Search Results (1,889)

Pile foundations are critical structural elements, and their integrity is essential for ensuring the stability and safety of construction projects. Low-strain pile integrity testing (LSPIT) is widely used for defect detection; however, conventional manual interpretation of reflectograms is both time-consuming and susceptible to human error. This study presents a deep learning-driven approach utilizing transfer learning with convolutional neural networks (CNNs) to automate pile defect detection. A dataset of 328 reflectograms collected from real construction sites, including 246 intact and 82 defective samples, was used to train and evaluate the model. To address class imbalance, oversampling techniques were applied. Several state-of-the-art pretrained CNN architectures were compared, with ConvNeXtLarge achieving the highest accuracy of 98.2%. The accuracy reported was achieved on a dedicated test set using real reflectogram data from actual construction sites, distinguishing this study from prior work relying primarily on synthetic data. The proposed novelty includes adapting pre-trained CNN architectures specifically for real-world pile integrity testing, addressing practical challenges such as data imbalance and limited dataset size through targeted oversampling techniques. The proposed approach demonstrates significant improvements in accuracy and efficiency compared to manual interpretation methods, making it a promising solution for practical applications in the construction industry. The proposed method demonstrates potential for generalization across varying pile lengths and geological conditions, though further validation with broader datasets is recommended. Full article

Desert plant communities play a vital role in sustaining the stability of arid ecosystems; however, they demonstrate limited resilience to environmental changes. A critical aspect of understanding community assembly mechanisms is determining whether soil texture heterogeneity affects vegetation diversity in arid deserts, especially under conditions of extreme water scarcity and restricted nutrient availability. This study systematically examined the relationships between plant diversity and soil physicochemical properties across four soil texture types—sand, sandy loam, loamy sand, and silty loam—by selecting four representative desert systems in the Hami region of Xinjiang, China. The objective was to elucidate the mechanisms through which soil texture may impact desert plant species diversity. The findings revealed that silty loam exhibited distinct characteristics in comparison to the other three sandy soil types. Despite its higher nutrient content, silty loam demonstrated the lowest vegetation diversity. The Shannon–Wiener index (H′), Simpson dominance index (C), Margalef richness index (D), and Pielou evenness index (Jsw) for silty loam were all lower compared to those for sand, sandy loam, and loamy sand. However, silty loam exhibited higher values in electrical conductivity (EC), urease activity (SUR), and nutrient content, including soil organic matter (SOM), ammonium nitrogen (NH⁴⁺-N), and available potassium (AK), than the other three soil textures. This study underscores the significant regulatory influence of soil texture on plant diversity in arid environments, offering new insights and practical foundations for the conservation and management of desert ecosystems. Full article

Protein S-nitrosylation is a selective post-translational modification in which a nitrosyl group is covalently attached to the reactive thiol group of cysteine, forming S-nitrosothiol. This modification plays a pivotal role in modulating physiological and pathological cardiovascular processes by altering protein conformation, activity, stability, and other post-translational modifications. It is instrumental in regulating vascular and myocardial systolic and diastolic functions, vascular endothelial cell and cardiomyocyte apoptosis, and cardiac action potential and repolarization. Aberrant S-nitrosylation levels are implicated in the pathogenesis of various cardiovascular diseases, including systemic hypertension, pulmonary arterial hypertension, atherosclerosis, heart failure, myocardial infarction, arrhythmia, and diabetic cardiomyopathy. Insufficient S-nitrosylation leads to impaired vasodilation and increased vascular resistance, while excessive S-nitrosylation contributes to cardiac hypertrophy and myocardial fibrosis, thereby accelerating ventricular remodeling. This paper reviews the S-nitrosylated proteins in the above-mentioned diseases and their impact on these conditions through various signaling pathways, with the aim of providing a theoretical foundation for the development of novel therapeutic strategies or drugs targeting S-nitrosylated proteins. Full article

The increasing integration of 3D technologies and machine learning is fundamentally reshaping mineral sciences and cultural heritage, establishing the foundation for an emerging “Mineralogy 4.0” framework. However, public engagement with digital 3D collections is often limited by complex or costly interfaces, such as VR/AR systems and traditional touchscreen kiosks, creating a clear need for more intuitive, accessible, and more engaging and inclusive solutions. This paper presents PETRA, an open-source, gesture-controlled system for exploring 3D rocks and minerals. Developed in the TouchDesigner environment, PETRA utilizes a standard webcam and the MediaPipe framework to translate natural hand movements into real-time manipulation of digital specimens, requiring no specialized hardware. The system provides a customizable, node-based framework for creating touchless, interactive exhibits. Successfully evaluated during a “Long Night of Museums” public event with 550 visitors, direct qualitative observations confirmed high user engagement, rapid instruction-free learnability across diverse age groups, and robust system stability in a continuous-use setting. As a practical case study, PETRA demonstrates that low-cost, webcam-based gesture control is a viable solution for creating accessible and immersive learning experiences. This work offers a significant contribution to the fields of digital mineralogy, human–machine interaction, and cultural heritage by providing a hygienic, scalable, and socially engaging method for interacting with geological collections. This research confirms that as digital archives grow, the development of human-centered interfaces is paramount in unlocking their full scientific and educational potential. Full article

Foundation pit pumping induces groundwater drawdown both inside and outside the pit, consequently causing surrounding land subsidence. Based on actual engineering cases, this study established a three-dimensional numerical model using ABAQUS software (version 6.14-4) to systematically investigate the temporal evolution of groundwater drawdown and land subsidence during pit pumping, while quantifying the relationship between drawdown and subsidence stabilization time under different parameters. The key findings are as follows: (1) land subsidence stabilization time (50 days) is governed by external phreatic layer response, reaching 2.3 times longer than isolated aquifer conditions (22 days); (2) medium-permeability strata (0.01–10 K_0,AdII) showed peak sensitivity to drawdown–subsidence coupling; (3) pumping from a confined aquifer extends the subsidence stabilization time by a factor of 1.1 compared to phreatic aquifer conditions. These findings provide valuable insights for the design and risk assessment of dewatering strategies in foundation pits within multi-aquifer systems. Full article

Acoustic tweezers, as advanced micro/nano manipulation tools, play a pivotal role in biomedical engineering, microfluidics, and precision manufacturing. However, piezoelectric-based acoustic tweezers face performance limitations due to multi-physical coupling effects during microfabrication. This study proposes a novel approach using injection molding with embedded electronics (IMEs) technology to fabricate piezoelectric micro-ultrasonic transducers with micron-scale precision, addressing the critical issue of acoustic node displacement caused by thermal–mechanical coupling in injection molding—a problem that impairs wave transmission efficiency and operational stability. To optimize the IME process parameters, a hybrid multi-objective optimization framework integrating NSGA-II and MOPSO is developed, aiming to simultaneously minimize acoustic node displacement, volumetric shrinkage, and residual stress distribution. Key process variables—packing pressure (80–120 MPa), melt temperature (230–280 °C), and packing time (15–30 s)—are analyzed via finite element modeling (FEM) and validated through in situ tie bar elongation measurements. The results show a 27.3% reduction in node displacement amplitude and a 19.6% improvement in wave transmission uniformity compared to conventional methods. This methodology enhances acoustic tweezers’ operational stability and provides a generalizable framework for multi-physics optimization in MEMS manufacturing, laying a foundation for next-generation applications in single-cell manipulation, lab-on-a-chip systems, and nanomaterial assembly. Full article

Cybersecurity represents a critical challenge for data-sharing platforms involving multiple stakeholders, particularly within complex and decentralized systems such as livestock supply chain networks. These systems demand novel approaches, robust security protocols, and advanced data management strategies to address key challenges such as data consistency, transparency, ownership, controlled access or exposure, and privacy-preserving analytics for value-added services. In this paper, we introduced the Framework for Framework for Livestock Empowerment and Decentralized Secure Data eXchange (FLEX), as a comprehensive solution grounded on five core design principles: (i) enhanced security and privacy, (ii) human-centric approach, (iii) decentralized and trusted infrastructure, (iv) system resilience, and (v) seamless collaboration across the supply chain. FLEX integrates interdisciplinary innovations, leveraging decentralized infrastructure-based protocols to ensure trust, traceability, and integrity. It employs secure data-sharing protocols and cryptographic techniques to enable controlled information exchange with authorized entities. Additionally, the use of data anonymization techniques ensures privacy. FLEX is designed and implemented using a microservices architecture and edge computing to support modularity and scalable deployment. These components collectively serve as a foundational pillar of the development of a digital product passport. The FLEX architecture adopts a layered design and incorporates robust security controls to mitigate threats identified using the STRIDE threat modeling framework. The evaluation results demonstrate the framework’s effectiveness in countering well-known cyberattacks while fulfilling its intended objectives. The performance evaluation of the implementation further validates its feasibility and stability, particularly as the volume of evidence associated with animal identities increases. All the infrastructure components, along with detailed deployment instructions, are publicly available as open-source libraries on GitHub, promoting transparency and community-driven development for wider public benefit. Full article

High-precision positioning is the foundation for the functionality of various intelligent agents. In complex environments, such as urban canyons, relative pose estimation using cameras is a crucial step in high-precision positioning. To take advantage of the ability of an inertial measurement unit (IMU) to provide relatively accurate gravity prior information over a short period, we propose a minimal solution method for the relative pose estimation of a stereo camera system assisted by the IMU. We rigidly connect the IMU to the camera system and use it to obtain the rotation matrices in the roll and pitch directions for the entire system, thereby reducing the minimum number of corresponding points required for relative pose estimation. In contrast to classic pose-estimation algorithms, our method can also calculate the camera focal length, which greatly expands its applicability. We constructed a simulated dataset and used it to compare and analyze the numerical stability of the proposed method and the impact of different levels of noise on algorithm performance. We also collected real-scene data using a drone and validated the proposed algorithm. The results on real data reveal that our method exhibits smaller errors in calculating the relative pose of the camera system compared with two classic reference algorithms. It achieves higher precision and stability and can provide a comparatively accurate camera focal length. Full article

Addressing the stability control challenges of roadways with composite roofs in the No. 34 coal seam of Donghai Mine under high-strength mining conditions, this study employed integrated methodologies including laboratory experiments, numerical modeling, and field trials. It investigated the mechanical response characteristics of the composite roof and developed a synergistic control system, validated through industrial application. Key findings indicate significant differences in mechanical behavior and failure mechanisms between individual rock specimens and composite rock masses. A theoretical “elastic-plastic-fractured” zoning model for the composite roof was established based on the theory of surrounding rock deterioration, elucidating the mechanical mechanism where the cohesive strength of hard rock governs the load-bearing capacity of the outer shell, while the cohesive strength of soft rock controls plastic flow. The influence of in situ stress and support resistance on the evolution of the surrounding rock zone radii was quantitatively determined. The FLAC^3D strain-softening model accurately simulated the post-peak behavior of the surrounding rock. Analysis demonstrated specific inherent patterns in the magnitude, ratio, and orientation of principal stresses within the composite roof under mining influence. A high differential stress zone (σ₁/σ₃ = 6–7) formed within 20 m of the working face, accompanied by a deflection of the maximum principal stress direction by 53, triggering the expansion of a butterfly-shaped plastic zone. Based on these insights, we proposed and implemented a synergistic control system integrating high-pressure grouting, pre-stressed cables, and energy-absorbing bolts. Field tests demonstrated significant improvements: roof-to-floor convergence reduced by 48.4%, rib-to-rib convergence decreased by 39.3%, microseismic events declined by 61%, and the self-stabilization period of the surrounding rock shortened by 11%. Consequently, this research establishes a holistic “theoretical modeling-evolution diagnosis-synergistic control” solution chain, providing a validated theoretical foundation and engineering paradigm for composite roof support design. Full article

There is a lack of systematic research on the comprehensive regulatory effects of urea and organic fertilizer application on soil quality and cotton yield in summer direct-seeded cotton fields in the Yangtze River Basin. Additionally, there is a redundancy of indicators in the cotton field soil quality evaluation system and a lack of reports on constructing a minimum dataset to evaluate the soil quality status of cotton fields. We aim to accurately and efficiently evaluate soil quality in cotton fields and screen nitrogen application measures that synergistically improve soil quality, cotton yield, and nitrogen fertilizer utilization efficiency. Taking the summer live broadcast cotton field in Jiangxi Province as the research object, four treatments, including CK without nitrogen application, CF with conventional nitrogen application, N1 with nitrogen reduction, and N2 with nitrogen reduction and organic fertilizer application, were set up for three consecutive years from 2022 to 2024. A total of 15 physical, chemical, and biological indicators of the 0–20 cm plow layer soil were measured in each treatment. A minimum dataset model was constructed to evaluate and verify the soil quality status of different nitrogen application treatments and to explore the physiological mechanisms of nitrogen application on yield performance and stability from the perspectives of cotton source–sink relationship, nitrogen use efficiency, and soil quality. The minimum dataset for soil quality evaluation in cotton fields consisted of five indicators: soil bulk density, moisture content, total nitrogen, organic carbon, and carbon-to-nitrogen ratio, with a simplification rate of 66.67% for the evaluation indicators. The soil quality index calculated based on the minimum dataset (MDS) was significantly positively correlated with the soil quality index of the total dataset (TDS) (R² = 0.904, p < 0.05). The model validation parameters RMSE was 0.0733, nRMSE was 13.8561%, and the d value was 0.9529, all indicating that the model simulation effect had reached a good level or above. The order of soil quality index based on MDS and TDS for CK, CF, N1, and N2 treatments was CK < N1 < CF < N2. The soil quality index of N2 treatment under MDS significantly increased by 16.70% and 26.16% compared to CF and N1 treatments, respectively. Compared with CF treatment, N2 treatment significantly increased nitrogen fertilizer partial productivity by 27.97%, 31.06%, and 21.77%, respectively, over a three-year period while maintaining the same biomass, yield level, yield stability, and yield sustainability. Meanwhile, N1 treatment had the risk of significantly reducing both boll density and seed cotton yield. Compared with N1 treatment, N2 treatment could significantly increase the biomass of reproductive organs during the flower and boll stage by 23.62~24.75% and the boll opening stage by 12.39~15.44%, respectively, laying a material foundation for the improvement in yield and yield stability. Under CF treatment, the cotton field soil showed a high degree of soil physical property barriers, while the N2 treatment reduced soil barriers in indicators such as bulk density, soil organic carbon content, and soil carbon-to-nitrogen ratio by 0.04, 0.04, 0.08, and 0.02, respectively, compared to CF treatment. In summary, the minimum dataset (MDS) retained only 33.3% of the original indicators while maintaining high accuracy, demonstrating the model’s efficiency. After reducing nitrogen by 20%, applying 10% total nitrogen organic fertilizer could substantially improve cotton biomass, cotton yield performance, yield stability, and nitrogen partial productivity while maintaining soil quality levels. This study also assessed yield stability and sustainability, not just productivity alone. The comprehensive nitrogen fertilizer management (reducing N + organic fertilizer) under the experimental conditions has high practical applicability in the intensive agricultural system in southern China. Full article

This study provides a comprehensive assessment and synthesis of the literature on short-selling. It performs a lexicometric analysis, providing a quantitative review of 1093 peer-reviewed journal articles to identify and illustrate the main themes in short-selling research. Almost half the published literature on short-selling is thematically clustered around portfolio management techniques. Other key themes involve short-selling as it relates to risk management, strategic management, and market irregularities. Descending hierarchical classification examines the overall structure of the textual corpus of the short-selling literature and the relationships between its key terms. Similarity analysis reveals that the short-selling literature is highly concentrated, with most conceptual groups closely aligned and fitting into overlapping or conceptually similar areas. Some notable groups highlight prior short-selling studies of market dynamics, behavioral factors, technological advancements, and regulatory frameworks, which can serve as a foundation for market regulators to make more informed decisions that enhance overall market stability. Additionally, this study proposes a conceptual framework in which short-selling can be either a driver or an outcome by integrating the literature on its antecedents, consequences, explanatory variables, and boundary conditions. Finally, it suggests directions for future research. Full article

Thin-walled hemispherical shell structures are mainly used in the aerospace industry as energy absorbers. However, their thin walls frequently lead to stability problems. To create a stable structure, double-layered thin-walled hemispherical shell structures were developed. In this study, we investigated the deformation behaviors of these structures through both experimental and numerical methods. The shell span diameter is taken as 200 mm. Monolithic layers have thicknesses of 1.0 mm compared with double-layered shells which have thicknesses of 0.5 mm (inner)/0.5 mm (outer). We developed numerical models to simulate the structural responses of monolithic and double-layered spherical shell structures using ABAQUS/CAE^® V6.14 software. These models were validated against experimental results. Our results show that double-layered shells absorb more energy compared to monolithic shells. These insights provide a foundation for improved designs of hemispherical structures, ultimately enhancing their energy absorption performance. Full article

Mandelic acid (MA), as an important chiral aromatic hydroxy acid, is widely used in medicine, the chemical industry, and agriculture. With the continuous growth of market demand, traditional chemical synthesis methods are increasingly inadequate to meet the requirements of green and sustainable development due to issues such as complex processes, poor stereoselectivity, numerous byproducts, and serious environmental pollution. MA synthesis strategies based on biocatalytic technology have become a research hotspot due to their high efficiency, environmental friendliness, and excellent stereoselectivity. Significant progress has been made in enzyme engineering modifications, metabolic pathway design, and process optimization. Importantly, biomechanical research provides a transformative perspective for this field. By analyzing the mechanical response characteristics of microbial cells in bioreactors, biomechanics facilitates the regulation of relevant environmental factors during the fermentation process, thereby improving synthesis efficiency. Molecular dynamics simulations are also employed to uncover stability differences in enzyme–substrate complexes, providing a structural mechanics basis for the rational design of highly catalytically active enzyme variants. These biomechanic-driven approaches lay the foundation for the future development of intelligent, responsive biosynthesis systems. The deep integration of biomechanics and synthetic biology is reshaping the process paradigm of green MA manufacturing. This review will provide a comprehensive summary of the applications of MA and recent advances in its biosynthesis, with a particular focus on the pivotal role of biomechanical characteristics. Full article

This study examined the dynamic interconnectedness and portfolio implications within the cryptocurrency ecosystem, focusing on five representative digital assets across the core functional categories: Layer 1 cryptocurrencies (Bitcoin (BTC) and Ethereum (ETH)), decentralized finance (Uniswap (UNI)), stablecoins (Dai), and crypto infrastructure tokens (Maker (MKR)). Using the Extended Joint Connectedness Approach within a Time-Varying Parameter VAR framework, the analysis captured time-varying spillovers of return shocks and revealed a heterogeneous structure of systemic roles. Stablecoins consistently acted as net absorbers of shocks, reinforcing their defensive profile, while governance tokens, such as MKR, emerged as persistent net transmitters of systemic risk. Foundational assets like BTC and ETH predominantly absorbed shocks, contrary to their perceived dominance. These systemic roles were further translated into portfolio design, where connectedness-aware strategies, particularly the Minimum Connectedness Portfolio, demonstrated superior performance relative to traditional variance-based allocations, delivering enhanced risk-adjusted returns and resilience during stress periods. By linking return-based systemic interdependencies with practical asset allocation, the study offers a unified framework for understanding and managing crypto network risk. The findings carry practical relevance for portfolio managers, algorithmic strategy developers, and policymakers concerned with financial stability in digital asset markets. Full article

The intensifying global climate warming caused by human activities poses severe challenges to ecosystem stability. Constructing an ecological security pattern can identify ecological land supply and an effective spatial distribution baseline and provide a scientific basis for safeguarding regional ecological security. This study analyzes land-use data from 2000 to 2020 for Golog Tibetan Autonomous Prefecture. The PLUS model was utilized to project land-use potential for the year 2030. The InVEST model was employed to conduct a comprehensive assessment of habitat quality in the study area for both 2020 and 2030, thereby pinpointing ecological sources. Critical ecological restoration zones were delineated by identifying ecological corridors, pinch points, and barrier points through the application of the Minimum Cumulative Resistance model and circuit theory. By comparing ecological security patterns (ESPs) in 2020 and 2030, we proposed a dynamic restoration framework and optimization recommendations based on habitat quality changes and ESPs. The results indicate significant land-use changes in the eastern part of Golog Tibetan Autonomous Prefecture from 2020 to 2030, with large-scale conversion of grasslands into bare land, farmland, and artificial surfaces. The ecological security pattern is threatened by risks like the deterioration of habitat quality, diminished ecological sources as well as pinch points, and growing barrier points. Optimizing the layout of ecological resources, strengthening barrier zone restoration and pinch point protection, and improving habitat connectivity are urgent priorities to ensure regional ecological security. This study offers a scientific foundation for the harmonization of ecological protection and economic development and the policy development and execution of relevant departments. Full article