Search Results (18,907)

Over the past decade, an increasing number of functional microbial-like terpene synthases (MTPSLs) have been reported in non-seed plants. However, whether the traditional Chinese medicinal plant H. serrata harbors such enzymes and their corresponding functions remains unexplored. In this study, we mined the transcriptome of H. serrata and identified a microbial-like terpene synthase, HsMTPSL1, which produces multiple diterpene products. Following isolation and structural elucidation, seven distinct compounds were obtained, representing three skeletal types: spatane, prenylkelsoene-type, and biflorane. Among these, compound 7 is a novel biflorane diterpene. Structural analysis and subsequent mutagenesis revealed critical residues governing the formation of distinct skeletons, uncovering the multifunctional nature of this enzyme. Notably, the S224A mutation significantly enhanced the production of spatane diterpene compound 1 by 11.6-fold, demonstrating the potential for protein engineering to improve the yield of this bioactive marine-specific diterpene. Transcriptomic profiling revealed that HsMTPSL1 is highly expressed in sporangia, and co-expression analysis with cytochrome P450s identified the CYP781 subfamily as candidates potentially involved in the downstream modification of these skeletons. Collectively, we report the first MTPSL from H. serrata and characterize it as a multifunctional diterpene synthase. Through structure-guided mutagenesis, we uncovered the molecular basis of its functional versatility, with the S224A mutation providing a powerful tool for enhancing the yields of all three diterpene skeletons, thereby laying a foundation for future protein engineering and synthetic biology applications. Full article

Social Network Analysis (SNA) has been widely applied to risk identification research. However, two key constraints, namely rating bias and the subjectivity of threshold selection, undermine the reliability and reproducibility of analytical results. To address this di-lemma, this study aims to construct a standardized and robust analytical framework for SNA-based risk identification. The core research objectives are as follows: elucidate the differential impact mechanism of threshold variation on the macro-topological structure and micro-level node ranking of risk networks, examine the cross-threshold robustness of core risk node rankings, and delimit the effective threshold range for stable risk identification. Accordingly, to fulfill the above objectives, this study proposes a multi-threshold robustness inspection method based on individual rating patterns, and conducts systematic empirical analysis with industrial projects in the post-support period of reservoir resettlement as research cases. The results indicate that threshold variation exerts marked systematic effects on the macro-topological structure of risk networks, whereas the relative rankings of core risk nodes remain robust. The effective threshold range for risk identification in such projects is α ∈ [0.1,0.3]. This study provides a repeatable quality control framework for SNA-based risk identification, with favorable cross-domain transferability. Full article

Lithium is a rare metal widely used in the renewable energy industry. The Altyn region in Xinjiang, China, contains abundant granitic pegmatite-type lithium resources; however, the deeply incised and complex terrain limits the accuracy of conventional two-dimensional remote sensing approaches for dike identification and segmentation. To address this limitation, a remote sensing segmentation method incorporating terrain information was proposed. A digital elevation model (DEM) derived from LiDAR data, together with its associated topographic factors, was integrated into the Spatial–Spectral Mamba framework to enable the joint utilization of spectral and terrain features. Rather than performing explicit three-dimensional geometric modeling, the proposed approach enhances a two-dimensional segmentation framework by introducing elevation-derived information, allowing the model to capture terrain-related spatial variations of pegmatite dikes. This design enables improved representation of both the planar distribution and terrain-influenced morphological characteristics of dikes under deeply incised conditions. The Xichanggou lithium deposit in the Altyn region is a large-scale, economically valuable pegmatite-type lithium deposit, and was therefore selected as the study area for pegmatite dike segmentation. The results demonstrated that, compared with conventional two-dimensional approaches and representative machine learning methods, the proposed method achieved higher segmentation accuracy in complex terrain. Improvements were also observed in the continuity and spatial consistency of the extracted dike patterns. Field verification indicated that the major pegmatite dikes delineated by the model were highly consistent with their actual surface exposures. Sampling analyses further confirmed the validity and reliability of the identification results. Overall, the terrain-integrated remote sensing segmentation approach exhibited good applicability and robustness under deeply incised and complex geomorphological conditions. Full article

In response to the reduced system inertia and increased frequency security risks in high-renewable power systems, as well as the limitations of single energy storage technologies, a coordinated optimal scheduling method for electrochemical energy storage (EES) and compressed air energy storage (CAES) considering the minimum inertia requirement (MIR) is proposed. The method constructs a coordination framework, leveraging the fast response of EES and the sustained support and equivalent inertia contribution of CAES. An MIR evaluation model considering RoCoF and frequency nadir constraints is established, and the inertia deficit is converted into fast reserve demand, forming an inertia–reserve coupling mechanism. To address nonlinear frequency constraints, an adaptive piecewise linearization method is adopted to transform the model into a mixed-integer linear programming problem. Case studies show that, compared with the benchmark hybrid energy storage scheduling strategy without inertia–reserve coordination, the proposed method reduces thermal generation cost by 4.5% and renewable curtailment by 74.8%. Moreover, the proposed APWL method improves computational efficiency by 47% compared with the conventional PWL method. Full article

Timely and accurate monitoring of surface water dynamics via remote sensing is critical, given water resources’ importance. However, accurate water body delineation based on high-resolution remotely sensed imagery is still challenging due to the complexity of water bodies’ boundaries and the diversity of their shapes and sizes, which can lead to boundary ambiguity and varying degrees of confusion with near-water vegetation in water body maps. To address this challenge, we introduce an uncertainty-aware hybrid CNN–Transformer model for delineating water bodies using remotely sensed imagery. In our designed network, a multi-scale transformer (MST) module is first designed to effectively model and refine the multi-scale global semantic dependencies of water bodies. Subsequently, an uncertainty-guided multi-scale information fusion (MSIF) module is constructed to extract water body mapping information from these multi-scale features output from the MST module and fuse them adaptively. Across different scales, the extracted features differ in their ability to distinguish water bodies from non-water bodies and in their levels of uncertainty. Consequently, during the adaptive fusion of multi-scale water body information in the MSIF module, the mapping uncertainty is quantified and suppressed to minimize its impact, thus yielding enhanced precision in water body delineation. Ultimately, a comprehensive loss function is designed for model optimization to generate the final water body map. Furthermore, to promote water body segmentation models’ development, this study also presents the HBD_Water water body sample dataset, which contains 44 multispectral, 5000 × 5000-pixel images at 2 m spatial resolution, and will be released on the LuojiaSET platform soon. Finally, to verify the proposed model and its constituent MST and MSIF modules, extensive water mapping experiments were performed on three datasets. The experimental results substantiate their effectiveness. Furthermore, comparative experiment results demonstrate that the proposed model performs better at water body extraction than advanced networks including TransUNet, DeeplabV3+, and ADCNN. Full article

This study aimed to evaluate the compensatory effects of amino acid (AA) supplementation on laying hens fed a low-protein diet, focusing on production performance, egg quality, blood immunity, total tract retention, and intestinal health. A total of 180 Hy-Line Brown laying hens (35 weeks old) were randomly allocated to three dietary treatments with 12 replicates (5 hens/replicate): (1) control diet (15.90% crude protein, CON), (2) reduced-protein diet (15.20% crude protein, NG), and (3) reduced-protein diet supplemented with 400 g/t methionine, 400 g/t lysine, and 300 g/t threonine (15.20% crude protein, LAA). Over the 12-week experimental period, production parameters were monitored weekly. The results showed that compared to the NG group, AA supplementation significantly increased laying rates during weeks 1–4 (p < 0.05) and reduced the feed-to-egg ratio during weeks 9–12 (p < 0.05), with a 3.10% decrease in feed conversion ratio (FCR). By week 12, the NG group exhibited lower Haugh unit values than both the CON and LAA groups (p < 0.05), indicating improved egg quality with AA supplementation. Serum analysis revealed elevated immunoglobulin Y levels and upregulated expression of the anti-inflammatory cytokine IL-10 in the LAA group (p < 0.05). Total tract retention of crude protein (CP) and phosphorus (P) was significantly enhanced in the LAA group compared to CON and NG groups (p < 0.05). However, in terms of cecal microbiota, no significant differences were observed among the experimental groups. These findings demonstrate that AA supplementation alleviates the adverse effects of low-protein diets by enhancing nutrient utilization and immune modulation, thereby improving productive performance, egg quality, and total tract retention in laying hens. Full article

Background: Family caregivers remain closely involved in communication, care planning, and shared decision-making in long-term care (LTC) facilities. In this context, the quality of the relationship between family caregivers and professional staff may influence trust, collaboration, and satisfaction with care. However, few instruments have been specifically adapted to assess caregiver–staff relationship quality in Taiwanese LTC settings. Objectives: This study aimed to culturally adapt and preliminarily validate the Family Caregiver Relationship Quality (FCRQ) Scale for use in Taiwanese LTC facilities. Methods: A cross-sectional psychometric validation study was conducted with 205 primary family caregivers recruited from 20 LTC facilities in Taiwan. The original Relationship Quality Scale was adapted to the LTC context through contextual revision, expert review, bilingual verification, and pilot testing. Psychometric evaluation included confirmatory factor analysis, internal consistency assessment, convergent validity, and structural equation modelling with Bollen–Stine bootstrap correction to address potential non-normality. Results: The initial 16-item model required refinement, and three items with low standardized factor loadings were removed. The revised 13-item model met the prespecified fit criteria and showed acceptable internal consistency and convergent validity. The retained items reflected three conceptually related domains of relationship quality: trust, commitment, and satisfaction. Overall, the findings provided preliminary psychometric support for the adapted scale in Taiwanese LTC settings. Conclusions: The adapted FCRQ Scale may be a useful tool for assessing caregiver–staff relationship quality in Taiwanese long-term care facilities, particularly in the context of shared decision-making and family-centred care. Nevertheless, the findings should be interpreted as preliminary, and further validation in larger and more diverse samples is needed before broader clinical or research application. Full article

Astragalus membranaceus is an important perennial medicinal plant whose roots constitute its primary medicinal organ; however, its cultivation is severely constrained by root rot caused by Fusarium oxysporum. This study aimed to characterize differences in the rhizosphere microbiome between healthy and diseased plants, identify antagonistic microorganisms from healthy rhizosphere soils, and investigate their suppressive effects on F. oxysporum and the associated host metabolic responses. High-throughput sequencing was used to compare bacterial and fungal communities in the rhizospheres of healthy and diseased plants. Microorganisms were isolated from healthy rhizosphere soils and screened for antagonistic activity against F. oxysporum, followed by validation in pot experiments. Metabolomic analysis was further conducted to assess host metabolic responses to microbial treatment. Root rot disease significantly altered the dominant composition of rhizosphere microbial communities and was associated with reduced fungal diversity and lower bacterial richness in diseased soils. Co-occurrence network analysis revealed increased complexity in bacterial networks and strengthened positive correlations among fungal taxa under diseased conditions. A total of 81 microbial strains were isolated from healthy rhizosphere soils, among which Penicillium halotolerans exhibited the strongest inhibitory activity against the mycelial growth of F. oxysporum. Pot experiments further supported its suppressive effect on Astragalus root rot. Metabolomic analysis indicated that P. halotolerans treatment was associated with changes in host metabolic profiles related to energy metabolism, defense-associated protein synthesis, and nutrient uptake. Overall, this study identified P. halotolerans as a fungal strain with antagonistic activity against F. oxysporum and provided initial evidence for its association with the suppression of Astragalus root rot. These findings offer candidate microbial resources and mechanistic insights for understanding rhizosphere-associated disease suppression in Astragalus membranaceus. Full article

The external relations of small towns are an important dimension in the regional urban system. However, the “metropolitan bias” in existing studies results in a lack of empirical verification of their characteristics, hindering effective regional policymaking. Applying Central Flow Theory (CFT), mobile phone data, and a multiscale geographically weighted regression (MGWR) model, this study investigates the spatially non-stationary associations between built environment factors and the “city-ness” and “town-ness” of small towns in the Yangtze River Delta. The results show: (1) Enterprise density in metropolitan shadow areas is positively associated with cross-city jobs–housing separation; in peripheral areas, both enterprise density and housing prices exhibit a strong correlation with intra-municipal jobs–housing separation. (2) Middle schools consistently correlate with localized intra-municipal flows, suggesting a plausible spatial anchoring role; around metropolises, medical and commercial facilities link to recreational flows and commuting town-ness, while in distal small towns, medical facilities coincide with intratown jobs–housing balance, and commercial facilities correlate with localized consumption and cross-town employment mobility. (3) Higher road network density corresponds to a shrinking commuting radius near metropolises and intra-municipal intertown interconnection in distal towns, rather than mere external relation channels. This study empirically supports CFT at the small-town scale, explores plausible mechanisms, and informs differentiated planning strategies. Full article

Gallium-based liquid metals have garnered significant attention due to their distinct combination of metallic and liquid behavior at room temperature. This review systematically examines the fundamental properties and advanced multifunctional applications of this class of materials. Key characteristics such as low melting point, excellent fluidity, high electrical and thermal conductivity, and biocompatibility are first highlighted. Subsequently, progress in four major application areas is discussed. In sensing, these materials enable the fabrication of highly compliant and responsive devices capable of monitoring strain, temperature, and electromagnetic fields. Within biomedical engineering, their inherent low toxicity and biocompatibility underpin advances in biosensing platforms, precision drug delivery, and engineered tissue scaffolds. For energy-related applications, they are utilized in batteries and high-efficiency thermoelectric systems for converting heat into electricity. In catalysis, their dynamic and tunable interfaces facilitate efficient carbon dioxide conversion and selective thermocatalytic reactions. This review summarizes current advances in the application of gallium-based liquid metals and provides critical perspectives on future developments and opportunities in this technology. Full article

With the continuous expansion of Pleurotus ostreatus cultivation, substantial quantities of post-harvest spent mushroom substrate (SMS) are generated. Improper disposal of this organic waste poses potential threats to soil health, including contamination and ecological imbalance. Consequently, a rigorous safety assessment is indispensable to support the sustainable and agronomically viable utilization of SMS as a soil amendment. In this study, P. ostreatus SMS was subjected to sterilized and non-sterilized treatments, and a controlled co-culture system integrating P. ostreatus mycelium with wheat was established. This system facilitated a comprehensive evaluation of residual mycelium impacts on wheat growth and development at phenotypic, cytological, and non-targeted metabolomics (LC-MS) levels. Results demonstrated that direct field application of non-sterilized SMS severely compromised wheat performance, inducing root necrosis and significantly reducing grain set. Comparative experiments confirmed that non-sterilized SMS—not its sterilized counterpart—exerted pronounced phytotoxic effects, markedly inhibiting seedling growth and triggering wilting symptoms. To elucidate the temporal dynamics of mycelial interaction, wheat seedlings were inoculated with viable P. ostreatus mycelium and co-cultured for seven days. Under these conditions, the mean root length of the control group (10.82 cm) was approximately threefold that of the treatment group. Histopathological analysis revealed a progressive infection pattern initiating at the root apex and extending basipetally; prolonged exposure ultimately caused complete root system collapse. Scanning electron microscopy further showed extensive mycelial colonization on infected root surfaces, accompanied by characteristic cellular damage—including severe cell wall wrinkling and widespread cell death. LC-MS profiling identified 1867 annotated compounds. Comparative analysis revealed significant dysregulation of secondary metabolism, with 495 metabolites upregulated and 419 metabolites downregulated in the treatment group. Collectively, these findings provide robust evidence that unprocessed P. ostreatus SMS poses tangible agronomic risks upon direct soil application. This study establishes a critical scientific foundation for developing safe, evidence-based protocols for the valorization and integrated management of SMS. Full article

This study systematically elucidated the developmental characteristics and molecular regulatory mechanisms of the testis during the critical period of sexual maturation in Kazakh horses by combining histological observation of one- and two-year-old testicular tissues with transcriptomic sequencing. In the testes of one-year-old horses, no obvious lumen was observed, and the interior is mainly comprising supporting cells and spermatogonia on the basement membrane; in contrast, in the testes of two-year-old horses, the tubular lumen was complete with spermatogonia, spermatocytes, and spermatozoa, indicating that spermatogenic function had approached maturity. Transcriptome profiling identified 979 differentially expressed genes (DEGs), with 209 up-regulated genes, including CYP11A1 and CATSPER2, and 770 down-regulated genes, including CD9. Gene Ontology (GO) annotation indicated primary enrichment of DEGs in biological processes related to multicellular organism development, cell membrane composition, and ion binding. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed significant enrichment of DEGs in the calcium signaling pathway, cell adhesion molecules, and neuroactive ligand–receptor interaction, among other key pathways. Protein–protein interaction (PPI) network analysis further highlighted core genes, including TNF, CATSPER2, and CDH13. Validation by RT-qPCR confirmed the reliability of the RNA-Seq data. Our findings reveal the dynamics of testicular development in Kazakh horses through histological and molecular analyses, thereby providing a theoretical framework and candidate genes to further elucidate regulatory mechanisms and guide genetic improvement in reproductive traits. Full article

Existing energy consumption models suffer from accuracy degradation and limited robustness in complex urban environments due to insufficient consideration of the route spatiotemporal characteristics of electric buses. To address this limitation, a Time-Partitioned Dual-Layer LSTM (TP-D-LSTM) framework driven by cloud data and spatiotemporal characteristics is proposed. First, a spatiotemporal characteristics analysis is conducted on urban bus routes to reveal the underlying traffic flow dynamics. Based on these insights, a time-partitioning strategy is developed to classify the continuous operating data into independent periods while preserving the kinematic continuity of individual trips. Subsequently, a Dual-Layer LSTM (D-LSTM) is constructed to precisely capture the distinct energy consumption mechanisms within each partitioned scenario. Experiments based on real-world cloud-logged data demonstrate that the proposed TP-D-LSTM framework is superior to existing baseline models. By alleviating the limitations of global mixed modeling, the TP-D-LSTM significantly reduces the Root Mean Square Error (RMSE) to 6.15, achieving an improvement of over 50% compared to the D-LSTM, and exhibits remarkable stability under highly volatile traffic conditions. Full article

Subway-hub blocks are critical areas where the pressures of metropolitan populations and environmental quality are closely interconnected. This study constructs a “pressure–context–carrier–response” (PCRC) framework (F1–F7) to systematically reveal the correlations between built-environment characteristics and environmental performance. The results demonstrate that resource allocation (F7) and comprehensive response (F5) display notable “asymmetric differentiation”. The socio-economic environment (F2, F3) considerably influences the concentration of green-space resource allocations (F7) (p < 0.01), with affluent blocks demonstrating a clear advantage in resource distribution. The thermo-ecological composite response (F5), which includes NDVI and LST, demonstrates “statistical convergence” (p = 0.894) across various block types, indicating that resource inputs cannot be linearly transformed into environmental efficiency. This disconnection is ascribed to two physical limitations: firstly, the stochastic nature of spatial distribution (Global Moran’s I ≈ 0) restricts the scale effects of green spaces; secondly, the nonlinear limitations of the physical medium indicate that under conditions of high pressure load (F1) and elevated spatial capacity (F6), the regulatory effectiveness of greening demonstrates a significant diminishing marginal return effect. Therefore, intervention planning must shift from controlling macro-level indicators to optimising micro-level accuracy to address ecological performance constraints in densely populated metropolitan areas. Full article

Accurate classification of rock fracture modes is essential for understanding rock mass instability mechanisms. To address the limitation of traditional acoustic emission (AE) classification methods that treat a single AE signal as a single fracture event, overlooking its composite nature from multiple fracture events and leading to misclassification, this study proposes a novel rock fracture mode classification method based on AE spectral analysis. This study details the development framework, theoretical model, classification criteria, application process, and experimental validation of the new rock fracture mode classification method. Uniaxial compression tests on granite, marble, and limestone, along with rockburst simulation tests on granite, were conducted to validate the classification of fracture modes. In rockburst simulations, shear fracture signals accounted for 48% on average, composite signals 40%, and tensile signals 12%. The method effectively distinguishes multiple fracture events within a single AE signal, accurately classifies fracture modes, and elucidates the dynamic evolution of fracture modes during the rockburst precursor stage, offering significant advantages for rock fracture mode classification and mechanistic insight. Full article