Search Results (10,067)

Previous studies of train-induced tunnel responses have mainly focused on completed tunnels or symmetric loading conditions, while the dynamic behavior of unfinished double-arch tunnels subjected to unilateral train loading through temporary trestles remains insufficiently understood. To address this gap, this study investigates the asymmetric load-transfer mechanism and short-term structural response of an unfinished double-arch tunnel–trestle system and identifies critical locations for construction-stage monitoring and speed control. A three-dimensional ABAQUS model was established for train speeds of 10–70 km/h and validated using a 63-day field-monitoring program comprising 15 train passages at speeds of approximately 9.4–56.2 km/h. Both numerical and monitoring results show that stress and deformation increase with train speed and are concentrated at the loaded-side invert, lower middle partition wall, and trestle wheel-load region. At 70 km/h, the calculated maximum lining compressive stress and trestle stress reached 6.353 and approximately 172 MPa, respectively, while the maximum horizontal deformations of the loaded and unloaded tunnel bores were 1.110 and 0.565 mm. At the maximum monitored speed of 56.2 km/h, the measured peak compressive stress of the middle partition wall was 5.95 MPa. The mean monitoring-to-simulation ratios for the evaluated responses were approximately 0.94–0.97, demonstrating satisfactory agreement and a slightly conservative numerical prediction. The results clarify the asymmetric coupling response of the tunnel–trestle system and support the identification of sensitive monitoring locations. Based on the combined numerical and field evidence, approximately 30 km/h is recommended as a conservative, project-specific construction-stage operational-control value. This study provides a quantitative basis for monitoring and risk control in similar temporary rail-transport projects, although further verification under different geological, structural, and loading conditions is required. Full article

In molten salt reactors, multiphase transport of fission products produces nonuniform nuclide inventories throughout the primary loop, thereby affecting subsequent decay heat evolution. Although fission product transport has been widely studied, its influence on post-shutdown wall-deposited decay heat remains insufficiently characterized. Here, the bubble transport capability of the Thorium Fission Products Migration Code (ThorFPMC) was extended using a drift-flux model to investigate the effects of operating void fraction on the magnitude, spatial distribution, nuclide composition, and subsequent evolution of wall-deposited decay heat under an idealized post-drainage condition. Results showed that, for the baseline bubble diameter of 0.508 mm, the initial wall-deposited decay heat decreased from 41.33 to 6.63 kW as the operating void fraction increased, corresponding to an 84.0% reduction; bubble diameter sensitivity calculations preserved the same monotonic trend. The source remained strongly nonuniform, with the heat exchanger consistently dominant, while increasing the void fraction reduced the core fraction and increased the relative external-loop contribution. Nuclide contributions evolved from a broad early distribution to long-term dominance by ⁹⁵Nb and ¹⁰³Ru, with precursor feeding shaping several important daughter nuclides. These results link operating period multiphase transport to component-resolved residual decay heat sources and provide a basis for operating-condition-dependent source terms in shutdown thermal and system analyses. Full article

Agricultural threshing mixtures are moist, heterogeneous, and dynamically disturbed, conditions that reduce the selectivity of cleaning systems based solely on size, density, and aerodynamic response. Electrostatic separation introduces an additional property dimension, but its application to raw paddy rice remains constrained by moisture-sensitive charging, irregular particle motion, wall deposition, and variable feed conditions. This critical review synthesizes rice-specific studies on dielectric and material-state sensing with evidence concerning particle charging, electro-aerodynamic transport, multiphysics modelling, and process control. The available literature shows that dielectric measurements can characterize moisture- and density-dependent material states, but they do not directly quantify charge retention or electrostatic separability. Rice-specific evidence remains concentrated in dielectric characterization and machinery operating conditions, whereas electrostatic processing studies mainly concern processed rice-derived materials or analogous particle systems. Direct evidence from raw paddy threshing mixtures under continuous and field-relevant operating conditions remains limited. Based on the evidence, a four-zone framework is proposed comprising feed dispersion, charge acquisition, electro-aerodynamic deflection, and outlet collection. The framework identifies the measurements, model parameters, and validation steps required to relate dielectric state, charge decay, particle trajectories, and control actions, thereby providing a research basis for the development and rice-specific validation of electrostatic cleaning systems. Full article

Bio-asphalt–rubber (BAR) binders combine plant-based bio-oil, end-of-life tire crumb rubber, and petroleum asphalt binder, but their climate advantage remains uncertain because bio-oil supply chains, asphalt-binder inventories, and tire-rubber allocation choices can substantially change cradle-to-gate results. This study develops a probabilistic cradle-to-gate life-cycle assessment for one metric ton of binder at plant gate. Eight alternatives were evaluated: a neat petroleum binder, a rubberized binder, a bio-oil modified binder, and five BAR binders with crumb rubber contents of 20–30% and bio-oil contents of 5–15%, expressed relative to neat asphalt mass. The model includes A1 material production, A2 inbound transport, and A3 binder blending energy. Plant-based bio-oil was represented using a literature-derived inventory, while crumb rubber was evaluated under cut-off, avoided-burden, and clinker-fuel system-expansion scenarios. A 10,000-iteration Monte Carlo simulation propagated inventory, transport, energy, and allocation uncertainty. Under cut-off allocation, mean GWP decreased from 496 kg CO2e/t for the neat binder to 446–471 kg CO2e/t for BAR binders, with BAR_30CR_15BIO showing the lowest mean impact and a 98.8% probability of outperforming the control. Avoided-burden allocation strengthened the apparent benefit, whereas system expansion against clinker fuel reversed the conclusion for rubber-containing alternatives. Results show that BAR can reduce binder-level GWP, but the conclusion is not inherent to the material; it depends strongly on tire-rubber counterfactuals and asphalt-binder inventory assumptions. Full article

The transition toward disaggregated, software-defined 5G Standalone (SA) infrastructures has shifted much of the end-to-end latency budget from the radio interface into the transport and computational layers, where bufferbloat and congestion-window collapse degrade Quality of Service before any packet is lost. Contemporary congestion control remains fundamentally reactive, acting only after a bottleneck has materialized. This study designs and evaluates a machine learning-based early warning system that anticipates transport-layer bottlenecks several seconds in advance. We built an isolated, reproducible 5G SA testbed using Open5GS and srsRAN, emulating the air interface through ZeroMQ so that every variation in round-trip time, jitter, and throughput is attributable to queuing and protocol dynamics rather than radio-frequency noise. A stochastic generator injected variable multi-user loads over runs of up to six hours, yielding open one-second telemetry. Round-trip-time forecasting was framed as multivariate, multi-horizon regression under a strict honest-forecasting protocol that prevents temporal leakage. Across Ridge, Random Forest, HistGradientBoosting, GRU, and LSTM models, tree ensembles forecast short horizons accurately ($R^2\approx 0.90$ at one second), temporal memory improves mid-range horizons, and all models converge to the trivial baseline at twenty seconds. As a binary early-warning task, the system catches most impending bottlenecks at high precision at five seconds. The dataset and pipeline are fully documented to support reproducibility and provide a transparent benchmark for proactive, zero-touch network orchestration. Full article

The present study experimentally investigates the influence of n-octanol addition to Jet-A fuel on the combustion performance and emission behavior of a micro-turboprop-based hybrid UAV (“Unmanned Aerial Vehicle”) power system. The experiments were conducted on a dedicated hybrid propulsion test bench equipped with a KingTech micro-turboprop engine mechanically coupled to a T-Motor electric generator and supplying a regulated 48 V DC bus. The system is capable of delivering approximately 3 kW of continuous electrical power, with peak values reaching 3.5 kW. Jet-A and three n-octanol/Jet-A blends containing 10%, 20%, and 30% n-octanol by volume, denoted O10, O20, and O30, respectively, were tested under four operating regimes ranging from idle to 2500 W electrical load. Exhaust gas temperature, carbon monoxide, sulfur dioxide, nitrogen oxides, electrical output, and near-field pollutant dispersion were evaluated. The results show that n-octanol addition affects engine behavior in a strongly load-dependent manner. At idle, the O10 blend reduced CO concentration from approximately 2520 ppm for Jet-A to approximately 2270 ppm, corresponding to a reduction of about 9.9%. At the same operating condition, O10 reduced exhaust gas temperature from approximately 498.3 °C to 463.2 °C, while O20 and O30 produced stronger cooling effects. At intermediate regimes, the oxygenated molecular structure of n-octanol contributed to lower CO formation in selected cases, indicating improved combustion-completeness behavior. At high load, however, exhaust gas temperatures converged toward or exceeded those of Jet-A, particularly for O30, showing that higher octanol fractions may introduce additional thermal constraints. Among the tested fuels, O10, corresponding to 10% n-octanol by volume, provided the most balanced behavior across the investigated operating range, from idle to 2500 W electrical load. The dispersion measurements performed at 30 m from the source further showed that ambient pollutant concentrations are strongly influenced by wind speed, wind direction, and plume transport. These findings support moderate n-octanol blending as a promising transitional strategy for small-scale hybrid UAV propulsion systems, while highlighting the need for future repeated testing, direct fuel-flow measurement, and numerical dispersion modeling. Full article

Object detection under adverse weather conditions remains a challenging problem for autonomous driving systems due to image degradation caused by rain, snow, haze, and complex illumination. Although RT-DETR achieves a good balance between detection accuracy and efficiency, its performance is limited in adverse weather scenarios due to weather-induced feature distortion and unreliable query selection. In this paper, we propose WFG-RT-DETR, a robust real-time object detection framework for adverse weather conditions. A Weather-Focused Guidance (WFG) module is introduced to enhance feature representation by combining frequency-domain noise suppression with spatial structural compensation. Furthermore, a Weather-Aware Query Selection (WAQS) module is proposed to improve query initialization by incorporating weather-aware noise estimation, reducing false-positive proposals caused by environmental interference. An Exponential Moving Average (EMA) strategy is also employed to stabilize model training. Extensive experiments on the DAWN and WEDGE datasets demonstrate the effectiveness of the proposed method. Compared with RT-DETR, WFG-RT-DETR improves the mAP@50 on the DAWN dataset from 64.62% to 68.89% while maintaining real-time inference capability. Cross-dataset evaluations on the WEDGE dataset further verify its robustness and generalization under diverse adverse weather conditions. The proposed framework provides an effective solution for reliable object detection in intelligent transportation and autonomous driving applications. Full article

Intelligent Transportation Systems (ITS) increasingly combine sensing, communication, computation, data platforms, and mobility services. This article presents a structured, literature-based mapping review of ITS applications from a standards-oriented perspective. The study analyzes 42 studies organized into five thematic groups and evaluated through 63 article–standard assessments using selected ITU-T Recommendations as an analytical lens. The rubric used in this work examined whether each study reported, or allowed reviewers to infer, evidence on architecture, data handling, interoperability, security and privacy, deployment assumptions, and digital-twin capabilities. Partial alignment was the most frequent outcome, accounting for 25 of 63 article–standard assessments (39.7%). At group level, satisfactory or optimal alignment occurred in 5 of 8 assessments (62.5%) in the digital-twin group and in 3 of 13 (23.1%) in the Big Data group; in the latter, 6 of 13 assessments (46.2%) showed limited or no alignment. Stronger alignment was usually found when studies described architectures, data flows, sensing mechanisms, service workflows, physical–virtual modeling, or system-management components relevant to the Recommendation, and weaker alignment when they focused mainly on algorithms, datasets, prediction accuracy, authentication, or secure dissemination without sufficient detail on interfaces, data governance, gateway roles, deployment conditions, or platform integration. The review proposes a five-dimension standards-facing reporting checklist addressing interoperability, data lifecycle and governance, security and privacy, operational readiness, and standards-facing evidence. It supports traceable reporting through explicit evidence-status categories and locations, and can be implemented as a Standards and Interoperability Reporting Statement (SIRS) for authors, reviewers, and editors. Overall, the findings show that standards-oriented assessment depends not only on technical performance but also on explicit and traceable integration evidence, while the proposed reporting profile provides a practical mechanism for making such evidence more systematically visible in future ITS studies. Full article

The industrial scalability and economic competitiveness of biomass-to-bioenergy and biorefinery systems depend on reliable feedstock supply, consistent biomass quality, and efficient logistics. An aspect that remains underexplored in biomass-to-biorefinery supply chain optimization is the incorporation of biomass quality uncertainty into decision-making models. Biomass quality characteristics, including ash content, moisture, chemical composition, and dry matter loss, can influence storage, preprocessing, transportation, conversion efficiency, biorefinery yields, process reliability, and overall energy utilization. Although these characteristics are difficult to model due to their spatial, temporal, and operational variability, ignoring their effects can lead to suboptimal supply-chain designs, inaccurate cost estimates, and unrealistic assessments of biorefinery performance. This paper reviews the treatment of biomass quality characteristics in the literature on quantitative modeling and analysis of biomass-to-biorefinery supply chains. Positioned from an Operational Research (OR) perspective, this review emphasizes mathematical modeling, computer simulation, optimization, and decision-support approaches for biomass-to-bioenergy systems. A total of 71 English-language published articles are reviewed and classified according to modeling approach and quality characteristic(s) considered. Across the selected literature that quantified biomass quality effects, cost reductions along supply chain operations ranging from 6% to 31% were reported when quality-aware models were compared with approaches that ignored quality or assumed unrealistic biomass quality characteristics. Despite these findings, biomass quality remains underrepresented in current analytical models; ash content, dry matter loss, and chemical composition were considered in only 10.4%, 4.3%, and 0.9% of the reviewed literature, respectively. This review summarizes the current state of research and outlines a future research agenda for integrating biomass quality control, uncertainty modeling, and optimization into scalable bioenergy and biorefinery systems. Full article

The aim of this study was to summarize current evidence on dust-related diseases of the bronchopulmonary system, medicinal plants, herbal formulations, and their underlying mechanisms of action. A literature review was conducted based on publications indexed in ScienceDirect, Google Scholar, SciFinder, Scopus, and Medline (PubMed), focusing on the mechanisms underlying dust-related diseases of the bronchopulmonary system, pneumoconiosis, and the potential of phytotherapeutic approaches to modulate these processes. The following keywords were used: bronchopulmonary system, pneumoconiosis, dust-related lung diseases, medicinal plants, herbal preparations, pulmonary rehabilitation, and lymphatic sanitation. The pathogenesis of pneumoconiosis involves the deposition of inhaled dust particles in the lung tissue, followed by chronic inflammation, oxidative stress, and progressive fibrosis. In experimental models, flavonoids, alkaloids, terpenoids, glycosides, tannins, and other phytochemical groups have demonstrated therapeutic potential in bronchopulmonary diseases. Among the compounds investigated, emodin, celastrol, kaempferol, sodium tanshinone IIA sulfonate, astragaloside IV, and dioscin have shown promising effects by modulating key signaling pathways and reducing inflammatory responses. Experimental evidence indicates that these phytochemicals can target major pathways involved in inflammation and fibrogenesis, thereby exerting antioxidant, anti-inflammatory, and antifibrotic effects. The lymphatic system also contributes to the pathogenesis of pneumoconiosis by transporting inhaled dust particles to regional lymph nodes, where their accumulation may promote lymph node sclerosis. Therefore, lymphatic sanitation may represent an important therapeutic mechanism of action of herbal formulations in pneumoconiosis. Our proposed lymphotropic herbal formulation enhances physiological lymphatic drainage and may positively influence the motility and functional activity of the tracheobronchial lymph nodes. The therapeutic potential of medicinal plants and herbal formulations in pneumoconiosis is supported by experimental findings for Tripterygium wilfordii (celastrol, through suppression of the EDNRB/Kng1 – (endothelin receptor type B/kininogen1), Delphinium, Camellia, and Berberis species (kaempferol, through inhibition of TLR4 (Toll-like receptor 4 signaling), Astragalus membranaceus (astragaloside IV, through antifibrotic activity mediated by inhibition of the TGF-β1/Smad3 (transforming growth factor beta1)pathway), and Reynoutria japonica Houtt., Rheum, and Aloe species (emodin, through inhibition of Smad3 (Smad family member 3) and NF-κB (nuclear factor kappa B)phosphorylation and reduction of TGF-β1, α-SMA (alpha-smooth muscle actin), collagen I, TNF-α (tumor necrosis factor alpha), and IL-1β (interleukin-1 beta) levels in lung tissue). For these and several other medicinal plants and their flavonoids, antifibrotic activity has been demonstrated through inhibition of the Akt/NF-κB (protein kinase B/nuclear factor kappa B) signaling pathway. A promising direction for future research is to evaluate the combined use of herbal formulations with established antifibrotic agents to determine whether synergistic therapeutic effects can be achieved. Full article

Truck–multi-drone collaborative delivery can reduce last-mile costs, but fleet sizing and routing are often optimized separately, making it difficult to match resources with demand under a delivery-period constraint. This study addresses the scenario of collaborative delivery involving multiple trucks and multiple drones by constructing a two-stage optimization framework that integrates fleet sizing and route planning. In the first stage, queueing models and continuous approximation are employed to determine the initial configuration of trucks and drones based on demand intensity and delivery cycle constraints. The second stage introduces continuous drone delivery and cross-vehicle retrieval to enhance the flexibility of truck–drone collaboration; while optimizing collaborative routes, the framework adjusts the allocation of trucks and drones—adding or reducing resources based on route feasibility and equipment utilization—thereby achieving the joint optimization of transport capacity and collaborative routes with the objective of minimizing total system costs. A node–resource–flow-separated three-chain encoding and an adaptive large neighborhood search–simulated annealing algorithm are designed to solve the model. Multi-scale numerical experiments show that, compared with four simplified fleet-sizing strategies, the proposed framework achieves average cost savings of 15.4–15.5% for medium- and large-scale instances. The results reveal an economic saturation point of the delivery period that shifts with node scale and a non-monotonic relationship between fleet size and coordination efficiency. The framework supports demand-driven fleet configuration and provides operational guidance for cost-effective truck–drone last-mile delivery. Full article

Lightweight and high-strength sandwich panels are used across aerospace, transportation, marine, energy, civil and protective systems because large face separation can provide high flexural rigidity and specific load capacity at low mass. This review treats the panel as a coupled material–structure–interface–process system rather than ranking core topology in isolation. A scoping-review workflow was updated to 24 July 2026 and yielded a curated evidence corpus of 112 total references. The review reports the search and screening logic explicitly, uses descriptive rather than field-wide bibliometric claims, and organizes the synthesis around component roles, governing mechanisms, connection regions, performance requirements and application-driven selection. Conventional foam, honeycomb and corrugated cores are compared with lattice-truss, auxetic, origami/kirigami, hierarchical, bio-inspired, graded and triply periodic minimal-surface (TPMS) architectures. Particular emphasis is placed on face-core and nodal junctions, static and dynamic failure-mode competition, fatigue and environmental degradation, fire/thermal/acoustic functions, additive-manufacturing defects, modelling fidelity, and active/adaptive concepts using shape-memory alloys and piezoelectric actuation. Cross-study numerical envelopes that could not be traced to harmonized test conditions are not used as universal rankings; instead, a mechanism-based screening matrix identifies design strengths, limitations and reporting requirements. The synthesis indicates that engineering deployment depends on preserving intended load paths in the as-manufactured panel, controlling interfaces and defects, validating multi-hazard durability and connections at scale, and integrating multifunctional or adaptive functions without creating new weak links. Full article

Mycobacterium tuberculosis (M. tb) possesses a unique, lipid-rich cell envelope that is critical for virulence, drug resistance, and persistence. Here, we identify the PPE family protein PPE57 as a key regulator of mycolic acid transport and host lipid exploitation. PPE57 physically interacts with the essential lipid transporter MmpL3, promoting trehalose monomycolate (TMM) translocation, enhancing trehalose dimycolate (TDM) synthesis, and increasing cell wall lipid content. Site-directed mutagenesis identified G175 as a critical residue for PPE57-MmpL3 binding. Deletion of PPE57 reduces cell wall thickness, alters lipid composition, and impairs biofilm formation. Mechanistically, PPE57 facilitates bacterial cholesterol acquisition, and during infection, activates the host PPAR-γ pathway in macrophages, leading to enhanced cholesterol uptake, lipid droplet accumulation, and increased intracellular triglyceride and cholesteryl ester levels. These changes provide a nutrient-rich niche that promotes bacterial survival and persistence. In a mouse model of infection, PPE57 deficiency results in reduced bacterial burden, milder lung pathology, and diminished lipid droplet-positive cell accumulation in lung tissues. These findings establish PPE57 as an essential accessory component of the MmpL3 lipid transport system, bridging mycobacterial cell wall assembly with host nutrient exploitation during persistent infection. Full article

Plant protein-derived bioactive peptides have attracted increasing interest as potential ingredients for health-promoting functional foods because of their reported cardiometabolic, antioxidant, anti-inflammatory, immunomodulatory, antimicrobial, gastrointestinal, and satiety-related activities. However, the field remains dominated by peptide discovery, in silico prediction, enzyme-inhibition assays, simulated digestion, and preclinical models, whereas successful translation into clinically supported and technologically viable food products is still limited. This review critically examines the gap between mechanistic promise and functional food implementation. It integrates evidence on plant protein sources, peptide-generation strategies, structure–activity relationships, gastrointestinal stability, intestinal transport, local gut activity, food-matrix interactions, processing effects, encapsulation, sensory constraints, human efficacy, regulatory substantiation, commercial feasibility, and consumer acceptance. Particular attention is given to the limited predictive value of isolated in vitro activity when peptides are exposed to digestion, epithelial barriers, complex food matrices, realistic processing conditions, and achievable dietary doses. The review also highlights that systemic absorption is not the only relevant pathway, as selected peptides may act locally within the gastrointestinal tract. Overall, the evidence indicates that peptide discovery should not be treated as the principal endpoint of research. Future progress will require translation-oriented development in which bioactivity, digestion stability, matrix compatibility, sensory quality, manufacturing reproducibility, realistic intake, human evidence, and regulatory credibility are evaluated as interdependent criteria. The most promising plant-derived peptides will therefore be those that retain sufficient activity and acceptability under real conditions of food production and consumption. Full article

Acid mine drainage (AMD) generation in sulfide waste rock deposits involves complex hydrogeochemical processes that require controlled experimental approaches to improve our understanding of them. In this study, a laboratory-scale waste rock dam reactor was operated for 31 weeks using representative materials from the Iberian Pyrite Belt. Continuous monitoring of physicochemical parameters and weekly chemical analyses generated a big dataset that was evaluated using graphical and statistical approaches. The reactor successfully reproduced the principal hydrogeochemical processes characteristic of AMD environments, including sulfide oxidation, contaminant transport and attenuation. Graphical and statistical analyses consistently validated the proposed conceptual hydrogeochemical model. Sulfate concentrations were identified as the main control on electrical conductivity, while alternating wet and dry periods governed pH fluctuations through precipitation–dissolution and redissolution processes. The progressive decrease in dissolved metals and sulfate along the reactor reflected precipitation processes comparable to those observed in natural AMD systems. The reactor reproduced, at a small scale, both the temporal evolution and the three hydrological phases described for natural waste rock dams, demonstrating its reliability as a reproducible experimental platform for hydrogeochemical modeling and the investigation of AMD generation under controlled conditions. An effective diagnosis of contamination processes in mine waters is essential for future remediation interventions. Full article