Search Results (4,722)

Offshore wind farms are increasingly and rapidly expanding due to their ability to harness strong and consistent wind energy resources. Large offshore wind farms are connected to mainland grids through High-Voltage Direct Current (HVDC) technology. However, offshore wind farms can often experience disturbances related to sudden wind changes, voltage drops/dips, faults related to converter switching, and unbalanced grid conditions which affect both the HVDC operation and wind turbine output. As a result, there is a growing need for more advanced and reliable modeling and monitoring tools. Moreover, traditional proportional-integral (PI) controllers are widely applied in wind turbines and HVDC systems due to their simple structure, easy implementation, and reliability. However, PI controllers perform poorly under non-linear and abnormal/fast-changing conditions, especially during sudden drops in wind power and grid faults. With this background, this paper first develops a digital twin model of an offshore wind farm that enables remote operation and monitoring of individual wind turbines. Also, an artificial intelligence (AI)-based controller, namely a fuzzy logic controller (FLC), is proposed to maintain transient stability of a full digital twin-based offshore wind farm connected to the HVDC grid under fault conditions. The effectiveness of the proposed FLC is demonstrated by considering a digital twin-enabled 700 MW offshore wind farm. The performance of the proposed FLC has been compared with that of the PI controller. Simulations performed by the MATLAB/Simulink software show that during the moderate voltage dip at 15 s, the PI controller experienced a 29.8% power reduction with a recovery time of approximately 9 s, whereas the FLC reduced the power drop to 23.1% and recovered within 6 s. During the severe converter disturbance at 15 s, the PI controller recorded a 36.9% power reduction compared to 23.4% for the FLC. Similarly, during the short-duration turbulence at 15 s, the PI controller exhibited a 36.73% power drop and recovered in approximately 7 s, while the FLC limited the power reduction to 19.17% and recovered within 5s. Overall, the FLC provided improved voltage stability, faster recovery, reduced oscillations, and superior fault ride-through capability compared with the conventional PI controller, demonstrating its effectiveness for digital twin-enabled offshore wind farm application. Full article

An emerging environmental pollutant, microplastics have garnered global attention due to their widespread presence in soil and aquatic ecosystems. Early research primarily treated microplastics as single pollutants, focusing on their individual toxic effects. However, microplastics in the environment exist as a complex mixture, comprising various polymer types, sizes, shapes, and aging states. This diversity influences how microplastics regulate ecosystem carbon and nitrogen cycles and intervene through pathways such as direct carbon input, physical disturbance, microbial community restructuring, and coupled effects. This paper systematically reviews the characteristics of microplastic diversity and its mechanisms influencing carbon and nitrogen cycles: the chemical structure of polymers determines bioavailability and degradation rate, with biodegradable plastics altering carbon and nitrogen transformations more significantly than conventional plastics; microplastics of different sizes affect nitrogen transformation dynamics by modulating specific surface area and microbial colonization, with small-sized biodegradable microplastics particularly inhibiting plant nitrogen uptake; aging modifies surface properties and dissolved organic carbon release, thereby enhancing their role in promoting greenhouse gas emissions. Existing studies are largely confined to short-term laboratory simulations, leaving a gap in understanding the comprehensive effects of microplastic diversity under long-term, field conditions. Future research should focus on standardized methods and long-term experiments with multi-factor coupling to provide a scientific basis for ecological risk assessment of microplastic pollution. Full article

Oocyte formation occurs successfully within a meticulously controlled follicular environment characterized by well-documented endocrine, metabolic, and paracrine signals. Yet, the immunological landscape of the follicle and its role in influencing oocyte competency has received less attention in research. Growing research indicates that the ovarian follicle functions as an immunological-active niche necessitating a precise equilibrium between controlled inflammation and targeted immune tolerance. The programmed cell death-1 (PD-1) receptor and its ligand PD-L1 constitute a crucial immune checkpoint pathway, essential for sustaining peripheral immunological tolerance and averting excessive immune activation. Despite their comprehensive research in cancer biology and maternal–fetal interactions, their possible function in the follicular microenvironment remains mostly unexamined. We propose that PD-1/PD-L1 signaling may facilitate the formation of a localized immune-tolerant milieu inside the follicle to safeguard the developing oocyte from inflammatory injury and immune-mediated stress. The disturbance of this suggested equilibrium may lead to a pro-inflammatory follicular environment, compromised granulosa cell function, and modified oocyte maturation, hence affecting fertilization and embryonic developmental potential. In clinical contexts with immunological dysregulation, such as endometriosis, polycystic ovarian syndrome, and unexplained IVF failure, such processes may be especially significant. The purpose of this narrative review is to assimilate the current comprehension of immune regulation in the follicle with the established biology of PD-1/PD-L1 and to investigate a potential correlation between immune checkpoint signaling, oocyte competence, and assisted reproductive outcomes. Considering the follicle as an immune-regulated microenvironment offers a new paradigm for comprehending infertility and identifying novel indicators or therapeutic targets. Full article

Background: Kidney disorders are strongly related to metabolic disturbances, including obesity and type 2 diabetes. Excessive intake of sugar and saturated fats promotes lipid accumulation, cellular energy issues and inflammatory responses. Cannabigerol (CBG), a non-psychotropic phytocannabinoid, has recently gained attention for its metabolic, anti-inflammatory and potential protective properties. Methods: The present study investigated the effect of two weeks of CBG administration (last 14 days of the experiment) on fatty acid (FA) composition, FA metabolic pathways and FA transporters in rats subjected to a high-fat high-sucrose diet (HFHS) for 6 weeks. Male Wistar rats were divided into four groups: Control, CBG, HFHS, and HFHS+CBG. Kidney tissue and urine samples were analyzed by gas–liquid chromatography (GLC) for lipid fractions and FA profiles, while protein expression of FA transporters and metabolic enzymes was assessed by immunoblotting. Polysaccharides and collagen fibers were visualized using Periodic Acid-Schiff (PAS) and AZAN staining, respectively. ELISA and colorimetric kits were used to measure urinary albumin and creatinine contents. Results: HFHS feeding altered renal lipid homeostasis, increasing saturated and monounsaturated fatty acids (SFA and MUFA, respectively) levels and affecting desaturation and elongation ratios. CBG supplementation affected renal lipid metabolism by lowering triacylglycerol (TAG) accumulation, restoring polyunsaturated fatty acids (PUFA) in phospholipid (PL) and altering FA ratios, suggesting an improvement in lipid balance. CBG also increased the expression of carnitine palmitoyltransferase 1 (CPT1) and lipoprotein lipase (LPL) and decreased the expression of stearoyl-CoA desaturase 1 (SCD1) and fatty acid synthase (FAS), suggesting a shift toward enhanced FA oxidation and reduced lipogenesis. Conclusions: Overall, CBG exerted good effects on renal lipid metabolism and may mitigate early lipid-mediated injury associated with metabolic kidney disorders. Full article

Fear is a transdiagnostic construct implicated in multiple psychiatric disorders, reflecting a partial dissociation between clinical phenotypes and underlying neurobiological mechanisms. Converging evidence suggests that aberrant fear processing plays a central role in cognitive and psychopathological models of psychosis. In this narrative review, we synthesize evidence on the neurobiological mechanisms of aberrant fear modulation in schizophrenia from a translational perspective, integrating findings from neuroimaging, preclinical models, pharmacological interventions, and psychotherapy. Schizophrenia is characterized by aberrant emotional processing and inappropriate neural responses to stimuli with reduced or absent objective salience, reflecting impaired discrimination of relevant environmental information. At the system level, evidence implicates dysregulation of cortico-limbic and salience-processing networks in altered fear learning, threat appraisal, and emotional prediction. Neurochemical findings indicate that dopamine–glutamate dysregulation and associated intracellular signaling pathways act as upstream modulatory mechanisms contributing to these network-level abnormalities. Therapeutic interventions, including antipsychotic drugs and psychotherapeutic approaches, partially modulate these systems, although effects remain heterogeneous. Overall, the evidence supports a hierarchical model in which aberrant fear processing in schizophrenia arises from disrupted salience attribution and impaired integration across cognitive, affective, and neurobiological levels. This intermediate dysfunction links molecular alterations to large-scale network disturbances and clinical symptom expression, providing a framework for more mechanism-based therapeutic strategies. Full article

Forest decline in genus Abies has been increasingly associated with drought, warming, pollution, and biotic disturbances. However, the importance of these drivers and the degree to which drought–bark beetles’ interactions have been studied in Abies remain insufficiently documented. This review aimed to identify the main reported causes of decline in Abies species worldwide and to assess the current state of knowledge on the drought–bark beetles’ interaction, with special attention to sacred fir (Abies religiosa) because of its ecological importance in Mexico and its role as a winter habitat for the monarch butterfly (Danaus plexippus). We reviewed 237 articles indexed in Scopus and complemented this analysis with bibliometric indicators and keyword co-occurrence maps generated using the Bibliometrix R package (version 5.4.1) and VOSviewer (version 1.6.12). The main causes of decline were drought, pollution, and rising temperatures, affecting 41 taxa in 28 countries. Although drought has been reported throughout the study period (1977–2026), publications linking drought and warming to Abies decline have increased markedly during the last 15 years. Bibliometric results indicate that drought–bark beetles’ interactions have been extensively studied in Pinus and Picea, whereas comparable evidence for Abies remains limited. Future management should integrate monitoring, stand-density regulation, pest surveillance, and climate-adaptation strategies implemented by forest managers, conservation agencies, and local communities. Full article

To address the problems of closed-loop task organization, strong corridor constraints, and path failure after local disturbances in unmanned aerial vehicle (UAV) inspection of gas-insulated switchgear (GIS) rooms, this paper proposes a topology-and-corridor-guided bias-suppressed D* (TCG-BS-D*) method for closed-loop three-dimensional (3D) path planning and local replanning. The proposed method constructs a structured guidance model based on the inspection-corridor topology, generates local 3D path segments according to a predetermined inspection sequence, and forms a nominal closed-loop inspection path through bias suppression and path regularization. Meanwhile, for local maintenance blockage and dynamic disturbance scenarios, an alternative local replanning strategy is applied to the affected path segments. Simulation results show that, under the static closed-loop inspection condition, the proposed method achieves a total path length of 700.22 m, a total inspection time of 269.32 s, an average safety clearance of 8.18 m, 37 large-angle turns, a corridor adherence rate of 80.73%, and a task completion rate of 100%, showing superior performance in inspection efficiency, safety margin, trajectory regularity, and corridor consistency. Under the local blockage condition, the replanned path introduces path-length and time increments of 71.29 m and 25.88 s, respectively, while maintaining the minimum safety clearance at 1.52 m and increasing the corridor adherence rate to 83.91%. Under dynamic disturbance conditions, the minimum dynamic safety clearance is improved from −2.71 m to 17.84 m, effectively eliminating the local dynamic collision risk. The results demonstrate that the proposed method can balance closed-loop path-generation efficiency, corridor-structure consistency, safety margin, and adaptability to local disturbances, providing an effective solution for UAV inspection path planning in GIS rooms. Full article

Walking is not merely locomotion but a window into the nervous system, integrating cortical, subcortical, cerebellar, spinal, and peripheral networks into a unified motor behavior. Across neurological diseases—including Parkinson’s disease, atypical parkinsonism, cerebellar ataxias, stroke, multiple sclerosis, neuropathies, neuromuscular disorders, and functional gait syndromes—gait disturbances are among the most disabling clinical features, contributing to falls, loss of independence, institutionalization, and premature mortality. Traditional bedside observation remains indispensable, but it lacks the sensitivity and reproducibility needed to capture subtle, episodic, or prodromal abnormalities. Over the past decade, advances in wearable sensors, marker-based and markerless motion capture, pressure-sensitive walkways, force plates, artificial intelligence, and machine learning have positioned digital mobility outcomes as promising, ecologically valid biomarkers of neurological function. These measures can support differential diagnosis, provide prognostic information on falls and survival, and serve as sensitive endpoints in therapeutic trials. They may also detect early abnormalities, such as increased stride-to-stride variability or prolonged double-support time, before overt clinical deterioration becomes evident. Clinical applications are increasingly evident across disorders, including distinguishing Parkinson’s disease from atypical parkinsonism, quantifying treatment response in normal-pressure hydrocephalus, tracking progression in ataxia and multiple sclerosis, predicting functional decline in motor neuron disease, and guiding rehabilitation after stroke. Integration with neuroimaging, electrophysiology, and molecular biomarkers is beginning to reveal the circuits underlying variability, instability, and freezing, positioning gait as a systems-level marker of neural integrity. Nevertheless, methodological heterogeneity, limited disease-specific validation, insufficient longitudinal data, and lack of consensus on clinically meaningful parameters continue to constrain translation. Cognitive, affective, and environmental influences also remain insufficiently represented in digital frameworks, while equity, accessibility, algorithmic bias, and privacy require careful ethical governance. Reconceptualizing gait as a “sixth vital sign” reframes mobility as a multidimensional biomarker of neural and systemic health. With harmonized protocols, robust validation, multimodal integration, and appropriate ethical frameworks, gait analysis could become a cornerstone of precision neurology. Full article

Diabetic encephalopathy (DE) is a severe complication of diabetes mellitus affecting the central nervous system (CNS), characterized by cognitive dysfunction. This review systematically explores how the interplay between brain insulin resistance (BIR) and neuroinflammation contributes to the pathogenesis of DE. BIR refers to the diminished responsiveness of the CNS to insulin signaling, resulting in the suppression of the PI3K/Akt and MAPK pathways, impaired glucose metabolism, and dysfunction across multiple neural cell types—including neurons, astrocytes, microglia, brain endothelial cells, and oligodendrocytes. These disturbances manifest as impaired energy metabolism, compromised synaptic plasticity, disruption of the blood–brain barrier, and reduced myelination. Importantly, BIR and neuroinflammation form a vicious cycle within these cells, mutually exacerbating each other and jointly driving the pathological progression of DE. Finally, we have compiled a list of currently available drugs that can improve BIR and suppress neuroinflammation, along with the latest progress in clinical trials, to provide new insights for the future of precision treatment for DE. Full article

The phoD gene encodes alkaline phosphatase, which hydrolyzes organic phosphorus and releases bioavailable phosphorus for direct utilization by marine organisms. phoD-harboring bacteria are reported to be sensitive to environmental changes. As a common ecological disturbance, annual Ulva prolifera green tides in the southern Yellow Sea pose significant ecological challenges, yet the responses and assembly processes of phoD-harboring bacterial communities remain poorly understood. In this study, high-throughput sequencing was used to characterize these communities across the pre-bloom, bloom and post-bloom stages. The results revealed significant stage-specific shifts in community structure, with the bloom and post-bloom stages exhibiting higher similarity to each other than the pre-bloom stage. Abundant taxa were more sensitive to environmental fluctuations across all stages and were characterized by broader niche breadths but reduced phylogenetic diversity during the bloom. In contrast, rare taxa maintained relatively stable diversity but showed marked niche contraction. Neutral community model and βNTI analyses demonstrated that stochastic processes dominated community assembly overall. Green tide drove rare taxa toward heterogeneous selection and drift, while abundant taxa shifted toward homogeneous selection during the post-bloom stage. Co-occurrence network analysis showed increased microbial correlations during the bloom, implying a trend toward greater network stability of phoD-harboring bacterial communities under green tide disturbance. The lagged responses, functional redundancy and divergent ecological strategies of abundant and rare taxa may explain how green tides drive variations in microbes involved in the phosphorus cycle. These findings provide new insights into the microbial regulatory mechanisms of the nutrient cycle in coastal ecosystems affected by large-scale U. prolifera green tides. Full article

Disturbance events and subsequent management practices significantly shape the ecological legacies of affected sites. This study evaluated the impacts of a 2022 derecho and the subsequent forest management on forest structure and arthropod diversity by comparing affected forests at Fogwell Forest Nature Preserve and Fox Island County Park with control forests at Blue Cast Springs and Hammer Wald Nature Preserves. Arthropod communities were sampled using pitfall traps, while forest structure was assessed through detailed surveys of understory, midstory, and overstory vegetation. Results indicated a decrease in overall arthropod diversity across all sites since 2016, variably attributed to forest maturation, climatic variability, and the 2022 disturbance, with some taxa showing declines, such as Formicidae and Curculionidae. Fogwell exhibited a significant decline in arthropod diversity, likely linked to the derecho, while Fox Island’s diversity aligned more closely with undisturbed control sites. Notable midstory reductions were observed across sites over time, especially at Fox Island, due to harvest and storm impacts. Meanwhile, overstory diversity varied between properties. Regression modeling revealed that forest management practices at Fox Island may have mitigated the disturbance’s effects, aiding arthropod recovery. All in all, these findings highlight the importance of forest management strategies in influencing biodiversity and ecological recovery post-disturbance. Full article

This paper treats the 2016 reform of the vertical management of environmental protection agencies as a quasi-natural experiment. Using data from Chinese A-share-listed companies on the Shanghai and Shenzhen stock exchanges from 2012 to 2022, we employ a multi-period difference-in-differences (DID) approach to examine the impact of environmental governance structural reforms on firms’ total factor productivity (TFP). The study finds that the vertical management reform of environmental protection agencies significantly suppressed TFP in pilot regions. This conclusion remains valid after robustness tests, including parallel trend tests, placebo tests, PSM-DID, alternative TFP estimation methods, and the exclusion of contemporaneous policy disturbances. Mechanism tests suggest that the reform may affect firm productivity by weakening firms’ technological innovation capabilities and reducing capital allocation efficiency; further green innovation tests did not find a significant innovation compensation effect. Heterogeneity analysis indicates that this negative impact is more pronounced in state-owned enterprises, firms subject to weaker regulation, and firms in the eastern region. This paper extends research on the economic consequences of environmental policies from traditional regulatory instruments to the level of environmental governance structural reforms, providing micro-level empirical evidence for understanding the relationship between environmental governance reforms and firm efficiency. Full article

Rapid urbanization and industrialization have profoundly affected aquatic ecosystems in urban rivers, with phytoplankton taxa and functional group composition being particularly sensitive to environmental changes. Field surveys were conducted in the Nanming River, Guiyang, in October 2018 and July 2019, with 33 sampling sites evenly distributed across the upstream, midstream, and downstream reaches. The results revealed that: (1) The phytoplankton community comprised 6 phyla, 53 genera, and 61 species, dominated by Bacillariophyta, Chlorophyta, and Cyanobacteria. The community was classified into 20 functional groups, among which B, D, MP, P, and S1 were dominant and exhibited clear spatial heterogeneity along the longitudinal gradient. (2) Analysis of variance indicated that physicochemical parameters were the dominant factors explaining the variation in phytoplankton taxonomic and functional groups, with their independent contribution significantly higher than that of anthropogenic disturbance indicators and geographical factors. Redundancy analysis further identified NH₄-N, TP, and TN as key environmental factors. Spearman’s correlation analysis further indicated that human activities alter ambient environmental conditions, which are significantly correlated with dissolved oxygen and chlorophyll a levels, thereby driving the differentiation of phytoplankton niches. (3) Functional group succession followed a distinct spatial pattern: upstream areas were dominated by groups P, SN, and Y, reflecting agricultural non-point source inputs; midstream areas were dominated by groups W1, H1, and S1, characteristic of urban complex pollution; and downstream areas were dominated by groups C and X1, indicating cumulative nutrient loading. Collectively, this study elucidates the driving mechanisms of phytoplankton dynamics in karst urban rivers and provides a scientific foundation for water quality monitoring, eutrophication risk pre-warning, and aquatic ecological restoration. Full article

Heavy metal(loid) pollution in watersheds surrounding mining areas originates from multiple and complex sources, posing persistent threats to terrestrial–aquatic ecosystems and human dietary safety. This study systematically investigated the pollution characteristics, spatial distribution, ecological risks and human health hazards of seven typical heavy metal(loid)s (As, Pb, Cr, Cd, Cu, Zn, and Ni) in the integrated water–soil–vegetable continuum of a mining-affected watershed in Southwest China. Field sampling was carried out in three functional zones with different mining disturbance intensities, and inductively coupled plasma mass spectrometry (ICP-MS) was used to detect heavy metal(loid) concentrations in all samples. Multiple pollution evaluation indices and the USEPA human health risk assessment model were adopted for comprehensive quantitative analysis. The results showed that 44.0% of surface water samples exceeded national permissible limits, with high-pollution areas concentrated in intensive mining zones, presenting moderate overall aquatic heavy metal(loid) pollution. Although the average concentrations of seven heavy metal(loid)s in riparian soils complied with Chinese agricultural soil screening standards, localized significant enrichment was observed for As (1.98 times), Cd (4.62 times), Cu (1.81 times), and Zn (2.72 times) compared with regional background values, causing mild comprehensive soil pollution. Farmland soils exhibited prominent Cu and Zn accumulation, and leafy vegetables in the study area suffered severe Pb and Cd pollution, with potential dietary exposure risks. Health risk assessment indicated that children face higher non-carcinogenic and carcinogenic risks than adults via soil hand-to-mouth exposure; dietary intake of vegetables leads to moderate carcinogenic risks for children caused by As and Ni exposure. Overall, this study clarifies the migration and enrichment rules of heavy metal(loid)s in the water–soil–vegetable system of mining watersheds, confirms the prominent ecological and human health risks of Cd, As and Pb in the study area, and provides targeted basic data for regional heavy metal(loid) pollution prevention and food safety management. Full article

Fireworks have been used in China for more than a millennium, though they are an increasing part of celebration globally. Consumption of fireworks is on the rise despite increased regulation of their use. This review examines the key themes that are apparent in contemporary research: contamination of air, water and soil, in addition to waste debris, noise and light pollution, along with contemporary approaches to mitigate environmental impact. Research is, as expected, more frequent from countries with high fireworks use, so some rather small countries such as the Netherlands, Malta and Iceland are notably active. Concentrations of emitted gases (especially SO₂) and fine particles are frequently studied, along with associated toxic metals and semimetals (especially Cu, Zn, Cd, As, Ba and Sr). There are many projections of effects of fireworks, but relatively few epidemiological studies of health outcomes or the impact of contamination on local ecosystems. Fireworks waste and debris is an environmental problem; it is expensive to clear and aesthetically unpleasing. Excessive noise (up to 137 dB) created by fireworks affects pets and wildlife, as well as posing a risk to pyrotechnicians. Fireworks produce bursts of light that can be distracting to motorists and disturb wildlife, while smoke particles cause lowered visibility. Green fireworks and festivals of light with lasers or drone technology present routes to lower impact. Contemporary society is sympathetic towards restricting fireworks, but recognition of their cultural importance remains. Full article