Search Results (18,719)

Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technology, with its advantages in large-scale and high-precision deformation monitoring, has become an essential tool for monitoring surface subsidence in coal mining areas. To address the issue of missing deformation values resulting from interferometric decoherence when using InSAR technology for surface subsidence monitoring in mining areas, this study proposes a combined approach integrating SBAS-InSAR with KTree Adaptive Inverse Distance Weighting (KTree-AIDW). The method constructs a dynamic neighborhood search mechanism through the KTree algorithm, considering the spatial heterogeneity between the interpolation points and adjacent sample points, and optimizes the weight distribution of heterogeneous sample points. The study is based on Sentinel-1 data with a 12-day revisit cycle, focusing on the 2021 grouting working face of the Liangbei Mine in Yuzhou, Henan Province, China. The results show the following: (1) Along both the strike and dip lines, the correlation coefficient between the SBAS-InSAR + KTree-AIDW results and leveling result is 0.95, with an overall root mean square error (RMSE) of 22.08 mm and a relative root mean square error (RRMSE) of 9.48%. The Mean Absolute Error (MAE) of characteristic points in the decoherence region is 19.05 mm, indicating a significantly improved accuracy in the decoherence region compared to traditional methods. (2) The cumulative maximum subsidence in the study area reached 233 mm, with an average maximum subsidence rate of 171 mm/yr. The maximum positive/negative inclines were 2.4 mm/m and −2.9 mm/m; the maximum positive/negative curvatures were ±0.18 mm/m². The surface structures are within the threshold values specified for Class I damage. The proposed method effectively addresses the decoherence issue that leads to missing deformation data in mining areas, providing a novel technical approach to accurate surface subsidence monitoring under grouting and backfilling conditions. Full article

Objective: The Mediterranean diet (MedDiet) is characterized by its emphasis on plant-based foods, olive oil, and fish products, and has been associated with providing relevant fatty acids (FAs) for adolescent physiology. This study aims to investigate the relationship between adherence to the MedDiet and the FA composition of red blood cell (RBC) membranes in an adolescent population. Methods: The current research examines the relationship between MedDiet adherence, assessed using the KIDMED questionnaire, and the composition of RBC membranes, specifically measuring 22 FAs in a cross-sectional analysis of adolescents from two cohorts (mean age = 14.55). Baseline data from 552 participants with complete dietary adherence and FA information were analyzed using multivariable regression models and principal component analysis (PCA) as confirmatory analysis. All regression models were adjusted by age, sex, body mass index, physical activity, maternal education and cohort enrollment. Results: Main results shown that “Good adherence” to the MedDiet was positively associated with omega-3 FAs, including eicosapentaenoic acid (β = 0.34; 95% CI: 0.17, 0.52; p-value < 0.001) and docosahexaenoic acid (β = 0.29; 95% CI: 0.11, 0.46; p-value = 0.001), and inversely associated with specific omega-6 FAs, such as arachidonic acid (β = −0.28; 95% CI: −0.46, −0.11; p-value = 0.002) and adrenic acid (β = −0.19; 95% CI: −0.30, −0.08; p-value < 0.001). PCA identified distinct FA patterns, with “Good adherence” to the MedDiet being associated with an increase in the omega-3 FAs pattern (β = 0.32; 95% CI: 0.14, 0.49; p-value < 0.001). These findings remained robust after multiple test comparisons. Conclusions: This study underscores the potential of the MedDiet to promote optimal RBC FA composition in healthy adolescents, characterized by high levels of omega-3 FAs and reduced levels of arachidonic acid and adrenic acid in RBC membranes. Full article

This study explores advanced methods for analyzing the two-parameter alpha-power exponential (APE) distribution using data from a novel generalized progressive hybrid censoring scheme. The APE model is inherently asymmetric, exhibiting positive skewness across all valid parameter values due to its right-skewed exponential base, with the alpha-power transformation amplifying or dampening this skewness depending on the power parameter. The proposed censoring design offers new insights into modeling lifetime data that exhibit non-monotonic hazard behaviors. It enhances testing efficiency by simultaneously imposing fixed-time constraints and ensuring a minimum number of failures, thereby improving inference quality over traditional censoring methods. We derive maximum likelihood and Bayesian estimates for the APE distribution parameters and key reliability measures, such as the reliability and hazard rate functions. Bayesian analysis is performed using independent gamma priors under a symmetric squared error loss, implemented via the Metropolis–Hastings algorithm. Interval estimation is addressed using two normality-based asymptotic confidence intervals and two credible intervals obtained through a simulated Markov Chain Monte Carlo procedure. Monte Carlo simulations across various censoring scenarios demonstrate the stable and superior precision of the proposed methods. Optimal censoring patterns are identified based on the observed Fisher information and its inverse. Two real-world case studies—breast cancer remission times and global oil reserve data—illustrate the practical utility of the APE model within the proposed censoring framework. These applications underscore the model’s capability to effectively analyze diverse reliability phenomena, bridging theoretical innovation with empirical relevance in lifetime data analysis. Full article

A bioresorbable cannulated bone screw was developed using PLA/PCL-based composites reinforced with hydroxyapatite (HA) and titanium dioxide (TiO₂), two additives previously reported to enhance mechanical compliance, biocompatibility, and molding feasibility in biodegradable polymer systems. The design incorporated a crest-trimmed thread and a strategically positioned gate in the thin-wall zone opposite the hexagonal socket to preserve torque-transmitting geometry during micromolding. To investigate shrinkage behavior, a Taguchi orthogonal array was employed to systematically vary micromolding parameters, generating a structured dataset for training a back-propagation neural network (BPNN). Analysis of variance (ANOVA) identified melt temperature as the most influential factor affecting shrinkage quality, defined by a combination of shrinkage rate and dimensional variation. A hybrid AI framework integrating the BPNN with genetic algorithms and particle swarm optimization (GA–PSO) was applied to predict the optimal shrinkage conditions. This is the first use of BPNN–GA–PSO for cannulated bone screw molding, with the shrinkage rate as a targeted output. The AI-predicted solution, interpolated within the Taguchi design space, achieved improved shrinkage quality over all nine experimental groups. Beyond the specific PLA/PCL-based systems studied, the modeling framework—which combines geometry-specific gate design and normalized shrinkage prediction—offers broader applicability to other bioresorbable polymers and hollow implant geometries requiring high-dimensional fidelity. This study integrates composite formulation, geometric design, and data-driven modeling to advance the precision micromolding of biodegradable orthopedic devices. Full article

Fruit tree rootstock breeding is prolonged by extended juvenile phases, high heterozygosity, limited germplasm diversity, and hybrid incompatibilities, often requiring four decades to release new cultivars. Direct somatic embryogenesis (DSE) in established peach rootstocks presents a promising avenue for rapid genetic transformation and breeding. However, peach is highly recalcitrant to in vitro regeneration, posing major challenges for organogenesis and somatic embryogenesis (SE). This study evaluated the effects of 2,4-dichlorophenoxyacetic acid (2,4-D) and Kinetin (KIN) on SE %, SE productivity, and callus % rate in the widely used Guardian^® peach rootstock. A 5 × 3 full factorial completely randomized design was used to test 15 different combinations of 2,4-D and KIN on immature cotyledons, classified as upper or lower based on their position on the preculture medium. Media formulation containing a higher concentration (3.2 µM) of 2,4-D and KIN induced SE in ~50% of lower and ~85% of upper cotyledons. Optimal SE productivity occurred with higher KIN (3.2 µM) and reduced 2,4-D (2.6 µM). Callus formation peaked with 1.8 µM 2,4-D and 3.2 µM KIN. This highly reproducible research establishes a robust whole plant regeneration system via DSE in Guardian^® peach rootstock using immature cotyledons, providing a foundation for expedited trait manipulation through biotechnological approaches. Full article

To address the challenge of postharvest spoilage in flat peaches and white apricots, we developed fermented peach–apricot mixed juice (PAMJ) using these fruits as raw materials through multi-strain synergistic fermentation. Its fermentation processes were optimised through uniform design and single-factor experiments. The flavour characteristics of PAMJ were analysed using an electronic nose, an electronic tongue, gas chromatography–mass spectrometry (GC-MS) and sensory evaluation indices. PAMJ demonstrated optimal performance in terms of peach–apricot flavour profile, sweetness-sourness balance, and overall acceptability, achieving the highest sensory scores. Additionally, GC-MS analysis identified 116 volatile organic compounds, with PAMJ exhibiting the highest contents of terpenes and ketones. PAMJ was identified as the optimal fermentation matrix. Subsequently, response surface methodology was used to optimise its fermentation parameters. PAMJ represented a post-mixing fermentation system wherein peaches and apricots were initially mixed and subsequently fermented with a bacterial consortium comprising Limosilactobacillus fermentum (15%), Lactobacillus acidophilus (10%), Levilactobacillus brevis (34%), Lacticaseibacillus paracasei subsp. Tolerans (13%), Lactiplantibacillus plantarum subsp. plantarum (13%) and Limosilactobacillus reuteri (15%). After fermentation with an initial inoculum concentration of 5.2 × 10⁶ CFU/mL at 37 °C for 20 h, the initial soluble solid content of PAMJ increased from 16 to 16.5 °Brix, superoxide dismutase (SOD) activity increased from 250 to 295 U/mL and the number of volatile compounds (NVC) increased from 60 to 66. Furthermore, the storage stability of pasteurised PAMJ was evaluated by monitoring SOD and NVC at 5-day intervals. The data were analysed using kinetic and Arrhenius equations. The shelf life of PAMJ at 4 °C, 25 °C and 37 °C was 69, 48 and 39 days when NVC was used as the index and 99, 63 and 49 days when SOD activity was used as the index, respectively. These findings indicate that fermentation with lactic acid bacteria exerts positive effects on the quality of mixed juices, providing a novel strategy for processing speciality fruits in Xinjiang. Full article

Robotic milling offers significant advantages for machining large aerospace components due to its low cost and high flexibility. However, compared to computerized numerical control (CNC) machine tools, robot systems exhibit lower stiffness, leading to force-induced deformation during milling process that significantly compromises path accuracy. This study proposed a dynamic robot posture programming method to enhance the stiffness for aluminum alloy milling task. Firstly, a milling force prediction model is established and validated under multiple postures and various milling parameters, confirming its stability and reliability. Secondly, a robot stiffness model is developed by combining system stiffness and milling forces within the milling coordinate system to formulate an optimization index representing stiffness performance in the actual load direction. Finally, considering the constraints of joint limit, singular position and joint motion smoothness and so on, the robot posture in the milling trajectory is dynamically programmed, and the joint angle sequence with the optimal average stiffness from any cutter location (CL) point to the end of the trajectory is obtained. Under the assumption that positioning errors were effectively compensated, the experimental results demonstrated that the proposed method can control both axial and radial machining errors within 0.1 mm at discrete points. For the specific milling trajectory, compared to the single-step optimization algorithm starting from the initial optimal posture, the proposed method reduced the axial error by 12.23% and the radial error by 8.61%. Full article

The development of alternative transportation methods has become paramount in the context of sustainable urban population connectivity. The promise of hyperloop as a high-speed, low-emission travel means motivates both academic and industrial interests. The present work centers on the design of hyperloop levitation systems. A component-level optimization is outlined for the appropriate selection of levitation module geometric parameters, followed by an integration into a capsule and bogie system. Two heteropolar levitation module types are numerically studied in realistic operating conditions: a hybrid electromagnet configuration with permanent magnets and a fully active one. To give means for comparison, both configurations are designed with the aid of a general multi-objective optimization approach. For the hybrid case, a position controller is synthesized with a zero-power policy and a specific frequency response function. The active configuration features comparable behavior. Two main power consumption streams are considered: gap control and magnetic drag. While the former depends on the position control effort, the latter depends on the losses of ferromagnetic elements. The two systems are compared in smooth and irregular track conditions over the studied speed range of 400–700 km/h. This study demonstrates that the hybrid heteropolar case achieves a minimum of 97.6% in specific power consumption reduction at the maximum speed of 700 km/h under smooth track conditions. Under irregular track conditions, a benefit in average specific consumption reduction is noted up to 662 km/h for the hybrid case. The maximum reduction in specific consumption is 57.2% at the minimum speed of 400 km/h. Full article

Data of operational conditions of structural components, acquired, e.g., in structural health monitoring (SHM), is of great interest to optimise products from one generation to the next, for example, by adapting them to occurring operational loads. To acquire data for this purpose in the desired quality, an optimal sensor placement for so-called shape and load sensing is required. In the case of large-scale structural components, wireless sensor networks (WSN) could be used to process and transmit the acquired data for real-time monitoring, which furthermore requires an optimisation of sensor node positions. Since most publications focus only on the optimal sensor placement or the optimisation of sensor node positions, a methodology for both is implemented in a Python tool, and an optimised WSN is realised on a demonstration part, loaded at a test bench. For this purpose, the modal method is applied for shape sensing as well as a physics-informed neural network for solving inverse problems in shape sensing (iPINN). The WSN is realised with strain gauges, HX711 analogue-digital (A/D) converters, and Arduino Nano 33 IoT microprocessors for data submission to a server, which allows real-time visualisation and data processing on a Python Flask server. The results demonstrate the applicability of the presented methodology and its implementation in the Python tool for achieving high-accuracy shape sensing with WSNs. Full article

This study aims to investigate the effects of dietary supplementation with different concentrations of oligofructose (FOS) on growth performance, antioxidant capacity, immunity, and intestinal microbial composition in growing rabbits. One hundred female Dehua black rabbits (34 d of age) were randomly assigned to four groups (CON, FOS-1, FOS-2, and FOS-3), with twenty-five rabbits in each group. The CON group received only a basal diet, while the FOS-1/FOS-2/FOS-3 group received the diet supplemented with 0.3%/0.6%/0.9% FOS, respectively. The trial period lasted for 72 days. Our results revealed that FOS supplementation could improve the growing performance of rabbits and decrease the feed/gain ratio. FOS significantly enhanced serum antioxidant enzyme (SOD) and total antioxidant capacity (T-AOC) while reducing malondialdehyde (MDA). The levels of plasmic immunoglobulin (IgG, IgA, and IgM) and intestinal immune factors (IL-1α, IL-2, and sIgA) were significantly improved with the FOS supplement. Additionally, FOS can improve intestinal morphology and enhance the activity of intestinal enzymes, including cellulase, lipase, and protease. Furthermore, FOS supplementation influenced the composition of intestinal microflora by increasing the abundance of Lachnospiraceae_NK4A136_group (barrier-enhancing) and Monoglobus (fiber-degrading). In conclusion, the addition of FOS has a positive impact on the growth performance, antioxidant capacity, immunity, and intestinal health of growing rabbits. The optimal dietary addition for rabbits was identified as 0.6% oligofructose. Full article

A systematic investigation was conducted on the laser shock forming (LSF) process of carbon steel Q355ME sheets and practical skin components, focusing on the influence of absorption layer types, laser energy, and impact cycles on forming capacity and surface properties. Three kinds of absorbing layers were compared in the experiment: no absorbing layer, 0.1 mm aluminum foil and 0.12 mm black tape. The results show that when the black tape is used as the absorbing layer, the forming effect is the best, the arc height value reaches 2.63 mm, and the radius of curvature is 1066 mm. Using 0.1 mm thick black tape as the absorption layer and laser parameters of 10% overlap rate, 15 ns pulse width, 4 mm spot, and 1064 nm wavelength, the single impact of 13 J, 15 J, and 17 J, and one, two, and three impacts of 15 J energy were carried out on the plate. It was found that the increase in laser energy and impact times resulted in increases in deformation, surface roughness, microhardness, and residual stress of the plate. The surface work hardening phenomenon of Q355ME plate after laser shock slowed down the increase in these performance parameters. The experimental results show that the laser energy is linearly positively correlated with the residual stress in a certain energy range. Under the optimized laser process parameters, the forming error of the actual skin parts is controlled within ± 0.4 mm, the surface residual stress increases by 368.9%, and the surface microhardness increases by 10.4%. The ultra-high strain plastic deformation and grain refinement on the surface of the sheet were caused by multiple laser shock peenings, which confirmed that LSF technology can improve the formability of carbon steel skin parts and improve its surface properties. Full article

The ocean harbors vast potential for oil and gas resources, positioning offshore drilling as a critical approach for future energy exploration. However, high-temperature and high-pressure offshore reservoirs present formidable challenges, as conventional water-based drilling fluids are prone to thermal degradation and rheological instability, leading to wellbore collapse and stuck-pipe incidents. Offshore oil-based drilling fluids (OBDFs), typically water-in-oil emulsions, offer advantages in wellbore stability, lubricity, and contamination resistance, yet their stability under extreme high-temperature conditions remains limited. This study reveals the enhancement of offshore OBDFs performance in harsh conditions by employing nano-SiO₂ to synergistically improve emulsion film stability and non-Newtonian rheological behavior while systematically elucidating the underlying mechanisms. Nano-SiO₂ forms a composite film with emulsifiers, reducing droplet size, enhancing mechanical strength, and increasing thermal stability. Optimal stability was observed at an oil-to-water ratio of 7:3 with 2.5% nano-SiO₂ dispersion and 4.0% emulsifier. Rheological analyses revealed that nano-silica enhances electrostatic repulsion, reduces plastic viscosity, establishes a network structure that increases yield stress, and promotes pronounced shear-thinning behavior. Macroscopic evaluations, including fluid loss, rheological performance, and electrical stability, further confirmed the improved high-temperature stability of offshore OBDFs with nano-SiO₂ at reduced emulsifier concentrations. These findings provide a theoretical basis for optimizing offshore OBDFs formulations and their field performance, offering breakthrough technological support for safe and efficient drilling in ultra-high-temperature offshore reservoirs. Full article

As a part of sustainable transportation, robotaxis have been rapidly developing around the world because of their advantages in energy saving, improving road safety, and enhancing environmental sustainability, thereby providing consumers with sustainable transportation services. In China, as the number of pilot cities increases, more people are using robotaxi services. This study investigates the factors that affect consumer satisfaction and behavioral intentions after using a robotaxi, aiming to provide data to guide market strategy decisions. To do this, the value-based adoption model was extended and modified by including the technology readiness variable to examine satisfaction, intention to reuse, and electronic word-of-mouth (e-WOM) intentions. Using 425 valid responses, structural equation modeling (SEM) and multi-group analysis were carried out with AMOS 26.0. The results indicate that perceived usefulness, enjoyment, optimism, and innovativeness positively influence service satisfaction, whereas perceived risk and discomfort have negative effects. Consumer satisfaction positively affects both intention to reuse and e-WOM intention. Additionally, uncertainty avoidance shows a moderating effect between satisfaction and intention to reuse. Full article

To meet the vibration isolation requirements of engines under diverse operating conditions, this paper proposes a novel magnetorheological fluid-elastomer isolator with high load and tunable parameters. The mechanical and magnetic circuit structures of the isolator were designed and optimized through theoretical calculations and finite element simulations, achieving effective vibration isolation within confined spaces. The dynamic performance of the isolator was experimentally evaluated using a hydraulic testing system under varying excitation amplitudes, frequencies, initial positions, and magnetic fields. Experimental results indicate that the isolator achieves a static stiffness of 3 × 10⁶ N/m and a maximum adjustable compression load range of 105.4%. In light of the asymmetric nonlinear dynamic behavior of the isolator, an improved nine-parameter Bouc–Wen model is proposed. Parameter identification performed via a genetic algorithm demonstrates a model accuracy of 95.0%, with a minimum error reduction of 28.8% compared to the conventional Bouc–Wen model. Full article

Wheat domestication and selection for aboveground traits may have influenced belowground traits, reducing genetic diversity critical for adaptation to stress such as drought. However, the impacts on root system architecture and root–endophytic fungal interactions remain unclear. This study evaluated variation in root traits and associations with arbuscular mycorrhizal fungi (AMF) and dark septate endophytes (DSE) among nine diploid Aegilops tauschii accessions (wild progenitor), one tetraploid Triticum turgidum cv. ‘Langdon’ (LNG), and one hexaploid Triticum aestivum cv. ‘Norin 61’ (N61). Root traits and fungal colonization varied significantly among genotypes. All Ae. tauschii accessions showed superior root development and lower (DSE) colonization compared to LNG and N61. AMF colonization was highest in accessions AT76 and KU-2126 (54% and 53%, respectively), while N61 exhibited the highest specific root length (SRL) and (DSE) colonization. AMF positively correlated with most root traits (except SRL), while (DSE) showed the opposite trend. Although Ae. tauschii accessions shared broadly favorable root traits, variation in their fungal interactions were more pronounced. A clustering heatmap incorporating both root and biotic traits clustered the genotypes into four groups, clearly separating the Ae. tauschii accessions into two clusters based on their root characteristics and root-fungal associations. These results highlight the hidden interspecific and intraspecific variations in Ae. tauschii and its potential as a genetic resource for optimizing root–endophytic fungal interactions, and improving wheat resilience to biotic and abiotic stress in a changing climate. Full article