Search Results (3,010)

Titanium alloys are irreplaceable in aerospace, biomedical and marine industries due to their low density, high specific strength and excellent biocompatibility. Conventional manufacturing methods suffer from low material utilization and difficulty in fabricating complex components, while additive manufacturing (AM) realizes near-net-shape forming of customized structures but introduces unique non-equilibrium microstructures and defects, which significantly alter the corrosion behavior and limit the long-term service reliability of additively manufactured (AMed) titanium alloys. This work systematically analyzes the corrosion behavior of titanium alloys fabricated by four mainstream AM processes: LPBF (laser powder bed fusion)/SLM (selective laser melting), EBM (electron beam melting), DED (directed energy deposition) and WAAM (wire arc additive manufacturing). It quantitatively summarizes the key electrochemical parameters and discusses the regulatory effects of matrix composition, post-treatment and service environment on their corrosion behaviors. The universal corrosion mechanisms—namely, passive film breakdown, micro-galvanic corrosion, and defect-induced localized corrosion—as well as process-specific corrosion mechanisms inherent to AMed titanium alloys are systematically elucidated. This study offers theoretical foundations for optimizing corrosion resistance and ensuring the reliable engineering implementation of AMed titanium alloys. Full article

Against the backdrop of coordinated development in the Beijing–Tianjin–Hebei region, Hebei Province serves as an ecological safety barrier for the Beijing–Tianjin–Hebei urban agglomeration. Conducting research on land use and land cover change (LUCC) and ecosystem service value (ESV) holds significant theoretical and practical value for elucidating the mechanisms underlying ESV evolution under the combined effects of rapid urbanization and major ecological engineering projects, and for applying these findings to regional land-use planning and ecological conservation and restoration efforts. This research aligns with the United Nations Decade on Ecosystem Restoration (2020–2030). Based on land-use data from 2000, 2010, and 2020, along with 11 categories of natural and socio-economic drivers, this study systematically analyses regional LUCC and calculates ESV using locally adjusted equivalence factors. It examines the spatiotemporal evolution patterns of ESV through the analysis of local spatial autocorrelation indices (LISAs), centroid, and standard deviation ellipses, and employs a GeoDetector to measure ESV drivers. Three scenarios—a natural evolution scenario (NES), economic development scenario (EDS), and ecological protection scenario (EPS)—were established. The patch-generating Land use simulation (PLUS) model was employed to simulate LUCC for 2030 (Kappa = 0.840) and calculate ESV. Results show that from 2000 to 2020, forest land and impervious surfaces in Hebei Province continued to expand, while cropland and grassland decreased. The cumulative ESV increased by 4.85 billion yuan. Slope was the primary driver of spatial variation in ESV, and the interaction between natural and socioeconomic factors demonstrated significantly stronger explanatory power. In 2030, the total ESV under all three scenarios was lower than in 2020. The EPS reached an ESV of 344.72 billion yuan, representing a relatively suitable model that balances development and conservation. Full article

(1) Background. Food sovereignty and local sustainability are ensured by large agro-industrial holdings and small-scale farms; this synergy forms a complementary model of the agrifood system. Maintaining this model’s balance requires the creation of a unified digital ecosystem that integrates all suppliers and consumers into production chains, thereby eliminating unnecessary intermediaries. (2) Methods. This study employs a comprehensive methodological framework, including systems analysis and mathematical modeling, to develop service algorithms. Object-oriented design and software engineering methods facilitated the development and implementation of a service-oriented architecture for the digital system. (3) Results. The study presents a multi-tier architecture featuring an integration bus based on a service-oriented approach. To implement direct supply-and-demand coupling strategies, the system integrates both internal services (microeconomic indicators) and external services (macroeconomic indicators). Additionally, a recommender system based on neural networks and mathematical models was developed to personalize consumer requests and manage product sales. (4) Conclusions. The software solution is consistent with the AgTech 4.0 concept and enables the creation of a seamless environment for interstate trade. The implementation of the system enhances the transparency of the “product footprint”, facilitates the redistribution of surpluses, and, consequently, contributes to price stabilization. Full article

Gravel soil used as backfill behind rockfall barriers in mountainous roads can extend structural service life and support sustainable resource utilization. However, rainfall-induced erosion may cause soil loss and reduce its buffering capacity. The fibers are short discrete fibers with a length of approximately 12 mm and an average diameter of 32.7 μm, corresponding to an aspect ratio of approximately 367. Reinforcement is achieved through fiber–soil interaction mechanisms, including particle bridging, interfacial friction, and pull-out resistance. The effects of polyurethane and fiber contents on compressive strength, shear strength, and impact resistance were evaluated using response surface methodology. Scanning electron microscopy was used to examine the microstructural features associated with the reinforcement mechanisms, and engineering-scale model tests were conducted to assess erosion and impact resistance under representative service conditions. The results show that polyurethane and fibers produce significant nonlinear enhancement effects on the mechanical properties of gravel soil, mainly through their individual contributions, whereas their interaction is limited. Multi-objective optimization indicates that the optimal mixture contains 6.8% polyurethane and 0.19% fiber, with prediction errors below 5%. The unconfined compressive strength of the gravelly soil increased from 107.6 kPa to 931.5 kPa, representing a 765.7% increase. Cohesion increased from 23.4 kPa to 83.44 kPa, representing a 256.4% increase. The internal friction angle increased from 43.4° to 61.23°, corresponding to a 41.08% increase. Under 1 h of intense rainfall erosion, the stabilized soil exhibited only slight surface particle detachment and maintained overall integrity. In impact tests, the velocity attenuation rate reached 65.6–71.4%. The proposed material provides a sustainable solution for improving buffer layers in rockfall barriers. Full article

Long and narrow shielded confined spaces, represented by traffic tunnels and underground utility tunnels, constitute critical application scenarios for indoor and underground positioning services. Despite their relatively simple geometric configurations, such environments suffer from severe spatial distortion of geometric dilution of precision (GDOP). Coupled with pervasive low-elevation signal propagation and intensive multipath reflection effects, conventional BeiDou Navigation Satellite System (BDS) positioning services are unable to provide continuous and reliable coverage in these scenarios. To date, existing research on high-precision pseudolite positioning for narrow confined spaces remains largely confined to theoretical analysis and laboratory experimental verification, while systematic studies on application-oriented signal atlas feature network design are significantly insufficient, forming a prominent gap that restricts the practical engineering deployment of relevant technologies. To address the aforementioned technical bottlenecks, this paper proposes a novel BDS pseudolite signal atlas network design method to improve the continuity, stability and comprehensive positioning performance in spatially distorted narrow shielded environments. Field vehicular tests were carried out in actual engineering tunnels and underground utility tunnels to systematically analyze the variation characteristics of raw BDS pseudolite observation data, including pseudorange, carrier phase, carrier-to-noise ratio (C/N₀) and Doppler shift. The test results verified that kinematic Doppler parameters exhibited outstanding stability in complex shielded environments with strong multipath interference. On this basis, a spatial feature model based on kinematic Doppler measurements was constructed, and wavelet denoising technology was adopted to extract effective typical spatial feature parameters. Combined with the deterministic one-to-one mapping relationship between Doppler peak characteristics and spatial positions, a multi-peak kinematic Doppler atlas was established, which eliminates the dependence on pre-deployment data collection, dedicated database construction and offline model training. Furthermore, comprehensively considering multi-dimensional constraints such as spatial environment scale, carrier dynamic characteristics and terminal output rate, the atlas network scheme was optimized to achieve a balanced trade-off among positioning detection accuracy, absolute positioning precision and suppression of the pseudolite near-far effect. Comparative experimental results demonstrate that the proposed BDS pseudolite atlas network effectively resolves the inherent GNSS positioning difficulty in long and narrow shielded spaces. Benefiting from the rational spectral peak configuration strategy, the system can satisfy the continuous and stable positioning requirements of multiple carrier types including motor vehicles and railway locomotives under variable motion speeds and terminal output rates. This study provides a robust and feasible technical solution for high-precision BDS positioning services in long and narrow shielded confined spaces, and holds favorable engineering application prospects for underground navigation scenarios. Full article

3D city models (3DCMs) are increasingly used in urban simulations, cadastral workflows, and digital building permit processes, and automated validation of these models has become a routine requirement. Existing validation services typically produce dense, frequently generated by SHACL engines, text-based reports that are difficult for users without a semantic-web background to interpret. This paper describes the CHEK Validation Results Viewer (CHEK VRV), a Flask-based web application that couples the OGC Data Completeness Validator with an interactive Three.js 3D viewer of the CityJSON input. SHACL violations and geometric invalidities are spatially explorable on a visual representation of the model, and the tool supports both predefined CHEK Building Block Profiles and user-uploaded custom profiles. We report a formative usability study with twelve domain experts (urban planners, data vendors, academics) and use it to identify the tool’s current strengths, its limitations, and a prioritized development roadmap. As reported by the participant experts, such a presentation is easier to interpret than the raw JSON-LD report. Full article

Intrusion detection in industrial cyber-physical systems is constrained by small labelled-attack corpora and by the subtler signal of physical-process attacks compared with classical IT-network intrusions, motivating renewed interest in foundation-model-based detectors; classical detectors are typically trained per dataset and degrade under the distribution shift that is common in operational technology, where attack repertoires evolve faster than retraining cycles. Two foundation-model families are now plausible candidates: open-source Large Language Models (LLMs) and recent tabular foundation models (TabPFN, TabICL) pre-trained for in-context tabular inference. We compare the two families head-to-head, alongside Random Forest and XGBoost classical anchors, across three established industrial security benchmarks (SWaT, HAI, WUSTL-IIoT-2021) under a controlled multi-seed full-holdout protocol with paired McNemar and cross-seed Mann–Whitney tests. The empirical picture is dataset-dependent rather than universal: tabular foundation models establish a strong, previously unreported baseline that is competitive with or superior to classical anchors on every dataset evaluated, while LLMs are complementary detectors with a specific advantage on schemas that carry process-engineering semantics (such as SWaT’s named sensor channels). A per-class analysis on the WUSTL five-class attack taxonomy shows that the two families have structurally different strengths: tabular methods dominate traffic-rich attacks (Denial-of-Service, Reconnaissance), whereas LLMs are competitive on rare attack types (Backdoor, Command Injection). A confidence-gated cascade that escalates only low-confidence tabular decisions to an LLM exceeds either detector alone at a small query budget, and a leave-one-attack-type-out analysis shows that foundation-model detectors generalise to unseen attack families substantially better than the classical anchors. The appropriate detector choice in industrial cyber-physical security is therefore informed by the dataset’s feature schema, the attack-type mix, and the operational cost envelope, rather than by a specific performance metric. Full article

This technical note aims to present a theoretical analysis for cybertronics engineering (CE) for a class of dynamic supply chains for artificial intelligence (AI)-based products, services or hybrid solutions. The cybertronics-based analysis encompasses three classes of supply chains: (1) energy-based dynamic supply chains (DSC); (2) semiconductor manufacturing and quantum supply chains; and (3) retailing of the AI-based DSC solutions generated. Considering the nonlinear nature of DSC, to provide solutions for products and services based on AI-chained supply chains, novel robust control is addressed via sliding mode control (SMC) with proper stability analysis for the DSC. Full article

The Internet of Vehicles (IoV) is reshaping intelligent transportation through pervasive connectivity, real-time data exchange, cooperative perception, and vehicle–edge–cloud services, while also expanding cybersecurity and privacy risks across heterogeneous cyber–physical environments. This paper presents a PRISMA 2020-informed systematic review of IoV security and privacy protection research. A cross-layer and lifecycle-oriented analytical framework is developed by integrating a four-layer IoV architecture—sensing layer, network access layer, coordinative computing layer, and application layer—with a five-stage data lifecycle covering data collection, transmission, storage, usage, and disposal. Based on this framework, the paper examines representative threat surfaces, vehicle-to-everything (V2X) communication security, public key infrastructure (PKI) based authentication, trust management, privacy-preserving data sharing, intrusion detection, active defense, and AI-assisted security analytics. Privacy-preserving mechanisms, including differential privacy, federated learning, blockchain, homomorphic encryption, and secure multi-party computation, are further compared in terms of deployment layer, lifecycle stage, real-time suitability, and representative performance evidence. In addition, the review discusses the engineering relevance of UNECE WP.29 R155/R156, ISO/SAE 21434, and related national standards, with emphasis on compliance evidence, over-the-air (OTA) governance, supply-chain coordination, and lifecycle cybersecurity management. The review shows that no single protection mechanism can simultaneously satisfy the requirements of real-time performance, scalability, privacy preservation, trustworthiness, and regulatory compliance in dynamic IoV environments. Future research should emphasize lightweight and adaptive protection, cross-layer trust coordination, privacy–utility co-optimization, trustworthy AI-assisted security operations, and evidence-based lifecycle governance. This review provides a structured reference for researchers and a practical basis for secure and privacy-aware IoV system design. Full article

Most airline passengers and crew assume that the air in the cabin is free from harmful or hazardous substances, as is mandated by airworthiness regulations. While fresh air entering the cabin is sterile (and if recirculated is usually efficiently filtered to remove microorganisms), if the fresh air is bled off the turbine compressors (as is the case in about 95% of airliners currently in service), it may be contaminated with traces of engine oil and ultrafine particles abraded from the turbine blades, and possibly traces of hydraulic fluid leaking from servo systems. Engine oil contains tricresyl phosphate (TCP) as an essential antiwear agent, but it is also a well-known neurotoxin, and it has been suggested that there may be no safe lower limit of exposure, not least because of considerable variation among individuals in sensitivity to tri-ortho-cresyl phosphate (ToCP) and other isomers with at least one ortho constituent. This paper reviews current knowledge about these hazards and discusses the medical and economic motivations for diminishing them. A calculation based on maintaining the life quality index shows that eliminating xenobiotic hazards in aircraft cabin air is likely to be affordable. Full article

With the rapid development of the hydrogen economy, Type IV composite pressure vessels have emerged as the core components of on-board hydrogen storage systems. However, accurate fatigue life prediction remains a critical bottleneck limiting their design optimization and safe operation. Existing methods often exhibit prediction errors exceeding ±50% due to the inherent scatter, anisotropy, and complex service environments of composites. This study proposes an improved simulation method for fatigue life prediction of Type IV cylinders. Systematic tension–tension fatigue tests were conducted on carbon fiber-reinforced polymer (CFRP) laminates at four ply angles (0°, ±15°, ±30°, ±45°) and PA6 liner at three temperatures (−30 °C, 25 °C, 82 °C) to establish comprehensive S-N curve databases. The results reveal that ply angle is the predominant factor governing CFRP fatigue performance, while temperature significantly influences PA6 behavior, and failure mode transitions from fiber fracture to matrix-dominated damage as ply angle increases. A fatigue analysis model was developed in nCode, incorporating the ply fatigue Algorithm to characterize the anisotropic fatigue behavior of CFRP overwraps. Full-scale validation on Type IV cylinders under cyclic pressure (2–87.5 MPa) confirmed the method’s effectiveness, achieving prediction errors of 11.5% and 35.3% for the two failed specimens, with failure locations well predicted. This study provides a rapid and reliable engineering calculation method and data support for the anti-fatigue design, safety assessment, and life management of Type IV cylinders. Full article

Fiber-reinforced polymer (FRP) composites are extensively used in aerospace, civil engineering, and defense applications because of their low density, high specific strength, corrosion resistance, and structural design flexibility. However, prolonged exposure to hygrothermal conditions, ultraviolet (UV) radiation, and thermo-oxidative environments can progressively damage these materials, leading to mechanical degradation and shortened service life. This review examines environmental aging in FRP composites at the levels of the polymer matrix, fiber/matrix interface, and reinforcing fibers. Representative predictive models, finite element methods, and experimental characterization techniques are summarized, together with the evolution of mechanical properties under different aging conditions. Hygrothermal degradation is mainly associated with moisture diffusion, matrix swelling, and interfacial debonding, whereas UV and thermo-oxidative aging are largely governed by photo-oxidation and thermally activated free-radical reactions. These processes may induce chain scission, crosslinking, matrix embrittlement, and interface damage. Under coupled environmental exposure, degradation is not simply additive because moisture transport, oxidation kinetics, and failure pathways may interact. Future research should emphasize multiscale characterization, anti-aging modification, interface engineering, protective coatings, and reliability-oriented lifetime prediction. Full article

This paper shifts the research perspective from “Buddhist monasteries” to “monastic Buddhism,” using Nālandā Mahāvihāra as a micro-level case to illuminate the broader support mechanism of Indian Buddhist monasteries, with particular focus on the concept of “non-exhaustible endowment”. Drawing on epigraphic evidence, Vinaya texts, and Chinese pilgrims’ records, it finds that major donors supported monasteries through religious rituals, land grants, and cash investments, primarily in the form of landed property and gold and silver currency, which were designated as non-exhaustible endowments. Monasteries then engaged in agriculture, handicrafts, building industry, commerce, and lending, transforming static assets into a non-exhaustible cycle of capital that benefited both monastics and laity. Systems such as Yizhi (robe funds) and Gongfu zhi Zhuang (robe-providing estates) reveal mature financial services that not only liberated monks from economic constraints but also stimulated the cotton textile trade between India and China. The wealth possessed by monasteries was not static but perpetually engaged in a dynamic cycle of capital. Major Buddhist monasteries thus emerged as regional economic engines, which became the core value for continuous royal patronage, as well as the key incentive for their violent destruction by Turkic Muslims. However, the transformation of the religious landscape and economic network in late medieval Bihār was not a simplistic process. Faced with a changing political and religious environment over time, Sufi saints, Jain followers, Shaiva ascetics and other religious communities, each grounded in their own faiths, landholdings, commercial networks and educational systems, gradually displaced, restructured and undermined the Buddhist monastery-centered endowment mechanism, causing Buddhism to progressively lose its regional dominance as an institutionalized religion. Full article

DoS and DDoS attacks remain a major threat to service availability in modern IP and IoT networks, yet many learning-based detectors depend on dataset-specific flow exports, feature tables, or preprocessing conventions. This article presents a unified sequence-level detection pipeline designed to process heterogeneous public datasets through the same representation. Raw PCAP/PCAPNG traces from CIC-IDS-2017, CIC-DDoS-2019, and CICIoT2023 are converted into one-second aggregates per destination host using header-only features derived from IP, TCP, UDP, and ICMP metadata, source diversity, and packet timing. Dataset-specific annotations are used only to assign binary DoS/DDoS labels to this common representation. The resulting time-ordered aggregates are grouped into fixed-length temporal windows and classified by a compact transformer encoder, TemporalDosTransformer, which produces a window-level attack probability. The study focuses on whether a clean PCAP-based aggregation and labelling flow can support consistent DoS/DDoS detection across multiple datasets without payload inspection, flow-exporter dependence, or dataset-specific feature engineering. Full article

Retrofitting existing buildings has become a critical strategy for reducing energy consumption, improving thermal comfort, and achieving carbon reduction targets in the built environment. Among retrofit measures, wall insulation plays a pivotal role in minimizing heat loss and enhancing building energy efficiency. Conventional insulation materials, although effective, are often associated with high embodied energy, limited recyclability, and environmental concerns. Consequently, bio-based composite materials derived from natural fibers, agricultural residues, and renewable binders have emerged as promising sustainable alternatives. However, the moisture sensitivity of lignocellulosic materials remains a major challenge that can compromise thermal performance, durability, and long-term service life. This review provides a comprehensive and critical assessment of bio-based hydrophobic composite panels for wall insulation in retrofit applications. Unlike previous reviews that have primarily examined bio-based insulation materials, natural-fiber composites, or hydrophobic modifications separately, this study integrates these interconnected research domains within a unified framework. The review systematically examines raw material selection, composite panel manufacturing processes, hydrophobic surface-engineering strategies, thermal and moisture-related performance, durability characteristics, retrofit implementation approaches, and sustainability considerations. The analysis demonstrates that hydrophobic modification significantly reduces moisture uptake, enhances dimensional stability, and preserves thermal-insulation performance under varying environmental conditions. Natural-fiber-based composites, including hemp, flax, jute, bamboo, coconut fiber, and agricultural residues, exhibit competitive thermal conductivity (λ) values while offering reduced environmental impacts compared with conventional insulation materials. Furthermore, the integration of advanced hydrophobic treatments improves resistance to water penetration, biological degradation, and freeze–thaw damage, thereby increasing the long-term reliability of retrofit insulation systems. Full article