Search Results (371)

A flexible skin patch based on thermochromic liquid crystals (TLCs) embedded within a polydimethylsiloxane (PDMS) elastomer is presented for passive visualization of skin–vein thermal contrasts. Five ternary TLC formulations composed of cholesteryl oleyl carbonate (COC), cholesteryl nonanoate (CN), and cholesteryl benzoate (CB) were systematically engineered to tune mesophase stability and helical pitch sensitivity within the physiological temperature range (32–37 °C). Small compositional adjustments (≤1 wt.%) produced pronounced and predictable shifts in color-play bandwidth and optical sensitivity, governed by thermally induced contraction of the cholesteric helix. Patterned TLC microdomains were integrated onto optically absorptive PDMS substrates and encapsulated within a transparent PDMS overlayer, yielding thin, mechanically compliant, and breathable films with uniform thermal transmission. Optical spectroscopy, optical microscopy, and RGB analysis revealed linear wavelength–temperature relationships (R² > 0.9) and red-to-green sensitivities of up to ~87 nm °C⁻¹, demonstrating high thermochromic sensitivity within the physiological skin temperature range. Mechanical characterization confirmed skin-matched elasticity, while preliminary sterilization studies indicated that the films retained their mechanical properties following ethanol immersion and UV exposure. As a feasibility study, the results demonstrate the potential of a compositionally tunable thermochromic elastomer platform for visualizing physiological skin temperature variations associated with superficial veins, providing a basis for further development toward wearable vein visualization for self-cannulation in home hemodialysis and related thermal sensing applications. Full article

Marine heatwaves repeatedly trigger summer mortality of the farmed Pacific oyster (Crassostrea gigas), forcing its haemocytes to reprogramme metabolism under thermal stress. The metabolic nodes governing this adaptation remain poorly defined. Integrating publicly available transcriptomics, single-cell analysis, enzyme inhibition, and molecular dynamics simulation, we identify argininosuccinate synthetase (CgASS) as a key node of this response. Heat stress drove sustained metabolic remodelling of the haemocyte transcriptome, and network analysis placed CgASS at the centre, where it was preferentially expressed in haemocytes and developmentally regulated. Single-cell virtual knockout selectively reshaped minor haemocyte populations, markedly expanding a stress-activated effector population while contracting immunomodulatory and cytoskeletal populations. In vivo inhibition with α-methyl-DL-aspartate raised citrulline, lowered argininosuccinate, and further suppressed respiration and feeding under heat, confirming that CgASS activity sustains aerobic performance. CgASS inactivation constricts arginine supply, thereby depriving both the nNOS–NO pathway that sustains respiration and feeding and the AMD–polyamine pathway that supports cytoprotection. Molecular dynamics revealed that CgASS collapses into an abnormally compact, rigid conformation at 30 °C, constraining the flexibility required for catalysis. Together, these results suggest CgASS as a potential key node of a metabolic compensation–decompensation axis and a molecular target for breeding thermally resilient shellfish. Full article

Non-communicable diseases (NCDs) represent a growing challenge for developing countries, as they are among the leading causes of morbidity and mortality within the working-age population. Beyond their effects on health outcomes, NCDs are associated with reductions in labor productivity, which may influence long-term development dynamics through human capital. This study estimates the conditional labor productivity penalty associated with Non-Communicable Diseases (NCDs) among employed workers in Mexico using an observational high-dimensional framework. By addressing high-dimensional confounding under the Conditional Independence Assumption (CIA), the analysis isolates the relationship between NCD status and hourly labor earnings. Using microdata from the Mexican National Survey of Household Income and Expenditure, labor productivity is defined as the ratio of labor income to hours worked. To obtain robust causal estimates, a Double Machine Learning (DML) framework is implemented, integrating regularized regression and machine learning algorithms to control for high-dimensional confounding factors. These covariates include socioeconomic, demographic, and health-related variables, allowing for flexible adjustment of observable heterogeneity across individuals. The empirical findings demonstrate a statistically significant conditional negative penalty of −11.44% (p = 1.03 × 10⁻¹¹, 95% CI: [−14.59, −8.40]) on hourly labor earnings under the cross-fitted DML specification using XGBoost and Random Forest. To resolve an observational measurement artifact where chronic individuals report artificially inflated hourly wages due to severe hours contraction, a presenteeism adjustment factor ($\theta *=0.8125$) was calibrated. Incorporating this presenteeism correction, the aggregate national economic burden among the employed population is estimated at approximately 496.82 billion pesos annually. The findings suggest that NCDs constitute a relevant constraint on labor productivity at the microeconomic level. The study highlights the importance of prevention-oriented health strategies, workplace health promotion, and early disease management. From a methodological perspective, the results illustrate the usefulness of Double Machine Learning for purging high-dimensional confounding in cross-sectional survey data, providing robust conditional empirical benchmarks for public health policy. Full article

The high-Andean forests formed by Polylepis rugulosa in southern Peru are key ecosystems for biodiversity conservation and the provision of ecosystem services; however, they are facing fragmentation and degradation processes associated with human activities and climate change. In this context, the present study modeled the near-term and future potential distribution of P. rugulosa under the SSP1-2.6, SSP3-7.0, and SSP5-8.5 shared socioeconomic pathways, considering three analysis periods: 2011–2040, 2041–2070, and 2071–2100. To achieve this, occurrence records, bioclimatic variables, and topographic variables were integrated in BIOMOD2 and complemented with spatial analyses in QGIS. After controlling for multicollinearity using the Variance Inflation Factor (VIF), seven non-redundant environmental predictors were retained and incorporated into an ensemble model built from the four algorithms with the highest predictive performance: Random Forest (RF), Gradient Boosting Machine (GBM), Flexible Discriminant Analysis (FDA) and Artificial Neural Network (ANN). The final ensemble model achieved high predictive accuracy, with True Skill Statistic (TSS) values close to 0.94 and ROC/AUC values ranging from 0.997 to 0.998. Continuous habitat suitability projections were subsequently reclassified into four habitat suitability categories: most unsuitable, marginally unsuitable, marginally suitable, and most suitable. Under the SSP3-7.0 scenario, the most suitable areas decreased from 30,965 ha during 2011–2040 to 374 ha during 2071–2100, indicating a progressive contraction of favorable habitat. A spatiotemporal analysis was then conducted, in which areas of habitat loss, stability, and gain were further disaggregated into specific projected habitat categories: immediate loss, long-term loss, stable niche, expansion and establishment, and delayed expansion. The probability density curves of key environmental variables revealed that stable habitat was mainly associated with mean diurnal temperature ranges of 10.5–11.5 °C, precipitation during the driest quarter of 35–45 mm, slopes of 30–40°, and altitudes of 4000–4500 m a.s.l. Finally, based on the projected habitat trajectories of P. rugulosa, three strategic management typologies were defined: conservation in stable areas, restoration in areas experiencing habitat loss, and preventive conservation and monitoring in areas with future establishment potential. Full article

Facing China’s complex operating environment, in which the spot electricity market is still at an early stage of development and the mechanism price policy for new energy is implemented in parallel, this paper addresses the mechanism adaptability challenges that arise when high-proportion new energy participates in the spot electricity market on a full-volume basis. A trading and settlement mechanism with trading flexibility, multi-timescale coordination, and policy alignment is then constructed. Full-volume electricity on both the generation and consumption sides is incorporated into spot market clearing and settlement, thereby strengthening the role of the spot market in resource allocation. Differentiated bidding, settlement, and responsibility-bearing mechanisms are further designed according to electricity type and participant category, thereby clarifying responsibility boundaries and supporting imbalance-fund allocation. A multi-timescale trading mechanism is constructed to link short-cycle flexible trading, day-ahead bidding, intraday rolling adjustment, and real-time balancing. In addition, a differentiated medium- and long-term contract mechanism and a secondary settlement system are designed to meet the needs of system peak-regulation and market risk management. These designs also support coordination with the mechanism price policy for new energy, priority generation of hydropower and nuclear power, guaranteed electricity consumption, and grid-company agency purchasing. Case studies show that the proposed mechanism can help mitigate market efficiency distortions, improve the adaptability of the spot market to high-proportion new energy, and support the reasonable allocation of policy-related compensation costs and system regulation costs. Full article

The authorization and operation of the public data supply chain is an important pathway for unlocking the value of public data and cultivating the data element market. However, in practice, it faces challenges such as insufficient data supply and insufficient stakeholder incentives. This paper focuses on the differentiated subsidy policies of the fiscal department, constructing a differential game model involving multiple participants, including data providers, data managers, and data operators. The paper systematically compares the optimal effort decisions of each stakeholder, the evolution trajectory of public data product value, and the trajectory of overall system profits under two subsidy models: cost subsidies and transaction subsidies. It further analyzes the regulatory role of revenue distribution ratios and cost-sharing contracts in shaping the effectiveness of these subsidy mechanisms. The study finds that: (1) cost subsidies provide more balanced and stable incentives for all stakeholders and contribute more to the final value trajectory of public data products; transaction subsidies are more effective in improving overall system profits but offer weaker incentives for the supply and management sides, requiring flexible use in conjunction with cost-sharing contracts; (2) cost-sharing contracts play a regulatory role under different subsidy models and effectively reduce the data provider’s dependence on fiscal subsidies under the transaction subsidy mechanism; (3) the revenue distribution ratio only positively affects the effort decisions of the supply and management sides under the transaction subsidy model, and the optimal subsidy ratio of the fiscal department is closely related to the revenue distribution ratio. Therefore, differentiated subsidy strategies should be implemented based on specific decision-making contexts and internal revenue distribution ratios. This paper reveals the synergistic incentive mechanism between differentiated subsidy models and cost-sharing contracts, providing a theoretical basis for the design of subsidy policies for public data authorization and operation. Full article

Electric vehicle (EV) charging has a large, spatially clustered, schedulable load whose vehicle-to-grid flexibility can be sold back to the power system. That flexibility has grid value only when the committed quantity can be reliably delivered under uncertainty. Open forecasting benchmarks operators rely on report-only point predictions. The dispatch models that turn forecasts into firm commitments assume a constant round-trip efficiency, so the committed flexibility is systematically over-scheduled. This study contributes two complementary modules, validated separately on public data. The first is a calibrated probabilistic charging forecaster that provides, to our knowledge, the first prediction intervals with reported empirical coverage on the UrbanEV benchmark. It is a gradient-boosted quantile-regression model that combines each zone’s own-history lags with adjacency-weighted neighbor-mean features and exogenous price and calendar inputs. It is calibrated by conformalized quantile regression and scored over thirty zones across a 120-day hourly window. The second is a deliverable-flexibility envelope whose returnable-energy bounds are set by measured, state-of-charge- and rate-dependent vehicle-to-grid (V2G) discharge efficiency rather than a constant round-trip number. These bounds are fit to the measured discharge traces of three V2G-capable vehicles in the Esser bidirectional-charging dataset. Chosen as a lightweight, reproducible baseline, the forecaster keeps its prediction intervals within a five-percentage-point coverage tolerance at both the 80% and 90% nominal levels. Measured coverage is 0.823 and 0.911. It also improves on the continuous ranked probability score of its conformalized-point counterpart at matched point accuracy. This calibration holds across the hyperparameter neighborhood and under data deficiency. On the delivery side, a leave-one-vehicle oracle shows the efficiency-aware envelope short-delivers less than the constant-average-efficiency aggregator on held-out vehicles. Its residual shortfall is 1.21% against the aggregator’s 2.03% at the conservative operating point. The margin widens as commitments grow more aggressive and discharges reach the lowest states of charge. Each of these two measured properties, calibrated demand-side uncertainty and state-dependent discharge physics, imposes a material, separately validated constraint on how much contracted EV flexibility can be delivered, a constraint the point-forecasting frontier leaves unaddressed. Full article

Endometriosis is a disease associated with pain symptoms and reduced fertility, characterized by the presence of endometrial tissue outside the uterus. SETD3 is an actin-specific histidine N-methyltransferase that regulates actin stability and flexibility. Here, we investigate the effects of altered SETD3 expression on cytoskeletal function and endometriotic cell motility. SETD3 expression in endometriotic lesions was analyzed using EndometDB, and in uteri of the superfertile Dummerstorf mouse line FL1 by RT-qPCR. The functional impact of siRNA-mediated SETD3 depletion on endometriotic 12Z cells and primary endometriotic stroma cells was studied in vitro. Cell motility, contractility, invasiveness, morphology and gene expression were analyzed by RT-qPCR, Western blotting, immunofluorescence, scratch wound, collagen contraction and Matrigel invasion assays. In patient tissue, SETD3 expression was slightly increased in deep endometriotic lesions, whereas SETD3 was downregulated 1.6-fold in the uteri of superfertile mice. SETD3 depletion delayed cell motility, reduced invasiveness of 12Z cells, and reduced the capability to contract collagen gels. Cytoskeletal gene expression was moderately changed. Our data suggest that the histidine N-methyltransferase SETD3 contributes to cytoskeletal remodeling that plays a key role in cell migration and invasion. A dysregulation of SETD3 could therefore be related to the pathogenesis of endometriosis, particularly in deep endometriosis. Full article

This study presents a nuanced understanding of how butterflies may respond to climate change, suggesting that although many species could experience noticeable contractions in their climatic niches, a substantial number may still have the potential to considerably expand their geographic ranges. We modeled the distributions of 200 butterfly species across Asia using the MaxEnt algorithm. Habitat suitability maps were produced for both current conditions and future scenarios under moderate (SSP245) and high (SSP585) greenhouse gas emissions. To analyze niche dynamics, we projected the realized niches of species onto principal component environmental spaces, which allowed us to quantify key processes including niche stability, expansion, unfilling, abandonment, and pioneering. These indices were then mapped spatially to identify potential changes in climatic niche configurations and geographic distributions in response to climate change. Our findings indicate that by 2070, under the moderate-emissions scenario (SSP245), 185 species are projected to show expansion in suitable habitat by an average of 38%, while 15 species may face an average decline of 11%. Under the high-emissions scenario (SSP585), 184 species are projected to show increases in suitable habitat by 55% on average, with 16 species showing an average decrease of 13%. Additionally, species are predicted to maintain approximately 63% of their current climatic niche stability under SSP585. Niche expansion averages 12%, reflecting potential range growth, whereas unfilling accounts for around 16%, indicating possible loss of some currently suitable areas. Niche abandonment or niche contraction, representing climatic spaces no longer projected to be occupied, comprises about 8%, and pioneering into entirely new climatic conditions remains limited at roughly 1%. The modeled presence of niche unfilling and abandonment suggests that butterflies may retain considerable ecological flexibility, potentially allowing them to shift into new environments under changing climate conditions. This projected adaptability may enhance their resilience by facilitating potential movement into novel or previously unoccupied habitats, though actual range shifts will depend on factors beyond climatic suitability alone. Full article

This study investigated the feasibility and biomechanical effects of volitional electromyography (EMG)-based control of a powered transtibial ankle prosthesis. Four male participants completed static and dynamic EMG assessments and gait analysis while using both their prescribed passive prosthesis and an EMG-controlled powered prototype during level walking at self-selected and fast speeds, as well as ramp ascent and descent. Selective activation of residual tibialis anterior and gastrocnemius muscles was quantified using a co-contraction index, and lower-limb kinematics and kinetics were compared between prosthetic conditions. Participants were able to generate task-dependent residual muscle activity, supporting the feasibility of EMG-based volitional control. However, muscle selectivity was reduced during dynamic tasks, with higher co-contraction during gait than during seated static contractions, and substantial inter-subject variability was observed. Compared to the prescribed passive prosthesis, the EMG-controlled prototype generally produced lower prosthetic-side ankle range of motion and ankle power, although ankle moments were sometimes slightly greater. These findings suggest that EMG control is feasible, but that future controller design must remain flexible to individual users’ neuromuscular abilities and dynamic control limitations. The results provide important guidance for the development and testing of more adaptive, personalized, and functionally effective EMG-controlled prosthetic ankle systems. Full article

In this paper, we introduce a new class of contractions, called dual connected-image contractions, for a pair of self-mappings on a metric space endowed with a directed graph. This concept extends the notion of connected-image contractions by incorporating the interaction between two mappings through the graph structure. By employing a class of auxiliary functions, we establish existence and uniqueness results for common fixed points under this generalized contractive framework. The proposed approach not only unifies and extends several known results in the literature but also provides greater flexibility in handling nonlinear problems. As an application, the theoretical results are applied to a class of nonlinear fractional differential equations with nonlocal integral boundary conditions, where the existence of solutions is established by reformulating the problems as equivalent integral equations and applying the developed common fixed point framework. Full article

The increasing integration of distributed energy resources (DERs), including photovoltaic systems, battery energy storage systems, electric vehicles, and flexible loads, is transforming modern power systems and creating new challenges for coordination, control, and cybersecurity. Conventional Virtual Power Plant (VPP) architectures typically rely on centralized energy management systems, which may face scalability limitations, communication bottlenecks, cybersecurity risks, and reduced resilience to failures. This paper presents a blockchain-enabled decentralized Virtual Power Plant framework for secure and autonomous coordination of distributed energy resources. The proposed architecture combines blockchain technology, smart contracts, IoT-based communication infrastructure, and decentralized energy management functions within a unified multi-layer coordination framework. Smart contracts automate energy scheduling, peer-to-peer transaction validation, and settlement processes, reducing dependence on centralized control entities. Lightweight blockchain consensus mechanisms are employed to improve scalability while limiting computational overhead. The effectiveness of the proposed framework is evaluated through simulation-based case studies involving decentralized DER coordination, peer-to-peer energy trading, and resilience assessment under node-failure conditions. Its performance is compared with that of a conventional centralized VPP architecture in terms of scalability, coordination reliability, communication overhead, transaction transparency, and fault tolerance. The results indicate that the decentralized framework improves operational resilience, coordination transparency, and scalability under increasing DER participation while maintaining satisfactory energy balancing performance. Although blockchain-based coordination introduces additional transaction latency, the proposed approach enhances cybersecurity, reduces dependence on centralized control structures, and provides a flexible foundation for future intelligent smart-grid applications. Full article

Under the dual impact of new urbanization and rural population mobility, divorced rural women in China face severe challenges in obtaining collective membership qualification for land expropriation compensation. The newly enacted Rural Collective Economic Organization Law (RCEOL) contains ambiguous provisions, hindering effective implementation. This study asks: How can collective membership qualification for divorced rural women be determined based on pre-enactment court judgments to refine the law’s ambiguities? Adopting a qualitative design, data were collected from China Judgments Online. Through systematic keyword search, 238 court judgments were retrieved and analyzed using a three-level coding procedure (open, axial, selective). The theoretical framework draws on Amartya Sen’s capability approach. Three main findings are briefly summarized. First, a concrete determination scheme is proposed: the “stable rights-obligations relationship” is operationalized via collective medical insurance purchase and non-abandonment of contracted land; “basic livelihood security” emphasizes land’s security function without requiring primary income reliance; the “stable production-living relationship” criterion should be discarded. Second, the household registration (hukou) condition is becoming ambiguous, but such ambiguity reflects governance adaptation to complexity, moving toward “de-hukouization.” Third, legal ambiguity, while challenging, creates a flexible space for adaptive rural governance. This study contributes by introducing Sen’s capability approach into the analysis of divorced rural women’s membership qualification and providing empirical grounds for clarifying Article 11 of the RCEOL. Future research may observe changes in case volume and litigant testimonies after the law’s implementation to evaluate its real effects, further enriching the discussion on institution—agency interaction. Full article

Background: The retention of Clinical Research Associates (CRAs) is critical for the integrity and sustainability of clinical trials in South Africa, an emerging hub for global clinical research. High CRA turnover threatens trial quality, data continuity, and site relationships, yet the context-specific drivers of turnover within the South African clinical research landscape remain poorly understood. This study explores the factors influencing job satisfaction and turnover intentions among CRAs to inform targeted retention strategies. Methods: A qualitative, interpretivist study was conducted using semi-structured interviews. Twelve CRAs with experience in South African Contract Research Organizations (CROs) were sampled on LinkedIn using purposive sampling. Data were analyzed iteratively using thematic analysis within Atlas.ti 26.0.1.33961 software, guided by Herzberg’s Two-Factor Theory and Mobley’s Turnover Model. Results: The analysis revealed a complex model of turnover drivers. Compensation was the most salient factor, operating not only as a hygiene factor but also as a direct motivator for job mobility in a competitive market. Unsustainable workload and a culture stigmatizing discussions of overload were key push factors. Intrinsic motivators were equally decisive: misalignment with therapeutic area preferences caused profound dissatisfaction, while alignment fostered engagement. Career growth manifested dual pathways: ambition for vertical progression and a redefined search for horizontal growth into roles offering greater work-life flexibility. Conclusions: CRA turnover is driven by an interplay of extrinsic pressures and intrinsic motivational deficits. To enhance retention, managers must adopt a multi-pronged strategy: implement market-competitive, well-being-oriented compensation; foster a culture that supports open workload dialogue; create transparent career architectures with dual progression tracks; and facilitate internal mobility across therapeutic areas. This study provides a foundational framework for developing context-sensitive retention policies, thereby contributing to the stability and quality of clinical research in South Africa. Full article

Background: Epidemiological alerts about the possible spread of different pathogens have highlighted the risk of international travelers contracting infectious diseases when visiting endemic areas. The role of travelers in disease transmission underscores the importance of pre-travel consultations, which provide critical information on health risks, vaccinations, and preventive measures. Understanding travelers’ risk perceptions and behaviors is essential for enhancing global health security in the post-pandemic era. Methods: A cross-sectional study (June 2023–January 2024) was conducted by administering an anonymous questionnaire at the Rome-Fiumicino Airport International Prophylaxis Clinic (USMAF-SASN). The questionnaire explored demographics, travel patterns, risk perceptions, vaccination behaviors, and sources of health information. Descriptive statistics and a multivariable logistic regression analysis were performed to identify low-risk perception predictors. Results: Among 217 participants, 89.8% were Italian, with a balanced representation of genders. The primary purpose of travel was tourism (61.6%), followed by work-related trip (23.1%). While 77.1% rated preventive measures as effective, 23.2% evaluated infection risk as low. Being male (aOR 3.63, 95% CI 1.37–9.61), and being a hotel user (aOR 6.27, 95% CI 2.43–16.15), was significantly associated with a lower risk perception. As expected, healthcare professionals and individuals using institutional healthcare sources showed a higher risk awareness. Vaccination uptake at the Airport Clinic was motivated by self-protection, vaccine confidence, and poor time flexibility to access local vaccination services, and last-minute plans, making the airport a more convenient option. Conclusions: Travelers’ risk perception is influenced by gender, profession, accommodation type, and information sources. Public health strategies should enhance health literacy, promote pre-travel consultations, and improve access to preventive services. Strengthening collaborations between health authorities, educational institutions, and the travel sector is key to mitigating health risks and ensuring global health security. Future interventions should address structural vaccination barriers and improve outreach to under-informed travelers. Full article