Search Results (135)

This study investigates the long-term flexural performance of prestressed concrete double tees under sustained loading. Six full-scale specimens were subjected to a comprehensive experimental program, including a 320-day storage period following prestress release, a short-term flexural test, and a 990-day sustained loading phase. Mid-span deflections were measured using a string-line method, while the effective prestress in tendons was continuously monitored with fiber Bragg grating (FBG) sensors. Results showed a pronounced increase in camber during the storage phase, with long-term camber reaching approximately three times the initial value. Under short-term loading, the slabs exhibited a clear bilinear moment–deflection behavior. During sustained loading, most of the long-term deflection developed in the early stages, and an inverse relationship between load level and deflection growth was observed. Additionally, data from 20 short-term tests were compiled, and a bilinear stiffness model was proposed to estimate flexural stiffness in the cracked state. These findings contribute to a deeper understanding of long-term deformation in prestressed concrete double tees and provide reference data for serviceability evaluation and design refinement. Full article

The transportation sector, as a major source of carbon emissions, plays a crucial role in the realization of dual carbon goals worldwide. In this study, an improved least absolute shrinkage and selection operator (LASSO) is used to identify six key factors affecting transportation carbon emissions (TCEs) in China. Aiming at the spatio-temporal characteristics of transportation carbon emissions, a CNN-BiLSTM neural network model is constructed for the first time for prediction, and an improved whale optimization algorithm (EWOA) is introduced for hyperparameter optimization, finding that the prediction model combining spatio-temporal characteristics has a more significant prediction accuracy, and scenario forecasting was carried out using the prediction model. Research indicates that over the past three decades, TCEs have demonstrated a rapid growth trend. Under the baseline, green, low-carbon, and high-carbon scenarios, peak carbon emissions are expected in 2035, 2031, 2030, and 2040. The adoption of a low-carbon scenario represents the most advantageous pathway for the sustainable progression of China’s transportation sector. Consequently, it is imperative for China to accelerate the formulation and implementation of low-carbon policies, promote the application of clean energy and facilitate the green transformation of the transportation sector. These efforts will contribute to the early realization of dual-carbon goals with a positive impact on global sustainable development. Full article

A monocular deflectometric system comprises a camera and a screen that collaboratively facilitate the reconstruction of a specular surface under test (SUT). This paper presents a methodology for solving the slope distribution of the SUT utilizing pose estimation derived from reflections, based on vision ray calibration (VRC). Initially recorded by the camera, an assisted flat mirror in different postures reflects the patterns displayed by a screen maintained in a constant posture. The system undergoes a calibration based on the VRC to ascertain the vision ray distribution of the camera and the spatial relationship between the camera and the screen. Subsequently, the camera records the reflected patterns by the SUT, which remains in a constant posture while the screen is adjusted to multiple postures. Utilizing the VRC, the vision ray distribution among several postures of the screen and the SUT is calibrated. Following this, an iterative integrated calibration is performed, employing the calibration results from the preceding separate calibrations as initial parameters. The integrated calibration amalgamates the cost functions from the separate calibrations with the intersection of lines in Plücker space. Ultimately, the results from the integrated calibration yield the slope distribution of the SUT, enabling an integral reconstruction. In both the numeric simulations and actual measurements, the integrated calibration significantly enhances the accuracy of the reconstructions when compared to the reconstructions with the separate calibrations. Full article

Seed germination is a critical phase in the plant lifecycle of Camellia oleifera (oil tea), directly influencing seedling establishment and crop reproduction. In this study, we examined transcriptomic and physiological changes across five defined germination stages (G0–G4), from radicle dormancy to cotyledon emergence. Using RNA sequencing (RNA-seq), we assembled 169,652 unigenes and identified differentially expressed genes (DEGs) at each stage compared to G0, increasing from 1708 in G1 to 10,250 in G4. Functional enrichment analysis revealed upregulation of genes associated with cell wall organization, glucan metabolism, and Photosystem II assembly. Key genes involved in cell wall remodeling, including cellulose synthase (CESA), phenylalanine ammonia-lyase (PAL), 4-coumarate-CoA ligase (4CL), caffeoyl-CoA O-methyltransferase (COMT), and peroxidase (POD) showed progressive activation during germination. A Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed dynamic regulation of phenylpropanoid and flavonoid biosynthesis, photosynthesis, carbohydrate metabolism, and hormone signaling pathways. Transcription factors such as indole-3-acetic acid (IAA), ABA-responsive element binding factor (ABF), and basic helix–loop–helix (bHLH) were upregulated, suggesting hormone-mediated regulation of dormancy release and seedling development. Physiologically, cytokinin (CTK) and IAA levels peaked in G4, antioxidant enzyme activities were highest in G2, and starch content increased toward later stages. These findings provide new insights into the molecular mechanisms underlying seed germination in C. oleifera and identify candidate genes relevant to rootstock breeding and nursery propagation. Full article

Black rockfish (Sebastes schlegelii) is a marine ovoviviparous teleost that exhibits significant sexual dimorphism, with females growing faster and reaching larger sizes than males. Establishing stable oogonial stem cells (OSCs) is critical for understanding germline stem cell dynamics and facilitating all-female breeding. In this study, we successfully isolated and cultured OSCs from S. schlegelii for 12 passages. These cells exhibited alkaline phosphatase activity, expressed germline marker genes (ddx4, cdh1, klf4), and maintained a diploid karyotype (2n = 48). Transcriptomic comparisons between early (P3) and late (P12) passages revealed significant metabolic dysfunction and cell cycle arrest in the late-passage cells. Specifically, the down-regulation of glutathione-related and glycolysis-related genes (gstm3, gstt1, mgst3, gsta1, gsta4, gsto1, gapdh) and key mitotic regulators (cdk1, chk1, cdk4, e2f3, ccne2, ccnb1) suggested that metabolic imbalance contributes to oxidative stress, resulting in cell cycle inhibition and eventual senescence. This study provides a marine fish model for investigating metabolism-cell cycle interactions in germline stem cells and lays the foundation for future applications in germ cell transplantation and all-female breeding. Full article

Existing deepfake detection methods heavily rely on specific training data distributions and struggle to generalize to unknown forgery techniques. To address the challenge, this paper focuses on two critical research gaps: (1) the lack of systematic mining of standard features across multiple forgery methods; (2) the unresolved distribution shift problem in the strong supervised learning paradigm. To tackle these issues, we propose a self-supervised learning framework based on feature disentanglement, which enhances the generalization ability of detection models by uncovering the intrinsic features of forged content. The core method comprises three key components: self-supervised sample construction and training samples for feature disentanglement, which are generated via an image self-mixing mechanism; feature disentanglement network, where the input image is decomposed into two parts—content features irrelevant to forgery and discriminative forgery-related features; and conditional decoder verification, where both types of features are used to reconstruct the image, with forgery-related features serving as conditional vectors to guide the reconstruction process. Orthogonal constraints on features are enforced to mitigate the overfitting problem in traditional methods. Experimental results demonstrate that, compared with state-of-the-art methods, the proposed framework exhibits superior generalization performance in cross-unknown forgery technique detection tasks, effectively breaking through the dependency bottleneck of traditional supervised learning on training data distributions. This study provides a universal solution for deepfake detection that does not rely on specific forgery techniques. The model’s robustness in real-world complex scenarios is significantly improved by mining the common essence of forgery features. Full article

In the face of increasingly complex urban challenges, a critical question arises: can urban ecosystems maintain resilience, vitality, and sustainability when confronted with external threats and pressures? Taking Kunming—a plateau-mountainous city in China—as a case study, this research constructs an urban ecosystem resilience (UER) assessment model based on the DPSIR (Driving forces, Pressures, States, Impacts, and Responses) framework. A total of 25 indicators were selected via questionnaire surveys, covering five dimensions: driving forces such as natural population growth, annual GDP growth, urbanization level, urban population density, and resident consumption price growth; pressures including per capita farmland, per capita urban construction land, land reclamation and cultivation rate, proportion of natural disaster-stricken areas, and unit GDP energy consumption; states measured by Evenness Index (EI), Shannon Diversity Index (SHDI), Aggregation Index (AI), Interspersion and Juxtaposition Index (IJI), Landscape Shape Index (LSI), and Normalized Vegetation Index (NDVI); impacts involving per capita GDP, economic density, per capita disposable income growth, per capita green space area, and per capita water resources; and responses including proportion of natural reserve areas, proportion of environmental protection investment to GDP, overall utilization of industrial solid waste, and afforestation area. Based on remote sensing and other data, indicator values were calculated for 2006, 2011, and 2016. The entire-array polygon indicator method was used to visualize indicator interactions and derive composite resilience index values, all of which remained below 0.25—indicating a persistent low-resilience state, marked by sustained economic growth, frequent natural disasters, and declining ecological self-recovery capacity. Forecasting results suggest that, under current development trajectories, Kunming’s UER will remain low over the next decade. This study is the first to integrate the DPSIR framework, entire-array polygon indicator method, and Grey System Forecasting Model into the evaluation and prediction of urban ecosystem resilience in plateau-mountainous cities. The findings highlight the ecosystem’s inherent capacities for self-organization, adaptation, learning, and innovation and reveal its nested, multi-scalar resilience structure. The DPSIR-based framework not only reflects the complex human–nature interactions in urban systems but also identifies key drivers and enables the prediction of future resilience patterns—providing valuable insights for sustainable urban development. Full article

Camellia oleifera, a prominent species of edible oil tree in China, depends on improved soil fertility for its sustainable growth. Although the application of bacterial manure has been demonstrated to enhance soil nutrient conditions, the specific contributions of endophytes within fertilizers and their interactions with soil microbial ecosystems remain inadequately explored. This study investigates the impact of organic fertilizers combined with three endophytes (CoT10, CoH27, and CoH17) on the physicochemical properties, enzymatic activities, and microbial diversity of soils in C. oleifera plantations. Findings indicate that the integration of endophytes with organic fertilizers significantly improved soil nutrient levels (including total nitrogen, total phosphorus, and hydrolysable nitrogen), enzymatic activities (such as phosphatase, amylase, and nitrate reductase), and microbial diversity compared to the application of organic fertilizer alone. Notably, the endophyte CoT10, when applied alone with organic fertilizer, resulted in increased levels of total nitrogen, total phosphorus, and hydrolysable nitrogen in the soil, as well as a marked enhancement in the activities of soil phosphatase, amylase, and nitrate reductase. Furthermore, the combination of CoT10 with other endophytes in organic fertilizer improved the functionality of the other microorganisms and the efficiency of organic fertilizer utilization. This study underscores the synergistic effects of endophytes and organic fertilizers, providing scientific insights and practical strategies for the sustainable cultivation of C. oleifera. Full article

The heterogeneity of shale pore systems, which is controlled by thermal maturation, fundamentally governs hydrocarbon storage and migration. Artificial sequence maturity samples of Xiamaling shale were obtained through a temperature–pressure simulation experiment (350–680 °C, 15–41 MPa). In combination with low-pressure CO₂/N₂ adsorption experiments, mercury intrusion porosimetry experiments and fractal theory, the heterogeneity of the pore size distribution of micropores, mesopores and macropores in shale of different maturities was quantitatively characterized. The results reveal that the total porosity follows a four-stage evolution with thermal maturity (R_o = 0.62–3.62%), peaking at 600 °C (R_o = 3.12%). Multifractal parameters indicate that areas with a low probability density are dominant in terms of pore size heterogeneity, while monofractal parameters reflect enhanced uniform development in ultra-over maturity (R_o > 3.2%). A novel Fractal Quality Index (FQI) was proposed to integrate porosity, heterogeneity, and connectivity, effectively classifying reservoirs into low-quality, medium-quality, and high-quality sweet-spot types. The findings contribute to the mechanistic understanding of pore evolution and offer a fractal-based framework for shale gas reservoir evaluation, with significant implications for hydrocarbon exploration in unconventional resources. Full article

Compared with powder metallurgy, centrifugal casting, jet molding, and other technologies, Laser Melting Deposition (LMD) stands out as an advanced additive manufacturing technology that provides substantial advantages in the melt forming of functional gradient materials and composites. However, when high-temperature and high-speed laser energy is applied, the resulting materials are susceptible to porosity, which restricts their extensive use in fatigue-sensitive applications such as turbine engine blades, engine connecting rods, gears, and suspension system components. Since fatigue cracks generally originate near pore defects or at stress concentration points, it is crucial to investigate evaluation methods for pore defects and stress concentration in LMD applications. This study examines the effect of pore defects on stress concentration in LMD-manufactured AlSi10Mg using the crystal plasticity finite element method and proposes a stress concentration coefficient characterization approach that considers pore size, morphology, and location. The simulation results indicate a competitive mechanism between pores and grains, where the larger entity dominates. Regarding the influence of aspect ratio on stress concentration, as the aspect ratio decreases along the stress direction, the stress concentration increases significantly. When pores are just emerging from the surface (s/r = 1), the stress concentration caused by the pore reaches its maximum, posing the highest risk of material failure. To assess the extent to which the aspect ratio, position, and size of pores affect stress concentration, a statistical correlation analysis of these variables was conducted. Full article

To duly and correctly deliver parcels, both the capacity and the delivery route of a delivery vehicle need to be considered. Thus, the delivery process of a delivery vehicle can be characterized as a capacitated vehicle routing problem with three-dimensional loading constraints (3L-CVRP), which is an NP-hard problem. To solve the problem, a mathematical model is established in this paper to minimize the total delivery distance and maximize the loading rate, simultaneously. Additionally, a hybrid algorithm that combines a three-dimensional (3D) packing algorithm based on the residual space optimized (RSO) strategy and an improved genetic algorithm (IGA) is proposed. Initially, the proposed hybrid algorithm employs a modified Clarke–Wright savings algorithm to generate a feasible set of route solutions. Furthermore, building upon the traditional genetic algorithm, an elite retention strategy is introduced, and an enhanced order crossover method is utilized to improve the stability of the hybrid algorithm and its global search capability for optimal solutions. Finally, during each iteration of the algorithm, the RSO algorithm is integrated to verify the feasibility of 3D packing scheme. Two comparative experiments are conducted on 22 modified benchmark instances and actual logistics data of a university against two other algorithms, demonstrating that the proposed RSO-IGA algorithm achieves superior solutions in delivery efficiency. Full article

This paper presents an enhanced bipolar control strategy for 400 Hz three-phase inverters in aviation ground power supplies, with a focus on maintaining symmetry in power output under unbalanced load conditions. The strategy integrates Linear Active Disturbance Rejection Control (LADRC) for robust positive sequence voltage regulation, Proportional Integral with repetitive control (PI + RC) for harmonic suppression in positive sequence currents, and a Quasi-Proportional Resonance (QPR) controller for negative sequence components in the static coordinate system. By doing so, it simplifies negative sequence control and combines PI + RC to improve the dynamic response and eliminate periodic errors. In the context of symmetry, the proposed strategy effectively reduces the total harmonic distortion (THD) and the three-phase current imbalance degree. Simulation results show significant improvements: under balanced loads, THD is reduced by 41.5% (from 1.95% to 1.14%) compared to traditional PI control; under single-phase and three-phase unbalanced loads, THD decreases by 52.7% (2.56% to 1.21%) and 48.1% (2.39% to 1.24%), respectively. The system’s settling time during load transients is shortened by over 30%, and the three-phase current imbalance degree is reduced by 60–70%, which validates the strategy’s effectiveness in enhancing power quality and system stability, thus restoring and maintaining the symmetry of the power output. Full article

Host metabolic reprogramming is a critical strategy employed by many viruses to support their replication, and the key metabolic enzyme plays important roles in virus infection. This study investigates the role of pyruvate kinase M2 (PKM2), a glycolytic enzyme with non-canonical functions, in the replication of classical swine fever virus (CSFV). Using PK-15 cells and piglet models, we demonstrate that CSFV infection upregulates PKM2 expression both in vitro and in vivo, creating a proviral environment. knockdown of PKM2 by siRNA reduced CSFV proliferation, while PKM2 overexpression significantly increased virus propagation, which was evaluated by viral protein synthesis, genome replication, and progeny virion production. A direct interaction between PKM2 and CSFV NS5B protein was identified by co-immunoprecipitation and GST-pulldown assays, and PKM2 affected NS5B polymerase activity in a dual-luciferase reporter assay, with PKM2 depletion reducing RdRp function by 50%. Temporal analysis of the first viral replication cycle confirmed PKM2-dependent enhancement of CSFV RNA synthesis. These findings establish PKM2 as a proviral host factor that directly binds NS5B to potentiate RdRp activity, thereby bridging metabolic adaptation and viral genome replication. This study provides new evidence of a glycolytic enzyme physically interacting and enhancing viral polymerase function, offering new information about CSFV–host interaction. Full article

The objective of this study was to enhance the tracking effectiveness of the position adjustment for the electronic throttle in electric vehicles, as well as boost fuel efficiency and the dynamic performance of the vehicles. Firstly, a mathematical model, which pertains to the electronic throttle system, is established, and subsequently, the nonlinear uncertain system is made into a linear uncertain system. Subsequently, a self-coupling PID control law is designed, and an analysis is conducted on the system’s stability and its capacity to reject disturbances. Secondly, taking into consideration that the parameters of the PID controller with self-coupling mechanism are related to the system’s response speed, disturbance rejection capability, and overshoot, a self-adjusting speed factor transition function is put forward to address the conflict between speed and overshoot. Finally, numerical simulations and experimental tests are carried out. The results verify that, compared with the conventional PID controller, ADRC (Active Disturbance Rejection Control), and fuzzy PID, the proposed controller has a faster response speed, higher control accuracy, and better robustness. Full article

In this paper, a digitalized polarization fading suppression and phase demodulation technique for a phase-sensitive optical time-domain reflectometry (φ-OTDR) sensing system utilizing polarization diversity virtual coherence is proposed, in which virtual cross-coherence between the polarization diversity digital signals is employed for simultaneous fading noise suppression and phase demodulation. The principle of the proposed demodulation algorithm is presented and analyzed. Based on this, the practicability and validity of the proposed demodulation method for fading noise suppression and distributed vibration sensing are confirmed through experiments. The experimental results indicate that the proposed demodulation scheme can effectively reduce the polarization fading noise caused by the polarization mismatch between the probe light and the reference light, and the phase changes induced by external interference can also be accurately recovered with a signal-to-noise ratio (SNR) of vibration signal localization of 27.14 dB and an SNR of vibration signal phase demodulation of 47.88 dB, which provides a simplified method for simultaneous polarization fading suppression and the phase demodulation of the φ-OTDR system. Full article