deep learning algorithms and the more conventional techniques of computational physics to achieve two goals. First, they use concepts from computational physics to develop an understanding of deep learning algorithms. Not surprisingly, many concepts in deep learning can be connected to similar concepts in computational physics, and one can utilize this connection to better understand these algorithms. Second, several novel deep learning algorithms can be used to solve challenging problems in computational physics. Thus, they offer someone who is interested in modeling a physical phenomena with a complementary set of tools.
Household water security and the human right to water and sanitation

The purpose of this book is to present an overview of the latest research, policy, practitioner, academic and international thinking on water security—an issue that, like water governance a few years ago, has developed much policy awareness and momentum with a wide range of stakeholders. As a concept it is open to multiple interpretations, and the authors here set out the various approaches to the topic from different perspectives. Key themes addressed include: Water security as a foreign policy issue The interconnected variables of water, food, and human security Dimensions other than military and international relations concerns around water security Water security theory and methods, tools and audits. The book is loosely based on a masters level degree plus a short professional course on water security both given at the University of East Anglia, delivered by international authorities on their subjects. It should serve as an introductory textbook as well as be of value to professionals, NGOs, and policy-makers.
Educational Content Generator from Huge Information Sets Using Artificial Intelligence

The rapid growth of digital educational resources has led to an abundance of unstructured information in various formats, including textbooks, lecture notes, research papers, websites, audio lectures, and video tutorials. Extracting wellorganized learning materials from these diverse sources remains a challenge for students and educators. This paper proposes an AI-based Educational Content Generator that transforms diverse educational content into structured, personalized study resources. The proposed system combines Optical Character Recognition (OCR), speech-to-text transcription, and Natural Language Processing techniques to convert different educational inputs into a unified text format. A large language model generates structured outputs such as study notes, quizzes, and revision flashcards. The system also includes learner-level personalization, modifying explanations for beginner, intermediate, and advanced learners. Experimental evaluations show that the system efficiently processes multimodal educational datasets and produces reliable, structured learning materials that improve knowledge accessibility and learning effectiveness.
Life in solid ice

Some microbes appear to be able to metabolize in glacial ice or permafrost. The rate depends on temperature, nutrient level, and bioelement availability, among other factors. I have developed a plausible argument that they do this while confined in veins filled with acidic or saline solution that provides nutrients and elements necessary for growth. Here I develop this scenario further and discuss some of its implications for ice-covered planetary bodies and for the the origin of life. An accompanying paper in the conference proceedings (Bay et al.) discusses plans to test this hypothesis using epifluorescence microscopy of pristine, unmelted ice samples and an optical biospectrologging tool to assay living and dead microbes in boreholes in glacial ice.
Prediction of the SYM‐H Index Using a Bayesian Deep Learning Method With Uncertainty Quantification

AbstractWe propose a novel deep learning framework, named SYMHnet, which employs a graph neural network and a bidirectional long short‐term memory network to cooperatively learn patterns from solar wind and interplanetary magnetic field parameters for short‐term forecasts of the SYM‐H index based on 1‐ and 5‐min resolution data. SYMHnet takes, as input, the time series of the parameters' values provided by NASA's Space Science Data Coordinated Archive and predicts, as output, the SYM‐H index value at time point t + w hours for a given time point t where w is 1 or 2. By incorporating Bayesian inference into the learning framework, SYMHnet can quantify both aleatoric (data) uncertainty and epistemic (model) uncertainty when predicting future SYM‐H indices. Experimental results show that SYMHnet works well at quiet time and storm time, for both 1‐ and 5‐min resolution data. The results also show that SYMHnet generally performs better than related machine learning methods. For example, SYMHnet achieves a forecast skill score (FSS) of 0.343 compared to the FSS of 0.074 of a recent gradient boosting machine (GBM) method when predicting SYM‐H indices (1 hr in advance) in a large storm (SYM‐H = −393 nT) using 5‐min resolution data. When predicting the SYM‐H indices (2 hr in advance) in the large storm, SYMHnet achieves an FSS of 0.553 compared to the FSS of 0.087 of the GBM method. In addition, SYMHnet can provide results for both data and model uncertainty quantification, whereas the related methods cannot.
Editorial: Public and community engagement in health science research: Openings and obstacles for listening and responding in the majority world

Artículo EDITORIAL Frente. Salud Pública, 31 de agosto de 2022Seg. Educación y promoción de la salud pública https://doi.org/10.3389/fpubh.2022.1012678
Dark Patterns Undermining Digital Fairness? – The Legal Framework Against Manipulative Designs — Analysising the impact of the three key EU directives for consumer protection on the use of dark patterns

Abstract                   The article offers an analysis of the current legal framework governing manipulative design and focusses in particular on the three key directives known as the backbone of EU consumer protection law: the Unfair Commercial Practices Directive (UCPD), the Consumer Rights Directive (CRD), and the Unfair Contract Terms Directive (UCTD). These three directives have been central to the fitness check by the European Commission evaluating whether and to what extent this current legal framework continues to ensure fairness for consumers in a digital environment. After a brief introduction (I.), the article first juxtaposes “digital fairness” and “dark patterns” in an effort to carve out the underlying notion of fairness (II.), before assessing each of the three directives in turn regarding their impact on “dark patterns” (III.) and summarising the results (IV.).
Aqueous Electrochemistry of Poly(vinylanthraquinone) for Anode-Active Materials in High-Density and Rechargeable Polymer/Air Batteries

A layer of poly(2-vinylanthraquinone) on current collectors underwent reversible electrode reaction at -0.82 V vs Ag/AgCl in an aqueous electrolyte. A repeatable charging/discharging cycles with a redox capacity comparable to the formula weight-based theoretical density at the negative potential suggested that all of the anthraquinone pendants in the layer was redox-active, that electroneutralization by an electrolyte cation was accomplished throughout the polymer layer, and that the layer stayed on the current collector without exfoliation or dissolution into the electrolyte during the electrolysis. The charging/discharging behavior of the polymer layer in the aqueous electrolyte revealed the capability of undergoing electrochemistry even in the nonsolvent of the pendant group, which offered insight into the nature of the anthraquinone pendants populated on the aliphatic chain. Charging/discharging capability of air batteries was accomplished by using the polymer layer as an organic anode-active material. A test cell fabricated using the conventional MnO(2)/C cathode catalyst exhibited a discharging voltage at 0.63 V corresponding to their potential gap and a charging/discharging cycle of more than 500 cycles without loss of the capacity.
The CompWHoB Corpus: Computational Construction, Annotation and Linguistic Analysis of the White House Press Briefings Corpus

The CompWHoB (Computational White House press Briefings) Corpus, currently being developed at the University of Naples Federico II, is a corpus of spoken American English focusing on political and media communication. It represents a large collection of the White House Press Briefings, namely, the daily meetings held by the White House Press Secretary and the news media. At the time of writing, the corpus amounts to more than 20 million words, covers a period of time of twenty-one years spanning from 1993 to 2014 and it is planned to be extended to the end of the second term of President Barack Obama. The aim of the present article is to describe the composition of the corpus and the techniques used to extract, process and annotate it. Moreover, attention is paid to the use of the Temporal Random Indexing (TRI) on the corpus as a tool for linguistic analysis.
Economic Value of Biological Control in Integrated Pest Management of Managed Plant Systems

Biological control is an underlying pillar of integrated pest management, yet little focus has been placed on assigning economic value to this key ecosystem service. Setting biological control on a firm economic foundation would help to broaden its utility and adoption for sustainable crop protection. Here we discuss approaches and methods available for valuation of biological control of arthropod pests by arthropod natural enemies and summarize economic evaluations in classical, augmentative, and conservation biological control. Emphasis is placed on valuation of conservation biological control, which has received little attention. We identify some of the challenges of and opportunities for applying economics to biological control to advance integrated pest management. Interaction among diverse scientists and stakeholders will be required to measure the direct and indirect costs and benefits of biological control that will allow farmers and others to internalize the benefits that incentivize and accelerate adoption for private and public good.