Search Results (39,515)

Autonomous mobility is reshaping how travel time is perceived, experienced, and monetised. Most existing studies have examined the value of time (VOT), willingness to pay (WTP), comfort and safety perception, digital services, and user perception as isolated phenomena, with limited efforts to integrate these dimensions into unified analytical frameworks. This study aims to address the fragmented nature of existing research by developing an integrated understanding of user behaviour in autonomous mobility, linking VOT, WTP, psychological constructs, and service-related factors within a unified analytical perspective. A systematic review methodology following PRISMA 2020 guidelines was applied. A total of 81 peer-reviewed studies published between 2015 and 2026 were included and analysed, focusing on Private Autonomous Vehicles (PAVs) and Shared Autonomous Vehicles (SAVs). The results reveal three main trends. First, autonomous travel introduces greater flexibility in time use and enables productive or leisure activities during travel. Second, behavioural aspects of VOT and WTP are strongly influenced by psychological constructs such as trust, safety, and risk perception. Third, notable differences emerge between PAV and SAV contexts, particularly in terms of comfort, control, and safety perception. The literature predominantly employs stated preference surveys, discrete choice models, and hybrid models incorporating psychological factors. However, fragmentation persists in modelling behavioural aspects of time perception and shared mobility services. This study provides a structured synthesis of existing evidence and highlights key research gaps by integrating economic, psychological, and service-related dimensions. The findings emphasise the importance of context-specific and psychologically informed modelling approaches to better understand user acceptance and behavioural adaptation in autonomous mobility systems. Full article

To clarify the hydrocarbon-generation potential of deep source rocks in the Qingyang Gas Field, this study focuses on the Shanxi and Taiyuan Formation source rocks at burial depths of 4000–5000 m. Integrated organic geochemical analyses were conducted to investigate organic matter abundance, kerogen type, thermal maturity, hydrocarbon-generation conditions, and their significance for natural gas accumulation. The TOC values of the 12 valid mudstone samples range from 0.07% to 2.53%, with an average of 0.77%, indicating generally poor to fair organic matter abundance. Rock-Eval results show that S2 values range from 0.0681 to 6.2797 mg/g, with an average of 1.5946 mg/g, whereas S1 + S2 values range from 0.0948 to 6.9066 mg/g, with an average of 1.8582 mg/g, indicating generally limited Rock-Eval hydrocarbon-generating capacity, with local improvement. The kerogen assemblage is heterogeneous and is generally dominated by Type III humic kerogen, with subordinate Type II components and minor Type I components in some samples, indicating mixed organic-matter input but an overall gas-prone character. Tmax values range from 420 to 482 °C; however, because Tmax may be unreliable in samples with very low S2 values, thermal maturity was evaluated mainly using vitrinite reflectance and natural gas geochemical evidence. R_o values range from 2.03% to 2.22%, with an average of 2.11%, indicating that the source rocks have reached a high- to overmature stage. The natural gas is methane-rich, with an average methane content of 91.73% and an average heavy hydrocarbon content of only 0.16%, indicating a typical dry-gas composition. The carbon isotope values of methane and ethane are both negative, with δ¹³C₁ values ranging from −35.59‰ to −20.65‰ and δ¹³C₂ values ranging from −37.82‰ to −28.44‰, consistent with high-maturity coal-derived gas generated from humic organic matter. The formation water is mainly medium- to high-salinity CaCl₂ type, indicating a relatively closed hydrologic environment favorable for natural gas preservation. Clay mineral assemblages dominated by kaolinite and illite provide supplementary evidence for depositional conditions, burial diagenesis, and fluid–rock interaction. Overall, although the Rock-Eval hydrocarbon-generating capacity of the Shanxi and Taiyuan Formation source rocks is generally limited, the Type III-dominated mixed kerogen, high- to overmature R_o values, methane-rich dry-gas composition, and carbon isotope characteristics collectively indicate that these source rocks experienced effective natural gas generation during geological evolution and are genetically related to the present deep natural gas accumulation. This study provides fundamental geochemical constraints for further integrated exploration and evaluation of the deep coal-measure gas system in the Qingyang Gas Field. Full article

Digital identity is increasingly treated as foundational infrastructure for digital economies and public services, yet national approaches remain fragmented and difficult to compare. This study presents a PRISMA-guided systematic artefact-based review of government digital identity programmes, using programme-relevant government artefacts as the review corpus, including strategies, trust frameworks, guidance, service documentation, and identity-enabled public-service materials. Adapting an NLP pipeline for large-scale digital identity text analysis, the study identifies recurring themes, constructs comparative programme profiles, and operationalises three artefact-based measures: alignment, transparency, and maturity. Rather than assessing innovation performance or operational system quality directly, it examines the documentary layer through which programmes are described, justified, and made comparable. The analysis reveals substantial variation in how highly digitalised societies articulate governance, trust, interoperability, security, privacy, and service delivery. The review contributes a repeatable artefact-based framework for cross-jurisdictional comparison and provides a baseline for ontology development and future triangulation against citizen perception, expert assessment, and technical evaluation. Full article

Post-disaster reconstruction programmes create an irreversible window for embedding or foreclosing residential energy efficiency at scale. This study examines the structural determinants of per capita residential electricity consumption (K_MES) across all 81 provinces of Türkiye over 2013–2022 using a balanced province-year panel. We develop two complementary panel models, both estimated by two-way fixed effects (province + year) with cluster-robust standard errors, and supported by GLS-AR(1) and random-effects GLS robustness checks. Note that K_MES measures the electricity component of residential energy use only; we, therefore, also estimate the building-stock model with a constructed total-energy dependent variable that combines residential electricity (H_MES) and natural-gas consumption (X_DG) in kWh-equivalent units. Model 1 isolates the macroeconomic transmission channel through which exchange-rate volatility shapes residential electricity demand. Because the USD/TRY rate has no cross-sectional variation, its identifying power in two-way fixed effects comes from its interaction with province-level natural-gas-heating exposure (sh_gas × EV_DA). The interaction is robustly negative across all full-sample specifications (β ≈ −0.022, p < 0.01), indicating that provinces with greater gas-heating penetration are buffered against currency-depreciation pass-through into electricity demand. Provincial GDP carries the dominant direct macro coefficient (β ≈ 0.27–0.29, p < 0.01), establishing income elasticity rather than the exchange rate as the headline aggregate driver. Model 2 decomposes the building stock by structural system, filler material, heating system, and heating fuel. The dominant predictors are the share of electric heating (β ≈ 1.16–1.27, p < 0.01) and the share of AC-only heating (β ≈ −1.0 to −1.13, p < 0.05), with a total-energy specification reaching R² = 0.92. In the comparative subsample of the eleven Kahramanmaraş-affected provinces, masonry construction emerges as the dominant pre-disaster predictor of per capita electricity consumption (β = 14.04, p < 0.05), revealing structurally distinct stock characteristics that pre-date the February 2023 earthquake. Two re-framings are required. First, since the panel covers 2013–2022, the disaster-province estimates capture pre-disaster structural heterogeneity rather than post-disaster market rupture. Second, the macroeconomic mechanism that prior work attributed to the exchange-rate level is more accurately understood as a fuel-mix-mediated exposure channel. The combined evidence implies that mandatory building-code enforcement and natural-gas grid extension are complementary policy levers in the 488,000-unit Turkish Housing Development Administration reconstruction programme: gas grid expansion reduces the macroeconomic vulnerability of residential energy demand, while masonry-replacement construction standards address the largest pre-disaster structural determinant of energy intensity in the affected region. Full article

Oxidative stress is a key contributor to aging and chronic diseases, highlighting the need for safe and effective natural antioxidants. Monascus yellow pigments (MYPs) and ginsenoside Rg3 exhibit antioxidant activity, but their applications are restricted by low solubility and limited natural abundance. In this research, a bidirectional liquid fermentation system of Monascus ruber using ginseng decoction was established for the simultaneous production of water-soluble MYPs (WSMYPs) and ginsenoside Rg3. Process conditions were optimized to enhance the yields and the antioxidant activity of the system. Antioxidant assays and H₂O₂-induced RAW264.7 cell models confirmed that WSMYPs were strongly correlated with antioxidant capacity, with ABTS and DPPH scavenging activities showing 2.28-fold and 3.33-fold increases, respectively, compared to the control. Their combination with Rg3 exerted synergistic protective effects by enhancing the activities of superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), and catalase (CAT). Network pharmacology and molecular docking further revealed that Monapurone C, a representative WSMYP, and Rg3 act through a multi-target, multi-pathway antioxidant network involving signaling pathways such as PI3K-Akt. This study demonstrates a cost-effective strategy for co-producing WSMYPs and Rg3, providing new insights into the value-added utilization of edible and medicinal resources. Full article

The semiconductor manufacturing industry depends on effective data collection and analysis for critical processes such as Root Cause Analysis (RCA) and Risk Assessment (RA). Both processes involve software-driven data collection and subsequent analysis by domain experts to support informed decision-making. However, the increasing complexity, volume, and decentralized nature of manufacturing data pose significant challenges for effective data collection. Data is distributed across multiple systems with varying formats and ownership, making conventional programming paradigms and manual data collection scripts inadequate for handling this decentralized data landscape. To address these challenges, this study proposes integrating Action-Oriented Programming (AcOP) with Automatic Agent Generation (AAG) as a novel solution. AcOP emphasizes actions as fundamental execution units, separating system behavior and data. Complementing this, AAG uses large language models (LLMs) to autonomously generate intelligent agents, which manage these actions and perform preliminary data analysis with domain-specific knowledge. Our experimental setup compares three microservice applications supporting RCA and RA: Object-Oriented Programming (OOP), AcOP, and AcOP integrated with AAG. Evaluation results indicate that AcOP improves modularity, adaptability, and error handling in decentralized systems. Integrating AAG enhances automation, provides a flexible, low-maintenance solution for data collection and analysis pipelines, and promotes autonomous microservice architectures in data-intensive environments. Full article

Bacterial infections pose a persistent global threat to public health, driving the demand for rapid, sensitive, and specific detection technologies applicable to disease diagnosis, food safety, and environmental monitoring. Conventional methods like plate culture and polymerase chain reaction are often hampered by lengthy procedures, dependence on complex instrumentation, and requirements for specialized personnel. The emergence of nanozymes and nanomaterials with enzyme-like catalytic activities has introduced a paradigm shift in biosensing, offering superior stability, cost-effectiveness, and tunable functionality compared to their natural counterparts. This review provides a comprehensive and systematic analysis of the latest advancements in nanozyme-mediated bacterial detection. It is structured around the primary signal transduction modalities: colorimetric, fluorescence, electrochemical, and surface-enhanced Raman scattering (SERS) analyses. For each approach, we outline the fundamental design principles, which commonly integrate a synergistic cascade of specific recognition, catalytic signal amplification, and signal readout, and present representative applications for detecting key pathogens like Staphylococcus aureus, Salmonella, and Listeria monocytogenes in complex samples. We evaluate and contrast the advantages, analytical performance, and appropriateness of these different platforms for various practical scenarios. Finally, we address current challenges, including achieving high specificity in complex matrices, precise modulation of nanozyme activity, and method standardization. Perspectives on future research directions aimed at developing next-generation, high-performance, and potentially portable bacterial detection systems are also provided. Full article

As the core pillar of international trade, the global shipping industry has seen its carbon and pollutant emissions become a key challenge in global environmental governance. Statistics indicate that ship carbon emissions account for 3% of the world’s total anthropogenic CO₂ emissions, while contributing 20% of global NO_x and 12% of SO₂ emissions, posing a serious threat to coastal ecosystems and public health. In response to the International Maritime Organization (IMO) “Net Zero Framework” and national green shipping policies, the transformation of ship power systems toward low-carbon and zero-carbon operation has become an inevitable trend. This paper systematically reviews the research progress and application status of green energy materials for ships, focusing on the working principles, technical characteristics, and engineering application cases of solar photovoltaic (PV) materials, wind energy utilization technologies, fuel cell materials, and alternative clean energy fuels (e.g., liquefied natural gas (LNG), methanol, and hydrogen energy). It also discusses the integration mode and optimization strategy of multi-energy hybrid power systems. The research findings show that solar photovoltaic technology has achieved large-scale application in coastal ships; hydrogen fuel cells are suitable for long-range ocean navigation scenarios due to their high energy density; LNG and methanol have become the current mainstream alternative fuels, relying on mature infrastructure; and hybrid energy systems can significantly improve power supply reliability and emission reduction efficiency through multi-energy complementarity. Finally, aiming at the existing bottlenecks (e.g., cost, energy storage, and safety) of various technologies, future development directions are proposed. This study provides a reference for the technological breakthrough and engineering practice of green energy power systems for ships and contributes to the realization of the “carbon neutrality” goal in the global shipping industry. Full article

Introduction: Metformin-associated lactic acidosis (MALA) involves mitochondrial Complex I inhibition, traditionally diagnosed via indirect markers. We present platelet high-resolution respirometry (HRR) as a novel “liquid biopsy” to directly quantify metformin-induced systemic bioenergetic lesions. A 65-year-old diabetic male presented with severe lactic acidosis, acute kidney injury, and profound hypoglycemia after intentionally overdosing on metformin (120 g), dapagliflozin (600 mg), and insulin glargine (300 U). While hemodialysis cleared plasma metformin and resolved the acidosis, refractory hypoglycemia required high-dose IV glucose for over six days. Day 2 platelet HRR revealed severe Complex I inhibition despite significantly decreased plasma metformin, indicating a profound “toxicodynamic lag.” Mitochondrial bioenergetics recovered by Day 7, reflecting natural platelet turnover. The protracted hypoglycemia was driven by a synergistic triad: metformin-inhibited gluconeogenesis, insulin glargine’s prolonged depot effect, and dapagliflozin-induced persistent renal glucose wasting. Platelet HRR has the potential to be a clinically applicable tool to reveal the “hidden” cellular phase of metformin toxicity missed by standard biomarkers. Furthermore, clinicians must anticipate severe, protracted hypoglycemia in mixed overdoses involving SGLT2 inhibitors. Full article

In the contemporary field of geographic information, place name services serve as a core application support in geographic information science, widely applied in public services, cultural tourism, emergency management, and other scenarios. Place name service composition is a critical link in the integration of spatiotemporal knowledge and intelligent services for place names, determining the ability to rapidly solve complex place name problems. Traditional case-based reasoning methods are primarily rule-driven, making it difficult to deeply integrate semantic and graph structural features, and they also lack precision in measuring the similarity of multi-type place name service cases. To address this, this paper integrates knowledge graphs and case-based reasoning to propose a place name service composition method that balances semantic and graph structural similarity, aiming to enhance the response efficiency and recognition accuracy of complex natural language queries. The method consists of two steps: the first is constructing a knowledge graph case base. Semantic feature extraction is performed on the standard geographic question-answering standard dataset GeoQuery corpus to build a place name service knowledge graph case base that integrates semantic associations and spatial attributes. The second step is constructing a similarity model. The method combines four similarity measures—DeBERTa, TF-IDF, SimHash, and maximum common subgraph—and employs the Analytic Hierarchy Process for weighting to develop a novel similarity evaluation model for case-based reasoning. Experiments demonstrate that this method achieves a 21% improvement in F1-score compared to traditional rule-based methods. Furthermore, the developed prototype system for the intelligent recommendation of place name service composition achieves a recommendation accuracy of 92.64%. This research holds significant practical implications and application value for advancing the geographic information field toward intelligent and precision-based development. Full article

The intermittent nature of renewable power sources, nonlinear load effects, and harmonic distortions induced by power electronic converters complicate the maintenance of high energy quality in microgrid-connected hybrid renewable power systems. In a range of operating conditions, conventional strategies-including fractional-order proportional-integral (FOPI) controllers-frequently prove ineffective in delivering both robust harmonic mitigation and expeditious dynamic response. To surmount these constraints, the present paper puts forth an intelligent control solution that is predicated on a fractional-order fuzzy logic (FOFL). The FOFL is integrated into a multi-converter HRPS, comprising a photovoltaic generator, a lithium-ion battery power storage system, and a wind turbine equipped with a permanent magnet synchronous generator. A multifunctional voltage source inverter has been developed to control these parts, which are interfaced via a common DC bus. Through the implementation of MATLAB 2021 simulation studies, the efficacy of the suggested algorithm is verified and evaluated in comparison to the FOPI. The findings indicate that the FOFL enhances system efficacy by minimizing harmonic distortion, improving energy quality, and achieving a faster dynamic response under various circumstances. In the context of grid-connected microgrid environments, the FOFL has been demonstrated to offer superior overall energy management, robustness, and adaptability when compared to other evaluated strategies. Full article

Dihydromyricetin (DHM), a naturally occurring flavanonol predominantly found in medicinal plants like Ampelopsis grossedentata, has emerged as a promising source of natural antioxidants with multi-target pharmacological activities relevant to drug discovery. DHM exhibits a strong redox-modulating capacity, effectively attenuating oxidative stress and inflammation central drivers of chronic disease pathogenesis. Beyond direct radical scavenging, DHM regulates multiple redox-sensitive and kinase-mediated signalling pathways, thereby influencing key cellular processes involved in disease initiation and progression. This review synthesizes current evidence on the therapeutic potential of DHM, critically evaluating its mechanistic basis and translational prospects, with emphasis on its dual redox-driven and kinase-mediated modes of action. We detail its roles in metabolic disorders such as diabetes, obesity, and liver diseases, neuroprotection, cardio protection, and cancer prevention, focusing on the modulation of critical networks such as AMPK, PI3K/Akt, MAPK, NF-κB, and Nrf2. The interplay between these pathways underpins DHM’s efficacy across disease models. Furthermore, we highlight structure–activity relationship (SAR) analyses and molecular modelling studies that elucidate how the flavanonol scaffold, hydroxylation pattern, and stereochemistry of DHM govern its biological activities and target engagement. Key pharmacokinetic limitations, advances in extraction techniques, bioavailability challenges, and emerging formulation strategies including advanced delivery systems are discussed to address translational hurdles. Despite compelling preclinical data, the clinical translation of DHM remains constrained by limited human studies and incomplete mechanistic resolution. This review underscores the need for integrated pharmacological studies and innovative delivery approaches to translate the multifaceted promise of DHM into viable clinical interventions. Full article

Volatile organic compounds (VOCs) have garnered substantial research interest in recent years due to their biodegradability, low toxicity, and potent antimicrobial properties against various plant pathogens. As a typical herbivore-induced plant volatile (HIPV) elicited by Nilaparvata lugens (Brown planthopper, BPH), (E)-2-hexenal has been identified as a promising natural antimicrobial agent. In this study, we investigated the protective potential of (E)-2-hexenal against Rhizoctonia solani (R. solani) in rice, focusing on both its direct antifungal activity and host-mediated defense mechanisms. In vitro antifungal assays demonstrated that treatment with 100 μL/mL (E)-2-hexenal resulted in a 91.07% inhibition of R. solani mycelial growth after 48 h. Scanning electron microscopy (SEM) observation and chitinase activity analysis revealed that (E)-2-hexenal suppressed fungal growth by disrupting the structural integrity of the pathogen cell wall. Furthermore, 100 μL/mL (E)-2-hexenal effectively conferred protection to detached rice leaves. Whole-plant inoculation assays confirmed that (E)-2-hexenal pretreatment significantly alleviated disease symptoms and triggered systemic resistance in rice plants. Physiological and biochemical analyses showed that (E)-2-hexenal treatment enhanced the activities of defense-related enzymes, elevated hydrogen peroxide (H₂O₂) levels, and promoted the accumulation of defensive metabolites in rice leaves. HPLC-MS quantification further revealed significant increases in the endogenous levels of jasmonic acid (JA) and salicylic acid (SA). Transcriptomic KEGG pathway enrichment analysis indicated that differentially expressed genes (DEGs) were mainly involved in alpha-linolenic acid metabolism, diterpenoid biosynthesis, phenylpropanoid biosynthesis, plant–pathogen interaction, and plant hormone signal transduction. Collectively, these results suggest that (E)-2-hexenal enhances rice resistance to sheath blight disease via a dual-action mechanism: direct inhibition of fungal development and activation of host immune responses. Our findings highlight the potential application of (E)-2-hexenal and other VOCs in developing eco-friendly strategies for sustainable rice disease management. Full article

Background/Objectives: Combination of antiparasitic drugs with different mechanisms of action has been suggested as an effective strategy to delay the development of parasite resistance. Considering the need to understand the pharmacological basis of drug combinations, the current study evaluated the potential pharmacokinetic (PK) interactions and the clinical efficacy (pharmacodynamic response) occurring after the subcutaneous administration of ivermectin (IVM) and levamisole (LEV), administered either as single treatments or concurrently to different groups of parasitized calves on three commercial farms (A, B and C). Methods: Forty-five (45) male calves naturally infected with gastrointestinal nematodes were randomly allocated into three groups (n = 15): IVM, treated with IVM by subcutaneous injection (0.2 mg/kg); LEV, treated subcutaneously with LEV (8 mg/kg); IVM + LEV, simultaneously treated with IVM and LEV (two subcutaneous injections at the same dose rates). Seven animals from each treated group (farm C) were randomly selected to perform the PK study. Drug concentrations were measured by HPLC. The therapeutic response (efficacy) was determined at 14 days after treatment by the fecal egg reduction test. Results: The mean area under the concentration vs time curve (AUC) for IVM obtained after administration of IVM alone (274 ± 65.1 ng.d/mL) was similar to that obtained when IVM was co-administered with LEV (295 ± 111 ng.d/mL). Likewise, mean LEV AUC values were similar after LEV administration alone (8.90 ± 2.69 µg.h/mL) or combined with IVM (9.11 ± 1.82 µg.h/mL). No adverse PK interactions were observed after the combined treatment, with similar PK parameters (p > 0.05) obtained between the single-drug and the combination-based strategies. On farm A, the overall fecal egg reductions were 38% (IVM), 99% (LEV) and 100% (IVM + LEV). While Cooperia spp. and Haemonchus spp. showed reduced susceptibility to IVM treatment, LEV demonstrated high efficacy against both genera, with only a minimal proportion of Haemonchus spp. remaining after treatment. Similarly, total fecal egg reductions were 42% (IVM), 99% (LEV) and 100% (IVM + LEV) on farm B, and 54% (IVM), 99% (LEV) and 100% (IVM + LEV) on farm C. On those farms, IVM was ineffective against Cooperia spp. and/or Haemonchus spp., while LEV failed to control Ostertagia spp. Remarkably, the combination of both molecules was the only treatment that achieved 100% efficacy against all nematode genera (Cooperia, Ostertagia, Haemonchus and Oesophagostomum spp.). Conclusions: Based on the described PK and pharmacodynamic (PD) assessments, the IVM + LEV combination appears to be a promising pharmacological option for controlling resistant gastrointestinal nematodes in cattle, with the additional potential to delay the progression of nematode anthelmintic resistance. Overall, the study provides original and robust pharmacokinetic and efficacy data that contribute to the optimization of parasite control strategies in cattle. This drug combination strategy may enhance treatment efficacy and contribute to improved parasite control in cattle production systems. Full article

Biological invasions are among the main threats to freshwater biodiversity, yet ecological patterns associated with assemblage structure and high relative abundances of non-native fishes in spring ecosystems remain insufficiently documented. We evaluated seasonal variation in community composition, reproductive traits, and trophic interactions in La Zarcita springs, part of the Natural Protected Area Laguna de Zacapu, central Mexico. Bimonthly sampling was conducted, including stomach content analysis and reproductive trait assessment. A total of 14 fish taxa were recorded (seven native and seven non-native), with the assemblage numerically dominated by Oreochromis niloticus (30%), Pseudoxiphophorus bimaculatus (24%), and Xiphophorus hellerii (14%). Overall diet composition did not differ significantly between taxa classified as native and non-native (PERMANOVA, p > 0.05), consistent with overlap in resource use within the assemblage. Exploratory assemblage-level analyses detected differences in omnivory index values among taxa grouped according to species origin (LMM, p < 0.05). Reproductive analyses detected variation in fertility values (GLMM, p < 0.05), reproductive activity (Wilcoxon test, p < 0.05), gonadosomatic index values, and Fulton’s condition factor values (LMM, p < 0.01) among taxa within the assemblage. Physicochemical variables varied seasonally but were not significantly associated with trophic composition, condition factor values, or reproductive traits in the statistical analyses performed. Overall, the results document variation in reproductive characteristics and trophic patterns among taxa within this urbanized spring system and highlight the value of assemblage-level ecological studies for understanding fish community structure in small freshwater habitats. Full article