Search Results (57,038)

Pavement energy harvesting has been investigated as a means of converting traffic loading, solar radiation, and pavement thermal gradients into usable electricity or heat. This paper reviews 135 publications available through March 2026 and evaluates the field from a pavement engineering perspective. The literature is organized into six technology families: piezoelectric systems, mechanical-electromagnetic systems, triboelectric systems, thermoelectric systems, hydronic/geothermal/solar-thermal pavements, and photovoltaic or pavement-integrated photovoltaic-thermal systems. The review considers not only reported energy output, but also structural compatibility, durability, constructability, maintenance requirements, safety, and deployment conditions. The synthesis shows that the most credible near-term roles of piezoelectric and triboelectric systems are self-powered sensing and other localized low-power functions rather than bulk electricity generation. Mechanical-electromagnetic systems can produce larger event-level output, but their practicality is limited to low-speed and highly controlled settings because they rely on deliberate surface displacement. Thermoelectric systems are mechanically compatible with pavements, yet their performance remains constrained by weak and transient temperature gradients. Hydronic and solar-thermal pavements are presently the most infrastructure-compatible option for large-area energy recovery because they deliver useful heat and align with snow-melting, seasonal storage, and adjacent building-energy applications. Photovoltaic and photovoltaic-thermal pavements offer direct electrical generation, but continued challenges with transparent cover layers, surface friction, durability, fouling, and maintenance still limit broad roadway deployment. Overall, the review indicates that future progress will depend less on maximizing peak output in isolated prototypes and more on integrated pavement-energy design, standardized performance reporting, durability assessment, techno-economic evaluation, and corridor-scale demonstration. Full article

The Taoping paleo-landslide poses a significant risk to local residents and critical infrastructure. However, traditional field surveys and deformation monitoring methods are often inadequate for capturing subtle, localized deformation characteristics—particularly at the head scarp and lateral margins—thereby limiting comprehensive assessments of slope instability. Surface strain data offer direct insights into internal stress redistribution during slope evolution and are essential for interpreting landslide mechanisms and forecasting failure. Given the current limitations in dense and wide-area strain monitoring technologies, this study proposes a novel method for modeling landslide strain fields based on Interferometric Synthetic Aperture Radar (InSAR) phase gradients. Using the phase gradient stacking approach, InSAR-derived phase gradients are transformed into strain-related parameters, enabling estimation of shear strain rates, principal strain rates, and their directional distributions. The application to the Taoping paleo-landslide reveals clear spatial patterns of compressive and tensile strain across the landslide body. Field investigations corroborate the InSAR-derived strain features through corresponding geomorphological evidence observed in both compressional and extensional zones. The proposed method enhances the understanding of landslide deformation behavior, supports evaluation of shear surface continuity and evolution, and offers a robust framework for early warning and risk mitigation in complex landslide-prone areas. Full article

As an important part of green manufacturing, remanufacturing has important practical significance for alleviating resource shortage and waste, developing circular economy and promoting sustainable development. In recent years, remanufacturing scheduling (RS), which can achieve high efficiency and green remanufacturing through the reasonable allocation of resources, has become a research hotspot in the field of remanufacturing. To offer a comprehensive evaluation of the research dynamics and development trends of RS, this paper systematically reviews the publications from 2010 to 2025 via Scopus, Web of Science, and the IEEE Xplore database. Firstly, the research background of RS, related remanufacturing policies and the generalized connotation of remanufacturing are introduced. Then, selected and valid publications are analyzed from time aspect, country aspect, and keyword aspect through Citespace software. In addition, based on remanufacturing level, modeling idea, optimization objectives, solution method, production scenarios and practical application, publications are further grouped and reviewed. In addition, according to the research gap existing in recent studies, some future development trends are accordingly pointed out, aiming to provide valuable insights for research related to RS. Finally, meaningful conclusions are drawn and the importance of RS is emphasized once again. Full article

Electric field distortion remains a fundamental challenge to the operational reliability of HVDC cable accessories, where localized stress intensifies space charge injection and accelerates insulation degradation. While nonlinear conductive composites incorporating functional fillers such as ZnO have shown potential for adaptive field grading, their dynamic interaction with space charge under non-uniform fields has yet to be fully resolved. This study experimentally examines the spatiotemporal evolution of space charge in double-layer dielectric structures comprising linear low-density polyethylene (LLDPE) and ZnO-based nonlinear composites, using the laser-induced pressure pulse (LIPP) technique. Localized field enhancement is introduced via metallic pin defects embedded on the cathode side. Comparative analysis reveals that composites with 40 vol% ZnO microvaristors markedly suppress charge injection compared to conventional semiconductive ethylene-vinyl acetate (EVA) layers. Specifically, interfacial charge accumulation during polarization is reduced by 71%, and residual charge density after depolarization decreases by 88%, leading to a more uniform internal field distribution. These findings provide direct experimental evidence of the field-regulating mechanism of nonlinear composites from the perspective of charge dynamics, supporting their application in intelligent HVDC insulation systems. Full article

Biosensors based on electrolyte-gated organic field-effect transistors (EGOFETs) have attracted considerable attention due to their advantages, including low cost, inherent signal amplification, and low-voltage operation. A critical step influencing sensing performance is the integration of specific receptors onto the device surface. Among various strategies, the covalent immobilization of biorecognition elements onto gold surfaces via thiol chemistry is one of the most widely used approaches. In this study, we report the optimization of a mixed self-assembled monolayer (SAM) composed of 11-mercaptoundecanoic acid (11-MUA) and 3-mercaptopropionic acid (3-MPA) for label-free detection of human IgG using EGOFETs. The quality of the SAM was systematically modulated by varying the total concentration from 10 to 400 mM and characterized using X-ray Photoelectron Spectroscopy (XPS), Electrochemical Impedance Spectroscopy (EIS), Cyclic Voltammetry (CV), and Atomic Force Microscopy (AFM). The results revealed that a concentration of 50 mM yielded a densely packed and well-ordered monolayer. After covalent immobilization of anti-IgG antibodies via 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide hydrochloride/N-hydroxysuccinimide (EDC/NHS) chemistry and subsequent blocking with ethanolamine and bovine serum albumin (BSA), the functionalized gate electrodes were integrated into poly(3-hexylthiophene) (P3HT)-based EGOFETs. Electrical measurements demonstrated that EGOFET biosensors functionalized with the 50 mM SAM achieved optimal sensing performance. The devices exhibited a highly linear response (R² = 0.998) over a wide concentration range from 1 fM to 10 nM, with a LOD of 2.82 fM, and showed excellent selectivity against non-target immunoglobulins A and M (IgA and IgM). This SAM concentration optimization strategy provides a versatile approach for engineering high-performance EGOFET biosensors, with potential applicability to a broad range of disease biomarkers. Full article

Biopolymer-based packaging films possess outstanding performances and are being developed as the alternatives to traditional petroleum-based plastic packaging films with many non-ignorable shortcomings. In this study, chitosan, succinylated pullulan (SP), and berberine (BBR) were combined to fabricate novel biopolymer-based composite films (CSSPB) via the layer-by-layer assembly method. The effects of the incorporation of BBR on the physicochemical properties of the film were investigated. It was found that after BBR was added, the tensile strength (TS), elongation at break (EAB), hydrophobicity, and antioxidant capacities of the film were enhanced. The chemical bonding, crystalline properties, elemental composition, and thermal stability of the films were also characterized by Fourier transform infrared (FT-IR) spectroscopy, X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and thermogravimetric analysis (TGA), respectively. The in vitro antifungal tests revealed the antifungal activities of the films with a relatively high BBR content against Colletotrichum gloeosporioides (CG). In the preservation experiments, the CSSPB films exhibited preservation effects on fresh-cut apples, which manifested as delaying browning, weight loss, an increase in the soluble solids content, and a decrease in hardness. The new CSSPB composite films were opined to hold application potential in the field of food packaging. Full article

Nuclear energy has emerged as a crucial technological solution for ensuring energy security and achieving carbon neutrality goals, given its ultra-high energy density and near-zero carbon emissions against the backdrop of rapid socioeconomic development, increasing energy demands, and accelerated global transition toward low-carbon energy structures. As the core component for energy conversion in nuclear reactors, fuel elements critically determine reactor efficiency and safety performance, with the fission product retention capability of silicon carbide layers in multilayer-coated fuel particles having been thoroughly validated through high-temperature gas-cooled reactor irradiation tests. The precise sphericity control of large-sized UO₂ fuel kernels represents a fundamental requirement for enhancing tristructural isotropic (TRISO) fuel particle performance and advancing Generation IV nuclear power plant development. This study presents a sphericity control strategy based on sol–gel processing that synergistically integrates physicochemical regulation of gelling media with multi-field washing flow field optimization. By implementing silicone oil-mediated interfacial tension gradient control, we effectively suppressed gel sphere destabilization while developing an innovative three-phase sequential washing technique involving kerosene washing, anhydrous ethanol interfacial transition, and ammonia solution replacement, which significantly enhanced mass transfer diffusion in stagnant liquid films and revolutionized fuel microsphere washing technology with improved efficiency and quality. Experimental results demonstrate that this integrated approach increases kernel sphericity qualification to 99.8%, reduces washing solution consumption by 79%, and achieves an average sphericity of 1.03. The research establishes a coupling mechanism between gelling media and multi-field washing processes, elucidating the synergistic effect between interfacial tension regulation and washing optimization, thereby providing both theoretical foundations and engineering application basis for the precision manufacturing of high-performance nuclear fuels. Full article

With the widespread application of deep neural networks across various fields, issues related to model security have become increasingly prevalent. Backdoor attacks, as a covert method of attack, can implant malicious behavior during the model training process, causing the model to perform predetermined tasks under specific trigger conditions. However, current backdoor attacks struggle to achieve a good balance between stealthiness and attack success rate, and there is an issue in which certain data transformation operations can negatively impact attack performance. To address these issues, this paper proposes a specialized backdoor attack method called Ditto. It first uses a boundary detection algorithm and a padding algorithm to determine the trigger’s insertion position. The trigger is then dynamically generated using a generative adversarial network, taking into account the texture features of the images. Subsequently, the trigger is applied to the images, and its level of stealthiness is adjusted. Compared to existing popular backdoor attack methods, the experimental results ensure a high level of stealthiness while also maintaining a high attack success rate and a high accuracy for clean data. Furthermore, our attack method exhibits considerable robustness and adaptability, demonstrating effective resistance against baseline backdoor defense techniques. Full article

Stereo matching constitutes a critical technology in applications such as autonomous driving and robot navigation. Conventional algorithms, however, often encounter limitations in real-time performance and resource efficiency when deployed on embedded platforms. This paper presents a real-time stereo matching system implemented on a Field-Programmable Gate Array (FPGA), which is built around a lightweight, hardware-optimized dual-path Semi-Global Matching (SGM) algorithm. The proposed method simplifies the traditional eight-path cost aggregation into horizontal and vertical dual-path aggregation, substantially reducing hardware resource consumption while preserving matching accuracy. The system employs a pipelined architecture that integrates image capture, DDR3 caching, and HDMI display output. Experimental results demonstrate that under the configuration of a 5 × 5 matching window and a disparity range of 64, the system generates stable disparity maps at 60 frames per second, with total power consumption below 2.2 W and FPGA core logic utilization under 30%. Compared to the conventional eight-path SGM, the dual-path strategy incurs only a marginal 6% increase in average bad pixel rate on standard stereo datasets while reducing Block RAM (BRAM) usage by approximately 30%. This achieves an effective practical balance between accuracy, computational efficiency, and power consumption. Full article

Pacific white shrimp (Litopenaeus vannamei) is a major aquaculture product worldwide. For consumers, discriminating domestic from imported sources of shrimp meat, and individual domestic sources, can be highly desirable because of the different meat quality and environmental contamination from geographically different origins of shrimp. This study evaluated the potential of stable isotope analysis (δ¹³C, δ¹⁵N, δ²H, δ¹⁸O) with chemometric models to authenticate the origins of Pacific white shrimp sold in China. Shrimp samples from domestic (Guangxi, Fujian, Shandong, Inner Mongolia) and foreign (Ecuador) sources were analyzed, using statistical analyses. The four-isotope model achieved 89.3% cross-validation accuracy in distinguishing domestic and foreign shrimp, with an overall prediction Area Under the Curve (AUC) of 0.901 (95% CI: 0.819–0.983)—significantly outperforming single-isotope models. Differences in δ¹³C and δ¹⁵N reflected feed source variations, while δ²H and δ¹⁸O (Variable Importance in the Projection (VIP) > 1, key discriminatory indicators) mirrored geographic environmental difference. Although δ¹⁵N did not differ significantly among groups, the combination of all four isotopes reduced limitations of individual δ²H/δ¹⁸O use. This approach enhanced the precision, reliability, and applicability of stable isotope analysis for origin authentication by leveraging complementary isotopic data and robust statistical frameworks. These findings demonstrate the proposed model’s potential as a cost-effective, copyright-compliant framework for shrimp origin authentication, with implications for isotopic traceability across food science fields. Full article

The large-scale use of compost in arable cropping systems is often limited by the large quantities required to meet the crop’s nutritional needs. Palletization can increase the nutrient density of organic fertilizers and improve their logistical feasibility by reducing storage, transport and application costs. This study evaluated the agronomic and environmental performance of compost pellets derived from pig slurry solids and olive pomace, using them as an alternative nitrogen source for wheat (Triticum aestivum L.) cultivated under Mediterranean conditions. A field experiment was conducted during the 2022–2023 growing season, with four treatments arranged in 24 m² replicated plots: an unfertilized control (C); pelletized compost (PSCOP); fresh pig slurry (PS); and mineral fertilization based on monoammonium phosphate and urea (IN). Excluding the control treatment, all fertilized plots received a uniform nitrogen rate of 150 kg N ha⁻¹. Soil chemical properties and nutrient availability (Pext, NH₄⁺-N and NO₃⁻-N) were evaluated at the beginning and end of the experiment, while wheat yield and grain quality were assessed at harvest. Greenhouse gas (GHG) emissions were monitored throughout the cropping season to evaluate environmental impacts. The results showed that the wheat yields achieved with PSCOP were comparable to those obtained with PS, although they remained lower than those achieved with mineral fertilization. Grain quality was not adversely affected by the application of PSCOP. Furthermore, PSCOP resulted in lower GHG emissions than mineral fertilization, with values closer to those observed in the unfertilized control. These findings suggest that pelletized organic fertilizers such as PSCOP may be a promising way to enhance nutrient circularity and reduce reliance on synthetic fertilizers and maintain crop productivity and limit environmental impact in Mediterranean agricultural systems. Full article

Wide-field infrared imaging systems are often constrained by detector size, cooling requirements, and payload limitations, leading to the need for multi-FOV detector sharing. However, conventional geometric multiplexing introduces severe spatial aliasing, which significantly degrades target localization performance. This paper proposes a polarization-encoded field-of-view multiplexing method for recovering spatial information from aliased detector measurements. The imaging plane is divided into multiple FOV regions, each assigned a distinct polarization state. After optical folding, the modulated sub-images are superimposed onto a common detector region. Six-channel polarization measurements are used to reconstruct pixel-wise Stokes vectors, and the spatial origin of each pixel is identified through polarization-domain similarity matching and target-level voting. MATLAB-based simulations were conducted using a nine-region multiplexing configuration. The proposed method achieves 97.3% pixel-level classification accuracy under ideal conditions and maintains over 95% accuracy at a noise level of σ = 0.02. The normalized Stokes reconstruction error is below 0.02, and stable performance is observed under polarization modulation deviations within ±10°. By introducing polarization as an additional encoding dimension, the proposed framework enables efficient separation of multiplexed spatial information without increasing detector resources, demonstrating its potential for compact wide-field infrared sensing applications. Full article

Meat quality serves as a pivotal determinant of consumer purchasing behavior and of the economic viability of the livestock industry; as such, research into its regulatory mechanisms is of critical significance for the development of modern agriculture. Traditional investigations into meat quality have predominantly centered on sensory and physicochemical assessments of ultimate phenotypic traits, thereby facing inherent limitations in systematically deciphering the intricate molecular regulatory networks underlying meat quality formation. By contrast, an integrated analysis of the transcriptome and metabolome effectively connects the cascade of “gene transcription—metabolic regulation—phenotypic determination,” which has emerged as a core methodological paradigm in contemporary research on the molecular mechanisms governing meat quality. This review systematically delineates the evolutionary trajectory and principal technological frameworks of meat quality evaluation systems, with a focused synthesis of recent advances achieved through combined transcriptomic and metabolomic analyses in the field of meat quality regulation. The scope of this review encompasses core transcriptional regulatory networks associated with meat quality attributes, pivotal metabolic pathways, signal transduction mechanisms, and protein degradation dynamics. Furthermore, the regulatory impacts exerted by genetic variation among breeds, nutritional modulation, rearing environments, and stress responses on meat quality characteristics are comprehensively elucidated. Integrative analysis reveals that combined transcriptome–metabolome approaches transcend the inherent limitations of single-omics investigations, systematically unraveling the hierarchical regulatory mechanisms governing fundamental meat quality traits, such as muscle fiber type differentiation, postmortem glycolytic progression, intramuscular fat deposition, and flavor compound accumulation. Such integrative strategies have facilitated the identification of functional genes and metabolic biomarkers with potential utility for the early prediction of meat quality outcomes. Concurrently, this review acknowledges persistent challenges confronting the field, including the absence of standardized protocols for multi-omics data integration, insufficient functional causal validation, and a discernible disconnect between research discoveries and practical industrial implementation. Building upon this comprehensive assessment, prospective directions for future multi-omics research in meat quality are proposed, accompanied by the formulation of an integrated end-to-end improvement framework spanning fundamental research, technological innovation, and industrial application. Collectively, this review provides a systematic theoretical foundation for the in-depth elucidation of mechanisms that determine meat quality and the precision-oriented regulation of quality-determining traits in livestock production practices, thereby offering substantial scientific guidance for quality improvement initiatives within the animal husbandry sector. Full article

Polymer-modified bituminous binders are widely used in road construction due to their enhanced mechanical performance; however, the effectiveness of these materials critically depends on the actual concentration of polymer modifiers, particularly styrene-butadiene-styrene (SBS). This study aims to develop and validate a rapid, reproducible Fourier Transform Infrared Spectroscopy—Attenuated Total Reflectance (FTIR-ATR) spectroscopy method for the quantitative determination of SBS content in polymer-modified bitumen (PMB). Since, to date, there is no clearly defined method for controlling the quantitative content of polymers in PMB, this creates difficulties in accepting the roadway into operation. Calibration PMB samples containing 1–4% SBS were prepared, tested for physical and mechanical properties, and analyzed spectroscopically to identify characteristic absorption bands at 966 cm⁻¹ and 699–760 cm⁻¹. A first-order calibration model was constructed to relate peak intensity to polymer concentration. The results demonstrate a clear linear correlation between SBS content and IR absorption features, confirming the suitability of FTIR as an instrumental method for routine laboratory control. Application of the model allowed determination of actual polymer mass fraction with high accuracy and reproducibility. The findings also showed that increased SBS levels improve softening point, elasticity, and low-temperature resistance, with 3–4% representing a performance-optimal range. Overall, the proposed FTIR-based approach provides an objective and efficient tool for quality control of polymer-modified binders and supports broader standardization efforts in the field. Full article

Sub-15 nm line structures are key building blocks for advanced device prototyping, nanoscale electrodes, and lithography templates such as etch/deposition masks. Although ultrahigh-voltage (≥100 kV) electron-beam lithography (EBL) can more readily achieve extremely small critical dimensions, its tool and infrastructure requirements limit widespread adoption in many laboratories. In contrast, 30 kV field-emission SEM platforms are far more accessible; however, resolution-limit patterning at 30 kV is more sensitive to beam current, exposure dose, and development conditions, motivating the establishment of a reproducible process flow and a well-defined process window. Here, we investigate the resolution limit of isolated lines using a Zeiss Gemini 460 system operated at 30 kV and an in-house pattern generator with 950 k PMMA C2 resist. To demonstrate device-level applicability, we develop a stable lift-off process, and all critical dimensions are evaluated on metal lines after e-beam evaporation and lift-off. By screening beam current and scanning dose to build the dose-to-size relationship, we show that reducing beam current significantly improves the achievable minimum line width. Under 35 pA, using CD ≤ 15 nm as the criterion for sub-15 nm window extraction, the usable dose range is [700, 804.3] µC/cm², corresponding to a dose latitude of ~14.9%. The best performance is obtained at 700 µC/cm², yielding a transferred metal line width of 13.85 nm after lift-off. This work provides a practical resolution-limit process flow and a quantitative process window for performing sub-15 nm patterning on accessible 30 kV platforms, supported by product-level lift-off validation. Full article