Search Results (245)

The energy transition takes a long time and requires a complex process involving stakeholder consensus. This study aims to explore the political, economic, and sociocultural dynamics that emerged during the short-term energy transition between the Moon and Yoon administrations in Korea, assessing the current energy transition, which stands at a crossroads, and provides conclusions and implications to inform future decisions on the findings. To this purpose, a multi-level perspective analytical framework was applied to investigate the two administrations’ conflicting energy transition mechanisms on the level of actors, technologies, and rules/institutions. According to the results, the Moon administration pursued a reconfiguration pathway of limited changes by attempting to phase out nuclear power plants and expand renewable energy, while the Yoon administration promoted a transformation pathway of partial change by abandoning the policy of phasing out nuclear power plants and further expanding existing nuclear energy. Differences in pathways were found to stem from differentiation based on political ideology and political purposes among key actors, rather than socio-technological innovation. This paper argues that Korea’s short-term energy transition was hastily pursued amidst a lack of public discourse, insufficient technological development, and institutional deficiencies, ultimately blocking the pathway to a desirable energy transition and having Korea locked in its existing energy system. This paper also suggests that no single pathway exists to carbon neutrality, and that future administrations can find desirable pathways by overcoming challenges and dilemmas through continuous improvement and adjustment. Full article

For the first time, this paper introduces Nabla fractional calculus into the distributed Nash equilibrium (NE) seeking problem of aggregative games (AGs) with partial decision information in undirected communication networks, and proposes two novel fractional-order distributed algorithms. In the considered setting, each agent can access to only local information and collaboratively estimates the global aggregate through communication with its neighbors. Both algorithms adopt a backward-difference scheme followed by an implicit fractional-order gradient descent step. One updates local aggregate estimates via fractional-order dynamic tracking and the other uses fractional-order average dynamic consensus protocols. Under standard assumptions, convergence of both algorithms to the NE is rigorously proved using nabla fractional-order Lyapunov stability theory, achieving a Mittag-Leffler convergence rate. The feasibility of the developed schemes is verified via numerical experiments applied to a Nash-Cournot game and the coordination control of flexible robotic arms. Full article

This systematic review examines chronic kidney disease-associated pruritus (CKD-aP) as a complex clinical manifestation in patients undergoing hemodialysis. Traditionally considered a secondary symptom of end-stage renal disease, emerging evidence now positions CKD-aP as a multidimensional disorder with substantial pathogenic influence on patient outcomes. Using the PRISMA 2020 methodology, we critically evaluated 54 peer-reviewed studies published between 2020 and 2025. Our synthesis highlights a convergence of five mechanistic frameworks underpinning CKD-aP: elevated levels of uremic toxins originating from gut microbial dysbiosis, immune activation driven by IL-31 and other pro-inflammatory cytokines, heightened peripheral and central neural sensitization, dysregulation of endogenous opioid receptor pathways favoring μ-receptor activation, and xerosis-related epidermal barrier dysfunction. These mechanisms contribute to a systemic cycle of microinflammation, pruritogenic signaling, and neural hyperexcitability. We also identified and compared validated assessment tools—including the NRS, VAS, Skindex-10, and the UP-Dial scale—that facilitate standardized quantification of disease burden. While available treatments such as gabapentinoids and phototherapy offer partial relief, targeted therapies—including κ-opioid receptor agonists—represent a major advancement, although long-term effectiveness and accessibility remain under investigation. Growing scientific consensus establishes CKD-aP as a priority therapeutic target in hemodialysis care, underscoring the need for integrated, mechanism-based management strategies to improve quality of life and clinical outcomes. This work represents a narrative systematic review, integrating evidence from mechanistic, translational, and clinical studies to critically examine the biological pathways underlying CKD-associated pruritus. Full article

Objective. The aim of this study was to define a structured competence model for nurses working in gastrointestinal endoscopy in Italy and to assess nurses’ perceptions of the number of procedural repetitions required to acquire and maintain competence across different endoscopic procedures. Methods. A cross-sectional online survey targeted registered nurses working in Italian gastrointestinal endoscopy units. The questionnaire, developed from guidelines and expert consensus, covered demographics, organizational context, and perceived repetition thresholds for 30 procedures. Partial Credit Models (PCMs) estimated acquisition and maintenance thresholds; Differential Item Functioning (DIF) tested differences by self-reported experience level. Results. A total of 332 nurses participated (68.4% female; mean age 47.1 years; mean endoscopy experience 10.1 years). For competence acquisition, most procedures were placed in the 11–30 or 31–50 repetition range, with higher values for complex techniques. Competence maintenance generally required fewer repetitions, but thresholds varied by procedure. Advanced or infrequently performed techniques were perceived as more demanding. More experienced nurses reported higher thresholds, reflecting stricter internal standards. Conclusions. Acquisition and maintenance of gastrointestinal endoscopy competences differ in intensity and frequency requirements, supporting the need for tailored, modular training pathways. Findings highlight the importance of national competence standards, adaptive learning technologies, and structured mentorship to enhance skill development, reduce variability, and promote consistent, high-quality patient care across Italy. Full article

Hydrogen is frequently incorporated in alkaline-earth oxides during crystal growth or post-deposition annealing. For MgO, several studies in the past showed that interstitial monatomic hydrogen can also favourably bind with oxygen vacancies to form stable substitutional defect complexes (substitutional hydrogen or U-defect centers). The present study reports first-principles density-functional calculations of the formation energies of both interstitial and substitutional forms of the hydrogen impurity in MgO. Determination of the site-resolved densities of electronic states allowed for a detailed identification of the nature of the impurity-induced levels, both in the valence-energy region and inside the band gap of the host. The stability and diffusion mechanisms of both hydrogen defects was also studied with the aid of nudged elastic-band (NEB) calculations. Interstitial hydrogen was found to be an amphoteric defect with the lower formation energy for any realistic environment conditions (temperature and oxygen partial pressure). The NEB calculations showed that it is a fast-diffusing species when it is thermodynamically stable as a positively-charged state (bare proton). In contrast, the hydrogen-vacancy complex is a shallow donor, extremely stable against dissociation and virtually immobile as an isolated defect. Its formation is found to be favoured for a range of mid-gap Fermi-level positions where positively-charged interstitial hydrogen and neutral oxygen vacancies (F centers) are both thermodynamically stable low-energy defects. The present findings are consistent with the established consensus on the electrical activity of hydrogen in MgO as well as with experimental observations reporting the remarkable thermal stability of substitutional hydrogen defects and their ability to act as electron traps. Full article

Empirical debates about a “crisis of trust” highlight long-lived pockets of high trust and deep distrust in institutions, as well as abrupt, shock-induced shifts between the two. We propose a probabilistic model in which such phenomena emerge endogenously from social learning on hierarchical networks. Starting from a discrete model on a directed acyclic graph, where each agent makes a binary adoption decision about a single assertion, we derive an effective influence kernel that maps individual priors to stationary adoption probabilities. A continuum limit along hierarchical depth yields a degenerate, non-conservative logistic–diffusion equation for the adoption probability $u(x,t)$, in which diffusion is modulated by $(1-u)$ and increases the integral of u rather than preserving it. To account for micro-level uncertainty, we perturb these dynamics by multiplicative Stratonovich noise with amplitude proportional to $u(1-u)$, strongest in internally polarised layers and vanishing at consensus. At the level of a single depth layer, Stratonovich–Itô conversion and Fokker–Planck analysis show that the noise induces an effective double-well potential with two robust stochastic phases, $u\approx 0$ and $u\approx 1$, corresponding to persistent distrust and trust. Coupled along depth, this local bistability and degenerate diffusion generate extended domains of trust and distrust separated by fronts, as well as rare, Kramers-type transitions between them. We also formulate the associated stochastic partial differential equation in Martin–Siggia–Rose–Janssen–De Dominicis form, providing a field-theoretic basis for future large-deviation and data-informed analyses of trust landscapes in hierarchical societies. Full article

Background/Objectives: Topical steroid withdrawal syndrome is an underrecognized (and at times controversial) diagnosis, predominantly seen in individuals with a history of prolonged medium- to high-potency steroid use with sudden cessation. We aim to present topical steroid withdrawal clinical cases along with a narrative review of the literature to better characterize this understudied phenomenon. Methods: A total of 16 patients with a history of topical steroid withdrawal were enrolled in an IRB-approved clinical trial (NCT04864886). Participants underwent clinical assessments at the National Institutes of Health, including a history and physical examination, photography, genome sequencing, and comprehensive blood work. A follow-up survey assessed symptom activity and functional impact. Results: All patients reported severe itch, heat and photosensitivity, erythema, skin dryness, and pain. A total of 11 patients exhibited elevated IgE levels, 9 patients noted metallic-smelling skin, and 4 had peripheral blood eosinophilia. Symptomatic relief was observed with dupilumab, berberine, naltrexone, and various home remedies including topical ointments, vitamins, and probiotics, though effectiveness varied and often required trial and error. At follow-up, most respondents reported partial but ongoing symptoms, with several describing residual itch and intermittent interference with daily activities. Some participants continued therapeutic interventions, such as berberine, over two years after their initial evaluation. Conclusions: Our findings report improvement in patient symptoms such as itch and detail emerging management strategies that have not been discussed before. Improved recognition, physician consensus, and systemic evaluation of therapeutic options are needed to guide care and enhance quality of life for affected patients. Full article

Species of the orders Charadriiformes and Anseriformes serve as the primary long-distance disseminators of various avulaviruses. The most economically significant among them is Newcastle disease virus (NDV), or Avian orthoavulavirus 1 (AOAV-1), which causes diseases of varying severity in both domestic and wild birds. Other avulaviruses have been studied to a much lesser extent, and for most of them, only single isolates are known, which does not allow a comprehensive assessment of their potential threat. To evaluate the biological diversity and potential risks posed by avian paramyxoviruses spread by wild waterfowl during autumn migration, fecal samples from mallards (Anas platyrhynchos) (n = 3604) were collected at water bodies in Moscow and the Moscow Region between 2008 and 2024. From these samples, AOAV-1 (n = 4) and Avian paraavulavirus 4 (APMV-4) (n = 9) were isolated and partially sequenced. Phylogenetic analysis revealed that all AOAV-1 isolates belong to genotype 1 of class II, while all APMV-4 isolates belong to the Eurasian subgenotype of genotype 1. Analysis of the F protein cleavage site motif indicated conformity with the consensus sequences characteristic of lentogenic and non-pathogenic avian paramyxoviruses in all isolates. Full article

(1) Background: Inhalation injury significantly worsens burn outcomes but lacks a standardized definition and diagnostic consensus, complicating prognosis. Existing diagnostic tools often show limited sensitivity and specificity, reducing clinical utility. This study aimed to identify potential clinical markers, recorded at or shortly after admission, for inhalation injury prognostication. (2) Methods: A retrospective cohort study of 59 burn patients admitted to Tygerberg Hospital’s Burn Centre (South Africa) between 23 April 2016 and 15 August 2017 was conducted. Descriptive statistics were reported based on data type and distribution. Fisher’s exact test, Spearman’s rank correlation (rho), and partial least squares regression (VIP scores) assessed associations, correlations, and predictive value. p < 0.05 (two-tailed) denoted significance. (3) Results: Severe inhalation injury accounted for 61% of admissions (mean 11.2; CI = 9.5–12.9), with a 38.9% mortality rate. Significant associations (p ≤ 0.008) and positive correlations (p ≤ 0.06) were noted for total body surface area (rho = 0.357), complications (rho = 0.690), and burns intensive care unit length of stay (BICU LOS, rho = 0.908). Complications and BICU LOS showed the strongest predictive contributions (VIP = 1.229 and 1.372). Lactate (rho = 0.331, p < 0.011) and hoarseness (rho = −0.314, p < 0.015) correlated significantly but lacked association. (4) Conclusions: Findings suggest elevated lactate may serve as a prognostic marker, while BICU LOS and complications may reflect disease progression. A multi-marker approach is recommended. Full article

Despite seven decades of international commitment—from the 1948 Universal Declaration of Human Rights through SDG 3.8—universal health coverage remains stubbornly out of reach. Two billion people, predominantly informal sector workers, lack access to sustainable health insurance. This entry explains the underlying cause: sustainable health insurance requires specific behavioral and institutional conditions for collective action—conditions that existing health insurance models systematically fail to satisfy, thereby structurally excluding informal populations. The Trinity Law framework formalizes these conditions as three multiplicatively interacting requirements—Trust (T), Consensus (C), and Dual Benefit (DB)—expressed as S = T × C × DB. Empirical analysis of community-based health insurance schemes across 24 countries identifies a robust trust threshold (τ* ≈ 0.68) operating as a behavioral phase transition: below this level, cooperation collapses; above it, participation becomes self-sustaining. Cross-country evidence from 274 organizations across 155 countries confirms consensus thresholds (C* ≈ 0.59), while analysis of 158,763 observations validates dual benefit mechanisms. The multiplicative structure explains why partial reforms fail: weakness in any single component drives overall sustainability toward zero. Applied to health insurance, this framework distinguishes conventional systems—Bismarckian employment-based, Beveridgean tax-financed, and commercial health insurance from sustainable systems like participatory community-based microinsurance that satisfy all three Trinity Law conditions through participatory design, transparent governance, and aligned incentives. The persistent UHC gap reflects not implementation failures but fundamental design incompatibilities that the Trinity Law makes explicit. This entry has three objectives: first, it states the Trinity Law conditions; second, it summarizes the empirical evidence for each component; third, it applies the framework to classify major health insurance models. Supporting datasets and code are available in the referenced Zenodo repositories. The term ‘law’ follows the tradition of social science regularities like the ‘law of demand’: a robust empirical pattern with strong predictive validity, not a claim to physical certainty. Full article

Accurate prediction of shrimp body weight is critical for optimizing harvest timing, feed management, and stocking density decisions in intensive aquaculture. While prior studies emphasize environmental factors, operational management variables—particularly harvesting metrics—remain understudied. This study quantified the predictive importance of harvesting-related variables using 5 years of industrial-scale operational data from 12 ponds (5479 cleaned records, 34.94% retention rate). We trained seven machine learning models and applied three independent feature importance methods: consensus importance ranking, SHAP explainability analysis, and Pearson correlations. Main findings: Operational variables (days of culture: 2.833 SHAP, stocking density: 1.871, cumulative feed: 1.510) ranked substantially above environmental variables (temperature: 0.123, pH: 0.065, dissolved oxygen: 0.077). Partial harvest frequency showed bimodal clustering, indicating two distinct viable operational strategies. The Weighted Ensemble model achieved the highest performance (R² = 0.829, RMSE = 4.23 g, MAE = 3.12 g). Model stability analysis via 10-fold GroupKFold cross-validation showed that the Artificial Neural Network (ANN) exhibited the tightest confidence bounds (0.708 g width, 27.7% coefficient of variation), indicating exceptional consistency. This is the first study to systematically analyze the importance of harvesting variables using SHAP explainability, revealing that operational management decisions may yield greater returns than marginal environmental control investments. Our findings suggest that operational optimization may be more impactful than environmental fine-tuning in well-managed systems. Full article

Background/Objectives: Protein kinase C-δ (PKC-δ) is a pivotal regulator of cellular signalling, and its dysregulation contributes to oncogenesis. While certain isolated PKC-δ domains have been crystallised, the full-length architecture and interdomain interactions remain largely unresolved, limiting mechanistic insight and the design of selective modulators. We aimed to define the full-length, inactive conformation of PKC-δ and identify accessible, functionally relevant binding sites for ligand discovery. Methods: We generated a consensus structural model of full-length inactive PKC-δ using multi-template comparative modelling guided by established inactivity markers. Molecular docking was used to predict ligands targeting the C2 domain, which were subsequently validated in breast cancer cell models, including wild-type and C2 domain-overexpressing lines. Results: Analysis of the model revealed the architecture of the C2/V5 interdomain space, providing a structural rationale for regulation of the nuclear localisation signal (NLS). Docking identified two ligand classes: ligand 1 engaged a C2 domain surface oriented toward the C2/V5 pocket, while ligand 2 targeted the C2 domain phosphotyrosine-binding domain (PTD). Experimental validation in breast cancer cell models demonstrated that both ligands reduced cell viability; ligand 1 showed enhanced effects in C2-overexpressing cells, consistent with predicted accessibility, whereas ligand 2 partially counteracted the C2 domain-induced viability phenotype, likely via interference with PTD-mediated interactions. Conclusions: Full-length structural context is essential for identifying accessible, functionally relevant binding sites and understanding context-dependent kinase regulation. Integrating computational modelling with phenotypic validation establishes a framework for selective PKC-δ modulation, offering insights to guide ligand discovery, improve isoform selectivity, and inform strategies to mitigate kinase inhibitor resistance in precision oncology. Full article

Voltage-sensing phosphatases (VSPs) provide a conserved framework for dissecting the mechanics of voltage sensing and for engineering genetically encoded voltage indicators (GEVIs). To evaluate how natural sequence diversity shapes function, we compared VSP voltage-sensing domains (VSDs) from multiple species by replacing the phosphatase domain with a fluorescent protein to enable optical detection of VSD responses. Every construct that reached the plasma membrane produced a voltage-dependent optical signal, underscoring the deep conservation of voltage sensing across VSP orthologs. Yet lineage-specific substitutions generated strikingly different phenotypes. A plankton VSP ortholog from Eurytemora carolleeae and the Sea Hare (Aplysia californica) VSP exhibited left-shifted activation ranges, producing robust fluorescence transitions during modest depolarizations of the plasma membrane. The human VSD of hVSP2 yielded weak, sluggish responses with poor recovery, but reintroduction of a conserved arginine in S1 (G95R) partially restored reversibility, implicating lipid-facing residues in conformational stability. The Chinese hamster (Cricetulus griseus) VSD, with atypical S4 sensing charges (RWIR), generated a slow fluorescence increase during depolarization, while reverting to the consensus arginine (RRIR) inverted the polarity to a decrease. These contrasting behaviors show that single residue changes can reshape how VSD movements influence the fluorescent reporter, highlighting the molecular precision revealed by GEVI measurements. Together, these results show that voltage-dependent signaling is deeply conserved across VSPs but shaped by lineage-specific sequence variation, establishing VSPs as powerful models for probing voltage sensing and guiding GEVI design. Full article

Background: Mapping anti–HLA class I cross-reactivity from single-antigen bead (SAB) mean fluorescence intensity (MFI) data supports donor selection. However, interpretation is complicated by analytical choices and assay variability. Methods: A total of 4327 SAB assays were analyzed (antigen × test matrix) using an interpretable, distance-based workflow. Antigen profiles were z-scored across tests. Multidimensional scaling (MDS) was used for visualization and hierarchical clustering analysis (HCA) for grouping, and complemented these with a common PCA space for model selection (K-Means via Silhouette; Gaussian Mixture Models via BIC), agglomerative (Ward and average-link on 1–correlation), spectral clustering on correlation-derived affinities, and a graph approach (k-NN ∪ minimum-spanning-tree with modularity-based communities). Non-linear embeddings (t-SNE/UMAP) and density-based HDBSCAN were used only for visual analytics, not for primary inference. Results: The pipeline revealed coherent reactivity neighborhoods that partially overlapped known cross-reactive antigen groups (CREGs) and eplet-based expectations while also highlighting less-documented relationships. Robustness was confirmed through bootstrap resampling, graph modularity, and consensus clustering across methods. Conclusions: This unified, auditable workflow converts descriptive maps into method-robust summaries of antibody reactivity and cross-reactivity. While exploratory and performed on a single dataset without linked outcomes, the approach provides a reproducible structure for comparing cohorts and prioritizing hypotheses that could be prospectively validated for clinical decision support in transplantation. Full article

Fall detection systems are a critical application of human pose estimation, frequently struggle with achieving real-world robustness due to their reliance on domain-specific datasets and a limited capacity for generalization to novel conditions. Models trained on controlled, canonical camera views often fail when subjects are viewed from new perspectives or are partially occluded, resulting in missed detections or false positives. This study tackles these limitations by proposing the Viewpoint Invariant Robust Aggregation Graph Convolutional Network (VIRA-GCN), an adaptation of the Richly Activated GCN for fall detection. The VIRA-GCN introduces a novel dual-strategy solution: a synthetic viewpoint generation process to augment training data and an efficient inference-time aggregation method to form consensus-based predictions. We demonstrate that augmenting the Le2i dataset with simulated rotations and occlusions allows a standard pose estimation model to achieve a significant increase in its fall detection capabilities. The VIRA-GCN achieved 99.81% accuracy on the Le2i dataset, confirming its enhanced robustness. Furthermore, the model is suitable for low-resource deployment, utilizing only 4.06 M parameters and achieving a real-time inference latency of 7.50 ms. This work presents a practical and efficient solution for developing a single-camera fall detection system robust to viewpoint variations, and introduces a reusable mapping function to convert Kinect data to the MMPose format, ensuring consistent comparison with state-of-the-art models. Full article