Search Results (1,225)

Lepidolite deposits are rare-metal deposits in which lepidolite is the principal industrial mineral. Owing to thin overburden and widespread open-pit mining, their exploitation supports raw material supply for the new energy industry but also continuously disturbs mining ecosystems, thereby threatening regional ecological security. Under the combined effects of fragile natural conditions and human-induced mining disturbance, traditional fixed-weight evaluation methods have difficulty identifying stage-wise changes and localized high-risk characteristics of ecological security in lithium mining areas. Taking the lithium mining area of Huaqiao Township, Yichun, as a case study, this study constructed an ecological-security evaluation system based on the Driver–Pressure–State–Impact–Response–Management (DPSIRM) framework and introduced variable weight (VW) theory to develop a penalty-dominated state variable weight model. This model enabled the dynamic adjustment of indicator weights across years and evaluation units, while the geographic detector was used to identify the main driving factors. Results showed that (1) from 2010 to 2024, ecological security exhibited a stage-wise pattern of initial improvement followed by degradation, and low-security areas first contracted and then expanded outward; (2) vegetation coverage was a key driving factor, while interactions between any two factors were stronger than the effect of a single factor, indicating that cumulative multi-stressor effects strongly shaped spatial differentiation; and (3) compared with the constant weight (CW) method, the VW method produced finer stratification within the severely degraded tail at the Shixiawo mining site across the four assessment years, demonstrating applicability at a representative mining site in this Huaqiao case study. These findings provide a scientific basis for ecological assessment, restoration, and coordinated resource management in lithium mining areas. Full article

The Springtime of Nations in 1990 was a great victory over the Evil Empire. We will examine some of its background in Croatia, concentrating on cultural phenomena and fine arts in particular. Even under Socialist Realism, there were some flights into “decadence”, such as the EXAT 51 exhibition in Zagreb, as Yugoslavia, threatened by the Russians, wanted to show its “pro-western” leanings. We will examine two outstanding Croatian artists who spanned the periods of Communism and its aftermath. The sculptor, Ljubo Dekarina (b. Rijeka, 1948), has mostly worked in the small Istrian township of Brseč. The painter, Ivan Rabuzin, from the Croatian Zagorje village of Ključ (b. 1921–d. 2008), maintained considerable ties with the Croatian capital of Zagreb. Thanks to them, we have discovered a world of an artistically contrived beauty and truth of eternal presence. Rabuzin’s is one of hills and groves, of rounded trees, and scattered hay-roofed homes, a short cut to paradise. Dekarina’s penetrations are entranceways into secret spaces of the beyond. Rabuzin and Dekarina just see better and know how to better communicate their experiences. It is the humanities that makes us human. Aristotle, as opposed to Plato, saw the arts as an improved and not a debased version of reality. Thus, the art experience comes close to religion, making us better, happier, more complete human beings. Art and religion are two aspects of that same pool. Full article

This study aimed to enhance the accuracy and interpretability of erosion gully classification within black soil regions by focusing on Changxing Township, Xinxing District, Qitaihe City, Heilongjiang Province as the research site. Utilizing RTK (Real-Time Kinematic) surveying technology, three-dimensional topographic data were collected for 139 actively developing erosion gullies. Key morphological parameters—including gully length, depth, gradient, average top width, average bottom width, and slope gradients on both sides—were extracted to construct interactive features. The variable set was refined through correlation analysis and variance inflation factor (VIF) diagnostics to mitigate multicollinearity. A random forest model was employed as the primary classification approach and benchmarked against logistic regression, support vector machines (SVM), decision trees, and backpropagation neural networks. To address class imbalance, a combination of class weighting, Synthetic Minority Over-sampling Technique (SMOTE), and undersampling methods was implemented. Model tuning and interpretability assessments were performed using cross-validation, grid search optimization, and SHapley Additive exPlanations (SHAP) analysis. The findings demonstrate that the random forest model achieved superior overall performance, with test set accuracy, macro-averaged F1 score, and balanced accuracy values of 0.9143, 0.8087, and 0.8427, respectively. Among imbalance handling techniques, class weighting yielded better results compared to oversampling and undersampling. Feature importance and SHAP analyses identified gully length, average crest width, and their interaction with gully depth as the principal determinants influencing gully grade classification. These results elucidate the synergistic developmental dynamics of gully longitudinal extension, vertical deepening, and lateral widening. The proposed methodology offers valuable technical support for the rapid surveying, classification, and management decision-making processes related to black soil erosion gullies. Full article

Dye-sensitized solar cells (DSSCs) remain attractive as low-cost photovoltaic devices; however, their practical efficiency is still constrained by electron-transport losses, interfacial recombination, and incomplete light harvesting in conventional titanium dioxide (TiO₂) photoanodes. The effects of TiO₂ film thickness, multi-walled carbon nanotube (MWCNT) incorporation, and multilayer oxide interface engineering on DSSC performance were examined. Degussa P25-TiO₂ photoanodes were first optimized with respect to thickness, after which controlled MWCNT loadings and sequential compact sol–gel TiO₂ and tin dioxide (SnO₂) sublayers were introduced. The optimum pristine P25-TiO₂ photoanode thickness was 9.11 μm, yielding an open-circuit voltage of 0.74 ± 0.01 V, a short-circuit current density of 14.10 ± 0.40 mA/cm², a fill factor of 56.24 ± 1.00%, and a power-conversion efficiency of 5.93 ± 0.20%. The incorporation of 0.025 wt% MWCNTs increased the efficiency to 6.04 ± 0.20%, corresponding to an absolute gain of 0.11 percentage points. The best performance was obtained with the sol–gel SnO₂/sol–gel TiO₂/P25-CNT multilayer photoanode, which delivered 0.74 ± 0.02 V, 16.22 ± 0.40 mA/cm², 57.59 ± 1.00%, and 6.89 ± 0.30%, respectively. FE-SEM, EIS, XRD, Heated Ultrasonic Cleaner and UV–visible analyses indicate that the multilayer architecture preserves porosity, enhances light harvesting, and suppresses interfacial recombination, while the CNT network facilitates charge transport. Full article

This study was conducted to investigate the effects of dietary supplementation with rumen-protected arginine (RP-Arg) on growth performance, rumen fermentation parameters, microbial diversity, and blood physiological and biochemical indices in fattening Altay sheep. A total of 24 healthy, 6-month-old Altay male lambs were randomly assigned to three groups, with eight replicates per group. The control group received a basal diet, while the experimental groups were supplemented with either 0.50% or 1.00% RP-Arg on a dry matter basis, respectively. The results indicated that RP-Arg supplementation had no significant effect on feed intake, growth performance, or slaughter performance of the lambs (p > 0.05), whereas backfat thickness decreased linearly (p < 0.05). With increasing RP-Arg levels, serum low-density lipoprotein cholesterol, leptin, and catalase activity increased linearly (p < 0.05), while blood ammonia, alanine aminotransferase, and Ig M exhibited a significant quadratic increase (p < 0.05). RP-Arg supplementation led to a linear decrease in ruminal propionate and valerate concentrations (p < 0.05). Analysis of bacterial diversity revealed that the class Vampirivibrionia and the order Gastranaerophilales were biomarkers for the 0.50% RP-Arg group, while several taxa within the phyla Proteobacteria and Thermoplasmatota served as biomarkers for the 1.00% RP-Arg group. In summary, although supplementation of a forage-based diet with RP-Arg partially modified rumen microbial composition and fermentation profile, and regulated several blood biochemical parameters, it did not translate into any beneficial effects on growth performance. Larger-scale studies are therefore warranted to further elucidate the role of RP-Arg in fattening lambs. Full article

As just transition debates extend into agricultural land use, this study examines landscape transition in Huwei Township, Taiwan, through a procedural justice lens. To address severe land subsidence, the state has promoted a shift from paddy rice cultivation to dryland farming, but the transition remains politically contested. Based on a systematic review of 55 empirical studies (2020–2026) and 12 semi-structured interviews, the study identifies a key mismatch in problem attribution: official accounts emphasize irrigation, whereas farmers point to urban development pressures and infrastructure burdens. The findings also show that cultivation-decoupled subsidies enable landowners to capture compensation while shifting operational risks onto tenant farmers and other vulnerable groups. The study argues that a socially sustainable transition depends on incorporating local knowledge and redesigning subsidy eligibility and risk-sharing rules to strengthen procedural justice, representativeness, and accountability. Full article

Wound healing research has advanced through nanotechnology-based delivery systems that enhance the stability and therapeutic potential of bioactive compounds. Resveratrol, a natural polyphenol with antioxidant and anti-inflammatory properties, shows promise for wound healing but is limited by poor bioavailability. This study investigates the efficacy of nano-liposome-encapsulated resveratrol in enhancing skin wound repair in adult zebrafish (Danio rerio). Using a laser-based ablation method, precise full-thickness skin wounds were induced and monitored over 50 days. Resveratrol-loaded liposomes were prepared and orally administered via gavage to facilitate systemic exposure. Compared to the control and blank liposome groups, resveratrol liposome treatment significantly accelerated wound closure, achieving earlier healing milestones (25%, 50%, and 75%). The zebrafish model provided a regenerative platform for real-time evaluation of nanomedicine-based therapies. This study demonstrates the wound healing effects of resveratrol and liposomal encapsulation, offering a targeted, systemically administered strategy for advanced systemic healing and highlighting zebrafish as a valuable model for preclinical regenerative medicine research. Full article

This paper studies the reliability and availability of a k-out-of-(M+S) retrial machine repair system with two-way communication, consisting of M primary components and S warm standby components. The system incorporates the retrial behavior of failed components. When the repairman becomes idle, he initiates outgoing calls after a random period either to failed components in the orbit for repair or to components outside the orbit for preventive maintenance. The main contribution of this study is the incorporation of proactive repairman behavior, which more realistically captures operational practices in certain engineering systems. By employing the matrix analytic method together with a recursive approach, the steady-state probabilities of the system are obtained, and several important performance measures are derived. Furthermore, the Runge–Kutta method is used to evaluate the system reliability and the mean time to failure. A sensitivity analysis is conducted to investigate the effects of key system parameters, supported by numerical experiments and graphical illustrations. Finally, a cost–benefit model is formulated, and a genetic algorithm is implemented to determine the optimal values of the decision variables that minimize the cost–benefit ratio. Full article

This review provides a comprehensive overview of the modulatory actions of plant-derived constituents on membrane ion channels in various cell types. Among their diverse bioactivities, ion channel regulation—governing membrane excitability, signal transduction, and cellular homeostasis—has emerged as a critical mechanistic basis for their pharmacological effects. Twenty-four representative phytoconstituents are discussed and classified into five major categories based on their structural features: alkaloids, terpenoids, lignans and acetogenins, polyphenols, and other aromatic and conjugated compounds. Across these categories, the reviewed compounds exhibit distinct and often highly specific effects on the amplitude and gating kinetics of multiple ionic currents, including voltage-gated Na⁺ currents (I_Na), delayed-rectifier K⁺ currents (I_K(DR)), M-type K⁺ currents (I_K(M)), hyperpolarization-activated cation currents (I_h), erg-mediated K⁺ currents (I_K(erg)), inwardly rectifying K⁺ currents, and Ca²⁺-activated K⁺ currents (I_K(Ca)). Alkaloids predominantly suppress voltage-gated K⁺ currents, with notable exceptions such as aconitine, which alters the properties of both I_Na and I_K(DR), thereby contributing to its proarrhythmic toxicity. Terpenoids, including cannabidiol, croton diterpenoids, lutein, thymol, and triptolide, exert multifaceted effects on I_K(M), I_h, inwardly rectifying K⁺ currents, and Ca²⁺-activated K⁺ channels. Lignans and acetogenins, such as gomisin A, honokiol, sesamin, and squamocin, primarily modulate I_Na, I_h, and I_K(Ca), with several compounds demonstrating strong links between ion-channel modulation and anti-neoplastic or neuroprotective actions. Polyphenolic compounds, including curcumin, eugenol, resveratrol, gastrodigenin, gastrodin, and pterostilbene, display diverse ion-channel targeting profiles, influencing multiple Na⁺ and K⁺ channel subtypes. Other aromatic or conjugated compounds, such as isoplumbagin, plumbagin, and verteporfin, regulate I_K(erg) and I_K(Ca), potentially contributing to both therapeutic efficacy and adverse effects. Collectively, the compound-specific modulation of current amplitude and gating kinetics offers valuable mechanistic insight into the pharmacological and toxicological significance of plant-derived natural products, highlighting the functional role of ion channel evaluation in guiding their therapeutic development and ensuring safety assessment. Full article

Leucine-rich repeat kinase 2 (LRRK2) is a multidomain serine/threonine kinase and a major genetic contributor to Parkinson’s disease (PD). Although LRRK2 has been extensively studied in neurodegeneration, emerging evidence indicates that it also plays a critical role in systemic metabolism. LRRK2 regulates glucose homeostasis through modulation of insulin signaling, vesicle trafficking, mitochondrial function, and inflammatory responses. Studies using LRRK2 knockout and knock-in models, including the pathogenic G2019S mutation, have revealed abnormalities in insulin sensitivity, adipose tissue inflammation, hepatic glucose production, and skeletal muscle metabolism. Mechanistically, LRRK2 phosphorylates Rab GTPases, thereby controlling insulin receptor trafficking and GLUT4 translocation. In addition, LRRK2 influences mitochondrial dynamics and reactive oxygen species production, linking metabolic stress to inflammatory signaling. Importantly, LRRK2 also regulates innate immune pathways, including TLR4–NFκB signaling and inflammasome activation, thereby connecting peripheral metabolic dysfunction to neuroinflammation. Here, we propose an integrated metabolic–neuroinflammatory crosstalk model in which LRRK2 functions as a molecular coordinator linking peripheral metabolic dysfunction to central neurodegeneration. In this framework, systemic metabolic stress—characterized by insulin resistance, chronic inflammation, advanced glycation end product (AGE) accumulation, and blood–brain barrier disruption—drives microglial activation and neurodegenerative processes. Understanding this systemic axis may provide new therapeutic opportunities targeting both metabolic dysfunction and neurodegeneration in PD. Full article

Under the background of highway ecological green construction and traffic-tourism integration, tourist highways in world natural heritage sites bear the dual responsibilities of heritage ecological protection and regional economic boosting, yet existing routes prioritize connectivity over ecological and economic values, damaging heritage integrity and failing to drive surrounding township development. This study aims to build a dual-coordinated route selection framework balancing ecological protection and economic development, taking Mount Fanjing as the case. Adopting literature research, field survey and spatial analysis, and grounding in road ecology, point-axis system and tourism space competition theories, it constructs a four-part framework covering township tourism potential evaluation, ecological suitability assessment, binary matrix model and route generation. Empirically, nine townships including Minxiao and Taiping are screened as core tourism service nodes, and the optimal layout of the ring Mount Fanjing tourist highway is determined via ecological suitability matching. The findings reveal the prominent contradiction between heritage protection and regional development in current heritage tourist highway construction, and the proposed dual coordination model effectively balances heritage conservation and local economic growth, providing a feasible planning reference for sustainable tourist highway layout in world natural heritage sites. Full article

Although tourists’ multi-attraction visitation behavior in tourism flow networks appears random, it actually follows underlying association rules. These rules may exhibit regional variations due to the influence of administrative barriers. Revealing the attraction association rules connected through tourist behavior can provide theoretical support for regional tourism planning and resource allocation. This study proposes a novel analytical framework to uncover hidden patterns and driving factors in tourists’ seemingly random behaviors across inter- and intra-township scales, with empirical evidence from the Pilot Zone of the Yangtze River Delta Green and Integrated Ecological Development Demonstration Area. Results show that the tourism flow network in the study area exhibits a distinct hierarchical structure. Nodes with high centrality are predominantly high-profile scenic spots that serve dual roles as both “cores” and “hubs” in the network. Most statistically significant association rules were observed at the intra-town level. In contrast, inter-town rules (exclusively among towns within Qingpu District, Shanghai) accounted for only a small proportion, where high-A-level tourist attractions frequently served as key nodes that enhanced cross-regional visitation probability. The determinants of tourist flow association rule intensity exhibit both commonalities and heterogeneities between intra-town and inter-town scales. Full article

In recent years, Large Language Models (LLMs) have demonstrated strong capabilities in contextual reasoning and knowledge retrieval. However, their application in industrial domains is limited by concerns regarding data security, reliance on cloud infrastructure, and high operational costs. To address these challenges, this study proposes the use of the Model Context Protocol (MCP) as a middleware framework that enables the deployment of offline-operable Small Language Models (SLMs) for industrial data processing. MCP facilitates structured interaction between SLMs and external resources (e.g., databases, APIs, and processors), allowing secure and controlled data access without exposing proprietary systems. As illustrated in the proposed framework, user input is first processed by the SLM (Qwen-7B) for intent determination. When external data is required, MCP coordinates the invocation of relevant resources and integrates the returned results into the model. The SLM then generates the final response. This approach enables SLMs to perform local computation for contextual analysis and decision support while maintaining low computational requirements and full data locality. The proposed system eliminates dependence on cloud-based LLM services and enhances security and cost efficiency. Experimental results demonstrate that the MCP-based architecture provides a practical and effective solution for deploying intelligent assistants in industrial environments without relying on large-scale external AI services. Full article

Driven by the goal of carbon neutrality, low-carbon development in township spaces is essential for sustainable urban–rural growth. This paper employs a carbon accounting methodology, taking Fuqiushan Town in the Dongting Lake Ecological Economic Zone as a case study to develop a detailed carbon measurement inventory at the township scale. Using spatial analysis techniques, it synthesizes multi-source data—including land use, agricultural inputs, and population—to estimate emissions from key sources such as crop cultivation, livestock and poultry breeding, industrial production, and residential activities. The study also evaluates the carbon sequestration capacity of sinks such as woodlands and water bodies, enabling the spatial visualization of both carbon emissions and carbon sinks. Key findings include: (1) Fuqiushan Town exhibits a carbon emission profile characterized by “industrial activities as the primary source, supplemented by agriculture, with additional contributions from residential and transportation sectors,” while forested areas and water bodies serve as core carbon sink zones. (2) An innovative multidimensional indicator system for low-carbon development efficiency was established, consisting of the Low-Carbon Development Efficiency Index in Production, the Daily Life Carbon Responsibility Efficiency Index, and the Ecological Carbon Sink Efficiency Index, which together form a Comprehensive Efficiency Index for Low-Carbon Development. (3) Analysis reveals significant spatial coupling relationships and efficiency differentiation patterns among carbon emissions, industrial structure, energy dependence, and ecological background. Based on dominant carbon emission types, low-carbon efficiency thresholds, and spatial factor interactions, the 17 villages and one forest farm in the township are classified into five zones: “Industrial High-Carbon Transition Zone,” “Agricultural Pollution Reduction and Carbon Emission Reduction Synergy Zone,” “Ecological Low-Carbon Conservation Zone,” “Human Settlements Balanced Development Zone,” and “Ecological Core Zone.” Tailored low-carbon spatial planning strategies for material resources are proposed for each zone. These results offer quantitative support and spatially targeted insights for low-carbon spatial planning in ecologically sensitive townships, contributing to the achievement of objectives such as “carbon reduction and sink increase” and “rural revitalization.” Full article

Accurate and timely information on tobacco cultivation is essential for macro-level regulation, tobacco monopoly management, and farmer support in China. Remote sensing offers an efficient means for mapping tobacco, yet most studies focus on mid- to late-season identification, while early-season detection remains underexplored. Therefore, we integrated multi-source remote sensing data with the Google Earth Engine (GEE) platform to quantify separability between tobacco and competing crops, determined the optimal early-season phenological window and discriminative features, and developed an early-season tobacco mapping approach using a stacked generalization ensemble. The results show that January–February period provides the most effective early identification window for Changting County, with near-infrared (NIR) and water-sensitive features contributing most to class discrimination. The stacked ensemble achieved an overall accuracy of 87.17%, with producer and user accuracies of 85.97% and 92.28%, respectively, outperforming individual classifiers. At the township scale, the mapped tobacco area was strongly associated with tobacco purchase volumes (R² = 0.819), supporting the reliability of the derived maps. Spatially, tobacco fields exhibited a pronounced corridor-like pattern, primarily influenced by proximity to water systems and terrain conditions. The proposed workflow provides tobacco management agencies with timely, spatially explicit information to support precise and intelligent tobacco production management. Full article