Search Results (38,825)

Background: Ganoderma lucidum triterpenes are bioactive compounds with recognized anti-inflammatory, antitumor, and immunomodulatory properties. This systematic review synthesizes evidence regarding the anti-inflammatory activity of these triterpenes based on studies from the last two decades. Methods: A systematic search was performed in PubMed, Medline, and Embase (2003–2025) for original in vitro and in vivo (non-clinical) studies evaluating G. lucidum triterpene extracts or isolated compounds. Clinical trials, reviews, and multi-species extracts were excluded. The review is registered on PROSPERO (CRD42024510982), and animal study quality was assessed using the SYRCLE Risk of Bias tool. Findings: From over 3000 records, 23 articles were included. Studies utilized diverse models, including macrophages, human PBMCs, and various animal strains (mice, rats, chickens). All studies reported significant anti-inflammatory effects via reduction in pro-inflammatory markers (TNF-α, IL-1β, IL-6), primarily through downregulation of MAPK and TLR-4/NF-κB signaling pathways. Meta-analysis of in vitro data confirmed significant reductions in NO levels (−3.29 [95% CI: −5.21, −1.37]; p = 0.0008), IL-6 (−3.51 [−4.73, −2.29]; p < 0.00001), and TNF-α (−2.20 [−2.93, −1.48]; p < 0.00001). Similar anti-inflammatory profiles were observed in vivo across hepatic and splenic tissues. Interpretation: Evidence consistently demonstrates the potent anti-inflammatory activity of G. lucidum triterpenes, highlighting their potential as therapeutic candidates for inflammatory diseases. However, the structural complexity and isomer diversity of these compounds remain significant barriers to pharmacological standardization. Future research must prioritize clinical translation by investigating compound synergism, bioavailability, and long-term toxicity profiles, which were notably absent in current non-clinical literature. Full article

Earthwork operations constitute a substantial share of infrastructure project costs and are critical to overall project efficiency. However, the construction industry still relies on conventional approaches and there is a lack of integrated fleet management systems for collaboratively working equipment. While telematics is widely used in other industries, its applications to monitor the complex interactions between excavators, dump trucks, and dozers in real time remain limited. This study proposes an intelligent fleet monitoring system that utilizes only satellite navigation data (GNSS) to analyze the real-time productivity of multiple earthwork machines without relying on additional sensors, such as IMU or accelerometers, thereby eliminating the need for separate measurement procedures. A lightweight site configuration step is required to define the work area/loading/dumping geofences on an existing site map. This research provides novel developed algorithms that facilitate a real-time productivity assessment for several earthwork equipment and provide planning-level recommendations for equipment deployment combinations. Dedicated motion classification algorithms were developed for excavators, dump trucks, and dozers to distinguish activity states, to compute working and idle times, and to quantify operational efficiency. The system integrates a web-based e-Fleet Management platform and a mobile e-Map application for visualization and equipment optimization. Field validation was conducted on two active earthwork projects to evaluate accuracy and feasibility. The results demonstrate that the developed algorithms achieved classification and productivity estimation errors within 2.5%, while enabling optimized equipment combinations and improved cycle time efficiency. The proposed system offers a practical, sensor-independent approach for enhancing productivity monitoring, real-time decision-making, and cost efficiency in large-scale earthwork operations. Full article

Urban flood disaster management is an interdisciplinary field that integrates hydrology, geology, engineering, and urban planning, with prediction, assessment, and optimization serving as its core components. However, a comprehensive and systematic synthesis of recent developments in this domain remains limited, constraining both theoretical understanding and practical advancement. To address this gap, this study conducts an in-depth analysis of urban flood management research as a systematic review, with a particular focus on advances in prediction, assessment, and optimization. Utilizing a multistep holistic review, combining bibliometric and scientometric analysis with structured literature categorization, the research critically examines and synthesizes relevant findings. This study analyzed 166 research papers related to urban flood management within the Web of Science database. Through co-citation and keyword co-occurrence analyses, five dominant research dimensions are identified: physics-based simulation methods, data-driven approaches, risk assessment tasks, optimization strategies, and miscellaneous emerging topics. Based on these insights, we propose a task-oriented framework that systematically integrates prediction, assessment and optimization across the four phases of disaster management: mitigation, prevention, emergency response and recovery. This framework aids scholars and practitioners in understanding and implementing effective techniques and strategies. The study’s findings shed light on key trends and potential future directions, providing a roadmap for further exploration of urban flood management and guiding professionals in related fields. Full article

Monitoring the development of increasingly essential collaborative skills at the individual level within a classroom context requires effective, easy-to-use, and quick measurement tools. These tools should provide global feedback on the skillset rather than reflecting performance in a single group task. A self-rated questionnaire is a beneficial option for this purpose. The aim of our research is to develop a self-rated scale for adolescents, the Collaborative Skills Scale (CoSS), which provides a global assessment of students’ teamwork competence. Additionally, using our assessment instrument, we seek to explore what patterns adolescents’ self-ratings show to be connected to their collaborative skills. A total of 2128 Grade 8 students participated in our online data collection. The Collaborative Skills Scale was developed based on the collaborative problem-solving model of the ATC21S project. Confirmatory factor analyses yielded a reliable and structurally valid 18-item scale (Cronbach’s α = 0.90; χ² = 1802.83, df = 132, p < 0.01; CFI = 0.944; TLI = 0.935; RMSEA = 0.077; SRMR = 0.031), which can provide educational practitioners with an effective formative assessment tool for monitoring and supporting the development of teamwork skills. Ideally, it should be utilized in combination with other instruments, such as peer- or teacher-rated scales, to ensure a comprehensive understanding of students’ collaborative skills. In line with previous findings, students tended to rate their teamwork skills above average. The implications of this potentially biased self-evaluation among adolescents in terms of collaborative competence are discussed. Full article

The use of instruments for recording neurophysiological metrics is increasingly prevalent in natural settings, driven by advances in portability, reduced invasiveness, and the advantages these technologies offer for objective assessment of cognitive processes. A key application is the investigation of cognitive processes underlying human learning. In this context, the use of electroencephalography (EEG) in educational settings has grown in recent years. This systematic review examines how EEG has been utilized over the past decade to study teaching and learning processes in higher education. Its objectives were to identify the purposes for which EEG has been employed, its integration with other instruments, the cognitive processes analyzed, and the main findings reported. Bibliographic sources included Scopus and Web of Science databases. Results indicate that EEG has been primarily used to investigate attention, memory, and cognitive load, often combined with other neurophysiological and behavioral instruments. This integration provides objective insights into learning while highlighting methodological limitations and the need for standardized approaches. Despite variations in study designs, devices, and analytical methods, EEG demonstrates substantial potential for exploring cognitive processes in both face-to-face and virtual learning environments. In conclusion, EEG is an effective tool for investigating learning-related cognitive processes in higher education, providing objective data to guide future research, and the development of innovative educational programs. This review offers a comprehensive overview of current research, supports the design of evidence-based educational strategies, and lays the groundwork for future studies aiming to enhance learning outcomes through neurophysiological methods. Full article

The elastic support stiffness coefficient $k_R$ of opposing horizontal struts constitutes a critical parameter in the design of strutted retaining structures for deep excavations. The determination of the fixed-point adjustment coefficient $\lambda$ serves as a fundamental prerequisite for the quantitative assessment of this stiffness coefficient. To identify the fixed-point location and establish a computational approach for $\lambda$, the endpoint displacements of opposing horizontal struts are classified into four distinct scenarios. For each scenario, the relationship between the lateral earth pressures on both sides of the excavation is derived, the support mechanism of the internal strut is elucidated, and the corresponding fixed-point locations of the struts are determined. Utilizing the response curve between the support-point displacement of the retaining structure and the lateral earth pressure, and adhering to the principle of linearization, analytical formulas for $\lambda$ under the four scenarios are formulated. The proposed method is employed to compute and evaluate the fixed-point adjustment coefficient of the opposing horizontal struts in a case study drawn from the literature, with the results rigorously compared against the existing published data. Furthermore, the $\lambda$ values for opposing horizontal struts in a metro station excavation project are computed and contrasted with values back-calculated from monitored horizontal displacements of the retaining structure. The findings demonstrate that the proposed method for determining $\lambda$ is both computationally efficient and practically applicable. The derived $\lambda$ values can be effectively used to predict internal forces and deformations in retaining structures for asymmetrically loaded deep excavations. This research offers substantial theoretical insights and practical implications for the scientifically informed design and construction of deep excavation support systems. Full article

Lignin, the most abundant renewable source of aromatic compounds, plays a pivotal role in advancing sustainable biorefineries and reducing dependence on fossil resources. Recent progress in integrated lignin valorization pathways has unlocked opportunities to convert this complex biopolymer into high-value chemicals, materials, and energy carriers, despite its structural heterogeneity and recalcitrance posing major challenges. This review highlights the significant advancements in depolymerization strategies, including catalytic, oxidative, and biological approaches, which are reinforced by innovations in catalyst design and reaction engineering that enhance selectivity and efficiency. It also discusses emerging technologies, such as hybrid chemo-enzymatic systems, solvent fractionation, and continuous-flow reactors, for their potential to improve scalability and sustainability. Furthermore, this review examines the integration of lignin valorization with upstream pretreatment and downstream recovery, emphasizing process intensification, co-product synergy, and techno-economic optimization to achieve commercial viability. Despite these developments, critical gaps remain in understanding the molecular complexity of lignin, developing universally applicable catalytic systems, and optimizing economic and environmental performance. To guide future research, it poses two key questions: how to design catalysts for selective depolymerization across diverse lignin sources, and how to configure biorefineries for maximum lignin utilization while ensuring sustainability? Addressing these challenges will be essential for lignin’s role in next-generation biorefineries and a circular bioeconomy. Full article

Spinal Cord Injury (SCI) rehabilitation is undergoing a transformative shift with the emergence of new treatment strategies. Historically, treatment options were limited, and few offered meaningful recovery. Recent work in human models has shown that neuromodulation specifically with spinal cord epidural stimulation (SCES) paired with task-specific training (TsT) can partially restore motor function such as the ability to stand, step, and perform volitional movements. Despite these advances, the recovery has been shown to plateau even with the combination of therapies. The recovery process typically leads to partial rather than complete restoration of function. This limitation arises because current approaches primarily reactivate existing circuits rather than repair the disrupted pathways. Scar tissue and loss of descending and ascending connections remain major barriers to full recovery, restricting the transmission of neural signals. We argue that the next phase of research should be a synergistic strategy building upon the successes of neuromodulation and TsT while incorporating a regenerative therapy such as stem-cell-based interventions. Whereas neuromodulation and task-specific training increases excitability and reorganizes existing networks, stem cells have the potential to repair structural damage and re-establish communication across injured regions or facilitating the establishment of dormant pathways. The future of SCI recovery relies on multi-modal synergistic interventions that are likely to maximize long-term functional outcomes. In the current perspective, we summarized the basic findings on applications of SCES on restoration of sensory-motor functions. We then projected on current interventions on utilizing stem cell therapy intervention. We highlighted the outcomes of randomized clinical trials, and the major barriers for considering the synergistic approach between SCES and stem cell intervention. We are hopeful that this perspective may lead to roundtable scientific discussion to bridge the gap on how to conduct numerous clinical trials in the field. Full article

This study presents a comprehensive analysis of the marginal capacity credit of utility-scale solar and wind power in South Korea using an effective load-carrying capability-based methodology. This research makes three key contributions distinguishing it from previous works. First, the study introduces the concept of marginal capacity credit to quantify the contributions of newly added renewable energy capacities in power systems that already host significant solar and wind power capacities. Second, it evaluates the interaction effects between solar and wind power, revealing their complementary potential in enhancing system adequacy across different penetration levels. Third, it investigates how integrating energy storage systems mitigates intermittency and aligns renewable generation with peak demand. Results indicate that solar power provides relatively high marginal capacity credit at low penetration levels due to its alignment with peak demand, but its contribution declines as deployment expands and peak hours shift. Conversely, wind power maintains more stable marginal capacity credit and eventually surpasses solar power at higher penetration levels due to its broader generation profile. Storage integration notably enhances marginal capacity credit for both resources, with solar power gaining greater benefit from optimized charging and discharging strategies. These findings provide practical guidance for improving power system reliability and capacity planning under growing renewable penetration. Full article

To address the urgent need for high-fidelity motion data for validating navigation algorithms for Unmanned Underwater Vehicles (UUVs), this paper proposes a data generation method based on a parametric motion model. First, based on the principles of rigid body dynamics and fluid mechanics, a decoupled six-degrees-of-freedom (6-DOF) Linear and Angular Acceleration Vector (LAAV) model is constructed, establishing a dynamic mapping relationship between the rudder angle and speed setting commands and motion acceleration. Second, a segmentation–identification framework is proposed for three-dimensional trajectory segmentation, integrating Gaussian Process Regression and Ordering Points To Identify the Clustering Structure (GPR-OPTICS), along with a Dynamic Immune Genetic Algorithm (DIGA). This framework utilizes real vessel data to achieve motion segment clustering and parameter identification, completing the construction of the LAAV model. On this basis, by introducing sensor error models, highly credible Inertial Measurement Unit (IMU) data are generated, and a complete attitude, velocity, and position (AVP) motion sequence is obtained through an inertial navigation solution. Experiments demonstrate that the AVP data generated by our method achieve over 88% reliability compared with the real vessel dataset. Furthermore, the proposed method outperforms the PSINS toolbox in both the reliability and accuracy of all motion parameters. These results validate the effectiveness and superiority of our proposed method, which provides a high-fidelity data benchmark for research on underwater navigation algorithms. Full article

The development of coal resources has created a large number of underground mined-out spaces, which can be utilized for cross-seasonal thermal storage through underground reservoirs to achieve seasonal heat storage. However, there is currently limited research on the cross-seasonal thermal storage capabilities and thermal storage performance evaluation of coal mine underground reservoirs. This study aims to evaluate the operational stability and long-term performance of a Coal Mine Underground Reservoir Energy Storage System (CMUR-ESS) under realistic geological conditions of the Shendong Coalfield. A multi-physics coupling model, integrating thermal-fluid processes, was developed based on the actual structure of the No. 5-2 coal seam goaf in the Dalinta Mine. Numerical simulations were conducted over five annual cycles, each comprising injection, storage, production, and transition stages. Results demonstrate that the system achieves progressive thermal accumulation, with the volume fraction of water above 70 °C increasing from 75.0% in the first cycle to 88.9% by the fifth cycle at the end of the storage stage. Production temperatures also improved, with peak and final temperatures rising by 6.2% and 6.8%, respectively, after five cycles. The analysis confirms enhanced heat retention and reduced thermal loss over time, indicating robust long-term stability and sustainability of the CMUR-ESS for seasonal energy storage applications. The results of this study can provide a reference for the design and evaluation of CMUR-ESS. Full article

Crushing is a critical step in the efficient utilization of quasi-brittle materials such as ores and solid wastes. During this process, materials undergo fracture, and the product particles are ejected, carrying significant kinetic energy. This study investigates typical quasi-brittle materials—concrete and quartz glass—by conducting impact crushing tests using a drop-weight apparatus under varying contact modes and input energy levels. High-speed camera was employed to capture the fracture patterns of the materials and the trajectories of the ejected particles, enabling the calculation of kinetic energy during crushing. The results indicate that under point contact loading, both kinetic energy and its proportion increase significantly with rising input energy. In contrast, under surface contact loading, the kinetic energy and its proportion exhibit minimal change as input energy increases. The average ejection velocity of particles from quartz glass specimens during crushing was 6.28 m/s, which is 2.21 times that of concrete specimens. Moreover, the average proportion of kinetic energy in quartz glass crushing was 5.049%, approximately 14.43 times greater than that in concrete. Enhancing material toughness and adopting surface contact loading help reduce both the kinetic energy and its proportion during crushing. This research contributes to minimizing kinetic energy loss and improving the efficiency of energy utilization in crushing processes. Full article

Research has demonstrated that incorporating nitrate into animal feed can effectively decrease methane production in ruminants, though its impact on carcass characteristics and meat attributes in Hu sheep requires further investigation. This experiment examined how a dietary inclusion of 3% calcium nitrate (CN) influenced slaughter parameters, meat properties, gut microbial populations, and host gene regulation in Hu sheep. The study involved sixty healthy male Hu sheep aged 120 days with comparable body weights (31.11 ± 3.39 kg), randomly allocated into two groups: a control group receiving standard feed (CON) and a CN-supplemented group. The trial lasted 60 days, including a 15-day adaptation period and a 45-day formal trial period. They were housed individually and fed twice daily (at 8:00 and 18:00). The findings revealed that CN supplementation notably reduced the water loss rate in the longissimus dorsi muscle (LD), elevated meat color brightness, and enhanced the proportion of polyunsaturated fatty acids (PUFA), particularly n-6 PUFA, along with the n-3/n-6 PUFA ratio. Conversely, it reduced the levels of saturated fatty acids such as myristic acid (C14:0) and oleic acid (C18:1n9t). Additionally, the treatment boosted ruminal Ammoniacal nitrogen content and total short-chain fatty acid production, thereby contributing to energy metabolism in the animals. Microbiological examination demonstrated that CN supplementation led to a decrease in Fibrobacterota and Methanobrevibacter populations within the ruminal environment, while promoting the growth of Proteobacteria in the duodenal region. The gene expression profiling of digestive tract tissues showed an increased activity in nitrogen processing genes (including CA4) and oxidative phosphorylation pathways (such as ATP6), indicating an improved metabolic efficiency and acid–base homeostasis in the host animals. These findings demonstrate that CN-enriched diets enhance the carcass characteristics of Hu sheep by modifying intramuscular lipid profiles through gastrointestinal microbial community restructuring and metabolic pathway adjustments. Such modifications affect energy utilization and acid–base equilibrium, ultimately impacting muscle characteristics and adipose tissue distribution, presenting viable approaches for eco-friendly livestock farming practices. Full article

Although there are theoretically expected associations between problematic smartphone use (PSU) and materialism, there is a lack of research that examines these associations using a longitudinal design, focusing on both within-person and between-person effects. Clarifying this relationship may inform interventions for these related conditions. Accordingly, data from three annual waves collected from a substantial group of Chinese adolescents (N = 3029, M_age = 12.26 ± 2.36, male: 50.00%) were used to assess within-person and between-person effects in the association between PSU and materialism. Traditional cross-lagged panel models were utilized to analyze the data, which consistently showed reciprocal positive associations between PSU and materialism across all waves. In contrast, the random intercept cross-lagged panel model revealed that PSU and materialism exhibited reciprocal associations over time at the between-person level. However, no significant cross-lagged linkage was observed between PSU and materialism at the within-person level. These findings enhance our understanding of the temporal dynamic relationship between PSU and materialism and underscore the necessity to disaggregate within-person and between-person effects to elucidate the nature of the longitudinal associations between PSU and materialism. The study also has implications for theoretical and practical understanding. Full article

Understanding how plants respond to water limitation is increasingly important under accelerating climate change. Lycoris aurea, a widely distributed ornamental and medicinal bulbous plant, frequently inhabits environments with fluctuating soil moisture, yet its molecular drought-response mechanisms remain largely unexplored. In this study, we investigated L. aurea growing under field-based, in situ soil moisture regimes, comparing low (~20% soil water content) and high (~40% soil water content) conditions. We combined soil property assessments with high-resolution transcriptomic and untargeted metabolomic profiling to characterize the adaptive responses of bulb tissues under contrasting soil water conditions. Although total nitrogen, phosphorus, and potassium levels were comparable across treatments, soil moisture, representing the primary contrasting field condition, and soil pH, a correlated environmental factor, were significantly associated with variation in gene expression and metabolite accumulation (p < 0.05, n = 3). Transcriptome analyses identified a total of 1034 differentially expressed genes enriched in pathways related to amino acid metabolism, cuticle formation, cell wall modification, and osmotic adjustment. Metabolomic analysis identified a total of 1867 differentially expressed metabolites belonging to carboxylic acids and prenol lipids, showing alterations involved in amino acids, lipids, phenolic acids, and alkaloids associated with osmoprotection, membrane stabilization, and structural reinforcement under low soil moisture. Pathway-based integration analysis highlighted four core pathways, including “alanine, aspartate and glutamate metabolism” (p = 0.00371) and “cutin, suberine and wax biosynthesis” (p = 0.00873), as central hubs linking transcriptional regulation with metabolic reconfiguration. Gene-metabolite-soil correlation networks further demonstrated that drought adaptation arises from tightly coordinated biochemical and structural adjustments rather than shifts in nutrient acquisition. Together, this species-specific study provides a comprehensive multi-omics framework for understanding drought tolerance in L. aurea, reveals key molecular targets associated with plant resilience, and offers potential targets and insights for the conservation of drought-resilient Lycoris cultivars. Full article