ethicalabs/Research-Intent-Collab huggingface dataset:
Climate Risk Stress Testing in California: A Geospatial Framework for Banking and Climate-Exposed Sectors

This paper develops a geospatial framework for climate risk stress testing in California with applications to banking and climate-exposed sectors such as agriculture, real estate, and tourism. The study integrates physical hazard mapping, sector-specific exposure analysis, and scenario-based financial risk assessment to evaluate how wildfires, drought, flooding, extreme heat, and transition risks may affect regional economic activity and financial stability. The framework is intended to support portfolio monitoring, climate scenario analysis, and institutional readiness under emerging disclosure and risk-management standards. In addition, the paper provides a survey-based implementation guide for benchmarking current climate-risk practices and data needs across industry and academic stakeholders.
The isotope and trace element geochemistry of basalts from the volcanic islands of the southern Red Sea

Abstract           Alkali basalts from the Hanish-Zukur and Zubair island groups in the southern Red Sea have been analysed for major, trace elements and Sr, Nd and Pb isotopes. They have close to primary compositions with high Mg# (60–70) and Ni and Cr concentrations up to 298 ppm and 597 ppm respectively. Many have only experienced olivine fractionation and this can be readily corrected. Compositional variations in the corrected analyses are interpreted to result from variations in the degree of melting, and a simple inversion of the corrected incompatible element abundances reveals a source composition intermediate between that of N-MORB and primitive mantle. This is suggested to result from the interaction of depleted asthenospheric mantle with less depleted material derived from the nearby Afar plume.                        The overall geochemical characteristics of the basalts are comparable with ocean island basalts erupted through thin (young) lithosphere. SiO             2             varies from 44.0–47.9%, Nb/Y from 0.8–1.4 and Ce/Y averages 1.64, close to values from Ascension Island.             143             Nd/             144             Nd ratios show minimal variation between 0.51301–0.51309 whereas             87             Sr/             86             Sr ranges between 0.70323–0.70396, and the analyses define a horizontal trend extending to the right of the mantle array. Pb isotopes also show marked variation,             206             Pb/             204             Pb values varying from 18.675–19.077, but the analyses remain within the ranges defined by MORB and are generally comparable with samples from the Red Sea axial trough and the Gulf of Aden.                      Comparison with basalts from Afar and the Main Ethiopian Rift (MER), together with those from other parts of the Red Sea and Gulf of Aden reveal systematic shifts in isotope ratios with degree of extension. Along the constructive plate margins and including the island basalts, isotope results are dominantly asthenospheric, showing variations from N-MORB towards a possible plume end-member. In Afar, where β factors are lower (&lt;2.5), isotope ratios show a greater deviation from oceanic basalts and this is most marked in the MER basalts where β factors are lowest (&lt; 1.2).           These data are tentatively related to a model of passive extension over a mantle plume, driven by plate motions, with the possibility of active, plume-driven extension being restricted to the early stages of Ethiopian flood basalt volcanism and the subsequent development of the MER during the Miocene.
Chemical-wet Synthesis and Electrochemistry of LiNi1/3Co1/3Mn1/3O2 Cathode Materials for Li-ion Batteries

Abstract   LiNi 1/3 Co 1/3 Mn 1/3 O 2  (LNCM) with a well-ordered layered structure, confirmed by X-ray diffraction, was synthesized by the chemical-wet synthesis incorporated with (i) a pulse microwave-assisted heating of LNCM precursors and (ii) a carbon coating technique. The microwave irradiation periods (i.e., 5–20 min) and amount of carbon additive (i.e., glucose content: 0.1–0.75%) served as key factors in modifying as-prepared LNCM powders. The electrochemical performance of as-prepared LNCM cathodes was well characterized by cyclic voltammetry and charge–discharge cycling at 0.1–5 C . Both appropriate microwave heating and carbon coating significantly improve discharge capacity, rate capability, and cycling stability of LNCM cathodes. This improved performance can be attributed to the facts that an appropriate microwave heating of LNCM precursors induces low cation mixing of the layered lattices and the carbon coating enables the creation of outer circuit of charge-transfer pathway, preventing cathode corrosion from direct contact to the electrolyte. The C-coated LNCM cathode shows the increased capacity retention from 70.2 to 93.3% after 50 cycles at 1 C . On the basis of the experimental results, both the microwave heating and the carbon coating provide a feasible potential way to improve the electrochemical performance of LNCM cathode, benefiting the development of Li-ion batteries.
Glassy dynamics as a melting process (On melting dynamics and the glass transition, Part II)

There are deep analogies between the melting dynamics in systems with a first order phase transition and the dynamics from equilibrium in super-cooled liquids. For a class of Ising spin models undergoing a first order transition - namely p-spin models on the so-called Nishimori line - it can be shown that the melting dynamics can be exactly mapped to the equilibrium dynamics. In this mapping the dynamical -or mode-coupling- glass transition corresponds to the spinodal point, while the Kauzmann transition corresponds to the first order phase transition itself. Both in mean field and finite dimensional models this mapping provides an exact realization of the random first order theory scenario for the glass transition. The corresponding glassy phenomenology can then be understood in the framework of a standard first order phase transition.
Chromatin regulators: weaving epigenetic nets

Abstract                   In multicellular organisms differentiated cells must maintain their cellular memory, which will be faithfully inherited and maintained by their progeny. In addition, these specialized cells are exposed to specific environmental and cell-intrinsic signals and will have to appropriately respond to them. Some of these stimuli lead to changes in a subset of genes or to a genome-wide reprogramming of the cells that will remain after stimuli removal and, in some instances, will be inherited by the daughter cells. The molecular substrate that integrates cellular memory and plasticity is the chromatin, a complex of DNA and histones unique to eukaryotes. The nucleosome is the fundamental unit of the chromatin and nucleosomal organization defines different chromatin conformations. Chromatin regulators affect chromatin conformation and accessibility by covalently modifying the DNA or the histones, substituting histone variants, remodeling the nucleosome position or modulating chromatin looping and folding. These regulators frequently act in multiprotein complexes and highly specific interplays among chromatin marks and different chromatin regulators allow a remarkable array of possibilities. Therefore, chromatin regulator nets act to propagate the conformation of different chromatin regions through DNA replication and mitosis, and to remodel the chromatin fiber to regulate the accessibility of the DNA to transcription factors and to the transcription and repair machineries. Here, the state-of-the-art of the best-known chromatin regulators is reviewed.
Health Care Providers in War and Armed Conflict: Operational and Educational Challenges in International Humanitarian Law and the Geneva Conventions, Part II. Educational and Training Initiatives

ABSTRACTNo discipline has been impacted more by war and armed conflict than health care has. Health systems and health care providers are often the first victims, suffering increasingly heinous acts that cripple the essential health delivery and public health infrastructure necessary for the protection of civilian and military victims of the state at war. This commentary argues that current instructional opportunities to prepare health care providers fall short in both content and preparation, especially in those operational skill sets necessary to manage multiple challenges, threats, and violations under international humanitarian law and to perform triage management in a resource-poor medical setting. Utilizing a historical framework, the commentary addresses the transformation of the education and training of humanitarian health professionals from the Cold War to today followed by recommendations for the future. (Disaster Med Public Health Preparedness. 2019;13:383-396)
Quantum-Inspired Optimization for Supply Chain Logistics and Inventory Management in E-commerce

E-commerce platforms face ever more complex dimensional SKU portfolios, demand volatility, returns, seasonality and cost pressures. Traditional optimization approaches (integer programming, heuristics, meta-heuristics) increasingly strain under scale, real-time demands and combinatorial explosion. Meanwhile, quantum-inspired optimization leveraging methods such as quantum annealing, coherent Ising machines, variational circuits and QUBO (Quadratic Unconstrained Binary Optimization) mapping offer near-term practical approaches to combinatorial logistics and inventory problems. This paper proposes a comprehensive framework for applying quantum-inspired optimization to e-commerce supply-chain logistics and inventory management: we provide an extended literature review of classical and quantum-inspired methods; we derive full mathematical formulations for logistics/inventory problems and map them into QUBO/quantum-inspired frameworks; we design a benchmarking/implementation methodology; we discuss industry architecture and deployment issues (data pipelines, latency, hybrid classical/quantum-inspired workflows, interpretability, cost benefit); we present use cases and discuss practical adoption in ecommerce. Our findings suggest that while fully  fault-tolerant quantum computing remains some years away, quantum-inspired optimization can deliver meaningful improvements in logistics and inventory decisions today, particularly for large-SKU e-commerce, multi-warehouse networks and time-sensitive delivery.
Systematic literature review on the effects of occupational safety and health (OSH) interventions at                     the workplace

Objectives The aim of this review was to assess the evidence that occupational safety and health (OSH) legislative and regulatory policy could improve the working environment in terms of reduced levels of industrial injuries and fatalities, musculoskeletal disorders, worker complaints, sick leave and adverse occupational exposures. Methods A systematic literature review covering the years 1966‒2017 (February) was undertaken to capture both published and gray literature studies of OSH work environment interventions with quantitative measures of intervention effects. Studies that met specified in- and exclusion criteria went through an assessment of methodological quality. Included studies were grouped into five thematic domains: (i) introduction of OHS legislation, (ii) inspection/enforcement activity, (iii) training, such as improving knowledge, (iv), campaigns, and (v) introduction of technical device, such as mechanical lifting aids. The evidence synthesis was based on meta-analysis and a modified Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach. Results The search for peer-reviewed literature identified 14 743 journal articles of which 45 fulfilled the inclusion criteria and were eligible for meta-analysis. We identified 5181 articles and reports in the gray literature, of which 16 were evaluated qualitatively. There was moderately strong evidence for improvement by OHS legislation and inspections with respect to injuries and compliance. Conclusions This review indicates that legislative and regulatory policy may reduce injuries and fatalities and improve compliance with OHS regulation. A major research gap was identified with respect to the effects of OSH regulation targeting psychological and musculoskeletal disorders.
Digital phenotyping for mental health of college students: a clinical review

Experiencing continued growth in demand for mental health services among students, colleges are seeking digital solutions to increase access to care as classes shift to remote virtual learning during the COVID-19 pandemic. Using smartphones to capture real-time symptoms and behaviours related to mental illnesses, digital phenotyping offers a practical tool to help colleges remotely monitor and assess mental health and provide more customised and responsive care. This narrative review of 25 digital phenotyping studies with college students explored how this method has been deployed, studied and has impacted mental health outcomes. We found the average duration of studies to be 42 days and the average enrolled to be 81 participants. The most common sensor-based streams collected included location, accelerometer and social information and these were used to inform behaviours such as sleep, exercise and social interactions. 52% of the studies included also collected smartphone survey in some form and these were used to assess mood, anxiety and stress among many other outcomes. The collective focus on data that construct features related to sleep, activity and social interactions indicate that this field is already appropriately attentive to the primary drivers of mental health problems among college students. While the heterogeneity of the methods of these studies presents no reliable target for mobile devices to offer automated help—the feasibility across studies suggests the potential to use these data today towards personalising care. As more unified digital phenotyping research evolves and scales to larger sample sizes, student mental health centres may consider integrating these data into their clinical practice for college students.
A Measurement of the Cosmic Microwave Background Lensing Potential and Power Spectrum from 500 deg² of SPTpol Temperature and Polarization Data

We present a measurement of the cosmic microwave background lensing potential using 500 deg² of 150 GHz data from the SPTpol receiver on the South Pole Telescope. The lensing potential is reconstructed with signal-to-noise per mode greater than unity at lensing multipoles L ≾ 250, using a quadratic estimator on a combination of cosmic microwave background temperature and polarization maps. We report measurements of the lensing potential power spectrum in the multipole range of 100 &lt; L &lt; 2000 from sets of temperature-only (T), polarization-only (POL), and minimum-variance (MV) estimators. We measure the lensing amplitude by taking the ratio of the measured spectrum to the expected spectrum from the best-fit Λ cold dark matter model to the Planck 2015 TT + low P + lensing data set. For the minimum-variance estimator, we find A_(MV) = 0.944±0.058(Stat.)±0.025(Sys.) restricting to only polarization data, we find A_(POL) = 0.906±0.090(Stat.)±0.040(Sys.). Considering statistical uncertainties alone, this is the most precise polarization-only lensing amplitude constraint to date (10.1σ) and is more precise than our temperature-only constraint. We perform null tests and consistency checks and find no evidence for significant contamination.
Skin Lesion Classification: A Deep Learning Approach with Local Interpretable Model-Agnostic Explanations (LIME) for Explainable Artificial Intelligence (XAI)

The classification of skin cancer is crucial as the chance of survival increases significantly with timely and accurate treatment. Convolution Neural Networks (CNNs) have proven effective in classifying skin cancer. However, CNN models are often regarded as "black boxes”, due to the lack of transparency in the decision-making. Therefore, explainable artificial intelligence (XAI) has emerged as a tool for understanding AI decisions. This study employed a CNN model, VGG16, to classify five skin lesion classes. The hyperparameters were adjusted to optimize its classification performance. The best hyperparameter settings were 50 epochs, a 0.1 dropout rate, and the Adam optimizer with a 0.001 learning rate. The VGG16 model demonstrated satisfactory classification performance. The Local Interpretable Model-Agnostic Explanations (LIME) method was implemented as the XAI tool to justify the predictions made by VGG16. The LIME explanation revealed that the correct predictions made by VGG16 were owing to its truthful extraction of the cancer or lesion area, especially for the “vascular lesion” class. Meanwhile, inaccurate classifications were attributed to VGG16 extraction of the background and insignificant parts of the skin as core features. In conclusion, The LIME model allowed visual inspection of the features selected by VGG16, paving the way for improving the CNN model for better feature extraction and classification of skin lesions, offering a promising direction for future research.
Structuring Context Entities for Knowledge Discovery’, in 2022 International Conference on Computational Science and Computational Intelligence

International audience
Negative aspects of Interaction Between Host Plant Resistance and Biological Control and Its Implication in Integrated Pest Management of Crops

Biological control and host plant resistance (HPR) are important components of Integrated Pest Management (IPM) which has received adequate attention in recent years. General thinking is that host plant resistance works in harmony with biological control (Adkisson and Dyck, 1980) and these are considered compatible pest management strategies. Very little has been understood about the possible effects of the allelochemicals responsible for HPR on biological control agents (parasitoids, predators and pathogens). Allelochemicals which are products of secondary metabolites and have been shown to play a role in the defence of plants against insects, at times also play negative interaction with natural enemies (Noris and Kogan, 1980). Many entomologists have expressed their views on the influence of HPR on biological control and one of the earliest and the most pragmatic was Painter (1951) who stated that profound effect on the physiology of the host which may result from feeding on resistant plants, might affect the establishment of insect parasitoids and predators. Subsequent researchers tended to be optimistic and concentrated upon theories that stressed the compatibility of the components. However, in the recent past, it has been observed that expression of morphological, physiological and chemical characteristics of host plants due to resistance genes do reduce the effectiveness of natural enemies in suppressing herbivores (Table 1). With the increased stress on development of resistant cultivars for many crop species, a better perception of the host plant- herbivore-natural enemies interaction is most essential in order to optimise the role of HPR and biological control in IPM. This review is an attempt to highlight the research on the negative interaction (incompatibility) between host plant resistance and parasitoids/predators and its impact on the success of these components in IPM of commercial crops.
A software-defined survivability approach for wireless sensor networks in future Internet of the Things.

The Internet of the Things (IoT) is evolving rapidly, and its significant impacts are expected to affect many application domains. Challenges in areas that humans have been striving to understand, measure, or predict—such as wildlife, healthcare, or environmental hazards—are likely to be addressed by the time IoT emerges. The underlying elements of IoT are wireless sensor networks (WSNs), which consist of a large number of sensor nodes. In the IoT sphere, sensor nodes represent tangible objects—Things—that monitor changes, collect information, and eventually send it through the Internet to a recipient party. Inherently, however, a wireless sensor node relies on limited computational resources with a limited power source. These undesirable qualities result in a low level of dependability. This research explores the viability of applying the unfolding network programmability concepts to overcome survivability obstacles in WSNs and the IoT. In particular, it examines the viability of software-defined networking (SDN) in network lifetime maximisation, failure detection, and failure recovery problems in WSNs. Software-defined networking is a new network programmability concept that separates the traditionally-tied control and data planes. It offloads the route computations and management from network devices to a logically centralised controller. This separation directly leads to better allocation of computational resources for the network nodes and allows endless orchestration possibilities for the controller. This thesis proposes an SDN-based solution to increase the survivability and resilience of WSN environments. Following an approach that conforms with the centralised nature of SDN environments and considers the limited resources of the WSN. A routing algorithm based on A-star was developed for WSNs, then deployed within an SDN environment to maximise the network lifetime. Apart from finding the path with the lowest energy burden, the algorithm offloads most of the control traffic from sensor nodes to the controller. This algorithm resulted in improved resource utilisation among the nodes due to plane decoupling. Additionally, it increased the lifetime of the network by 22.6% compared to the widely explored LEACH protocol. This thesis also investigates different failure detection and recovery practices in the SDN architecture. The simulation results show that adopting bidirectional forwarding detection (BFD) with the asynchronous echo mode for WSN in an SDN environment reduces control traffic for failure detection to between 27% and 48%. The thesis also evaluates the performance of multiple recovery approaches when adopting the premises of SDN. The simulation results indicate that path protection, using group tables from the OpenFlow protocol, has a recovery time up to eight times shorter than the restoration time. The results of the study reveal that using protection as a failure recovery technique significantly reduces control traffic overhead.