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The fatigue characteristics of notched specimens of L360 pipeline steel in hydrogen and nitrogen environments were investigated by high cycle fatigue life tests and fatigue crack growth rate tests. The fracture morphology in the nitrogen environment was dominated by microcracks and fatigue strips. The fatigue fracture had distinctly different regions in the hydrogen environment. The outer region of the fracture in the hydrogen environment was similar to the nitrogen environment, but a large number of hydrogen embrittlement features were found in the inner region. The fatigue crack growth rate tests were analyzed in conjunction with fatigue life tests. It was found that more fatigue cycles were required to achieve the stress intensity factor ΔK for rapid hydrogen-promoted crack propagation at lower stress. The region with hydrogen embrittlement features increases with decreasing stress. [ABSTRACT FROM AUTHOR]

For drone-based detection tasks, accurately identifying small-scale targets like people, bicycles, and pedestrians remains a key challenge. In this paper, we propose DV-DETR, an improved detection model based on the Real-Time Detection Transformer (RT-DETR), specifically optimized for small target detection in high-density scenes. To achieve this, we introduce three main enhancements: (1) ResNet18 as the backbone network to improve feature extraction and reduce model complexity; (2) the integration of recalibration attention units and deformable attention mechanisms in the neck network to enhance multi-scale feature fusion and improve localization accuracy; and (3) the use of the Focaler-IoU loss function to better handle the imbalanced distribution of target scales and focus on challenging samples. Experimental results on the VisDrone2019 dataset show that DV-DETR achieves an mAP@0.5 of 50.1%, a 1.7% improvement over the baseline model, while increasing detection speed from 75 FPS to 90 FPS, meeting real-time processing requirements. These improvements not only enhance the model's accuracy and efficiency but also provide practical significance in complex, high-density urban environments, supporting real-world applications in UAV-based surveillance and monitoring tasks. [ABSTRACT FROM AUTHOR]

The sea surface skin temperature (SSTskin) is of critical importance with regard to air–sea interactions and marine carbon circulation. At present, no single remote sensor is capable of providing a gap-free SSTskin. The use of data fusion techniques is therefore essential for the purpose of filling these gaps. The extant fusion methodologies frequently fail to account for the influence of depth disparities and the diurnal variability of sea surface temperatures (SSTs) retrieved from multi-sensors. We have developed a novel approach that integrates depth and diurnal corrections and employs advanced data fusion techniques to generate hourly gap-free SST datasets. The General Ocean Turbulence Model (GOTM) is employed to model the diurnal variability of the SST profile, incorporating depth and diurnal corrections. Subsequently, the corrected SSTs at the same observed time and depth are blended using the Markov method and the remaining data gaps are filled with optimal interpolation. The overall precision of the hourly gap-free SSTskin generated demonstrates a mean bias of −0.14 °C and a root mean square error of 0.57 °C, which is comparable to the precision of satellite observations. The hourly gap-free SSTskin is vital for improving our comprehension of air–sea interactions and monitoring critical oceanographic processes with high-frequency variability. [ABSTRACT FROM AUTHOR]

The rise of mobile communication, low-power chips, and the Internet of Things has made smartwatches increasingly popular. Equipped with inertial measurement units (IMUs), these devices can recognize user activities through artificial intelligence (AI) analysis of sensor data. However, most existing AI-based activity recognition algorithms require significant computational power and storage, making them unsuitable for low-power devices like smartwatches. Additionally, discrepancies between training data and real-world data often hinder model generalization and performance. To address these challenges, we propose LIMUNet and its smaller variant LIMUNet-Tiny—lightweight neural networks designed for human activity recognition on smartwatches. LIMUNet utilizes depthwise separable convolutions and residual blocks to reduce computational complexity and parameter count. It also incorporates a dual attention mechanism specifically tailored to smartwatch sensor data, improving feature extraction without sacrificing efficiency. Experiments on the PAMAP2 and LIMU datasets show that the LIMUNet improves recognition accuracy by 2.9% over leading lightweight models while reducing parameters by 88.3% and computational load by 58.4%. Compared to other state-of-the-art models, LIMUNet achieves a 9.6% increase in accuracy, with a 60% reduction in parameters and a 57.8% reduction in computational cost. LIMUNet-Tiny further reduces parameters by 75% and computational load by 80%, making it even more suitable for resource-constrained devices. [ABSTRACT FROM AUTHOR]

Equid herpesvirus type 8 (EqHV-8) is known to cause respiratory disease and miscarriage in horses and donkeys, which is a major problem for the equine farming industry. However, there are currently limited vaccines or drugs available to effectively treat EqHV-8 infection. Therefore, it is crucial to develop new antiviral approaches to prevent potential pandemics caused by EqHV-8. This study evaluates the antiviral and antioxidant effects of cepharanthine against EqHV-8 by employing both in vitro assays and in vivo mouse models to assess its therapeutic efficacy. To assess the effectiveness of cepharanthine against EqHV-8, we conducted experiments using NBL-6 and RK-13 cells. Additionally, we developed a mouse model to validate cepharanthine's effectiveness against EqHV-8. In our in vitro experiments, we assessed the cepharanthine's ability to inhibit infection caused by EqHV-8 in NBL-6 and RK-13 cells. Our results demonstrated that cepharanthine has a dose-dependent inhibitory effect, indicating that it possesses anti-EqHV-8 properties at the cellular level. Moreover, we investigated the mechanism through which cepharanthine exerts its protective effects. It was observed that cepharanthine effectively reduces the oxidative stress induced by EqHV-8 by activating the AMPK and Nrf2/HO-1 signaling pathways. Furthermore, when administered to EqHV-8 infected mice, cepharanthine significantly improved lung tissue pathology and reduced oxidative stress. The findings presented herein collectively highlight cepharanthine as a promising candidate for combating EqHV-8 infections. [ABSTRACT FROM AUTHOR]

This article addresses the challenge of minimizing landing impacts for legged space robots during on-orbit operations. Inspired by the agility of cats, we investigate the role of forelimbs in the landing process. By identifying the kinematic chain of the cat skeleton and tracking it using animal posture estimation, we derive the cushioning strategy that cats use to handle landing impacts. The results indicate that the strategy effectively transforms high-intensity impacts into prolonged low-intensity impacts, thereby safeguarding the brain and internal organs. We adapt this cushioning strategy for robotic platforms through reasonable assumptions and simplifications. Simulations are conducted in both gravitational and zero gravity environments, demonstrating that the optimized strategy not only reduces ground impact and prolongs the cushioning duration but also effectively suppresses the robot's rebound. In zero gravity, the strategy enhances stable attachment to target surfaces. This research introduces a novel biomimetic control strategy for landing control in the on-orbit operations of space robots. [ABSTRACT FROM AUTHOR]

Current super-resolution algorithms exhibit limitations when processing noisy remote sensing images rich in surface information, as they tend to amplify noise during the recovery of high-frequency signals. To mitigate this issue, this paper presents a novel approach that incorporates the concept of compressed sensing and explores the super-resolution problem of remote sensing images for space cameras, particularly for high-speed imaging systems. The proposed algorithm employs K-singular value decomposition (K-SVD) to jointly train high- and low-resolution image blocks, updating them column by column to obtain overcomplete dictionary pairs. This approach compensates for the deficiency of fixed dictionaries in the original algorithm. In the process of dictionary updating, we innovatively integrate the circle chaotic mapping into the solution process of the dictionary sequence, replacing pseudorandom numbers. This integration facilitates balanced traversal and simplifies the search for global optimal solutions. For the optimization problem of sparse coefficients, we utilize the orthogonal matching pursuit method (OMP) instead of the L1 norm convex optimization method used in most reconstruction techniques, thereby complementing the K-SVD dictionary update algorithm. After upscaling and denoising the image using the dictionary pair mapping relationship, we further emphasize image edge details with local gradients as constraints. When compared with various representative super-resolution algorithms, our algorithm effectively filters out noise and stains in low-resolution images. It not only performs well visually but also stands out in objective evaluation indicators such as the peak signal-to-noise ratio and information entropy. The experimental results validate the effectiveness of the proposed method in super-resolution remote sensing images, yielding high-quality remote sensing image data. [ABSTRACT FROM AUTHOR]

Hydraulic fracturing technology is vital for the efficient extraction of oil and gas from low-permeability tight sandstone reservoirs.Taking the central Bohai oilfield in China as an example, these fields are typically composed of thinly interbedded tight sandstone, characterized by low permeability and significant lithological heterogeneity between layers. Fractures may either be confined, limiting vertical growth and reducing production, or overextend into water-bearing zones, causing contamination and compromising reservoir integrity. Therefore, predicting vertical fracture propagation during field fracturing operations is critical for efficient resource extraction.However, there is still a lack of comprehensive understanding of the mechanisms governing vertical fracture growth offshore.This paper applies numerical simulations based on the finite element method to elucidate the interlayer fracture propagation behavior in low-permeability tight sandstone reservoirs. A fracture propagation model for thin interlayered tight sandstone formations is constructed, and the effects of various factors on hydraulic fracture propagation are systematically analyzed, including geological factors such as interlayer stress contrast, thickness, and differences in elastic modulus, as well as operational parameters including fracturing fluid viscosity and injection rate. This study clarifies the cross-layer propagation patterns of hydraulic fractures under the influence of multiple factors and yields a comprehensive prediction chart for fracture propagation thickness under the combination of complex factors. The results of this research can provide theoretical support for the design of reservoir stimulation operations in low-permeability tight sandstone oilfields. [ABSTRACT FROM AUTHOR]

The Loess Plateau is one of the most vulnerable areas in the world. Numerous studies have been conducted to investigate alfalfa fields with different planting years. Soil microorganisms and nematodes are vital in ecosystem functionality and nutrient cycling. Therefore, comprehending their response to alfalfa fields with varying years of planting is essential for predicting the direction and trajectory of degradation. Alfalfa fields with different planting years (2 years, 9 years, and 18 years) were used as the research object, and farmland was used as the control (CK). High-throughput sequencing and morphological methods determined the community composition of microorganisms and nematodes. Carbon metabolic footprints, correlation networks, and structural equations were used to study soil microorganisms and nematode interactions. Principal component analysis (PCA) results showed that alfalfa fields with different planting years significantly impacted soil microorganisms and nematode community structures. Planting alfalfa significantly increased the nematode channel ratio (NCR) and Wasilewska index (WI), but significantly reduced the soil nematode PPI/MI and dominance (λ). The correlation network results indicated that, for the 2-year and 18-year treatments, the total number of links and positive links are higher than other treatments. Conversely, the 9-year treatment had fewer positive links and more negative links compared to other treatments. Additionally, the keystone species within each network varied based on the treatment years. Structural equation results show that alfalfa planting years directly impact soil fungal community structure and plant-parasitic nematodes' carbon metabolism omnivorous-predatory nematodes. Furthermore, the carbon metabolism of omnivorous-predatory nematodes directly influences soil organic carbon fixation. Moreover, as the duration of alfalfa planting increases, the metabolic footprint of plant-parasitic nematodes decreases while that of omnivorous-predatory nematodes rises. Among treatments varying in alfalfa planting durations, the 9-year treatment exhibited the most incredible energy conversion and utilization efficiency within the soil food web, demonstrating the most stable structure. This study reveals optimal alfalfa planting duration for soil ecosystem stability in the Loess Plateau. Future research should explore sustainable crop rotations and alfalfa–soil–climate interactions for improved agricultural management. [ABSTRACT FROM AUTHOR]

Currently, the problem of heavy metal pollution in China is becoming increasingly serious, which poses grave threats to the environment and human health. Owing to the non-biodegradability and toxicity of heavy metals, a more sustainable and ecological approach to remediate heavy metal pollution has always been a focus of attention for environmental researchers. In recent years, many scientists have found that phytoremediation aided by endophytes has high potential to remediate heavy metals owing to its low cost, effectiveness, environmental friendliness, and sustainability compared with physical and chemical methods. Indeed, the mechanism of interaction between endophytes, plants, and heavy metals in the soil is pivotal for plants to tolerate metal toxicity and thrive. In this review, we focus on the mechanism of how endophytic bacteria resist heavy metals, and the direct and indirect mechanisms employed by endophytic bacteria to promote the growth of plants and enhance phytoextraction and phytostabilization. Moreover, we also discuss the application of combinations of endophytic bacteria and plants that have been used to remediate heavy metal pollution. Finally, it is pointed out that although there have been many studies on phytoremediation systems that have been assisted by endophytes, large-scale field trials are important to deliver "real" results to evaluate and improve phytoremediation assisted with microorganisms in polluted natural environments. [ABSTRACT FROM AUTHOR]

Heavy metal pollution has been a major environmental issue in recent years, seriously threatening land, water sources, agriculture, and human health. The remediation of heavy metal pollution has been a continuously vital issue for current research. Bioremediation is an effective and cost-efficient approach to reduce heavy metal toxicity. Phosphate-solubilizing fungi (PSF) have shown promise in heavy metal bioremediation due to their high tolerance and activity levels. However, the full potential of PSF in bioremediation needs further exploration. PSF activity, metabolite production, and environmental conditions can influence their efficiency in remediating heavy metals. These factors play a critical role in the practical application of PSF and necessitate improvement pathways. This article reviews potential strategies to enhance heavy metal remediation using PSF and optimizing bioprocesses and applications. [ABSTRACT FROM AUTHOR]

Fungal infections present a significant global health challenge, prompting ongoing research to discover innovative antifungal agents. The 110 kDa heat shock proteins (Hsp110s) are molecular chaperones essential for maintaining cellular protein homeostasis in eukaryotes. Fungal Hsp110s have emerged as a promising target for innovative antifungal strategies. Notably, 2H stands out as a promising candidate in the endeavor to target Hsp110s and combat fungal infections. Our study reveals that 2H exhibits broad-spectrum antifungal activity, effectively disrupting the in vitro chaperone activity of Hsp110 from Candida auris and inhibiting the growth of Cryptococcus neoformans. Pharmacokinetic analysis indicates that oral administration of 2H may offer enhanced efficacy compared to intravenous delivery, emphasizing the importance of optimizing the AUC/MIC ratio for advancing its clinical therapy. [ABSTRACT FROM AUTHOR]

Spiders have unique biological characteristics and excellent maneuverability, making them an ideal model for bionic robot design. However, traditional bionic spider robot designs usually have multiple degrees of freedom and confront many challenges. These challenges include complex control requirements, higher energy consumption, larger size and weight, higher risk of failure, and higher cost. This study proposes a leg design with two degrees of freedom to reduce its control and manufacturing costs. It can better control leg movement and improve leg force through a multi-link mechanism and a dual-motor system. In addition, the triangular gait and hexagonal body structure align the weight of the body with the support point, thereby enhancing stability. This study offers a comprehensive and organized approach to bio-inspired robot design, providing a valuable reference for future bionic robot development. [ABSTRACT FROM AUTHOR]

Bipolar plates are one of the most important components of proton exchange membrane fuel cells. With the miniaturization of bipolar plate flow channel sizes and the increasing demand for precision, springback has become a key focus of research in the bipolar plate forming process. In this paper, the hydroforming process for 316L stainless steel bipolar plates was studied, and an FEM model was built to examine the stress and strain at various locations on the longitudinal section of the plate. Modeling accuracy was validated by the comparison of experimental profile and thickness distribution. The effects of forming pressure and grain size on springback behavior are discussed. The results show that with increasing forming pressure, the springback value decreases initially, followed by an increase, but then again decreases. When the forming pressure is 80 MPa–100 MPa, the deformation of the lower element of the upper rounded corner is not uniform with more elastic regions, and the springback is positively correlated with forming pressure. The springback distribution pattern on the cross-section of the bipolar plate changes from a normal distribution to a distribution of "M" shape with increased pressure. The larger the grain size, the lower the yield strength elastic proportion, resulting in a decrease in springback of the sheet. The maximum amount of springback of the bipolar plate is 3.1 μm when the grain size is 60.7 μm. The research results provide a reference for improving the forming quality of metal bipolar plates with different flow channel shapes. [ABSTRACT FROM AUTHOR]

Fish invasions can damage the ecological environment of invaded areas, causing negative effects such as monotony of ecological types in invaded waters and endangerment of native species. It is important to monitor their presence and spread in invaded areas. This study aims to update the available data on non-native fish species in the inland waters of Guangxi and to determine their seasonal and spatial distribution in this region. Taking the inland waters of Guangxi as the study area, 34 sampling sites were set up in the major river systems, and systematic sampling was conducted in four seasons in 2023. The data showed that a total of 7690 non-native fish were collected from 23 species, belonging to 7 orders, 13 families, and 20 genera. Of the non-native fish species, 19 species were introduced for aquaculture purposes, and three species were introduced for ornamental purposes. The most non-native fish species were found in summer with 21 species, which were followed by 20 species in winter, 18 species in spring, and only 15 species in autumn. However, the distribution composition was similar in each season, with Coptodon zillii being dominant in each season, which was followed by Oreochromis niloticus. The Hongshuihe River had the highest number of non-native fish species with 16 species, followed by the Xunjiang River with 14 species, the Qianjiang River with 13 species, and the Npanjiang River had the lowest number of non-native fish species with 7 species. In addition, the Xunjiang River and the Qianjiang River showed significant separation in the PCoA results, and the overall test showed significant differences in non-native fish composition among the river system. The main reasons for the differences in their spatial distribution are geographical location and temperature. O. niloticus and C. zillii were found in all river systems and have become the main invasive non-native fish species in the inland waters of Guangxi. [ABSTRACT FROM AUTHOR]

Polymer-based composites with excellent dielectric properties are essential for advanced energy storage applications. In this work, the [6,6]-phenyl-C61-butyric acid methyl ester (PCBM) as a filler was incorporated into the poly(vinylidene fluoride-co-hexafluoropropylene) (P(VDF-HFP)) composite to improve its dielectric performance. P(VDF-HFP) composite films with varying PCBM concentrations were prepared via solution casting and their dielectric, energy storage, and charge–discharge properties were characterized. It was found that the doped PCBM could introduce new charge traps with an energy level of 1.25 eV that modulate charge transport and energy storage characteristics of the polymer matrix. The dielectric constant of the composites was enhanced to the maximum of 10.87 as 0.2 vol% PCBM was added, while the breakdown strength reached 455 MV/m, achieving an energy density of 7.38 J/cm3, which is 33% higher than the pristine P(VDF-HFP) film. Furthermore, the charge–discharge efficiency of the composites was enhanced 66% under the electric field of 300 MV/m. These results demonstrate that PCBM significantly improves the dielectric and energy storage properties of P(VDF-HFP) composites, providing a promising approach for the development of high-performance dielectric materials in flexible energy storage devices. [ABSTRACT FROM AUTHOR]

The emergence of hitherto unknown viral pathogens presents a great challenge for researchers to develop effective therapeutics and vaccines within a short time to avoid an uncontrolled global spread, as seen during the coronavirus disease 2019 (COVID-19) pandemic. Therefore, rapid and simple methods to identify immunogenic antigens as potential therapeutical targets are urgently needed for a better pandemic preparedness. To address this problem, we chose the well-characterized Modified Vaccinia virus Ankara (MVA)-T7pol expression system to establish a workflow to identify immunogens when a new pathogen emerges, generate candidate vaccines, and test their immunogenicity in an animal model. By using this system, we detected severe acute respiratory syndrome (SARS) coronavirus 2 (SARS-CoV-2) nucleoprotein (N)-, and spike (S)-specific antibodies in COVID-19 patient sera, which is in line with the current literature and our observations from previous immunogenicity studies. Furthermore, we detected antibodies directed against the SARS-CoV-2-membrane (M) and -ORF3a proteins in COVID-19 patient sera and aimed to generate recombinant MVA candidate vaccines expressing either the M or ORF3a protein. When testing our candidate vaccines in a prime-boost immunization regimen in humanized HLA-A2.1-/HLA-DR1-transgenic H-2 class I-/class II-knockout mice, we were able to demonstrate M- and ORF3a-specific cellular and humoral immune responses. Hence, the established workflow using the MVA-T7pol expression system represents a rapid and efficient tool to identify potential immunogenic antigens and provides a basis for future development of candidate vaccines. [ABSTRACT FROM AUTHOR]

The fusion of infrared and visible images together can fully leverage the respective advantages of each, providing a more comprehensive and richer set of information. This is applicable in various fields such as military surveillance, night navigation, environmental monitoring, etc. In this paper, a novel infrared and visible image fusion method based on sparse representation and guided filtering in Laplacian pyramid (LP) domain is introduced. The source images are decomposed into low- and high-frequency bands by the LP, respectively. Sparse representation has achieved significant effectiveness in image fusion, and it is used to process the low-frequency band; the guided filtering has excellent edge-preserving effects and can effectively maintain the spatial continuity of the high-frequency band. Therefore, guided filtering combined with the weighted sum of eight-neighborhood-based modified Laplacian (WSEML) is used to process high-frequency bands. Finally, the inverse LP transform is used to reconstruct the fused image. We conducted simulation experiments on the publicly available TNO dataset to validate the superiority of our proposed algorithm in fusing infrared and visible images. Our algorithm preserves both the thermal radiation characteristics of the infrared image and the detailed features of the visible image. [ABSTRACT FROM AUTHOR]

Greenhouse vegetable production has become increasingly important in meeting the increasing global food demand. Yet, it faces severe challenges in terms of how to maintain soil productivity from a long-term perspective. This review discusses the main soil productivity limiting factors for vegetables grown in greenhouses and identifies strategies that attempt to overcome these limitations. The main processes leading to soil degradation include physical (e.g., compaction), chemical (e.g., salinization, acidification, and nutrient imbalances), and biological factors (e.g., biodiversity reduction and pathogen buildup). These processes are often favored by intensive greenhouse cultivation. Mitigation strategies involve managing soil organic matter and mineral nutrients and adopting crop rotation. Future research should focus on precisely balancing soil nutrient supply with vegetable crop demands throughout their life cycle and using targeted organic amendments to manage specific soil properties. To ensure the successful adoption of recommended strategies, socioeconomic considerations are also necessary. Future empirical research is required to adapt socioeconomic frameworks, such as Science and Technology Backyard 2.0, from cereal production systems to greenhouse vegetable production systems. Addressing these issues will enable the productivity of greenhouse vegetable soils that meet growing vegetable demand to be sustained using limited soil resources. [ABSTRACT FROM AUTHOR]

This study investigates the impact of quadriceps fatigue on lower limb biomechanics during the landing phase of a single-leg vertical jump (SLJ) in 25 amateur male basketball players from Ningbo University. Fatigue was induced through single-leg knee flexion and extension exercises until task failure. Kinematic and dynamic data were collected pre-fatigue (PRF) and post-fatigue (POF) using the Vicon motion capture system and the AMTI force platform and analyzed using an OpenSim musculoskeletal model. Paired sample t-tests revealed significant changes in knee and hip biomechanics under different fatigue conditions, with knee joint angle (p < 0.001), velocity (p = 0.006), moment (p = 0.006), and power (p = 0.036) showing significant alterations. Hip joint angle (p = 0.002), moment (p = 0.033), and power (p < 0.001) also exhibited significant changes. Muscle activation and joint power were significantly higher in the POF condition, while joint stiffness was lower. These findings suggest that quadriceps fatigue leads to biomechanical adjustments in the knee and hip joints, which may increase the risk of injury despite aiding in landing stability. [ABSTRACT FROM AUTHOR]

Featured Application: Our research can be directly applied to the shot peening enhancement of herringbone gears, improving upon the previously uneven surface strengthening effect of herringbone gear teeth to achieve higher quality processing. In addition, we are able to reasonably match the shot peening process parameters that are suitable for herringbone gears among the numerous options, thereby achieving higher processing efficiency. Introduction: The complex geometry of herringbone gear can lead to uneven surface strengthening, which affects the overall effect of treatment. Methods: A discrete element model (DEM) of shot peening for herringbone gears was developed, incorporating accurate gear surface parameters to study impact characteristics along the tooth profile. A finite element model (FEM) was created for small local units of the gear surface to calculate the residual stress and roughness. Results: There are a large number of low-velocity shots at the root of the gear, and the closer to the top of the gear, the higher the impact velocity of the shots, but the number of impacts also decreases. The surface roughness Sa near the root of the tooth is the smallest, the Sa at the pitch circle is the largest, and the Sa at the top of the tooth is intermediate. However, the residual stress levels at different positions of the tooth surface are not significantly different. Conclusion: The difference in tooth surface roughness of herringbone gear is the synergistic effect of shot impact velocity and shot frequency, but this synergistic effect has no significant effect on the stress after shot peening. [ABSTRACT FROM AUTHOR]

This study systematically investigated the formulation optimization, performance evaluation, and practical application of epoxy-based composite materials for colored asphalt pavement. By conducting comprehensive experiments, we optimized the composition of epoxy-based composites, verifying their excellent bonding performance, good heat resistance, and UV aging resistance under various temperature conditions. The key optimized component ratios were determined as a 1:1 blend of Type I and Type II epoxy resins, 30 phr of curing agent, 10 phr of toughening agent, 5 phr of diluent, 10% filler, 12% flame retardant, and 10% pigment. At the recommended dosage of 2.0 kg/m2 of epoxy binder, the composite structure exhibited the best reinforcement effect, improving low-temperature performance significantly. Compared to ordinary asphalt mixtures, the colored pavement composite structure showed superior mechanical strength, deformation capacity, high-temperature stability (dynamic stability approximately three times higher), and water stability (TSR values up to 95.5%). Furthermore, its fatigue life decay rate was significantly lower, with fatigue limit loading frequencies more than three times those of ordinary asphalt mixtures, demonstrating excellent fatigue resistance. This study provides strong technical support and a theoretical basis for the development and practical application of colored asphalt pavement. [ABSTRACT FROM AUTHOR]

Simple Summary: Dietary composition is the main factor regulating the rumen microflora structure and fermentation mode. The change of the concentrate to roughage ratio of diets can cause the change of rumen microflora and affect the feed utilization and growth performance of ruminants. This study investigated the effects of the extreme transition from all-concentrate to all-roughage diets on the patterns and functions of the rumen microbiome in high-altitude yaks, cattle-yak, Tibetan yellow cattle and low-altitude yellow cattle by metagenomic sequencing. After diet conversion, the rumen microbial richness and diversity of the four herds increased, and the biggest difference between concentrate and roughage diets was yak and cattle-yak, followed by Tibetan yellow cattle and yellow cattle. The transformation in diets can change the metabolic pathways of rumen microorganisms in four herds and finally affect the fermentation mode of rumen. Compared with Tibetan yellow cattle and yellow cattle, yaks and cattle-yaks have better adaptability to roughage, and its utilization rate can be fully improved to reduce methane emission, and they are more suitable for intensive feeding on the plateau. The experiment was to compare the effects of switching all-concentrate to all-roughage diets on rumen microflora and functional metabolism of yak, cattle-yak, Tibetan yellow cattle and yellow cattle living in different altitudes. A total of 24 yaks, cattle-yaks, Tibetan yellow cattle and yellow cattle with a similar weight and good body condition aged 3.5 years were selected and divided into four groups according to species. They were fed a concentrate diet with 40% soybean meal and 60% corn meal for the first month (C group) and a roughage diet with dry corn stalks (100%) for the second month (R group); the formal experimental period was 60 d. These results showed that the conversion had a significant effect on the rumen microflora structure of the four herds, and the biggest difference between concentrate and roughage diets was yak and cattle-yak, followed by Tibetan yellow cattle and yellow cattle. At the phylum level, Bacteroidetes and Firmicutes still predominate in all groups. Compared with the C groups, the relative abundance of Lentisphaerae and Kiritimatiellaeota increased in all R groups, and Lentisphaerae was significantly increased in yak and cattle-yak (p < 0.05). At the genus and species levels, Prevotella had the highest abundance, and the relative abundances of Prevotella, Ruminococcus, Sarcina and Ruminobacter in R groups were lower, while the abundances of other differential genera, including Methanobrevibacter, Fibrobacter, Treponema, Eubacterium, Butyrivibrio, Succinivibrio and Succinimonas, were all higher. Roughage diets increased the number of unique genes and functional genes encoding different CAZymes in rumen microorganisms in all four herds. In the functional contribution analysis, with the exception of ABC transporters and methane metabolism, Prevotella was the main contributor to almost all of these functions. In methane metabolism, Methanobrevibacter had the highest relative abundance, followed by Prevotella, Clostridia and Bacteroidales in all groups. Compared with Tibetan yellow cattle and yellow cattle, yaks and cattle-yaks have better adaptability to roughage, and its utilization rate can be fully improved to reduce methane emission. The study indicates that when four herds are converted to high roughage at the later stage of feeding, the growth and reproduction of rumen microorganisms are affected, and the abundance and diversity of rumen microorganisms are increased to varying degrees. The transformation of concentrate to roughage diet can change the metabolic pathways of rumen microorganisms in yaks and finally affect the fermentation mode of rumen. The above results provide a theoretical basis for the research and development of fattening feeds for yaks, cattle-yaks, Tibetan yellow cattle and yellow cattle and the intensive feeding of livestock on the plateau. [ABSTRACT FROM AUTHOR]

In this paper, we introduce an innovative approach to multi-focus image fusion by leveraging the concepts of fractal dimension and coupled neural P (CNP) systems in nonsubsampled contourlet transform (NSCT) domain. This method is designed to overcome the challenges posed by the limitations of camera lenses and depth-of-field effects, which often prevent all parts of a scene from being simultaneously in focus. Our proposed fusion technique employs CNP systems with a local topology-based fusion model to merge the low-frequency components effectively. Meanwhile, for the high-frequency components, we utilize the spatial frequency and fractal dimension-based focus measure (FDFM) to achieve superior fusion performance. The effectiveness of the method is validated through extensive experiments conducted on three benchmark datasets: Lytro, MFI-WHU, and MFFW. The results demonstrate the superiority of our proposed multi-focus image fusion method, showcasing its potential to significantly enhance image clarity across the entire scene. Our algorithm has achieved advantageous values on metrics Q A B / F , Q C B , Q C V , Q E , Q F M I , Q G , Q M I , and Q N C I E . [ABSTRACT FROM AUTHOR]

Using deep learning methods to detect potential safety hazards in transmission lines is the mainstream method for power grid security monitoring. However, the existing model is too complex to adapt to edge device deployment and real-time detection. Therefore, an edge–real-time transmission line safety hazard detection method (ETLSH-YOLO) was proposed to reduce the model's complexity and improve the model's robustness. Firstly, a re-parameterized Ghost efficient layer aggregation network (RepGhostCSPELAN) was designed to effectively fuse the feature information of different layers while enhancing the model's expression ability and reducing the number of model parameters and floating-point operations. Then, a spatial channel decoupled downsampling block (CSDovn) was designed to reduce computational redundancy and improve the computational efficiency of the model. Then, coordinate attention (CA) was added in the process of multi-scale feature fusion to suppress the interference of complex background and improve the global perception ability of the model object. Finally, the Mish activation function was used to improve the network's training speed, convergence, and generalization ability. The experimental results show that the mAP50 of this model improved by 1.73% compared with the baseline model, and the number of parameters and floating-point operations were reduced by 33.96% and 22.22%, respectively. This model lays the foundation for solving the dilemma of edge device deployment. [ABSTRACT FROM AUTHOR]

Interferon-induced transmembrane proteins (IFITMs) are upregulated by interferons. They are not only highly conserved in evolution but also structurally consistent and have almost identical structural domains and functional domains. They are all transmembrane proteins and have multiple heritable variations in genes. The IFITM protein family is closely related to a variety of biological functions, including antiviral immunity, tumor formation, bone metabolism, cell adhesion, differentiation, and intracellular signal transduction. The progress of the research on its structure and related functions, as represented by IFITM3, is reviewed. [ABSTRACT FROM AUTHOR]

This investigation focuses on the prevalent continental oil shale within the Triassic Chang 7, a member of the Yanchang Formation in the Ordos Basin and the Permian Lucaogou Formation in the Junggar Basin of western China, and delves into the impacts of hydrocarbon generation and the derived organic acids on the physical attributes of oil shale reservoirs. Water-soluble organic acids (WSOAs) were extracted via Soxhlet extraction and analyzed by a 940 ion chromatograph (Metrohm AG), supplemented with core observations, thin-section analyses, pyrolysis, and trace element assays, as well as the qualitative observation of pore structures via FIB-SEM scanning electron microscopy. The study discloses substantial disparities in the types and abundances of organic acids within the oil shale strata of the two regions, with mono-acids being conspicuously more prevalent than dicarboxylic acids. The spatial distribution of organic acids within the oil shale strata in the two regions is non-uniform, and their generation is inextricably correlated with the type of organic matter, thermal maturity, and depth at which they are buried. During diverse stages of diagenesis, the hydrocarbons and organic acids produced from the pyrolysis of organic matter not only exert an impact on the properties of pore fluids but also interact with diagenetic processes such as compaction, dissolution, and metasomatism to enhance the reservoir quality of oil shale. The synergy between chemical interactions and physical alterations collectively governs the migration and distribution patterns of organic acids as well as the characteristics of oil shale reservoirs. Furthermore, the sources of organic acids within the oil shale series in the two regions demonstrate pronounced dissimilarities, which are intimately associated with the peculiarities of their sedimentary milieu. The oil shale of the Yanchang Formation was formed in a warm and humid freshwater lacustrine basin environment, while the oil shale of the Lucaogou Formation was deposited in a brackish to saline lacustrine setting under an arid to semi-arid climatic regime. These variances not only illuminate the intricacy and multiplicity of the sedimentary attributes of oil shale but also accentuate the impact of the sedimentary environment on the genesis and distribution of organic acids, especially the transformation and optimization of reservoir dissolution by organic acids generated during hydrocarbon generation—a factor of paramount significance for the precise identification and effective development of the "sweet spot" area of shale oil. These areas, characterized by an abundance of organic matter, their maturity, and superior reservoir properties, are the foci of the efficient exploration and development of continental shale oil. [ABSTRACT FROM AUTHOR]

Ice-covered transmission lines seriously affect the stable operation of the power system. Deploying a recognition network for measuring the ice thickness on transmission lines within a deicing robot, and controlling the robot to perform resonant deicing, is an effective solution. In order to solve the problem that the existing recognition network is not suitable for an edge device, an ice-thickness recognition network for transmission lines based on efficient dynamic perception (EDPNet) is proposed. Firstly, a lightweight multidimensional recombination convolution (LMRC) is designed to split the ordinary convolution for lightweight design and extract feature information of different scales for reorganization. Then, a lightweight deep fusion module (LDFM) is designed, which combines the attention mechanism with different features to enhance the information interaction between the encoder and decoder. Then, a new dynamic loss function is adopted in the training process to guide the model to perform refined detection of ice-covered boundaries. Finally, we count the ice pixels and calculate the ice thickness. The model is deployed on an OrangePi5 Plus edge computing board. Compared with the baseline model, the maximum ice-thickness detection error is 4.2%, the model parameters are reduced by 86.1%, and the detection speed is increased by 74.6%. Experimental results show that EDPNet can efficiently complete the task of identifying ice-covered transmission lines and has certain engineering application value. [ABSTRACT FROM AUTHOR]

Simple Summary: Bovine mastitis is one of the most common diseases in farms and has caused huge economic losses to farmers and led to a decline in milk quality. Antibiotics are a common treatment for mastitis. However, due to the emergence of bacterial resistance, they have brought great hidden dangers to public health and safety and also endanger people's health. Therefore, the development of antibiotic alternatives in the treatment of bovine mastitis is more urgent. Studies have found that yak IL-22 has tissue repair and inflammation inhibition effects. In this study, we used the yak IL-22 gene as a potential preparation to construct a mammary gland-specific plasmid for gene therapy for bovine mastitis and evaluated the role of this therapy in the disease, laying a foundation for the possible large-scale application of this preparation in the future. Since the development of dairy farming, bovine mastitis has been a problem plaguing the whole industry, which has led to a decrease in milk production, a reduction in dairy product quality, and an increase in costs. The use of antibiotics to treat mastitis can cause a series of problems, which can bring a series of harm to the animal itself, such as the development of bacterial resistance and dramatic changes in the gut flora. However, the in vivo and in vitro antibacterial activity of yak Interleukin-22 (IL-22) and its application in mastitis caused by Staphylococcus aureus have not been reported. In this study, the mammary gland-specific expression plasmid pLF-IL22 of the yak IL-22 gene was constructed and expressed in MAC-T cells and mammary tissue of postpartum female mice. The coding region of the IL-22 gene in yaks is 573 bp, which can encode 190 amino acids, and the homology difference in the IL-22 gene in yaks is less than 30%, which indicates certain conservation. IL-22 is a hydrophilic protein with a total positive charge of four, the presence of a signal peptide, and the absence of a transmembrane domain. Sufficient expression of IL-22 effectively inhibited the high expression of inflammatory factors caused by Staphylococcus aureus, reduced the symptoms of mammary gland histopathology, and alleviated mastitis. Under the action of IL-22, the intestinal flora of mastitis mice also changed, the abundance of intestinal Bacilli, Prevotellaceae, and Alloprevotella in mice increased after treatment, and the pathogenic bacteria decreased. These findings provide new insights into the potential application of the yak IL-22 gene in the treatment of bovine mastitis in the future. [ABSTRACT FROM AUTHOR]

To investigate the flexural performance of high-titanium heavy-slag concrete composite beams under loading, this study examined the impact of various factors on deflection development and crack propagation as well as the applicability of empirical formulas for monolithic concrete beams. Seven concrete beams were fabricated with variables such as the reinforcement ratio, prefabrication height, and material composition, and were subjected to two-point concentrated loading. By comparing deflection values and crack widths during loading and analyzing the correlations with empirical formulas from standards, theoretical formulas with significant deviations were modified and compared. The study indicated that the cracking moment and deflection correlated with the reinforcement ratio, material structure combination, and composite height. The empirical formulas for the maximum crack width and deflection of flexural members were applicable to high-titanium heavy-slag concrete composite beams, although some discrepancies existed compared with the experimental values. After modifications, these discrepancies were reduced. This research provides a comprehensive analysis of the deformation characteristics and fracture behavior of high-titanium heavy-slag concrete composite beams. [ABSTRACT FROM AUTHOR]

In the field of remote sensing image processing, pansharpening technology stands as a critical advancement. This technology aims to enhance multispectral images that possess low resolution by integrating them with high-spatial-resolution panchromatic images, ultimately producing multispectral images with high resolution that are abundant in both spatial and spectral details. Thus, there remains potential for improving the quality of both the spectral and spatial domains of the fused images based on deep-learning-based pansharpening methods. This work proposes a new method for the task of pansharpening: the Multi-Stage Progressive Pansharpening Network with Detail Injection with Redundancy Reduction Mechanism (MSPPN-DIRRM). This network is divided into three levels, each of which is optimized for the extraction of spectral and spatial data at different scales. Particular spectral feature and spatial detail extraction modules are used at each stage. Moreover, a new image reconstruction module named the DRRM is introduced in this work; it eliminates both spatial and channel redundancy and improves the fusion quality. The effectiveness of the proposed model is further supported by experimental results using both simulated data and real data from the QuickBird, GaoFen1, and WorldView2 satellites; these results show that the proposed model outperforms deep-learning-based methods in both visual and quantitative assessments. Among various evaluation metrics, performance improves by 0.92–18.7% compared to the latest methods. [ABSTRACT FROM AUTHOR]

A neuromorphic computing network based on SiCx memristor paves the way for a next-generation brain-like chip in the AI era. Up to date, the SiCx–based memristor devices are faced with the challenge of obtaining flexibility and uniformity, which can push forward the application of memristors in flexible electronics. For the first time, we report that a flexible artificial synaptic device based on a Ag NPs:a–SiC0.11:H memristor can be constructed by utilizing aluminum foil as the substrate. The device exhibits stable bipolar resistive switching characteristic even after bending 1000 times, displaying excellent flexibility and uniformity. Furthermore, an on/off ratio of approximately 107 can be obtained. It is found that the incorporation of silver nanoparticles significantly enhances the device's set and reset voltage uniformity by 76.2% and 69.7%, respectively, which is attributed to the contribution of the Ag nanoparticles. The local electric field of Ag nanoparticles can direct the formation and rupture of conductive filaments. The fitting results of I–V curves show that the carrier transport mechanism agrees with Poole–Frenkel (P–F) model in the high-resistance state, while the carrier transport follows Ohm's law in the low-resistance state. Based on the multilevel storage characteristics of the Al/Ag NPs:a–SiC0.11:H/Al foil resistive switching device, we successfully observed the biological synaptic characteristics, including the long–term potentiation (LTP), long–term depression (LTD), and spike–timing–dependent plasticity (STDP). The flexible artificial Ag NPs:a–SiC0.11:H/Al foil synapse possesses excellent conductance modulation capabilities and visual learning function, demonstrating the promise of application in flexible electronics technology for high-efficiency neuromorphic computing in the AI period. [ABSTRACT FROM AUTHOR]

Previous studies have focused on the design of video lectures to improve students' social presence by enhancing instructor presence for learners in lecture-based online courses; however, there has been limited emphasis on the peer presence in which learning from video lectures takes place. This study's first objective is to develop a social presence (SP)-based teaching strategy to design online learning activities aimed at improving students' social presence by providing social clues about peer presence and encouraging peer communication. The second objective is to compare students' social presence, social interaction, and academic performance from lecture-based online learning supported by either a conventional teaching strategy or an SP-based teaching strategy. Using a quasi-experiment, we selected 81 Chinese university students to participate in a ten-week online course. The participants were randomly assigned to either an experimental group (EG) (N = 43) or a control group (CG) (N = 38). This study revealed that the SP-based strategy enhanced EG members' social presence in online learning and that EG members achieved better academic performance than CG members. A significant correlation was found between the EG members' academic performance and their social presence. The researchers also identified more concentrated social network sociograms with more cohesive subgroups in the EG members' online interactions. The results indicate the necessity of applying an SP-based teaching strategy in lecture-based online courses to promote students' social presence, social interaction, and academic performance. [ABSTRACT FROM AUTHOR]

Simple Summary: Ants are highly adaptable insects that thrive in a variety of climates and habitats worldwide. This study examines how climate and habitat influence the morphological traits of the ant species Camponotus japonicus across 22 sites in mainland China. These sites represent three climate zones and three habitat types. Our analysis shows that both climate and habitat significantly shape the ants' morphological traits. Specifically, ants in mid-temperate farmlands exhibit more constrained morphological traits, while those in sparse woodlands show greater variation. Urban parks present a stable environment with less morphological variation. Temperature, precipitation, humidity, and altitude were found to be closely linked to these morphological traits. This research enhances our understanding of how ants adapt to environmental changes through morphological variation and underscores their critical ecological roles in various ecosystems. Ants are a highly adaptable group of insects that have globally established themselves in diverse climates and habitats. This study investigates the influence of climate and habitat on the morphological traits of Camponotus japonicus across 22 sites in mainland China. These sites span three climate zones (mid-temperate, warm temperate, and subtropical) and three habitat types (urban parks, farmlands, and sparse woodlands). Principal component analysis (PCA) was used to determine the principal axis of morphological variation, while hypervolume analysis and centroid distance calculation were used to verify the environmental filtering hypothesis and the optimal transfer hypothesis. The results support both hypotheses showing that climate and habitat significantly affect the morphological space of C. japonicus workers. In particular, the morphological space is more constrained in mid-temperate farmlands, while workers in sparse woodlands exhibit greater morphological variation. In contrast, urban parks are characterized by higher stability and reduced morphological differences. Additionally, robust regression analysis reveals that environmental factors such as temperature, precipitation, humidity, and altitude are closely linked to the morphological traits of the workers. Understanding how ant morphology responds to external environmental changes enhances our understanding of their adaptability and their essential ecological roles across various ecosystems. [ABSTRACT FROM AUTHOR]

To investigate hydrogen behaviors in the high-entropy alloy AlCrTiNiV, density functional theory and transition state theory were used to explore the molecular H 2 absorption and dissociation and the atomic H adsorption, diffusion, and penetration progress. The H 2 molecule, where the H-H band is parallel to the surface layer, is more inclined to absorb on the top site of the Ti atom site of first atomic layer on the AlCrTiNiV surface, then diffuse into the hollow sites, through the bridge site, after dissociating into two H atoms. Atomic H is more likely to be absorbed on the hollow site. The absorption capacity for atomic H on the surface tends to decline with the increase in H coverage. By calculating the energy barriers of atomic H penetration in AlCrTiNiV, it was indicated that lattice distortion may be one important factor that impacts the permeation rate of hydrogen. Our theory research suggests that high-entropy alloys have potential for use as a hydrogen resistant coating material. [ABSTRACT FROM AUTHOR]

Carbon dots (CDs) have garnered extensive interest in basic physical chemistry as well as in biomedical applications due to their low cost, good biocompatibility, and great aqueous solubility. However, the synthesis of multi-functional carbon dots has always been a challenge for researchers. Here, we synthesized novel CDs with a high quantum yield of 28.2% through the straightforward hydrothermal method using Diaminomaleonitrile and Boc-D-2, 3-diaminopropionic acid. The size, chemical functional group, and photophysical properties of the CDs were characterized by TEM, FTIR, XPS, UV, and fluorescence. It was demonstrated in this study that the prepared CDs have a high quantum yield, excellent photostability, and low cytotoxicity. Regarding the highly water-soluble property of CDs, they were proven to possess selective and sensitive behavior against Cu2+ ions (linear range = 0–9 μM and limit of detection = 1.34 μM). Moreover, the CDs were utilized in fluorescent ink in anti-counterfeiting measures. Because of their low cytotoxicity and good biocompatibility, the CDs were also successfully utilized in cell imaging. Therefore, the as-prepared CDs have great potential in fluorescence sensing, anti-counterfeiting, and bioimaging. [ABSTRACT FROM AUTHOR]

This study focused on developing an effective cell wall-breaking method for Phaffia rhodozyma, followed by utilizing subcritical fluid extraction to isolate, extract, and concentrate astaxanthin from the complex fermentation products of P. rhodozyma. A comprehensive comparison of seven distinct methods for disrupting cell walls, including dimethyl sulfoxide treatment, lactic acid treatment, sodium hydroxide treatment, β-glucanase enzymatic digestion, β-mannanase enzymatic digestion, and a combined enzymatic treatment involving both β-mannanase and β-glucanase was conducted. The results identified the lactic acid method as the most effective in disrupting the cell walls of P. rhodozyma. The software, Design Expert, was used in the process of extracting astaxanthin from cell lysates using a subcritical extraction method. Through fitting analysis and response surface optimization analysis by Design Expert, the optimal extraction conditions were determined as follows: an extraction temperature of 41 °C, extraction frequency of two times, and extraction time of 46 min. These parameters facilitated the efficient extraction, concentration, and enrichment of astaxanthin from P. rhodozyma, resulting in an astaxanthin concentration of 540.00 mg/L. This result can establish the foundation for its high-value applications. [ABSTRACT FROM AUTHOR]

Many traditional villages have been degraded to a certain extent due to urbanization and out-of-control management. In addition, due to the lack of recognition and continuation of spatial texture in some village conservation and planning that, in turn, resulting in the gradual disappearance of their distinctive landscape feature. Studying the spatial form of traditional villages helps preserve the authenticity of traditional villages as cultural landscape and inherits traditional historical characteristics. Using Puping Village in Zhangzhou City, Fujian Province as an example, this paper obtains the integrated information data of the village through UAV oblique photography, classifies and extracts the spatial constitution of the traditional village using digital technology, quantitatively analyses it from macroscopic to microscopic, and summarizes the spatial morphology analysis method of the traditional village. The results demonstrate that digital technology can effectively and accurately complete data collection and can provide an objective basis for zoning conservation of traditional villages based on the distinction between new and historic buildings. In addition, digital information collection on the traditional villages landscape features will prepare for the establishment of a database and comparative analysis in the future. We further suggest that digital technology analysis needs to be combined with traditional methods to have a deeper understanding of the formation process of village spatial morphology. The results of the practice in Puping Village show that the use of digital technology can provide a scientific basis for the protection and planning of traditional villages, and that this method is adaptable, which can help to efficiently collect and analyze data on landscape characteristics of other similar villages in China, and support innovative methodologies and technologies for China's rural revitalization efforts. [ABSTRACT FROM AUTHOR]

Grafting is a commonly employed technique for enhancing the yield and improving resistance to biotic and abiotic stress of cultivated plants. However, whether and how continuous cropping of grafted plants affects the composition, function, and stability of the soil fungal community remain poorly understood. In this study, we investigated the effects of planting years (including 0 years (Y0), 2 years (Y2), 10 years (Y10), and 18 years (Y18)) of grafted watermelon on the structure and functional composition of the soil fungal community under field conditions. Compared with the Y0 soil, the Y2, Y10, and Y18 soils exhibited a significant (p < 0.05) decrease in the richness, Shannon index, and evenness (56.8–65.7%, 22.4–46.3%, and 3.8–38.1%, respectively) in the alpha diversity of the fungal community, but a significant (p < 0.05) increase (0.4–1.3 times) in the fungal population. The structure, core and unique microbiomes, and functional composition of the soil fungal community differed significantly across different planting years. The Y2, Y10, and Y18 soils exhibited significant increases (p < 0.05) in relative abundances of Ascomycota and saprophytic fungi and the proportion of core OTUs, but significantly decreased abundances of Basidiomycota, Chytridiomycota, Rozellomycota, pathogenic and symbiotic fungi, and the proportion of unique OTUs when compared with the Y0 soil. The types of potential plant pathogens and their relative abundance were also significantly increased alongside the planting years (among Y2, Y10, and Y18 soils). Furthermore, the results indicated that the continuous cropping of grafted watermelon altered the co-occurrence networks, leading to a reduction in the complexity and stability of the fungal community networks. Overall, our findings suggest that continuous cropping of grafted watermelon may adversely affect the structure and functioning of soil microbial community, eventually decreasing the effectiveness of grafting technology disease control. [ABSTRACT FROM AUTHOR]

This paper proposes a current balancing loop that is obtained using the threshold median adjustment (TMA-CBL) to achieve the accurate current balancing of an interleaved constant frequency hysteresis (CFH) buck converter. The CFH control is implemented with a frequency phase loop based on a threshold width adjustment (TWA-FPL). To ensure the loop's stability and minimize the steady-state error, a multi-phase, coupled, small-signal model (MPC-SSM) is derived with a consideration of the coupling effect among the multiple phases. Furthermore, the current balancing error is analyzed in detail, with a consideration of the sensing resistance deviations in the loop. Finally, based on a 180 nm BCD process, a four-phase interleaved buck converter is fabricated to verify the effectiveness of the proposed TMA-CBL. The maximum current balancing error is within 0.68% when the sensing resistors are deviated by 5%. [ABSTRACT FROM AUTHOR]

The annual co-circulation of two influenza A subtypes, H1N1 and H3N2, viruses in humans poses significant public health threats worldwide. However, the continuous antigenic drift and shift of influenza viruses limited the effectiveness of current seasonal influenza vaccines, necessitating the development of new vaccines against both seasonal and pandemic viruses. One potential solution to this challenge is to improve inactivated vaccines by including multiple T-cell epitopes. In this study, we designed stabilized trimeric recombinant mosaic HA proteins named HAm, which contain the most potential HA T-cell epitopes of seasonal influenza A virus. We further evaluated the antigenicity, hemagglutinin activity, and structural integrity of HAm and compared its immunogenicity and efficacy to a commercial quadrivalent inactivated influenza vaccine (QIV) in mice. Our results demonstrated that the HAm vaccine was able to induce broadly cross-reactive antibodies and T-cell responses against homologous, heterologous, and heterosubtypic influenza-naive mice. Additionally, the HAm antigens outperformed QIV vaccine antigens by eliciting protective antibodies against panels of antigenically drifted influenza vaccine strains from 2009 to 2024 and protecting against ancestral viruses' lethal challenge. These results suggest that the HAm vaccine is a promising potential candidate for future universal seasonal and pandemic influenza vaccine development. [ABSTRACT FROM AUTHOR]

Simple Summary: As an important group of species in forensic entomology, sarcosaprophagous beetles can provide valuable clues to the postmortem interval of cadavers, especially in the late stages of decay. However, compared with flies, these species have not received much attention, and their potential value in forensic science is yet to be fully exploited. Therefore, in order to attract people's attention to them and to increase their use in forensic practice, we conducted a bibliometric analysis of the literature on sarcosaprophagous beetles, statistically analyzed the beetles mentioned in successions, cases, and other experiments in relation to cadavers, briefly introduced each family of sarcosaprophagous beetles, and discussed the value of their immature species identification and forensic postmortem interval estimation. In forensic entomology, research focused on sarcosaprophagous flies, but the sarcosaprophagous beetles, as important "forensic indicator species" of late-stage PMI in cadaver decomposition, received less attention. To increase attention on, and use and understanding of, sarcosaprophagous beetles in forensic entomology, this paper presents a bibliometric analysis of the available relevant literature. The occurrence frequency of beetle families and species from succession studies, actual cases, and experiments were calculated and illustrated using graphs. As a result, a total of 14 families and 1077 species associated with carcasses were collected, with Staphylinidae being the most frequently recorded among the families, and Necrobia rufipes (Fabricius, 1781) (Coleoptera: Cleridae) being the most frequently recorded species. In addition, a brief introduction of the cadaver-related beetles of each family is given, and research on the species identification of the immature stages, age estimation of the immature stages, and estimation of the arrival time of sarcosaprophagous beetles are discussed and prospected. This work will aid in the increased use of sarcosaprophagous beetles in forensic science practice in the future. [ABSTRACT FROM AUTHOR]

In order to increase nutrient input and alleviate the poor growth of blueberry (Vaccinium corymbosum L.) in neutral soil with strong nitrification, the application of nitrification inhibitor 3,4-dimethylpyrazole phosphate (DMPP) as an enhanced efficiency fertilizer is a strategy to reduce nitrogen (N) loss and improve N supply. However, few studies have systematically investigated the effect of DMPP application on blueberry and its soil condition in detail so far. In this study, a pot experiment was conducted to elucidate the effect of DMPP at four gradient levels including 0.5% (w/w applied-N) DMPP (DL), 1% DMPP (DM), 2% DMPP (DH), and no DMPP (CK) on the dynamics of soil mineral N (NH4+-N and NO3−-N), soil chemical properties, as well as the agronomic characteristics and physiological indexes of blueberry plants in the neutral soil–blueberry system. The addition of DMPP significantly increased the retention of soil ammonium nitrogen and the content of total mineral nitrogen. qPCR analysis showed that DMPP inhibited the ammoxidation process mainly by reducing the abundance of the ammonia-oxidizing bacteria (AOB) amoA gene rather than the ammonia-oxidizing archaea (AOA) amoA gene. No significant inhibitory effect of DMPP was observed for the nitrite dehydrogenase gene nxrA and nitrite reductase gene nirS. Soil NH4+-N and available phosphorus content were both enhanced with the DMPP application rates both in bulk and rhizosphere soil. Applying 1% DMPP to the neutral soil for blueberry was sufficient to safely inhibit soil nitrification, not only increasing ammonium nitrogen content by 10.42% and 26.79%, but also enhancing available phosphorus content by 9.19% and 22.41% compared with CK in bulk and rhizosphere soil, respectively. Moreover, 1% DMPP addition increased the nitrogen and phosphorus concentration of blueberry leaves by 12.17% and 26.42%, respectively, compared with CK. The total branch length and the dry weight of blueberry plant were also increased by 16.8% and 33.1%, respectively. These results provide valuable agronomic information for the application of DMPP in blueberry cultivation. Fertilization applied with 1% DMPP has great economic potential to improve both nitrogen and phosphorus absorption of blueberry so as to promote the vegetative growth of blueberry. [ABSTRACT FROM AUTHOR]

The field of carborane research has witnessed continuous development, leading to the construction and development of a diverse range of crystalline porous materials for various applications. Moreover, innovative synthetic approaches are expanding in this field. Since the first report of carborane-based crystalline porous materials (CCPMs) in 2007, the synthesis of carborane ligands, particularly through innovative methods, has consistently posed a significant challenge in discovering new structures of CCPMs. This paper provides a comprehensive summary of recent advances in various synthetic approaches for CCPMs, along with their applications in different domains. The primary challenges and future opportunities are expected to stimulate further multidisciplinary development in the field of CCPMs. [ABSTRACT FROM AUTHOR]

Cotton aphids (Aphis gossypii Glover) pose a significant threat to cotton growth, exerting detrimental effects on both yield and quality. Conventional methods for pest and disease surveillance in agricultural settings suffer from a lack of real-time capability. The use of edge computing devices for real-time processing of cotton aphid-damaged leaves captured by field cameras holds significant practical research value for large-scale disease and pest control measures. The mainstream detection models are generally large in size, making it challenging to achieve real-time detection on edge computing devices with limited resources. In response to these challenges, we propose GVC-YOLO, a real-time detection method for cotton aphid-damaged leaves based on edge computing. Building upon YOLOv8n, lightweight GSConv and VoVGSCSP modules are employed to reconstruct the neck and backbone networks, thereby reducing model complexity while enhancing multiscale feature fusion. In the backbone network, we integrate the coordinate attention (CA) mechanism and the SimSPPF network to increase the model's ability to extract features of cotton aphid-damaged leaves, balancing the accuracy loss of the model after becoming lightweight. The experimental results demonstrate that the size of the GVC-YOLO model is only 5.4 MB, a decrease of 14.3% compared with the baseline network, with a reduction of 16.7% in the number of parameters and 17.1% in floating-point operations (FLOPs). The mAP@0.5 and mAP@0.5:0.95 reach 97.9% and 90.3%, respectively. The GVC-YOLO model is optimized and accelerated by TensorRT and then deployed onto the embedded edge computing device Jetson Xavier NX for detecting cotton aphid damage video captured from the camera. Under FP16 quantization, the detection speed reaches 48 frames per second (FPS). In summary, the proposed GVC-YOLO model demonstrates good detection accuracy and speed, and its performance in detecting cotton aphid damage in edge computing scenarios meets practical application needs. This research provides a convenient and effective intelligent method for the large-scale detection and precise control of pests in cotton fields. [ABSTRACT FROM AUTHOR]

Mastitis is a significant inflammatory condition of the mammary gland in dairy cows. It is caused by bacterial infections and leads to substantial economic losses worldwide. The disease can be either clinical or sub-clinical and presents challenges such as reduced milk yield, increased treatment costs, and the need to cull affected cows. The pathogenic mechanisms of mastitis involve the activation of Toll-like receptors (TLRs), specifically TLR2 and TLR4. These receptors play crucial roles in recognizing pathogen-associated molecular patterns (PAMPs) and initiating immune responses through the NF-κB signaling pathway. Recent in vitro studies have emphasized the importance of the TLR2/TLR4/NF-κB signaling pathway in the development of mastitis, suggesting its potential as a therapeutic target. This review summarizes recent research on the role of the TLR2/TLR4/NF-κB signaling pathway in mastitis. It focuses on how the activation of TLRs leads to the production of proinflammatory cytokines, which, in turn, exacerbate the inflammatory response by activating the NF-κB signaling pathway in mammary gland tissues. Additionally, the review discusses various bioactive compounds and probiotics that have been identified as potential therapeutic agents for preventing and treating mastitis by targeting TLR2/TLR4/NF-κB signaling pathway. Overall, this review highlights the significance of targeting the TLR2/TLR4/NF-κB signaling pathway to develop effective therapeutic strategies against mastitis, which can enhance dairy cow health and reduce economic losses in the dairy industry. [ABSTRACT FROM AUTHOR]

A fault on the DC side of a flexible HVDC system, along with the rise in short-circuit current, develops rapidly. With the gradual expansion of flexible HVDC technology to large capacities and long-distance transmission and offshore transmission scenarios, the problem of short-circuit current calculation considering the characteristics of line distribution parameters needs urgent attention. Therefore, in order to solve the problem of the inaccurate calculation of the short-circuit current on the DC side, the lumped parameter model is used in a flexible DC system for long-distance transmission. This study analyzes the transmission line structure on the basis of the general model of the MMC short-circuit current calculation on the DC side and establishes a mathematical model of a long-distance transmission line considering the characteristics of distributed parameters. Two impedance equivalent models for different length lines are proposed to facilitate the analytical calculation of the short-circuit current. A short-circuit current calculation method for a flexible HVDC system with long-distance transmission lines is proposed. Additionally, the correctness of the proposed method is verified through the comparison of the simulation values and calculation values. The results show that the error of the lumped parameter calculation is about 10%, and the error of the distributed parameter calculation is less than 2%. [ABSTRACT FROM AUTHOR]

Pest damage is a major factor in reducing crop yield and has negative impacts on the economy. However, the complex background, diversity of pests, and individual differences pose challenges for classification algorithms. In this study, we propose a patch-based neural network (PMLPNet) for multi-class pest classification. PMLPNet leverages spatial and channel contextual semantic features through meticulously designed token- and channel-mixing MLPs, respectively. This innovative structure enhances the model's ability to accurately classify complex multi-class pests by providing high-quality local and global pixel semantic features for the fully connected layer and activation function. We constructed a database of 4510 images spanning 40 types of plant pests across 4 crops. Experimental results demonstrate that PMLPNet outperforms existing CNN models, achieving an accuracy of 92.73%. Additionally, heat maps reveal distinctions among different pest images, while patch probability-based visualizations highlight heterogeneity within pest images. Validation on external datasets (IP102 and PlantDoc) confirms the robust generalization performance of PMLPNet. In summary, our research advances intelligent pest classification techniques, effectively identifying various pest types in diverse crop images. [ABSTRACT FROM AUTHOR]

Abstract: Optimizing feed efficiency through the feed conversion ratio (FCR) is paramount for economic viability and sustainability. In this study, we integrated RNA-seq, ATAC-seq, and genome-wide association study (GWAS) data to investigate key functional variants associated with feed efficiency in pigs. Identification of differentially expressed genes in the duodenal and muscle tissues of low- and high-FCR pigs revealed that pathways related to digestion of dietary carbohydrate are responsible for differences in feed efficiency between individuals. Differential open chromatin regions identified by ATAC-seq were linked to genes involved in glycolytic and fatty acid processes. GWAS identified 211 significant single-nucleotide polymorphisms associated with feed efficiency traits, with candidate genes PPP1R14C, TH, and CTSD. Integration of duodenal ATAC-seq data and GWAS data identified six key functional variants, particularly in the 1500985–1509676 region on chromosome 2. In those regions, CTSD was found to be highly expressed in the duodenal tissues of pigs with a high feed conversion ratio, suggesting its role as a potential target gene. Overall, the integration of multi-omics data provided insights into the genetic basis of feed efficiency, offering valuable information for breeding more efficient pig breeds. [ABSTRACT FROM AUTHOR]

The acquisition of vegetation coverage information is crucial for crop field management, and utilizing visible light spectrum vegetation indices to extract vegetation coverage information is a commonly used method. However, most visible light spectrum vegetation indices do not fully consider the relationships between the red, green, and blue bands during their construction, making it difficult to ensure the accurate extraction of coverage information throughout the crop's entire growth cycle. To rapidly and accurately obtain potato vegetation coverage information, drones were used in this study to obtain high-resolution digital orthoimages of potato growth stages. Based on the differences in the grayscale values of potato plants, soil, shadows, and drip irrigation belts, this study presents a combination index of blue and green bands (BGCI) and a combination index of red and green bands (RGCI). The vegetation index intersection method was used with 10 vegetation information indices to extract vegetation coverage, and the differences in extraction accuracy were compared with those of the maximum entropy method and bimodal histogram method. Based on the high-precision fraction vegetation coverage (FVC) extraction results, the Pearson correlation coefficient method and random forest feature selection were used to screen 10 vegetation and 24 texture features, and the top six vegetation indices most strongly correlated with the FVC were selected for potato growth stage FVC estimation and accuracy verification. A high-precision potato vegetation coverage estimation model was successfully established. This study revealed that during the potato tuber formation and expansion stages, the BGCI combined with the vegetation index intersection method achieved the highest vegetation coverage extraction accuracy, with overall accuracies of 99.61% and 98.84%, respectively. The RGCI combined with the vegetation index intersection method achieved the highest accuracy, 98.63%, during the maturation stage. For the potato vegetation coverage estimation models, the model based on the BGCI achieved the highest estimation accuracy (R2 = 0.9116, RMSE = 5.7903), and the RGCI also achieved good accuracy in terms of vegetation coverage estimation (R2 = 0.8987, RMSE = 5.8633). In the generality verification of the models, the R2 values of the FVC estimation models based on the BGCI and RGCI were both greater than 0.94. A potato vegetation coverage estimation model was constructed based on two new vegetation information indices, demonstrating good accuracy and universality. [ABSTRACT FROM AUTHOR]