Search Results (1,076)

Catalytic and bioelectrocatalytic properties of four white rot fungal laccases (Trametes hirsuta, ThL; Coriolopsis caperata, CcL; Steccherinum murashkinskyi, SmL; and Antrodiella faginea, AfL) from different orthologous groups were comparatively studied in homogeneous reactions of electron donor substrate oxidation and in a heterogeneous reaction of dioxygen electroreduction. The ThL and CcL laccases belong to high-redox-potential enzymes (E⁰_T1 = 780 mV), while the AfL and SmL laccases are medium-redox-potential enzymes (E⁰_T1 = 620 and 650 mV). We evaluated the efficiency of laccases in mediatorless bioelectrocatalytic dioxygen reduction by the steady-state potential (E_ss), onset potential (E_onset), half-wave potential (E_1/2), and the slope of the linear segment of the polarization curve. A good correlation was observed between the T1 center potential of the laccases and their electrocatalytic characteristics; however, no correlation with the homogeneous reactions of electron donor substrates’ oxidation was detected. The results obtained are discussed in the light of the known data on the three-dimensional structures of the laccases studied. Full article

This paper examines the farming systems and operational structures in the Region of Western Macedonia (RWM), Greece and constructs a typology of farms based on structural, operational, and socio-economic characteristics. Agriculture remains a vital pillar of the regional economy, particularly in the context of RWM’s ongoing transition to a post-lignite development model. Using farm-level data from the 2018 Farm Accountancy Data Network (FADN), Principal Component Analysis (PCA) identified four latent dimensions of farm heterogeneity—income and productivity, asset base, land size, and labour structure. Hierarchical and K-means cluster analysis revealed three distinct farm types: (1) medium-sized, high-efficiency farms with moderate reliance on subsidies (30% of the sample); (2) small-scale, family farms with modest productivity and limited capitalisation (48%); and (3) large, asset-rich farms exhibiting structural inefficiencies and lower output per hectare (22%). These findings highlight structural vulnerabilities, particularly the predominance of undercapitalised smallholdings, and provide a data-driven foundation for Thdesigning differentiated policies that support farm resilience, generational renewal, and sustainable rural development. Full article

Rapid urbanization and escalating disaster risks necessitate resilient urban governance systems. Smart city initiatives that leverage digital technologies—such as the internet of things (IoT), big data analytics, and artificial intelligence (AI)—demonstrate transformative potential in enhancing emergency management capabilities. However, empirical evidence regarding their causal impact and underlying mechanisms remains limited, particularly in developing economies. Drawing on panel data from 275 Chinese prefecture-level cities over the period 2006–2021 and using China’s smart city pilot policy as a quasi-natural experiment, this study applies a multi-period difference-in-differences (DID) approach to rigorously assess the effects of smart city construction on emergency management capabilities. Results reveal that smart city construction produced a statistically significant improvement in emergency management capabilities, which remained robust after conducting multiple sensitivity checks and controlling for potential confounding policies. The benefits exhibit notable heterogeneity: emergency management capability improvements are most pronounced in central China and in cities at the extremes of population size—megacities (>10 million residents) and small cities (<1 million residents)—while effects remain marginal in medium-sized and eastern cities. Crucially, mechanism analysis reveals that digital technology application fully mediates 86.7% of the total effect, whereas factor allocation efficiency exerts only a direct, non-mediating influence. These findings suggest that smart cities primarily enhance emergency management capabilities through digital enablers, with effectiveness contingent upon regional infrastructure development and urban scale. Policy priorities should therefore emphasize investments in digital infrastructure, interagency data integration, and targeted capacity-building strategies tailored to central and western regions as well as smaller cities. Full article

This study addresses the limitations of conventional evaluation methods caused by low porosity, strong heterogeneity, and complex pore structures in tight sandstone reservoirs. Through integrated rock physics experiments and multi-physical field modeling, the research systematically investigates the coupled response mechanisms between electrical and elastic parameters. The experimental approach includes pore structure characterization, quantitative mineral composition analysis, resistivity and polarizability measurements under various saturation conditions, P- and S-wave velocity testing, and scanning electron microscopy (SEM) imaging. The key findings show that increasing porosity leads to significant reductions in resistivity and elastic wave velocities, while also increasing surface conductivity. Specifically, clay minerals enhance surface conductivity through interfacial polarization effects and decrease rock stiffness, which exacerbates wave velocity attenuation. Furthermore, resistivity exhibits a nonlinear negative correlation with water saturation, with sharp increases at low saturation levels due to the disruption of conductive pathways. By integrating the Modified Generalized Effective Medium Theory of Induced Polarization (MGEMTIP) and Kuster–Toksöz models, this study establishes quantitative relationships between porosity, saturation, and electrical/elastic parameters, and constructs cross-plot templates that correlate elastic wave velocities with resistivity and surface conductivity. These analyses reveal that high-porosity, high-saturation zones are characterized by lower resistivity and wave velocities, coupled with significantly higher surface conductivity. The proposed methodology significantly improves the accuracy of reservoir evaluation and enhances fluid identification capabilities, providing a solid theoretical foundation for the efficient exploration and development of tight sandstone reservoirs. Full article

The micro-scale interplay between the built environment and innovation has attracted increasing scholarly attention. However, discussions on how such microdynamics operate and vary across high-density cities remain insufficient. This study focuses on nine high-density urban centres along the G60 S&T Innovation Valley and employs a fine-grained grid unit, viz. 1 km × 1 km, combined with the gradient boosting decision tree (GBDT) model to address these issues. Results show that urban construction density-related variables, including the building density, floor area ratio, and transportation network density, generally rank higher than the amenity density and proximity-related variables. The former contributes 50.90% of the total relative importance in predicting invention patent application density (IPAD), while the latter two contribute 13.64% and 35.46%, respectively. Threshold effect analysis identifies optimal levels for enhancing IPAD. Specifically, the optimal building density is approximately 20%, floor area ratio is 5, and transportation network density is 8 km/km². Optimal distances to universities, city centres, and transportation hubs are around 1 km, 17 km, and 9 km, respectively. Furthermore, significant city-level heterogeneity was observed: most density-related variables consistently have an overall positive association with IPAD, with metropolitan cities (e.g., Hangzhou and Suzhou) exhibiting notably higher optimal values compared to medium and small cities (e.g., Xuancheng and Huzhou). In contrast, the threshold effects of proximity-related variables on IPAD are more complex and diverse. These findings offer empirical support for enhancing innovation in high-density urban environments. Full article

Medium-deep borehole heat exchanger (BHE) systems represent an emerging form of ground source heat pump technology. Their heat transfer process is significantly influenced by geothermal gradient and soil stratification, typically simulated using segmented finite line source (SFLS) models. However, this approach involves computationally intensive procedures that hinder practical engineering implementation. Building upon an SFLS model adapted for complex geological conditions, this study proposes a comprehensive simplified algorithm: (1) For soil stratification: A geothermally-weighted thermal conductivity method converts layered heterogeneous media into an equivalent homogeneous medium; (2) For geothermal gradient: A temperature correction method establishes fluid temperatures under geothermal gradient by superimposing correction terms onto uniform-temperature model results (g-function model). Validated through two engineering case studies, this integrated algorithm provides a straightforward technical tool for heat transfer calculations in BHE systems. Full article

The deep carbonate reservoirs in the Tarim Basin, Xinjiang, China, are widely developed with multi-scale complex reservoir spaces such as fractures, pores, and karst caves under the coupling of abnormal high pressure, diagenesis, karst, and tectonics and have strong heterogeneity. Among them, fracture–cavity carbonate reservoirs are one of the main reservoir types. Revealing the petrophysical characteristics of fracture–cavity carbonate reservoirs can provide a theoretical basis for the log interpretation and geophysical prediction of deep reservoirs, which holds significant implications for deep hydrocarbon exploration and production. In this study, based on the mineral composition and complex pore structure of carbonate rocks in the Tarim Basin, we comprehensively applied classical petrophysical models, including Voigt–Reuss–Hill, DEM (Differential Effective Medium), Hudson, Wood, and Gassmann, to establish a fracture–cavity petrophysical model tailored to the target block. This model effectively characterizes the complex pore structure of deep carbonate rocks and addresses the applicability limitations of conventional models in heterogeneous reservoirs. The discrepancies between the model-predicted elastic moduli, longitudinal and shear wave velocities (Vp and Vs), and laboratory measurements are within 4%, validating the model’s reliability. Petrophysical template analysis demonstrates that P-wave impedance (Ip) and the Vp/Vs ratio increase with water saturation but decrease with fracture density. A higher fracture density amplifies the fluid effect on the elastic properties of reservoir samples. The Vp/Vs ratio is more sensitive to pore fluids than to fractures, whereas Ip is more sensitive to fracture density. Regions with higher fracture and pore development exhibit greater hydrocarbon storage potential. Therefore, this petrophysical model and its quantitative templates can provide theoretical and technical support for predicting geological sweet spots in deep carbonate reservoirs. Full article

Background/Objectives: Anterior open bite (AOB) is a complex malocclusion characterized by the lack of vertical overlap between the upper and lower teeth during maximum intercuspation. It often results in functional impairments and aesthetic concerns. Traditional treatments for adult patients, including orthognathic surgery, are effective but invasive. Temporary anchorage devices (TADs) have emerged as a minimally invasive alternative. The aim of this systematic review and meta-analysis was to evaluate the effectiveness of TADs for molar intrusion in the correction of AOB. Methods: A systematic review was conducted according to the PRISMA 2020 guidelines. An electronic search was performed in PubMed and Scopus until March 2025. The inclusion criteria comprised clinical studies in humans published in English or Spanish in the last 10 years. The risk of bias was assessed using RoB 2, ROBINS-I, and the Joanna Briggs Institute tools. A random-effects meta-analysis was carried out to estimate pooled intrusion values, and heterogeneity was evaluated using Cochran’s Q test and the I² statistic. Results: Twelve studies were included. Molar intrusion using TADs achieved significant overbite improvements, with a pooled mean intrusion of 1.70 mm (95% CI: 0.53–2.87 mm). The heterogeneity among studies was high (I² = 88.5%). Despite variability in force magnitude and TAD type, lighter forces were generally associated with similar outcomes and fewer adverse effects. Conclusions: TADs offer a predictable and less invasive alternative to orthognathic surgery for AOB correction. When appropriately indicated and biomechanically managed, they provide effective vertical control and short- to medium-term stability in adult patients. Full article

This study presents a social life cycle assessment (S-LCA) of the F-CUBED Production System (FPS), an innovative process that converts wet biogenic residues—specifically paper biosludge, virgin olive pomace, and fruit and vegetable residues—into intermediate bioenergy carriers via hydrothermal treatment (TORWASH^®), pelletization, and anaerobic digestion. The hydrothermal carbonization of these low-grade, moisture-rich biogenic residues enhances the flexibility and reliability of renewable energy systems while also offering the potential to reduce environmental burdens compared to conventional disposal methods. Through this S-LCA, the study aims to evaluate the cradle-to-gate socioeconomic impacts of the FPS in three European contexts—Sweden, Italy, and Spain—using the 2020 UNEP Guidelines and the Social Hotspots Database (SHDB) and applying quantitative modeling via SimaPro. The functional unit is defined as 1 kWh of electricity produced. The assessment combines SHDB-based modeling with primary data from stakeholder surveys conducted in the three countries. Impact categories are harmonized between SHDB and UNEP typologies, and the results are reported in medium-risk-hour equivalents (mrheq). The results show a heterogeneous social impact profile across case studies. In Sweden, the treatment of paper biosludge delivers substantial benefits with minimal risk. In Spain (orange peel), the introduction of the FPS demonstrated a strong social benefit, particularly in health and safety and labor rights, indicating high institutional performance and good integration with local industry. Conversely, in Italy (olive pomace), the FPS revealed significant social risks, especially in the biopellet production and electricity generation sectors, reflecting regional vulnerabilities in labor conditions and governance. This suggests that targeted mitigation strategies are recommended in contexts like Southern Italy. These findings highlight that the social sustainability of emerging bioenergy technologies is context-dependent and sensitive to sectoral and regional socioeconomic conditions. This S-LCA complements prior environmental assessments and emphasizes the importance of integrating social performance considerations in the deployment and scaling of innovative bioenergy systems. Full article

To address the growing demand for industrial software in the digital transformation of small and medium-sized enterprises (SMEs) in the manufacturing sector, and to ensure the stable integration and operation of multi-source heterogeneous industrial software under complex conditions—such as heterogeneous compatibility, component dependencies, and uncertainty disturbances—this study established a comprehensive evaluation index system for service composition and optimal selection (SCOS). The system incorporated key criteria including service time, service cost, service reputation, service delivery quality, and availability. Based on this, a bi-objective SCOS model was established with the goal of maximizing both quality of service (QoS) and availability. To efficiently solve the proposed model, a hybrid enhanced multi-objective Gray Wolf Optimizer (HEMOGWO) was developed. This algorithm integrated Tent chaotic mapping and a Levy flight-enhanced differential evolution (DE) strategy. Extensive experiments were conducted, including performance evaluation on 17 benchmark functions and case studies involving nine industrial software integration scenarios of varying scales. Comparative results against state-of-the-art, multi-objective, optimization algorithms—such as MOGWO, MOEA/D_DE, MOPSO, and NSGA-III—demonstrate the effectiveness and feasibility of the proposed approach. Full article

Rural tourism has emerged as an efficient strategy for rural revitalization while having various impacts on rural governance. Previous studies predominantly focused on the social implications of rural tourism and its impact on institutional arrangements while neglecting the influence of rural tourism on collective action in rural governance. This study employed a social–ecological system (SES) framework to investigate the influence of rural tourism on rural collective action, utilizing survey data from 22 provinces (autonomous regions and municipalities directly under the central government), 178 villages, and 3282 rural households across China. The findings revealed that rural tourism exerted a positive influence on collective action, primarily through labor force reflow mechanisms. Specifically, the leadership of village cadres had a moderating role in enhancing this positive correlation. Further analysis revealed significant heterogeneity in tourism governance effects: non-plain regions and villages with medium to low economic development levels exhibited substantial improvements in collective action, whereas plain areas and economically advanced villages may manifest potentially negative impacts. Theoretically, this study contributes to elucidating tourism-driven self-governance mechanisms by applying the SES framework, thereby transcending the traditional dualistic debate between state-market and development-governance paradigms. Practically, we propose institutional designs that embed collective action mechanisms into the coupled synergistic development of rural tourism and community governance, thereby activating endogenous motivations for rural self-governance. Full article

The Shabaosi gold field is located in the western Mohe Basin, part of the northern Great Xing’an Range, NE China, and contains multiple gold deposits. However, the sources of the ore-forming materials, the fluid evolution, and the genesis of these gold deposits have been disputed, especially regarding the classification of these deposits as either epithermal or orogenic gold systems. Based on detailed field geological investigations and previous research, we conducted systematic research on the Shabaosi, Sanshierzhan, Laogou, and Balifang gold deposits using fluid inclusion and H-O-S-Pb isotope data, with the aim of constraining the fluid properties, sources, and mineralization processes. Fluid inclusion analyses reveal diverse types, including vapor-rich, vapor–liquid, CO₂-bearing, CO₂-rich, and pure CO₂. Additionally, only a very limited number of daughter mineral-bearing fluid inclusions have been observed exclusively in the Laogou gold deposit. During the early stages, the peak temperature primarily ranged from 240 °C to 280 °C, with salinity concentrations between 6 and 8 wt% NaCl equiv., representing a medium–low temperature, low salinity, and a heterogeneous CO₂-CH₄-H₂O-NaCl system. With the influx of meteoric water, the fluids evolved gradually into a simple NaCl-H₂O system with low temperatures (160–200 °C) and salinities (4–6 wt%). The main mineralization stage exhibited peak temperatures of 220–260 °C and salinities of 5–8 wt% NaCl equiv., corresponding to an estimated formation depth of 1.4–3.3 km. The δD_V-SMOW values (−138.3‰ to −97.0‰) and δ¹⁸O_V-SMOW values (−7.1‰ to 16.2‰) indicate that the magmatic–hydrothermal fluids were progressively diluted by meteoric water during mineralization. The sulfur isotopic compositions (δ³⁴S = −0.9‰ to 1.8‰) and lead isotopic ratios (²⁰⁸Pb/²⁰⁴Pb = 38.398–38.579, ²⁰⁷Pb/²⁰⁴Pb = 15.571–15.636, and ²⁰⁶Pb/²⁰⁴Pb = 18.386–18.477) demonstrate that the gold predominantly originated from deep magmatic systems, with potential crustal contamination. Comparative analyses indicate that the Shabaosi gold field should be classified as a epizonal orogenic gold system, which shows distinct differences from epithermal gold deposits and corresponds to the extensional tectonic setting during the late-stage evolution of the Mongol–Okhotsk orogenic belt. Full article

Background/Purpose: Conventional three-dimensional in vitro tumor models often fail to fully capture the complexity of the tumor microenvironment, particularly the diverse populations of cancer-associated fibroblasts that contribute to poor prognosis and treatment resistance. The purpose of this study is to develop a patient-specific gastric cancer assembloid model that integrates tumor epithelial cells with matched stromal cell subtypes, each derived using tailored growth media to enhance cancer preclinical research and advance personalized therapeutic strategies. Methods: Tumor tissue was dissociated, and cells expanded in media for organoids, mesenchymal stem cells, fibroblasts, or endothelial cells. The resulting tumor-derived subpopulations were co-cultured in an optimized assembloid medium supporting each cell type’s growth. Biomarker expression was assessed by immunofluorescence staining, and transcriptomic profiles were analyzed by RNA sequencing. Drug responsiveness was evaluated using cell viability assays following treatment with various therapeutic agents. Results: The optimized co-culture conditions yielded assembloids that closely mimicked the cellular heterogeneity of primary tumors, confirmed by the expression of epithelial and stromal markers. Compared to monocultures, the assembloids showed higher expression of inflammatory cytokines, extracellular matrix remodeling factors, and tumor progression-related genes across different organoids and stromal ratios. Drug screening revealed patient- and drug-specific variability. While some drugs were effective in both organoid and assembloid models, others lost efficacy in the assembloids, highlighting the critical role of stromal components in modulating drug responses. Conclusions: This assembloid system offers a robust platform to study tumor–stroma interactions, identify resistance mechanisms, and accelerate drug discovery and personalized therapeutic strategies for gastric cancer. Full article

In a warming climate, rising temperature are expected to influence atmospheric humidity. This study examined the spatio-temporal dynamics of temperature (TEMP) and relative humidity (RH) across Equatorial Africa from 1980 to 2020. The analysis used RH data from European Centre of Medium-range Weather Forecasts Reanalysis v.5 (ERA5) reanalysis, TEMP and precipitation (PRE) from Climate Research Unit (CRU), and soil moisture (SM) and evapotranspiration (ET) from the Global Land Evaporation Amsterdam Model (GLEAM). In addition, four teleconnection indices were considered: El Niño-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), North Atlantic Oscillation (NAO), and Pacific Decadal Oscillation (PDO). This study used the Mann–Kendall test and Sen’s slope estimator to analyze trends, alongside multiple linear regression to investigate the relationships between TEMP, RH, and key climatic variables—namely evapotranspiration (ET), soil moisture (SM), and precipitation (PRE)—as well as large-scale teleconnection indices (e.g., IOD, ENSO, PDO, and NAO) on annual and seasonal scales. The key findings are as follows: (1) mean annual TEMP exceeding 30 °C and RH less than 30% were concentrated in arid regions of the Sahelian–Sudano belt in West Africa (WAF), Central Africa (CAF) and North East Africa (NEAF). Semi-arid regions in the Sahelian–Guinean belt recorded moderate TEMP (25–30 °C) and RH (30–60%), while the Guinean coastal belt and Congo Basin experienced cooler, more humid conditions (TEMP < 20 °C, RH (60–90%). (2) Trend analysis using Mann–Kendal and Sen slope estimator analysis revealed spatial heterogeneity, with increasing TEMP and deceasing RH trends varying by region and season. (3) The warming rate was higher in arid and semi-arid areas, with seasonal rates exceeding annual averages (0.18 °C decade⁻¹). Winter (0.27 °C decade⁻¹) and spring (0.20 °C decade⁻¹) exhibited the strongest warming, followed by autumn (0.18 °C decade⁻¹) and summer (0.10 °C decade⁻¹). (4) RH trends showed stronger seasonal decline compared to annual changes, with reduction ranging from 5 to 10% per decade in certain seasons, and about 2% per decade annually. (5) Pearson correlation analysis demonstrated a strong negative relationship between TEMP and RH with a correlation coefficient of r = − 0.60. (6) Significant associations were also observed between TEMP/RH and both climatic variables (ET, SM, PRE) and large scale-teleconnection indices (ENSO, IOD, PDO, NAO), indicating that surface conditions may reflect a combination of local response and remote climate influences. However, further analysis is needed to distinguish the extent to which local variability is independently driven versus being a response to large-scale forcing. Overall, this research highlights the physical mechanism linking TEMP and RH trends and their climatic drivers, offering insights into how these changes may impact different ecological and socio-economic sectors. Full article

Whether and how digital transformation affects innovation in small and medium-sized enterprises (SMEs) remains to be examined. This study aims to answer this question using a sample of SMEs listed on the Chinese National Equities Exchange and Quotations (NEEQ) market from 2012 to 2023. Employing textual mining techniques, this paper measures the degree of digital transformation through keyword frequency analysis of annual reports, while innovation is measured by the number of patent grants. Panel fixed effects models show that digital transformation significantly enhances corporate innovation in SMEs. This relationship remains robust after comprehensive endogeneity and additional robustness tests. Mechanisms analysis reveals that digital transformation alleviates financial constraints and enhances supply chain diversity, enabling SMEs to allocate more resources toward innovation activities. Heterogeneity analysis reveals that the positive effect of digital transformation on innovation is more pronounced for firms located in cities with higher digital finance coverage, in midwestern regions, and in industries with lower digitalization levels. These findings shed light on the power of digital technology, highlighting how its adoption can significantly bolster the innovation capacity of SMEs and drive their growth in a rapidly evolving digital economy. Full article