ethicalabs/Research-Intent-Collab huggingface dataset:
Multiple time series database on microservice architecture for IoT-based sleep monitoring system

AbstractMonitoring health status requires collecting a large amount of data from the human body. The sensor can be used to collect data from the human body. The sensor transmits data for almost every second across the internet. The challenge of the health monitoring system is the massive amount of incoming data. Therefore, a system capable of sending, storing, analyzing, and visualizing vast amounts of data is required for health monitoring. A previous study proposed microservice and event-driven architecture. It also proposed a single database for all services and a relational database management system (RDBMS) for storing time series data, which might reduce the data transmission performance and reliability. This research intends to improve the monitoring system from the previous study to accommodate a greater throughput, faster database read and write operations, and a more reliable system design. The improvement consists of multiple changes in system architecture and technology. A multi-database is proposed in the system architecture to improve system reliability. Time series database and Message Queue Telemetry Protocol (MQTT) server are proposed as an upgrade on technology. As a result, the proposed system throughput is 2.43 times faster than the old system. On database performance, the new system's database write speed is 20.95 times faster and the database read speed is 1.64 times faster than the old system. The proposed system also achieves better scalability, resilience, and independence.
Quantum computing on the verge: correcting errors, developing algorithms and building up the user base

In the second of a two-part article, Philip Ball looks the challenges of error correction to build truly useful quantum computing; how algorithms will need to be platform-independent; and finally how early users will adopt quantum technologies.
Acceptance of health technology assessment submissions with incremental cost-effectiveness ratios above the cost-effectiveness threshold

Elizabeth A Griffiths, Janek K Hendrich, Samuel DR Stoddart, Sean CM Walsh HERON&trade; Commercialization, PAREXEL International, London, UK Objectives: In health technology assessment (HTA) agencies where cost-effectiveness plays a role in decision-making, an incremental cost-effectiveness ratio (ICER) threshold is often used to inform reimbursement decisions. The acceptance of submissions with ICERs higher than the threshold was assessed across different agencies and across indications, in order to inform future reimbursement submissions. Methods: All HTA appraisals from May 2000 to May 2014 from National Institute for Health and Care Excellence (NICE), Scottish Medicines Consortium (SMC), Pharmaceutical Benefits Advisory Committee (PBAC), and Canadian Agency for Drugs and Technologies in Health (CADTH) were assessed. Multiple technology appraisals, resubmissions, vaccination programs, and requests for advice were excluded. Submissions not reporting an ICER, or for which an ICER could not be determined were also excluded. The remaining appraisals were reviewed, and the submitted ICER, recommendation, and reasoning behind the recommendation were extracted. Results: NICE recommended the highest proportion of submissions with ICERs higher than the threshold (34% accepted without restrictions; 20% with restrictions), followed by PBAC (16% accepted without restrictions; 4% with restrictions), SMC (11% accepted without restrictions; 14% accepted with restrictions), and CADTH (0% accepted without restrictions; 26% with restrictions). Overall, the majority of higher-than-threshold ICER submissions were classified into the &quot;malignant disease and immunosuppression&quot; therapeutic category; however, there was no notable variation in acceptance rates by disease area. Reasons for accepting submissions reporting ICERs above the threshold included high clinical benefit over the standard of care, and addressing an unmet therapeutic need. Conclusion: Acceptance of submissions with higher-than-threshold ICERs varied by HTA agency and was not significantly influenced by disease category. Such submissions must be accompanied by robust, concrete, and transparent evidence in order to achieve patient access. Keywords: decision-making, incremental cost-effectiveness ratio, health technology assessment, QALY, cost-effectiveness
Learning From Failure: Integrating Negative Examples when Fine-tuning Large Language Models as Agents

Large language models (LLMs) have achieved success in acting as agents, which interact with environments through tools such as search engines. However, LLMs are optimized for language generation instead of tool use during training or alignment, limiting their effectiveness as agents. To resolve this problem, previous work has first collected interaction trajectories between LLMs and environments, using only trajectories that successfully finished the task to fine-tune smaller models, making fine-tuning data scarce and acquiring it both difficult and costly. Discarding failed trajectories also leads to significant wastage of data and resources and limits the possible optimization paths during fine-tuning. In this paper, we argue that unsuccessful trajectories offer valuable insights, and LLMs can learn from these trajectories through appropriate quality control and fine-tuning strategies. By simply adding a prefix or suffix that tells the model whether to generate a successful trajectory during training, we improve model performance by a large margin on mathematical reasoning, multi-hop question answering, and strategic question answering tasks. We further analyze the inference results and find that our method provides a better trade-off between valuable information and errors in unsuccessful trajectories. To our knowledge, we are the first to demonstrate the value of negative trajectories and their application in agent-tunning scenarios. Our findings offer guidance for developing better agent-tuning methods and low-resource data usage techniques.
Physician-patient communication and patient-reported outcomes in the actinic keratosis treatment adherence initiative (AK-TRAIN): A multicenter, prospective, real-life study of treatment satisfaction, quality of life and adherence to topical field-directed therapy for the treatment of actinic keratosis in Italy

Background: Patients with multiple actinic keratoses (AKs) should be treated with field-directed therapy. Such treatments challenge patients' adherence due to out-of-pocket costs, length of treatment and severity of local skin reactions (LSRs). Effective physician-patient communication (PPC) may buffer therapy-related distress, thus improving quality of life, treatment satisfaction and adherence. Objectives: We evaluated the interplay between PPC, LSR intensity (safety) and lesion clearance rates (effectiveness) on treatment satisfaction, quality of life and treatment adherence among patients with multiple AKs receiving topical field-directed therapies. Methods: In this observational, multicentre, longitudinal, cohort study, we included 1136 adult patients with discrete, clinically detectable, visible, multiple (three or more lesions in a 25 cm2area), Grade I/II AKs, for whom the attending dermatologist has prescribed treatment with a topical field-directed therapy. We matched self-reported data and medical information recorded by dermatologists in standard clinical forms. Patients were followed up at two time points (T1: 8 days; T2: 25-30 days) Results: Most patients were elderly, married, men with poor socio-economic status and multiple lesions of the scalp or face. The majority (n = 961) had a prescription of ingenol mebutate (IMB) and 175 received either diclofenac 3% in hyaluronic acid (DHA) or imiquimod 5% (IMQ). Clearance rate at 1 month was 84%. Most patients felt very supported (n = 819, 73%) and rated dermatologist's explanations very clear (n = 608, 54%). Treatment satisfaction (effectiveness and convenience scales) increased along the follow-up, especially for those on IMB (Δpre-post= -4.00; other: Δpre-post= -0.25; interaction P < 0.001). Communication clarity was associated with higher treatment satisfaction scores (β = 0.4-0.6, P < 0.01) and lower risk of non-adherence among IMB patients (risk difference: 16%, P < 0.01). Conclusion: Communication clarity was associated with patient-reported outcomes and adherence beyond AK-related clinical parameters. Our study questions the current episodic approach to AK management and provides the rationale to develop chronic care models fostering patients' engagement and treatment alliance. Journal of the European Academy of Dermatology and Venereology
Gut Microbiome Metagenomics Analysis Suggests a Functional Model for the Development of Autoimmunity for Type 1 Diabetes

Public Library of Science open access
Illumination of the accretion disk in black hole binaries: An extended jet as the primary source of hard X-rays

Context.The models that seek to explain the reflection spectrum in black hole binaries usually invoke a point-like primary source of hard X-rays. This source illuminates the accretion disk and gives rise to the discrete (lines) and continuum-reflected components.Aims.The main goal of this work is to investigate whether the extended, mildly relativistic jet that is present in black hole binaries in the hard and hard-intermediate states is the hard X-ray source that illuminates the accretion disk.Methods.We use a Monte Carlo code that simulates the process of inverse Compton scattering in a mildly relativistic jet rather than in a “corona” of some sort. Blackbody photons from the thin accretion disk are injected at the base of the jet and interact with the energetic electrons that move outward with a bulk velocity that is a significant fraction of the speed of light.Results.Despite the fact that the jet moves away from the disk at a mildly relativistic speed, we find that approximately 15−20% of the input soft photons are scattered, after Comptonization, back toward the accretion disk. The vast majority of the Comptonized, back-scattered photons escape very close to the black hole (h ≲ 6 rg, wherergis the gravitational radius), but a non-negligible amount escape at a wide range of heights. At high heights,h ∼ 500−2000 rg, the distribution falls off rapidly. The high-height cutoff strongly depends on the width of the jet at its base and is almost insensitive to the optical depth. The disk illumination spectrum is softer than the direct jet spectrum of the radiation that escapes in directions that do not encounter the disk.Conclusions.We conclude that an extended jet is an excellent candidate source of hard photons in reflection models.
Enhancing Supply Chain Agility and Sustainability through Machine Learning: Optimization Techniques for Logistics and Inventory Management

Background: In the current global market, supply chains are increasingly complex, necessitating agile and sustainable management strategies. Traditional analytical methods often fall short in addressing these challenges, creating a need for more advanced approaches. Methods: This study leverages advanced machine learning (ML) techniques to enhance logistics and inventory man-agement. Using historical data from a multinational retail corporation, including sales, inventory levels, order fulfillment rates, and operational costs, we applied a variety of ML algorithms, in-cluding regression, classification, clustering, and time series analysis. Results: The application of these ML models resulted in significant improvements across key operational areas. We achieved a 15% increase in demand forecasting accuracy, a 10% reduction in overstock and stockouts, and a 95% accuracy in predicting order fulfillment timelines. Additionally, the approach identified at-risk shipments and enabled customer segmentation based on delivery preferences, leading to more personalized service offerings. Conclusions: Our evaluation demonstrates the transforma-tive potential of ML in making supply chain operations more responsive and data-driven. The study underscores the importance of adopting advanced technologies to enhance deci-sion-making, evidenced by a 12% improvement in lead time efficiency, a silhouette coefficient of 0.75 for clustering, and an 8% reduction in replenishment errors.
Climate change consequences for insect pest management, sustainable agriculture and food security

By 2050, global agricultural production must double to meet increasing food demands due to human population growth. A range of Anthropocene stresses, including invasive species, habitat loss, various forms of pollution, and climate change are having effects on insect pests leading to negative consequences for sustainable agriculture and food security. Climate change directly impacts dispersal, survival, reproduction, and development of insects; but predicting the outcome of these effects is complicated by the fact that insects include both pest species and natural enemy species. The situation is further complicated by potentially strong indirect effects of climate change including plant-mediated phenomena as a consequence of the effects of temperature and atmospheric carbon dioxide (CO2) levels on resource availability and nutritional quality of crops. This paper synthesizes the often fragmented and narrowly focused literature to consider how aspects of climate change will affect insect pests, their mortality factors, and outcomes for pest management which needs to extend beyond the promotion of integrated pest management to encompass agroecological and holistic approaches for sustainable agriculture, and food security.
Managers’ leadership styles: organizational commitment, job autonomy and extra-role behaviors

Purpose                     Using a dyadic-level analysis, this study examines how organizational commitment accounts for the impacts of transformational and transactional leadership styles on service employees’ extra-role behavior and how job autonomy moderates the impacts of these leadership styles.                                                           Design/methodology/approach                     A matched sample of subordinates and superiors in the service industry was targeted. Data acquired from 271 customer service employees and 33 of their immediate supervisors at five-star hotels in Seoul, South Korea, was used for the analysis.                                                           Findings                     This study found that organizational commitment mediates the impacts of both leadership styles on extra-role behavior. Job autonomy, however, moderates the impact only of transformational leadership on organizational commitment.                                                           Originality/value                     This study provides theoretically meaningful implications that contribute to the literature on the impact of leadership styles on employees’ extra-role behavior.
Two mysterious universal dark matter-baryon relations in galaxies and galaxy clusters

Starting from the 1970s, some relations connecting dark matter and baryons were discovered, such as the Tully-Fisher relation. However, many of the relations found in galaxies are quite different from that found in galaxy clusters. Here, we report two new mysterious universal relations connecting dark matter and baryons in both galaxies and galaxy clusters. The first relation indicates that the total dynamical mass of a galaxy or a galaxy cluster $M_{500}$ has a power-law relation with its total baryonic mass $M_b$ within the `virial region': $M_{500} \propto M_b^a$, with $a \approx 3/4$. The second relation indicates that the enclosed dynamical mass $M_d$ is almost directly proportional to the baryonic mass for galaxies and galaxy clusters within the central baryonic region: $M_d \propto M_b$. The close relations between dark matter and baryons in both galaxies and galaxy clusters suggest that some unknown interaction or interplay except gravity might exist between dark matter and baryons.
Right to Privacy and State Surveillance

The conflict between state surveillance and the fundamental right of privacy is apparent even at the conceptual level. The rise of advanced surveillance mechanisms has been another abetting factor to this conflict while on the other hand many theorists have been at work to find a harmonisation between them. Surveillance techniques and mechanisms have indeed been helpful in thwarting the threats to national security and keeping the integrity of a nation. The chapter analyses whether the collective good that upholds state surveillance tends to override the individual interest that advocates the right to privacy. It considers the criteria or procedures followed to arrive at such a decision and whether the authorities could have been advised to find a better solution through harmonization rather than neglecting one in favour of the other. It explores the morality behind surveillance, including the panopticon model by Bentham, which was an example of promoting moral behaviour through surveillance.
Participation of African member states in the World Trade Organization dispute settlement mechanism

The WTO Dispute Settlement Understanding (DSU) is viewed as one of the success stories under the WTO. However, the participation of African member states in the DSU system has been minimal, and that is attributed to, among other things, lack of human capital, material costs of accessing the dispute settlement system and concerns about the quality of remedies available. Current negotiations under the Doha Development Round address some of these problems. The African Group representing African member states have presented their own proposals for reforms. A robust engagement by the African Group in current negotiations is advocated. Such intervention will contribute to the overall WTO jurisprudence whose interpretations will be sensitive to Africa's developmental needs. Other tentative recommendations are suggested, especially that suggesting the relocation of WTO headquarters to a suitable venue in Africa where the majority of LDCs are found. Such relocation will have trade related beneficial effects.
Redefining Health Care Data Interoperability: Empirical Exploration of Large Language Models in Information Exchange

Background                     Efficient data exchange and health care interoperability are impeded by medical records often being in nonstandardized or unstructured natural language format. Advanced language models, such as large language models (LLMs), may help overcome current challenges in information exchange.                                                           Objective                     This study aims to evaluate the capability of LLMs in transforming and transferring health care data to support interoperability.                                                           Methods                     Using data from the Medical Information Mart for Intensive Care III and UK Biobank, the study conducted 3 experiments. Experiment 1 assessed the accuracy of transforming structured laboratory results into unstructured format. Experiment 2 explored the conversion of diagnostic codes between the coding frameworks of the ICD-9-CM (International Classification of Diseases, Ninth Revision, Clinical Modification), and Systematized Nomenclature of Medicine Clinical Terms (SNOMED-CT) using a traditional mapping table and a text-based approach facilitated by the LLM ChatGPT. Experiment 3 focused on extracting targeted information from unstructured records that included comprehensive clinical information (discharge notes).                                                           Results                     The text-based approach showed a high conversion accuracy in transforming laboratory results (experiment 1) and an enhanced consistency in diagnostic code conversion, particularly for frequently used diagnostic names, compared with the traditional mapping approach (experiment 2). In experiment 3, the LLM showed a positive predictive value of 87.2% in extracting generic drug names.                                                           Conclusions                     This study highlighted the potential role of LLMs in significantly improving health care data interoperability, demonstrated by their high accuracy and efficiency in data transformation and exchange. The LLMs hold vast potential for enhancing medical data exchange without complex standardization for medical terms and data structure.
Scientific and technological uncertainty, the precautionary principle, scenarios and risk management

Uncertainty, the precautionary principle and scenario are three important concepts in current regulatory debates concerned with risk management. In this paper, each concept is described in relation to its regulatory context and a linkage between the three concepts is established. Three scenarios relating to increasing scientific and technical uncertainty are presented. The most obvious regulatory approach to uncertainty is to ban a product, process or substance under the aegis of the precautionary principle. However, this may not be appropriate in all cases and a range of other possible policy responses to uncertainty are discussed and avenues for further research suggested.
Deep Learning Enhanced Early Detection of Pancreatic Cancer Using Integrated Photonic Chip Based Optical Neural Networks

Employing Integrated Photonic Chip-Based ONNs for early pancreatic cancer detection, achieved an 80% Dice score, demonstrating efficient, high-speed alternatives to traditional electrical training systems for medical imaging.
Visualising Intangibility Through Sdijuno Dashboard. Information Design for Culinary Culture

The article critically assesses the effectiveness of Information Design and Data Visualisation methods to commodifying intangible cultural heritage, with specific reference to local cuisine traditions. Through the case study of "Sdijuno"—a visual dashboard of Abruzzese culinary culture—the study explores how communication design artefacts can tap into tacit knowledge and encode it into transmissible visual representations. The research introduces design as a mediator of cultures that is capable of bridging generations and preserving local uniqueness in the face of globalising forces.
Economic vulnerability and adaptation to climate hazards and climate change: Building resilience in the Barnegat Bay Region, final revised version

This study identifies key economic vulnerabilities to climate change and options for adaptation in the Barnegat Bay region of New Jersey. This study draws on stakeholder knowledge of the region, including understanding of existing development stresses, in order to identify critical economic vulnerabilities to climate change and to identify feasible options for adaptation. The study pays particular attention to key economic assets and activities that may be at risk from climate change, as well as vulnerable populations. The study also considers the implications of climate change for emergency management and hazard mitigation. The broader goal of the study is to provide stakeholder-based information about economic risks and vulnerabilities in the Barnegat Bay region that will contribute to efforts to build long-term resilience to climate-related hazards and climate change.