Search Results (784)

Chimonanthus praecox, a traditional ornamental plant in China, is admired for its ability to bloom during the cold winter season and is recognized as an outstanding woody cut flower. MADS-box genes encode transcription factors essential for plant growth and development, with key functions in regulating flowering time and the formation of floral organs. In this study, 74 MADS-box genes (CpMADS1–CpMADS74) were identified and mapped across 11 chromosomes, with chromosome 1 harboring the highest number (13 genes) and chromosome 3 the fewest (3 genes). Physicochemical property analysis revealed that all CpMADS proteins are hydrophilic and predominantly nuclear-localized. Phylogenetic analysis classified these genes into Type I and Type II subfamilies, highlighting a clear divergence in domain structure. Eighty simple sequence repeat (SSR) loci were detected, with dinucleotide repeats being the most abundant, and the majority located in Type II MADS genes. From 23 C. praecox samples, 10 polymorphic SSR markers were successfully developed and PCR-validated, enabling a cluster analysis that grouped these cultivars into three distinct clusters. This study offers significant insights into the regulation of flowering, floral organ development, genetic linkage map construction, and the application of marker-assisted selection in C. praecox. Full article

Aiming to resolve the problem of the poor peanut seed-filling effect under high-speed operation when developing high-speed peanut sowing with precision, a peanut precision seed-metering machine with an auxiliary air-suction seed-filling device was designed. Focusing on the force analysis of peanuts in the seed chamber, the peanut seed disturbance principle in the seed-metering machine for the blowing structure of an auxiliary air-suction seed-filling device was clarified. The seed-filling process was analyzed via DEM-CFD coupled simulation, and three factors affecting the seed-filling effect were identified, namely the seed-filling chamber ‘V’ angle γ, the bottom blow-air-hole cross-sectional area S, and the bottom blow-air-hole airflow velocity v_q, and the ranges of values of the three factors were determined. The Box–Behnken test was conducted using the seed-filling index and leakage index as the indexes. The results show that the seed-filling chamber ‘V’ angle γ is 56.59°, the bottom blowhole cross-sectional area S is 1088.4 mm², and the blowhole air velocity v_q is 12.11 m·s⁻¹. At this point, the peanut seed suction qualification index and leakage index are optimal, the seed suction qualification index is 96.33%, and the seed leakage index is 2.59%. At the same time, the field test shows that a sowing operation speed of 8–12 km·h⁻¹, a qualified index > 93%, and a leakage index < 4.5% are required to meet the agronomic requirements of peanut precision sowing. Full article

Sensing transparent objects has many applications in human daily life, including robot navigation and grasping. However, this task presents significant challenges due to the unpredictable nature of scenes that extend beyond/behind transparent objects, particularly the lack of fixed visual patterns and strong background interference. This paper aims to solve the transparent object segmentation problem by leveraging the intrinsic global modeling capabilities of transformer architectures. We design a Query Parsing Module (QPM) that innovatively formulates segmentation as a dictionary lookup problem, differing fundamentally from conventional pixel-wise mechanisms, e.g., via attention-based prototype matching, and a set of learnable class prototypes as query inputs. Based on QPM, we propose a high-performance transformer-based end-to-end segmentation model, Transparent Object Segmentation through Query (TOSQ). TOSQ’s encoder is based on the Segformer’s backbone, and its decoder consists of a series of QPM modules, which progressively refine segmentation masks by the proposed QPMs. TOSQ achieves state-of-the-art performance on the Trans10K-V2 dataset (76.63% mIoU, 95.34% Acc), with particularly significant gains in challenging categories like windows (+23.59%) and glass doors (+11.22%), demonstrating its superior capability in transparent object segmentation. Full article

Expansive soils, characterized by the presence of surface and subsurface cracks, over-consolidation, and swell-shrink properties, present significant challenges to slope stability in geotechnical engineering. Despite extensive research, preventing geohazards associated with expansive soils remains unresolved. This study investigates shallow sliding failures in slopes of highly expansive soils induced by rainfall, using model tests to explore deformation and mechanical behavior under cyclic wetting and drying conditions, focusing on the interaction between soil properties and environmental factors. Model tests were conducted in a wedge-shaped box filled with Nanyang expansive clay from Henan, China, which is classified as high-plasticity clay (CH) according to the Unified Soil Classification System (USCS). The soil was compacted in four layers to maintain a 1:2 slope ratio (i.e., 1 vertical to 2 horizontal), which reflects typical expansive soil slope configurations observed in the field. Monitoring devices, including moisture sensors, pressure transducers, and displacement sensors, recorded changes in soil moisture, stress, and deformation. A static treatment phase allowed natural crack development to simulate real-world conditions. Key findings revealed that shear failure propagated along pre-existing cracks and weak structural discontinuities, supporting the progressive failure theory in shallow sliding. Cracks significantly influenced water infiltration, creating localized stress concentrations and deformation. Atmospheric conditions and wet-dry cycles were crucial, as increased moisture content reduced soil suction and weakened the slope’s strength. These results enhance understanding of expansive soil slope failure mechanisms and provide a theoretical foundation for developing improved stabilization techniques. Full article

With the increasing severity of traffic congestion, the impact of random traffic patterns has emerged as an indispensable factor in the fatigue design and assessment of highway bridges. In this study, an analytical approach has been proposed for modeling the effects of random traffic patterns on fatigue damage. A fatigue damage ratio, referred to as RPEF, is introduced to establish the correlation between damage and traffic characteristics. Two quantitative parameters representing two characteristics of traffic loads, namely the average loading occurrence number (scale parameter) and the vehicle headway COVs (shape parameter), have been found to be excellent indices for clustering the different dimensional randomness of RPEFs. Based on a comprehensive case study, the realization of using equivalent RPEFs to evaluate bridge fatigue damage under mixed traffic conditions was explored. The results indicate that the actual fatigue damage of bridges can be evaluated through the superposition of different traffic pattern effects, provided that the pattern classification number fits the fluctuations in traffic flow. It is necessary to ensure the rationality of traffic pattern classification for structures with spans greater than 50 m, as an overly simplistic traffic pattern classification may lead to an underestimation of fatigue damage. Full article

Due to the long operation period of Beijing Metro Line 2 and the complex surrounding building environment, this paper comprehensively studied the mechanical properties of new tunnels using close-fitting undercrossing based on pre-support technology. To control structural deformation caused by the expansion project, methods such as laboratory tests, numerical simulation, and field tests were adopted to systematically analyze the tunnel mechanics during the undercrossing of existing metro lines. First, field tests were carried out on the existing Line 2 and Line 3 tunnels during the construction period. It was found that the close-fitting construction based on pre-support technology caused small deformation displacement in the subway tunnels, with little impact on the smoothness of the existing subway rail surface. The fluctuation range was −1 to 1 mm, ensuring the safety of existing subway operations. Then, a refined finite difference model for the close-fitting undercrossing construction process based on pre-support technology was established, and a series of field and laboratory tests were conducted to obtain calculation parameters. The reliability of the numerical model was verified by comparing the monitored deformation of existing structures with the simulated structural forces and deformations. The influence of construction methods on the settlement changes of existing line tracks, structures, and deformation joints was discussed. The research results show that this construction method effectively controls the settlement deformation of existing lines. The settlement deformation of existing lines is controlled within 1~3 cm. The deformation stress of the existing lines is within the concrete strength range of the existing structure, and the tensile stress is less than 3 MPa. The maximum settlement and maximum tensile stress of the station in the pre-support jacking scheme are −5.27 mm and 2.29 MPa. The construction scheme with pre-support can more significantly control structural deformation, reduce stress variations in existing line structures, and minimize damage to concrete structures. Based on the monitoring data and simulation results, some optimization measures were proposed. Full article

The phototherapeutic applications of porphyrin-based nanoscale metal–organic frameworks (nMOFs) are limited by the poor penetration of conventional excitation light sources into biological tissues. Radiodynamic therapy (RDT), which directly excites photosensitizers using X-rays, can overcome the issue of tissue penetration. However, RDT faces the problems of low energy conversion efficiency, requiring a relatively high radiation dose, and the potential to cause damage to normal tissues. Researchers have found that by using some metals with high atomic numbers (high Z) as X-ray scintillators and coordinating them with porphyrin photosensitizers to form MOF materials, the excellent antitumor effect of radiotherapy (RT) and RDT can be achieved under low-dose X-ray irradiation, which can not only effectively avoid the penetration limitations of light excitation methods but also eliminate the defect issues associated with directly using X-rays to excite photosensitizers. This review summarizes the relevant research work in recent years, in which researchers have used metal ions with high Z, such as Hf⁴⁺, Th⁴⁺, Ta⁵⁺, and Bi³⁺, in coordination with carboxyl porphyrins to form MOF materials for combined RT and RDT toward various cancer cells. This review compares the therapeutic effects and advantages of using different high-Z metals and introduces the application of the heavy atom effect. Furthermore, it explores the introduction of a chemodynamic therapy (CDT) mechanism through iron coordination at the porphyrin center, along with optimization strategies such as oxygen delivery using hemoglobin to enhance the efficacy of these MOFs as radiosensitizers. This review also summarizes the potential of these materials in preclinical applications and highlights the current challenges they face. It is expected that the summary and prospects outlined in this review can further promote preclinical biomedical research into and the development of porphyrin-based nMOFs. Full article

In the operation of enhanced geothermal systems (EGSs), complex physical and chemical coupling processes, which are crucial for the efficient exploitation of geothermal energy, are involved. In situ studies of multi-fracture hot dry rocks (HDRs) face significant challenges, leading to a shortage of experimental data for verifying numerical simulations and supporting experimental techniques. In this paper, a multi-field coupling experimental simulation technique was designed for a multi-fracture geothermal reservoir. This technique enables the experimental investigation of the effects of fracture and reservoir characteristics, working fluid parameters, and wellbore arrangement on the multi-field coupling transport mechanism inside geothermal reservoirs during EGS operation. In addition, the practicability and reliability of the experimental technique were proved via a two-dimensional multi-fracture model. The experimental technique addresses a research gap in studying multi-fracture geothermal reservoirs and holds potential to promote substantial progress in geothermal resource exploitation. Full article

This paper investigates the super-resolution reconstruction technology of coarse granular particle images for embankment construction in earth/rock dams based on Real-ESRGAN, aiming to improve the quality of low-resolution particle images and enhance the accuracy of particle shape analysis. The paper begins with a review of traditional image super-resolution methods, introducing Generative Adversarial Networks (GAN) and Real-ESRGAN, which effectively enhance image detail recovery through perceptual loss and adversarial training. To improve the generalization ability of the super-resolution model, the study expands the morphological database of earth/rock dam particles by employing a multi-modal data augmentation strategy, covering a variety of particle shapes. The paper utilizes a dual-stage degradation model to simulate the image degradation process in real-world environments, providing a diverse set of degraded images for training the super-resolution reconstruction model. Through wavelet transform methods, the paper analyzes the edge and texture features of particle images, further improving the precision of particle shape feature extraction. Experimental results show that Real-ESRGAN outperforms other traditional super-resolution algorithms in terms of edge clarity, detail recovery, and the preservation of morphological features of particle images, particularly under low-resolution conditions, with significant improvement in image reconstruction. In conclusion, Real-ESRGAN demonstrates excellent performance in the super-resolution reconstruction of coarse granular particle images for embankment construction in earth/rock dams. It can effectively restore the details and morphological features of particle images, providing more accurate technical support for particle shape analysis in civil engineering. Full article

Efficient individual identification is essential for advancing precision broiler farming. In this study, we propose YOLO-IFSC, a high-precision and lightweight face recognition framework specifically designed for dense broiler farming environments. Building on the YOLOv11n architecture, the proposed model integrates four key modules to overcome the limitations of traditional methods and recent CNN-based approaches. The Inception-F module employs a dynamic multi-branch design to enhance multi-scale feature extraction, while the C2f-Faster module leverages partial convolution to reduce computational redundancy and parameter count. Furthermore, the SPPELANF module reinforces cross-layer spatial feature aggregation to alleviate the adverse effects of occlusion, and the CBAM module introduces a dual-domain attention mechanism to emphasize critical facial regions. Experimental evaluations on a self-constructed dataset demonstrate that YOLO-IFSC achieves a mAP@0.5 of 91.5%, alongside a 40.8% reduction in parameters and a 24.2% reduction in FLOPs compared to the baseline, with a consistent real-time inference speed of 36.6 FPS. The proposed framework offers a cost-effective, non-contact alternative for broiler face recognition, significantly advancing individual tracking and welfare monitoring in precision farming. Full article

This paper focuses on the use of advanced optimization design strategies to improve the performance and service life of engine pistons, with emphasis on enhancing their stiffness, strength, and dynamic characteristics. As a core component of the engine, the structural design and optimization of the piston are of great significance to its efficiency and reliability. First, a three-dimensional (3D) model of the piston was constructed and imported into ANSYS Workbench for finite element modeling and high-quality meshing. Based on the empirical formula, the actual working environment temperature and heat transfer coefficient of the piston were accurately determined and used as boundary conditions for thermomechanical coupling analysis to accurately simulate the thermal and deformation state under complex working conditions. Dynamic characteristic analysis was used to obtain the displacement–frequency curve, providing key data support for predicting resonance behavior, evaluating structural strength, and optimizing the design. In the optimization stage, five geometric dimensions are selected as design variables. The deformation, mass, temperature, and the first to third natural frequencies are considered as optimization goals. The response surface model is constructed by means of the design of the experiments method, and the fitted model is evaluated in detail. The results show that the models are all significant. The adequacy of the model fitting is verified by the “Residuals vs. Run” plot, and potential data problems are identified. The “Predicted vs. Actual” plot is used to evaluate the fitting accuracy and prediction ability of the model for the experimental data, avoiding over-fitting or under-fitting problems, and guiding the optimization direction. Subsequently, the sensitivity analysis was carried out to reveal the variables that have a significant impact on the objective function, and in-depth analysis was conducted in combination with the response surface. The multi-objective genetic algorithm (MOGA), screening, and response surface methodology (RSM) were, respectively, used to comprehensively optimize the objective function. Through experiments and analysis, the optimal solution of the MOGA algorithm was selected for implementation. After optimization, the piston mass and deformation remained relatively stable, and the working temperature dropped from 312.75 °C to 308.07 °C, which is conducive to extending the component life and improving the thermal efficiency. The first to third natural frequencies increased from 1651.60 Hz to 1671.80 Hz, 1656.70 Hz to 1665.70 Hz, and 1752.90 Hz to 1776.50 Hz, respectively, significantly enhancing the dynamic stability and vibration resistance. This study integrates sensitivity analysis, response surface models, and genetic algorithms to solve multi-objective optimization problems, successfully improving piston performance. Full article

This study explores the swelling behavior of strong expansive soil from the Nanyang Section II canal bed of the South-to-North Water Diversion Middle Route Project, with practical relevance to foundation engineering. A total of 45 one-dimensional swelling tests were performed using a lever-type consolidation apparatus under K₀ stress conditions. The test matrix covered three dry densities (1.45, 1.50, and 1.55 g/cm³), three initial moisture contents (20%, 25%, and 30%) and five overburden pressures (0, 12.5, 25, 50, and 100 kPa). Results indicated that the swelling rate decreased in a logarithmic pattern with increasing pressure and was strongly influenced by compaction level and initial moisture. The highest observed swelling rate was 14.96% under zero loading. Based on the experimental data, a semi-empirical model was developed that accounts for dry density, water content, and overburden pressure. The model showed strong agreement with the test results (R² = 0.9888) and was further validated using an independent dataset (dry density = 1.60 g/cm³), achieving R² = 0.981 and RMSE = 0.606%. The proposed model serves as a practical tool for predicting swelling-induced deformation and supports engineering decisions on compaction, moisture conditioning, and foundation stability in expansive soil regions. Full article

Modular multiplication is a pivotal operation in public-key cryptosystems such as RSA, ElGamal, and ECC. Modular multiplication design is crucial for improving overall system performance due to the large-bit-width operation with high computational complexity. This paper provides a classification of integer multiplication algorithms based on their implementation principles. Furthermore, the core concepts, implementation challenges, and research advancements of multiplication algorithms are systematically summarized. This paper also gives a brief overview of modular reduction algorithms for various types of moduli and discusses the implementation principles, application scenarios, and current research results. Finally, the detailed research development of modular multiplication algorithms in four major classes over prime fields is deeply analyzed and summarized, making it essential as a guide for future research. Full article

Induction in pineapples requires the targeted delivery of specific chemical solutions into the plant’s central core to enable batch management, a task currently reliant on manual operation. This study addressed this challenge by analyzing the physical characteristics of pineapple plants and establishing a perception-based mathematical model for core position localization. An integrated hardware–software system was developed, complemented by a human–machine interface for real-time operational monitoring. Comprehensive experiments were conducted to evaluate the spraying accuracy, nozzle response time, and prototype performance. The results demonstrate that the actuation system—comprising solenoid valves, pumps, and flowmeters—achieved an average spraying error of 2.72%. The average nozzle opening/closing time was 0.111 s; with a standard operating speed of 0.5 m/s, a delay compensation distance of 55.5 mm was implemented. In human–machine comparative trials, the automated system outperformed manual spraying in both efficiency and stability, with average errors of 7.1% and 6.4%, respectively. The system reduced chemical usage by over 67,500 mL per hectare while maintaining a miss-spray rate of 5–6%. Both two-tailed tests revealed extremely significant differences (p < 0.001). These findings confirm that the developed solution meets the operational requirements for pineapple floral induction, offering significant improvements in precision and resource efficiency. Full article