Search Results (6,947)

Accurate stem-volume estimation is fundamental for urban tree inventory and management, but equations developed for forest-grown trees may not be directly suitable for open-grown urban trees with altered stem form and height–diameter relationships. This study developed species-specific, model-assisted stem-volume equations for four dominant urban broad-leaved species in Beijing, China: Quercus mongolica, Sophora japonica, Ginkgo biloba, and Populus davidiana. A total of 2679 standing trees from 535 plots were used for model development and evaluation. The diameter at breast height and ground diameter were field-measured, whereas tree height was obtained as a photogrammetry-derived non-destructive measurement using a handheld tree-measurement superstation. Bivariate DBH–height models, DBH-based linked models, and ground-diameter-based chained models were fitted using weighted nonlinear least squares. Model performance was assessed using validation statistics, 10-fold cross-validation, Monte Carlo uncertainty propagation, and an independent destructive reference dataset of 55 felled trees with section-measured stem volume. Across species, the bivariate models performed best, with mean percent standard errors of 8.68%–16.24%, compared with 9.76%–20.25% for DBH-based linked models and 15.13%–28.56% for ground-diameter-based models. Destructive reference validation showed acceptable agreement within the available validation dataset, with relative RMSE values of 2.30%–5.03% and relative bias values of 0.51%–2.51%. Monte Carlo simulation indicated species-specific propagation of photogrammetric height error, with the lowest average volume fluctuation in Ginkgo biloba. These results suggest that handheld photogrammetry combined with species-specific modelling provides a practical and uncertainty-aware basis for urban stem-volume estimation. This study directly estimates stem volume rather than biomass or carbon stock, and the equations may support future biomass- and carbon-related assessments when combined with appropriate conversion parameters. Full article

Graphite nozzles remain the dominant choice for small hybrid and solid rocket motors operating on laboratory and university budgets, owing to their low cost, ease of machining, and rapid turnaround during iterative design campaigns. These same programs, however, must contend with the fact that graphite erodes through coupled thermochemical and mechanical mechanisms when exposed to the oxidizing species generated by high-energy propellant combustion, and the resulting throat-area growth fundamentally alters the time histories of chamber pressure, thrust, and delivered specific impulse. This paper presents a nozzle-erosion reconstruction model that extracts the time-resolved throat area from coupled thrust and chamber-pressure measurements using the thrust coefficient relationship, scales the reconstructed area history against pre- and post-test throat measurements, identifies the onset and rate of erosion, and accounts for variable sensor lag between the thrust-stand and pressure-transducer signal chains. The model is exercised on two complementary sets of laboratory-scale GOX/ABS hybrid hot-fire data that together span roughly two orders of magnitude in total throat-area change and peak chamber pressures from 0.5 to 3.4 MPa: a controlled three-operating-point campaign conducted in support of the NASA Plume-Surface Interaction (PSI) program, and a set of higher-pressure firings from the laboratory development series in which the technique was matured. Reconstructed erosion-onset times, erosion rates, and total throat-diameter change are reported for each firing, the reconstruction accuracy is characterized as a function of erosion magnitude. A correlation of graphite erosion with chamber pressure is examined across the combined envelope. The results demonstrate the robustness of the reconstruction technique and provide a reusable framework for post-test reconstruction of transient nozzle geometry in rocket-engine ground testing. Full article

Blockchain-assisted off-chain storage for IoT must simultaneously manage low-latency tiered data placement, trusted and dynamic on-chain mapping, migration consistency, and failure recovery—four concerns that existing designs address in isolation. Tiered storage systems optimize placement without modeling the scalable coordination cost of keeping object–location bindings trustworthy, while blockchain-metadata studies assume static storage topologies with no dynamic tier migration. This paper presents a scalable and trusted metadata-coordinated tiered off-chain storage framework, which bridges traditional trust systems (e.g., legacy authentication) with blockchain networks powered by Proof of Capacity (PoC) consensus. In this framework, adaptive heat-driven placement, dynamic on-chain mapping evolution with batched commitment, migration-aware redirect control, and rollback-safe recovery operate as a single coordinated workflow, with the five-stage write–verify–commit–redirect–retire pipeline acting as a lightweight coordination protocol that maintains ordered and atomic state transitions under message loss, out-of-order delivery, and single-node failures. The distinctive contribution lies in the framework’s coupled control: every placement decision propagates through a verifiable metadata path that can be audited and, when necessary, rolled back. Simulation across multiple workload patterns shows that the proposed method reduces average access latency by 28% and raises the hot-tier hit ratio from 0.19 to 0.65 relative to a dynamic baseline without trusted mapping coordination under the simulated registry write cost. To achieve high-throughput mapping operations, batched on-chain commitment cuts metadata transactions by 50× at the cost of a tunable mapping freshness delay. The framework scales from 1 k to 50 k managed objects, effectively managing tens of millions of bytes of data (10+ MB scale) without disproportionate overhead growth; beyond this scale, hot-tier capacity rather than coordination becomes the dominant bottleneck, and smarter predictive placement becomes the natural next lever. All tested fault types achieve 100% rollback success with sub-millisecond local data plane interruption; audit-visible recovery depends on the assumed chain finality delay and, for heavily regulated IoT domains, such as finance and healthcare, should be treated as the operationally binding recovery time objective. These results, together with extended evaluations—including asymmetric write latency stress, coordination ablation, tail latency analysis, and benefit–complexity assessment—provide quantitative evidence that scalable, dynamic mapping coordination can be integrated into tiered off-chain data management at an acceptable and measurable operational cost under the simulated configuration. Full article

Long-term energy system planning depends on projections of future wind turbine characteristics, yet existing approaches rely on either costly expert elicitation or deterministic trend extrapolation without formal uncertainty quantification. We present a Bayesian logistic framework that models the temporal evolution of hub height, rotor diameter, and specific power as physically constrained growth and decay processes, producing full posterior predictive distributions via Markov Chain Monte Carlo sampling. The framework is validated across three major onshore wind markets: Austria (534 turbines, 2000–2025), Germany (31,202 turbines, 1988–2026), and the United States (71,457 turbines, 1986–2025); spanning different market structures, regulatory environments, and data availability. Systematic benchmarking against linear, polynomial, and maximum-likelihood alternatives demonstrates superior hindcast performance, particularly for long-range projections where physical saturation constraints become relevant. Prior sensitivity analysis reveals that posteriors are robust for data-rich regions but honestly reflect prior influence for small datasets, identifying where expert knowledge is essential. We extend the framework to climate-aware energy yield estimation by propagating turbine posteriors through synthetic power curves and site-specific wind resource projections under SSP2-4.5 and SSP5-8.5, decomposing the total uncertainty into technology and climate components. When climate uncertainty is measured by scenario spread alone, technology uncertainty dominates. However, accounting for the full inter-model spread across 13 CMIP6 global climate models reveals that climate uncertainty becomes substantial (14–56%) and region-dependent, underscoring that both sources require explicit quantification. The open-source pipeline is designed for direct adoption in energy system planning workflows. Full article

To address the difficulty in controlling the filtration performance of water-based drilling fluids under high-temperature and high-salinity conditions during the drilling of deep and ultra-deep wells, a salt-responsive micro-crosslinked polymer gel filtration loss reducer, designated LZX, was developed. The synthesis employed 2-acrylamido-2-methylpropane sulfonic acid (AMPS), N,N-dimethylacrylamide (DMAA), dimethyldiallylammonium chloride (DMDAAC), and a betaine monomer containing an unsaturated double bond as monomers, with polyethylene glycol diacrylate (PEGDA) introduced as a crosslinker. Experimental results showed that the product structure matched the design expectations, and the thermal decomposition temperature of the main molecular chain exceeded 290 °C, indicating good thermal stability. At 220 °C under saturated salt conditions, a dosage of 2.5 wt% LZX maintained the API filtration loss at 5.8 mL and the HPHT filtration loss at 28.6 mL. Comparative experiments at different temperatures demonstrated that LZX exhibited superior filtration control performance compared to the commercial high-temperature filtration reducer Driscal Temp and Driscal D. The micro-crosslinked structure of LZX enhanced the rigidity of the molecular chains, raising the upper limit of its thermal resistance. Rheological and viscosity-average molecular weight measurements revealed that LZX exhibited typical antipolyelectrolyte behavior in high-salinity environments—the molecular chains tended to extend and the filtration reduction capability was accordingly maintained—preliminarily achieving a functional transition from passive salt tolerance to active salt responsiveness. LZX is expected to support the construction of high-performance water-based drilling fluids with high temperature and high salt resistance for future deep-earth drilling. Full article

In recent years, seismic activity in the southern Sichuan region has increased significantly. Frequent moderate-to-strong earthquakes have caused severe building damage, casualties, and substantial economic losses, making regional seismic risk increasingly prominent. Based on historical seismic catalogs, geological settings, macroseismic intensity data, and strong motion records, this study systematically analyzes regional seismicity, spatial distribution, and strong ground motion characteristics, and quantitatively investigates the distribution and variation of seismic intensity. It further explores the impacts of earthquakes on various building structures, geological disaster chains, lifeline engineering, and human safety, as well as the underlying damage mechanisms. Finally, targeting the widely existing brick masonry structures, this paper proposes cost-effective and easy-to-implement seismic reinforcement measures combined with typical failure modes and casualty causes. The results provide a scientific basis for seismic disaster prevention planning, engineering seismic practice, and risk management in southern Sichuan and comparable regions. Full article

Against the backdrop of frequent global shocks and increasingly complex supply chain networks, supply chain disruption risk exposure has become a major challenge affecting firms’ operational stability and sustainable competitive advantage. Meanwhile, generative artificial intelligence is being increasingly embedded in business operations and has demonstrated strong application potential in information processing, risk identification, and decision support. Based on data from Chinese A-share listed firms from 2017 to 2024 and using text measures based on Management Discussion and Analysis (MD&A) disclosures of Generative AI application and supply chain disruption risk exposure, this study examines the relationship between Generative AI application and corporate supply chain disruption risk exposure, and further explores the channels through which this relationship may operate from the perspective of risk governance transformation. The results show that Generative AI application is significantly associated with lower corporate supply chain disruption risk exposure, and this relationship remains robust across a series of robustness checks and supplementary endogeneity analyses. Channel analyses suggest that this relationship may be related to firms’ risk governance transformation, mainly reflected in enhanced risk identification capability, improved resource allocation capability, and strengthened collaborative response capability. Heterogeneity analyses show that this association is more pronounced among firms facing higher environmental uncertainty, manufacturing firms, and firms located in cities with lower entrepreneurial vitality. This study provides text-based firm-level evidence for understanding the relationship between Generative AI application and supply chain risk governance, and offers managerial implications for firms seeking to promote scenario-based Generative AI application and enhance supply chain resilience and risk governance capability. Full article

Grain moisture content is a key variable for safe storage, drying control, and quality management. Microwave sensing is attractive because water strongly modulates the complex relative permittivity (ε* = ε′ – jε″) of granular agricultural products, thereby shaping broadband scattering-parameter spectra. This study presents a meter-referenced feasibility evaluation of an interpretable S-parameter–permittivity–moisture chain using a vector network analyzer over 2–18 GHz. Wheat, maize, and mung bean were prepared at six moisture levels, and the moisture values were referenced to two commercial grain moisture meters (MC_ref) to represent rapid on-site benchmarking rather than absolute gravimetric moisture determination. Therefore, the reported errors should be interpreted as commercial-meter-referenced calibration indicators rather than absolute gravimetric moisture prediction accuracy. Two free-space configurations were compared on the same platform: a two-horn transmission setup under controlled packing and a metal-backed double-pass reflection setup intended to represent single-sided access under loose bulk packing. After SOLT calibration and empty-holder background normalization, ε′ and ε″ were retrieved via complex-domain nonlinear least-squares fitting of physics-based slab models to measured S21 spectra. The results show that moisture-dependent dielectric responses were grain- and configuration-dependent. In particular, ε″ generally provided a more robust moisture-sensitive feature in the free-space transmission configuration, whereas the optimal single-parameter predictor in the metal-backed configuration differed among grains. A mid-band frequency window of approximately 8–16 GHz provided more stable inversion by avoiding low-frequency coupling artefacts and high-frequency signal-to-noise degradation. The metal-backed configuration preserved moisture trends but yielded lower effective ε′ values, likely due to increased air fraction under loose packing. These results indicate that packing state, grain type, and frequency-window selection are critical factors for transferring microwave moisture calibration from laboratory measurements to practical grain-handling scenarios. Full article

Exhaust emission assessment of heavy-duty diesel engines is commonly based on complementary steady-state and transient procedures, represented by the World Harmonized Steady-State Cycle (WHSC) and the World Harmonized Transient Cycle (WHTC). However, under transient operation, tailpipe NO_x and CO₂ signals cannot be directly assigned to instantaneous engine operating states because the measured response is affected by transport delay, analyser dynamics, and signal dispersion within the measurement chain. This paper proposes a machine-learning-assisted dynamic synchronization framework for aligning engine operating signals with tailpipe emissions under transient conditions. The method uses actual engine torque as the primary dynamic reference and determines local effective alignment between emission readings and the engine operating states that generated them. The synchronized data are then evaluated using an XGBoost-based modelling approach to assess whether emission characteristics obtained from WHSC steady-state operation can be transferred to WHTC transient operation. The results show that the proposed synchronization improves the physical consistency of transient emission data and provides a more reliable basis for comparing stationary and dynamic test outcomes. The transferability analysis indicates good predictive consistency for CO₂, whereas NO_x shows only partial transferability, reflecting stronger transient sensitivity and more complex formation dynamics. The proposed framework supports intelligent emission-data preprocessing, data-driven interpretation of heavy-duty engine tests, and assessment of the representativeness of steady-state tests under transient operating conditions. Full article

Field-Programmable Gate Array (FPGA) technology allows for the creation of unique hardware implementations based on mass-produced chips. The process of project prototyping for such systems using Hardware Description Languages (HDLs) remains complex, even with modern tools. The comparison of HDL coding styles, for example, a behavioral case statement against a structural binary-tree decomposition, shows that the choice is capable of affecting post-implementation timing and area. The performed study, using the open-source yosys/nextpnr toolchain, shows that the validity of such a comparison is decided by the fabric domain. Logic that falls through to generic Look-Up Table (LUT) mapping is governed by the mapper’s heuristic fixed point rather than by source intent: on the crossbar, the behavioral and structural netlists become identical in cell composition; on the priority encoder, the verdict reverses; and on the barrel shifter, the LUT area collapses, so the comparison does not isolate the coding-style variable. It was measured that the keep_hierarchy attribute restores a meaningful comparison at ~17% LUT cost (N = 8) and provides a structural invariant to the ABC mapper variant, but the behavioral result is mapper-sensitive and the N = 4 verdict reverses under the legacy -noabc9 mapper (Cohen’s d from +2.4 to −1.6). By contrast, logic that involves a dedicated primitive before LUT mapping—an adder bound to the carry chain or a multiplier bound to a DSP block—yields source-meaningful verdicts that do not reverse with a mapper. Replication on a second fabric (Lattice iCE40) confirms that this behavior is fabric- rather than vendor-specific. The main contribution of this work is the proposed first fabric-domain characterization of synthesis canonicalization as a methodological hazard for cross-HDL FPGA studies on open-source toolchains, which identifies the two-phase synthesis mechanism that delimits it and supplies a decision rule (inspect post-synthesis composition) to identify whether a given comparison is susceptible. Full article

Aging is a systemic degenerative process that can lead to functional decline in multiple organs, such as skeletal muscles and the heart, and accelerates the overall aging process through organ-to-organ interactions mediated by metabolites such as short-chain fatty acids (SCFAs). SCFAs serve as a crucial link connecting intestinal health and anti-aging, and their levels and functions undergo significant changes with aging. However, current research lacks understanding of the downstream molecular mechanisms of SCFAs, and intervention methods are mostly limited to simple regulation. This article clarifies the intrinsic relationship between SCFAs and aging from a systemic perspective, analyzes their regulatory mechanisms through key signaling pathways, examines their roles in tissue barrier protection, the improvement of metabolic disorders, and immune regulation, and summarizes their therapeutic potential and diversified intervention strategies in aging-related diseases. The detailed molecular mechanisms by which SCFAs regulate aging are still unclear, and there are no precise intervention plans for different aging stages and organ damage. In the future, we need to utilize techniques such as single-cell sequencing and organ models to explore the regulation of aging cell fates, providing support for the development of metabolite-mediated personalized anti-aging intervention measures. Full article

As the largest inter-basin water diversion project in eastern China, the Eastern Route of China’s South-to-North Water Diversion Project (ER-SNWDP) plays a crucial role in alleviating water shortages and ensuring regional ecological security. However, large-scale water diversion that uses natural lakes as impounded lakes across different basins has impacted on the structure and function of the original ecosystems. To explore the changes in the food web and ecosystem structure of the impounded lakes during different operation periods of the ER-SNWDP, we constructed Ecopath models for Hongze Lake in 2010–2011 (pre-operation), 2017–2018 (initial operation), and 2023–2024 (operational period). Our results showed that the trophic energy flow in Hongze Lake was dominated by the detrital food chain, with the highest trophic level ranging from 3.06 to 3.50. Energy flows at trophic levels I and II accounted for a high proportion of the total throughput, and the interactions between trophic levels were relatively simple, indicating that Hongze Lake is approaching a mature ecosystem. Compared with the pre-operation period, the average trophic level, food chain length, and energy conversion efficiency of Hongze Lake declined during the initial operation period, but rebounded during the operational period, though still remaining lower than the pre-operation period. Ecosystem stability followed a similar trajectory: the total primary production/total respiration (TPP/TR) and the system omnivory index (SOI) indicated that ecosystem maturity decreased during the initial operation and increased during the operational period. Fishing activities had negative effects on most functional groups during the pre-operation and initial operation periods, whereas the negative effects from zooplankton and non-native species groups increased during the operational period. Based on changes in the food web structure and ecosystem of Hongze Lake across different water diversion periods, we suggest that the management of Hongze Lake should establish precautionary fishing management measures targeting the effects of filter-feeding functional groups and non-native species, optimize the species and quantities of restocking initiatives, prioritize the protection of critical habitat integrity, and implement long-term ecological monitoring. Full article

Background: Insomnia and stress-related sleep disorders are increasingly recognized as systemic conditions linked to the microbiota–gut–brain axis (MGBA). With growing clinical interest in natural products that modulate the gut environment, this systematic review evaluates the efficacy and mechanisms of non-pharmacological interventions, specifically probiotics, prebiotics, dietary indices, and botanicals, in alleviating insomnia, restoring circadian rhythms, and modulating neurochemical markers. Methods: In strict accordance with PRISMA 2020 guidelines, we searched PubMed, ScienceDirect, Scopus, and The Cochrane Library for English language studies published from inception to March 31, 2026. Eligibility was restricted to studies with rigorously controlled designs, specifically randomized controlled trials (RCTs) and controlled in vivo animal studies. Interventions had to target the gut microbiota, with primary outcomes measuring sleep quality (subjective or objective) or sleep-related neurochemical markers. We excluded uncontrolled, single-arm, or observational designs; in vitro studies; non-original research; and studies involving subjects with severe medical or psychiatric comorbidities (e.g., cancer, ADHD, severe psychiatric disorders) to prevent confounding variables, though mild-to-moderate anxiety and depression were permitted. Risk of bias was assessed using the Cochrane RoB 2.0 and SYRCLE tools. Due to significant methodological heterogeneity, a narrative synthesis stratified by intervention and population was conducted. This review was not registered in PROSPERO. Results: A total of 56 studies (33 humans, 23 animals) met the inclusion criteria. Taxonomic nomenclature was updated to reflect 2020 reclassifications (e.g., Lactiplantibacillus plantarum). In human trials, interventions significantly improved subjective sleep metrics (PSQI, ISI). Recent additions demonstrated the efficacy of the Dietary Index for Gut Microbiota (DI-GM) and the improvement in N3 sleep latency by yeast mannan. Furthermore, whole-food patterns (e.g., the MIND diet) and Traditional Chinese Medicine (TCM) decoctions successfully enriched beneficial taxa, such as Bacteroides coprophilus, and increased short-chain fatty acid (SCFA) production. Animal models demonstrated that “psychobiotic” strains (Bifidobacterium breve, Lacticaseibacillus paracasei), prebiotics (GOS/PDX), and TCM formulas effectively restored GABA/5-HT profiles, lowered morning cortisol, and facilitated REM rebound in PCPA-induced models, while also consolidating non-rapid eye movement (NREM) sleep and downregulating clock genes (Per1/Per2). Conclusions: Psychobiotics, prebiotics, and botanicals represent a highly viable non-pharmacological strategy for treating insomnia. However, current evidence is constrained by a heavy reliance on subjective human questionnaires, short follow-up durations limiting insight into long-term stability, and a substantial translational gap between mechanistic rodent models and human clinical outcomes. Full article

Buffalo meat is widely consumed in Egypt; however, it may pose serious food safety risks due to microbial contamination during handling, preparation, and processing. This study investigated the prevalence and characterization of multidrug-resistant (MDR) enterotoxigenic Staphylococcus aureus in raw ground buffalo meat and ready-to-eat (RTE) kofta and liver sandwiches marketed in Mansoura, Egypt. S. aureus was detected in 62% (62/100) of raw buffalo ground meat, 41% (41/100) of RTE kofta, and 60% (60/100) of RTE liver samples, with an overall prevalence of 54.3% (163/300). All 660 isolates were confirmed as S. aureus via nuc gene detection, among which 46.8% (309/660) were mecA-positive and verified as methicillin-resistant (MRSA), and 21.8% (144/660) were vanA-positive and verified as vancomycin-resistant (VRSA). Enterotoxigenic strains were identified in 42.7% (282/660) of isolates, with the sea gene being most prevalent (67.7%; 191/282), followed by seb (58.2%; 164/282) and sec (39.7%; 112/282). The highest frequency of enterotoxigenic strains occurred in raw ground meat (47.2%), followed by kofta (45.1%) and liver (36%). Antimicrobial susceptibility testing against 15 antibiotics revealed that 7.6% (50/660) of isolates were extensively drug-resistant (XDR) with a MAR index of 0.9, while 82.9% (547/660) were MDR with MAR values between 0.3 and 0.7, indicating exposure to environments of intensive antibiotic use. The present findings highlight a high contamination level of buffalo meat products with MDR enterotoxigenic MRSA and VRSA, representing a significant public health hazard. Implementation of strict hygiene measures, wise antibiotic usage, and continuous surveillance is essential to control their dissemination through the food chain. Full article

Background: Eggshell membrane peptides (ESMPs) are natural bioactive compounds with reported chondroprotective properties. However, their regulatory effects on canine chondrocytes remain unclear. This study investigated ESMP in an interleukin-1β (IL-1β)-induced inflammatory model of canine chondrocytes. Methods: Chondrocytes were assigned to control (Cont), IL-1β, and ESMP + IL-1β groups. Cell viability was assessed using the Cell Counting Kit-8 (CCK-8) assay. NF-κB p65 nuclear translocation was evaluated by immunofluorescence staining. Real-time quantitative PCR (RT-qPCR) and Western blotting (WB) were used to measure mRNA and protein expression levels, respectively. Results: ESMP inhibited IL-1β-induced NF-κB p65 nuclear translocation and reduced the IL-1β-induced increases in interleukin-6 (IL-6), cyclooxygenase-2 (COX-2), inducible nitric oxide synthase (iNOS), and matrix metalloproteinase-13 (MMP-13) at both mRNA and protein levels. ESMP also decreased IL-6, nitric oxide (NO), and prostaglandin E₂ (PGE₂) levels in culture supernatants. ESMP reversed the IL-1β-induced reduction in type II collagen α1 chain (COL2A1) and aggrecan (ACAN) expression at both transcriptional and protein levels. Conclusions: ESMP attenuates IL-1β-induced inflammatory responses and extracellular matrix degradation in canine chondrocytes, potentially associated with suppression of NF-κB p65 nuclear translocation. This supports its potential application in promoting joint health in dogs. Full article