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Lysosomes in mammalian cells are recognized as key digestive organelles, containing a variety of hydrolytic enzymes that enable the processing of both endogenous and exogenous substrates. These organelles digest various macromolecules and recycle them through the autophagy–lysosomal system. Recent research has expanded our understanding of lysosomes, identifying them not only as centers of degradation but also as crucial regulators of nutrient sensing, immunity, secretion, and other vital cellular functions. The lysosomal pathway plays a significant role in vascular regulation and is implicated in diseases such as atherosclerosis. During atherosclerotic plaque formation, macrophages initially engulf large quantities of lipoproteins, triggering pathogenic responses that include lysosomal dysfunction, foam cell formation, and subsequent atherosclerosis development. Lysosomal dysfunction, along with the inefficient degradation of apoptotic cells and the accumulation of modified low-density lipoproteins, negatively impacts atherosclerotic lesion progression. Recent studies have highlighted that lysosomal dysfunction contributes critically to atherosclerosis in a cell- and stage-specific manner. In this review, we discuss the mechanisms of lysosomal biogenesis and its regulatory role in atherosclerotic lesions. Based on these lysosomal functions, we propose that targeting lysosomes could offer a novel therapeutic approach for atherosclerosis, shedding light on the connection between lysosomal dysfunction and disease progression while offering new insights into potential anti-atherosclerotic strategies. [ABSTRACT FROM AUTHOR]

Simple load forecasting and overload prediction models, such as LSTM and XGBoost, are unable to handle the increasing amount of data in power systems. Recently, various foundation models (FMs) for time series analysis have been proposed, which can be scaled up for large time series variables and datasets across domains. However, the simple pre-training setting makes FMs unsuitable for complex downstream tasks. Effectively handling real-world tasks depends on additional data, i.e., covariates, and prior knowledge. Incorporating these through structural modifications to FMs is not feasible, as it would disrupt the pre-trained weights. To address this issue, this paper proposes a frequency domain mixer, i.e., FreqMixer, framework for enhancing the task-specific analytical capabilities of FMs. FreqMixer is an auxiliary network for the backbone FMs that takes covariates as input. It has the same number of layers as the backbone and communicates with it at each layer, allowing the incorporation of prior knowledge without altering the backbone's structure. Through experiments, FreqMixer demonstrates high efficiency and performance, reducing MAPE by 23.65%, recall by 87%, and precision by 72% in transformer load forecasting during the Spring Festival while improving precision by 192.09% and accuracy by 14% in corresponding overload prediction, all while processing data from over 160 transformers with just 1M additional parameters. [ABSTRACT FROM AUTHOR]

(1) Background: Oxidative stress plays a pivotal role in the pathophysiologic of hyperemesis gravidarum (HG). Epidemiological studies have explored the associations of specific antioxidant foods and nutrients with HG. However, evidence regarding the relationship between an antioxidant-rich diet and the risk of HG remains limited. The objective of this research was to explore the relationship between antioxidant-rich diet and HG. (2) Methods: This was a population-based cross-sectional study. A total of 2980 pregnant women were included in our population. A composite dietary antioxidant index (CDAI) was calculated by summing the standardized intakes of vitamins A, C, and E, selenium, zinc, and total carotene. A dietary antioxidant potential score (DAPS) was derived using reduced rank regression. Binary logistic regression models were employed to analyze the associations of CDAI and DAPS with risk of HG. (3) Results: In total, 241 (8.09%) cases of HG were identified in this study. After adjusting for potential confounders, including age, socioeconomic status, ethnicity, physical activity, current smoking status, current alcohol consumption, pre-pregnancy body mass index, nutritional supplement usage, total energy intake, gestational week, menstruation regularity, family history of HG, primigravida status, and quality of life during pregnancy, ORs (95% CIs) of HG in the highest tertiles were 0.31 (0.21–0.47) for CDAI and 0.41 (0.28–0.57) for DAPS when comparing lowest tertiles (all p-trend < 0.001). Such associations remained robust across multiple sensitivity analyses and subgroup analyses. (4) Conclusions: Higher CDAI and DAPS, indicative of greater adherence to an antioxidant-rich diet, were associated with a lower risk of HG. This finding underscores the crucial role of consuming antioxidant-rich foods in the prevention of HG. [ABSTRACT FROM AUTHOR]

A composite hydrogen storage vessel (CHSV) is one key component of the hydrogen fuel cell vehicle, which always suffers random vibration during transportation, resulting in fatigue failure and a reduction in service life. In this paper, firstly, the free and constrained modes of CHSV are experimentally studied and numerically simulated. Subsequently, the random vibration simulation of CHSV is carried out to predict the stress distribution, while Steinberg's method and Dirlik's method are used to predict the fatigue life of CHSV based on the results of stress distribution. In the end, the optimization of ply parameters of the composite winding layer was conducted to improve the stress distribution and fatigue life of CHSV. The results show that the vibration pattern and frequency of the free and constrained modes of CHSV obtained from the experiment tests and the numerical predictions show a good agreement. The maximum difference in the value of the vibration frequency of the free and constrained modes of CHSV from the FEA and experiment tests are, respectively, 8.9% and 8.0%, verifying the accuracy of the finite element model of CHSV. There is no obvious difference between the fatigue life of the winding layer and the inner liner calculated by Steinberg's method and Dirlik's method, indicating the accuracy of FEA of fatigue life in the software Fe-safe. Without the optimization, the maximum stresses of the winding layer and the inner liner are found to be near the head section by 469.4 MPa and 173.0 MPa, respectively, and the numbers of life cycles of the winding layer and the inner liner obtained based on the Dirlik's method are around 1.66 × 106 and 3.06 × 106, respectively. Through the optimization of ply parameters of the composite winding layer, the maximum stresses of the winding layer and the inner liner are reduced by 66% and 85%, respectively, while the numbers of life cycles of the winding layer and the inner liner both are increased to 1 × 107 (high cycle fatigue life standard). The results of the study provide theoretical guidance for the design and optimization of CHSV under random vibration. [ABSTRACT FROM AUTHOR]

Glycosylation plays a critical role in various biological processes, yet identifying specific glycosyltransferase substrates remains a challenge due to the complexity of glycosylation. Here, we employ proximity labeling with biotin ligases BASU and TurboID to map the proximitome of MGAT3, a glycosyltransferase responsible for the biosynthesis of the bisecting GlcNAc structure, in HEK293T cells. This approach enriched 116 and 189 proteins, respectively, identifying 17 common substrates shared with bisecting GlcNAc-bearing proteome obtained via intact glycopeptide enrichment methods. Gene ontology analysis revealed that the enriched proteins were predominantly localized in the exosome, endoplasmic reticulum, and Golgi apparatus, consistent with subcellular localization of MGAT3 substrates. Notably, four novel substrates, GOLM2, CCDC134, ASPH, and ERO1A, were confirmed to bear bisecting GlcNAc modification, validating the utility of the proximity labeling method. Furthermore, we observed that bisecting GlcNAc modification inhibits breast cancer progression by promoting the degradation of α-galactosidase A (GLA). These findings demonstrate the efficacy of proximity labeling in identifying glycosyltransferase substrates and provide insights into the functional impact of bisecting GlcNAc modification. [ABSTRACT FROM AUTHOR]

Graphite oxidation to graphene oxide (GO) is carried out using methods developed by Brodie (GO-B) and Hummers (GO-H). However, a comparison of the antibacterial properties based on the physicochemical properties has not been performed. Therefore, this paper outlines a comparative analysis of GO-H and GO-B on antibacterial efficacy against Gram-positive and Gram-negative bacterial cultures and biofilms in an aqueous environment and discusses which of the properties of these GO nanomaterials have the most significant impact on the antibacterial activity of these materials. Synthesis of GO with Brodie's and modified Hummers' methods was followed by an evaluation of their structural, morphological, and physicochemical properties by Raman, FTIR, UV–vis spectroscopy, and X-ray diffraction (XRD). The GO-B surface appeared more oxidized than that of GO-H, which could be crucial for interactions with bacteria. According to our results, GO-B demonstrated notably superior anti-biofilm efficacy. Despite its higher production cost, GO-B exhibits more excellent capabilities in combating bacterial biofilms than GO-H. [ABSTRACT FROM AUTHOR]

In recent years, firefighter accidents and people injured by the collapse of steel structures during a fire have occurred frequently, which has attracted the attention of the National Emergency Management Department and the Fire and Rescue Bureau. It is urgent to carry out research on early warning systems for building collapse during a fire. Existing early warning methods mainly use characteristic parameters such as temperature, vibration, and structural deformation. Due to the complexity of an actual fire, it is difficult to accurately predict the critical temperature of fire−induced instability in columns and the failure mode after the instability, and there are deviations in the collapse warnings. In this study, changes in ultrasonic transverse and longitudinal wave velocities at high temperatures are used to monitor the stiffness degradation of columns in fire in real time and improve the accuracy of early warning systems. In this study, four common collapse modes of portal frames are obtained by using the results of parametric numerical analysis. According to key displacements and the displacement rates of simple key measuring points, the elastic modulus threshold of a three−level early warning for portal frame collapse with different collapse modes is obtained. Combined with an ultrasonic experiment, the theoretical relationships between the transverse and longitudinal wave velocities and the elastic modulus of steel at high temperatures are verified, and the relationship between the transverse and longitudinal wave velocities and the overall damage of the portal frame is further constructed; then, a new early warning method for portal frame stability during a fire is proposed. Based on the change in wave velocity, a three-level early warning index for predicting portal frame stability during a fire is determined. When the collapse mode of a portal frame is an overall inward collapse, transverse and longitudinal wave velocities are reduced to 2635 m/s and 5308 m/s, respectively. At a second-level warning, they are reduced to 2035 m/s and 4176 m/s, respectively. At 1504 m/s and 3030 m/s, respectively, third-level warnings are issued. This research shows that the real−time monitoring of wave velocities provides an effective way for early warning systems to identify structural collapse. The proposed early warning method can be used as a quick and efficient early warning system for the collapse of portal frames during a fire, and its accuracy and applicability are verified by experiments. [ABSTRACT FROM AUTHOR]

Increasing attention is being directed toward understanding the impact of urban built environments on children's health. The concept of the 15-minute city, or "15-minute life circle", in China is significant; however, the needs of the pediatric population are often overlooked. Walkability and accessibility to urban service facilities are crucial for promoting children's well-being. This paper focuses on the old city of Guilin in western China as a case study. It investigates the service facilities within a 15-minute life circle that affect children's physical health, mental health, and social engagement. Utilizing the Walking Index method, this study assesses the walkability and rationality of these facilities in 621 neighborhoods. Data were gathered from 200 questionnaires and interviews with children, concentrating on their daily use of these facilities, supplemented by a multi-source analysis. The findings reveal that the Walking Index in the study area is generally low, with an uneven distribution, primarily influenced by road network density, block size, and urban landscape patterns. This study proposes the development of a "Children's Healthy 15-minute Life Circle", which would increase child-friendly service facilities, pedestrian infrastructure, and urban road network density. It also advocates for constructing service facilities that enhance children's health and the optimization of the spatial arrangement of these facilities. Furthermore, it suggests the effective utilization of urban landscapes to create a diverse system of leisure spaces for children. This study offers valuable insights for enhancing the walkability of urban life circle service facilities and establishing a child-friendly city. [ABSTRACT FROM AUTHOR]

A combined seedling extraction device was developed that operates by first top loosening and then clamping the stem in order to solve the current issues with automated transplanting technology, such as low seedling extraction efficiency and a high rate of substrate loss. The pepper plug tray seedlings were selected as the experimental subjects for testing the mechanical properties of the stems. The tensile and compressive mechanical properties of the stems were obtained, and the kinematic model of the seedling spacing process and the mechanical model of the seedling clamping process were established. Key parameters of the seedling extraction device were analyzed and calculated, and an automated seedling extraction system was constructed. Using substrate moisture content, seedling age, and extraction frequency as experimental factors, orthogonal tests were conducted. Through variance analysis and 3D response surface analysis, the optimal rounded parameter values were determined: 48% substrate moisture content, 38-day-old seedlings, and a seedling extraction frequency of 60 plants/min. Under these conditions, the seedling extraction success rate was 94.44%, the substrate loss rate was 6.07%, and the seedling damage rate was 4.17%, meeting the requirements for automated seedling extraction. [ABSTRACT FROM AUTHOR]

Chinese coral snakes (Sinomicrurus) are highly neglected regarding their venom profiles and harm to humans, which impedes our ability to deeply understand their biological properties and explore their medicinal potential. In this study, we performed a comparative analysis to reveal the venom profiles of two Chinese coral snakes in terms of their venom yields, proteomic profiles, and immunorecognition by commercial antivenoms. The results showed that Sinomicrurus kelloggi expels more venom (lyophilized venom mass) than Sinomicrurus maccelellandi but possesses a similar solid venom content. These interspecific differences in venom yield were influenced by the snout–vent length. The venoms of these two species varied in their electrophoretic profiles, as well as in the presence or absence and relative abundance of protein families. They exhibited a 3-FTx-predominant phenotype, where the S. maccelellandi venom was dominated by 3-FTx (32.43%), SVMP (23.63%), PLA2 (19.88%), and SVSP (12.61%), while the S. kelloggi venom was dominated by 3-FTx (65.81%), LAAO (11.35%), and AMP (10.09%). While both the commercial Naja atra and Bungarus multicinctus antivenoms could immunorecognize these two Chinese coral snake venoms, the N. atra antivenom possessed a higher neutralization capability than the B. multicinctus antivenom for both species of coral snakes. Our findings show significant interspecific variations in the venom profiles of these Sinomicrurus snakes for the first time. We suggest screening or preparing specific antivenoms with high efficiency for the clinical treatment of envenomation caused by these snakes. [ABSTRACT FROM AUTHOR]

With the digital transformation of the manufacturing industry, data monitoring and collecting in the manufacturing process become essential. Pointer meter reading recognition (PMRR) is a key element in data monitoring throughout the manufacturing process. However, existing PMRR methods have low accuracy and insufficient robustness due to issues such as blur, uneven illumination, tilt, and complex backgrounds in meter images. To address these challenges, we propose an end-to-end PMRR method based on a decoupled circle head detection algorithm (YOLOX-DC) and a Unet-like pure Transformer segmentation network (PM-SwinUnet). First, according to the characteristics of the pointer dial, the YOLOX-DC detection algorithm is designed based on the exceeding you only look once detector (YOLOX). The decoupled circle head of YOLOX-DC detects the pointer meter dial more accurately than the commonly used rectangular detection head. Second, the window multi-head attention of the PM-SwinUnet network enhances the feature extraction ability of pointer meter images and solves problems of missed scale detection and incomplete pointer segmentation. Additionally, the scale and pointer fitting module is introduced into the PM-SwinUnet to locate the accurate position of the scale and pointer. Finally, through the angle relationship between the pointer and the first two main scale lines, the pointer meter reading is accurately calculated by the improved angle method. Experimental results demonstrate the effectiveness and superiority of the proposed end-to-end method across three-pointer meter datasets. Furthermore, it provides a rapid and robust approach to the digital transformation of manufacturing systems. [ABSTRACT FROM AUTHOR]

Heartwood, serving as the central constituent of the xylem, plays a crucial role in the growth, development, and resilience of trees. The process of heartwood formation constitutes a complex biological phenomenon influenced by various factors. A thorough examination of the mechanisms underpinning heartwood formation not only enhances our understanding of the growth and developmental paradigms regulating trees but also provides essential theoretical support and practical insights for the timber industry, forestry management, and ecological conservation. This paper offers an overview of the foundational processes involved in heartwood formation in plants. Furthermore, it presents a comprehensive review of the latest research advancements in this domain, covering five key aspects: metabolism, hormonal regulation, transcriptional regulation, cell biology, and environmental influences. This review serves as a valuable basis for future research endeavors in related academic fields. [ABSTRACT FROM AUTHOR]

Soil salinization is a serious land degradation phenomenon, posing a severe threat to regional agricultural resource utilization and sustainable development. It has been a mainstream trend to use machine-learning methods to achieve monitoring of large-scale salinized soil quickly. However, machine learning model training requires many samples and hyper-parameter optimization and lacks solvability. To compare the performance of different machine-learning models, this study conducted a soil sampling experiment on saline soils along the south bank of the Yellow River in Dalate Banner. The experiment lasted two years (2022 and 2023) during the spring bare soil period, collecting 304 soil samples. The soil salinity was estimated with the multi-source remote sensing satellite data by combining the extreme gradient boosting model (XGBoost), Optuna hyper-parameter optimization, and Shapley addition (SHAP) interpretable model. Correlation analysis and continuous variable projection were employed to identify key inversion factors. The regression effects of partial least squares regression (PLSR), geographically weighted regression (GWR), long short-term memory networks (LSTM), and extreme gradient boosting (XGBoost) were compared. The optimal model was selected to estimate soil salinity in the study area from 2019 to 2023. The results showed that the XGBoost model fitted optimally, the test set had high R2 (0.76) and the ratio of performance to deviation (2.05), and the estimation results were consistent with the measured salinity values. SHAP analysis revealed that the salinity index and topographic factors were the primary inversion factors. Notably, the same inversion factor influenced varying soil salinity estimates at different locations. The saline soils of the study area in 2019 and 2023 were 65% and 44%, respectively, and the overall trend of soil salinization decreased. From the viewpoint of spatial distribution, the degree of soil salinization showed a gradually increasing trend from south to north, and it was most serious on the side near the Yellow River. This study is of great significance for the quantitative estimation of salinized soil in the irrigated area on the south bank of the Yellow River, the prevention and control of soil salinization, and the sustainable development of agriculture. [ABSTRACT FROM AUTHOR]

The growth stage of wheat is key information for critical decision-making related to cultivar screening of wheat and farming activities. In order to solve the problem that it is difficult to determine the growth stages of a large number of wheat breeding materials grown in an artificial climate room accurately and quickly, the first attempt was made to determine the growth stages of wheat using image sequences of growth and development. A hybrid model (DenseNet–BiLSTM) based on the DenseNet and Bidirectional Long Short-Term Memory was proposed for determining the growth stage of wheat. The spatiotemporal characteristics of wheat growth and development were modeled by DenseNet–BiLSTM synthetically to classify the growth stage of each wheat image in the sequence. The determination accuracy of the growth stages obtained by the proposed DenseNet–BiLSTM model was 98.43%. Of these, the determination precisions of the tillering, re-greening, jointing, booting, and heading period were 100%, 97.80%, 97.80%, 85.71%, and 95.65%, respectively. In addition, the accurate determination of the growth stages and further analysis of its relationship with meteorological conditions will help biologists, geneticists, and breeders to breed, screen, and evaluate wheat varieties with ecological adaptability. [ABSTRACT FROM AUTHOR]

The effects of rare earth Y on the microstructures and tensile properties of ZL109 alloys were studied through metallographic observation, scanning electron microanalysis, X-ray diffraction, and tensile experiments, and the existence form and mechanism of Y were analyzed. The results show that the grain size of the ZL109 alloy is obviously reduced and that the strength of the ZL109 alloy is significantly increased after adding the Y element. When the Y content is increased to 0.2 wt.%, the tensile properties of the ZL109 alloy at room temperature and 350 °C are better than those without a rare earth addition, and the comprehensive tensile properties are better. This is due to the addition of the Y element; α-Al dendrites are obviously refined, and there is a tendency for them to change into fine isometric crystals. The size of the eutectic Si decreases, and its shape is modified. The morphology and size of high temperature enhanced phases, such as Al3CuNi, are optimized. The heat-resistant enhanced phase Al2Si2Y is formed after the addition of rare earth Y. However, with the addition of the Y element, the Al2Si2Y phase increases, and coarsening results in the decrease in alloy strength. [ABSTRACT FROM AUTHOR]

Residues of the pesticides chlorfenapyr (CFP) and emamectin benzoate (EMB) often coexist in the environment and can be accumulated in the body. To understand the impact of these two chemicals on health, we investigated their effect on the kidneys. In this study, rats were treated with CFP and/or EMB at low/medium/high doses of 1/3/9 mg/kg/day and 0.2/0.6/1.8 mg/kg/day, respectively, via oral gavage for 60 days. Kidneys and serum samples were collected and serum biochemistry and kidney histopathological changes were analyzed and examined. Kidney metabolome alterations were analyzed by using gas chromatography–mass spectrometry. The results showed that combined exposure to CFP and EMB elevated BUN levels and induced pathological damage, which presented as thinner renal tubular epithelial cells, an abnormal glomerular morphology, and an increased fibrotic area. CFP and/or EMB disrupted glutathione metabolism and carbohydrate metabolism, resulting in the alteration of kidney metabolomes and inducing oxidative stress in the cells of kidney tissues. In addition, CFP decreased ATP content and inhibited pyruvate PDH activity in the kidneys. These findings suggest that long-term exposure to CFP and EMB at environmentally relevant levels induce alterations in the renal metabolome, oxidative stress, and an insufficient energy supply, which may contribute to renal histopathological damage. [ABSTRACT FROM AUTHOR]

Hydrogen production through the catalytic pyrolysis of low-value organic solid waste offers a promising low-carbon and environmentally friendly pathway. However, the design of efficient hydrogen-producing catalysts remains a significant challenge. Herein, NiO/Al2O3 as a catalyst precursor was utilized to investigate the effects of reduction temperature gradients (300–800 °C) on the distribution of three-phase products and the composition of gaseous products during the pyrolysis of waste textiles. Compared to unreduced NiO/Al2O3, increasing the reduction temperature (300–700 °C) led to a gradual decrease in liquid-phase products and a notable increase in gas-phase products, with the latter rising by 10.59% at 700 °C. Most strikingly, hydrogen gas production increased by 6.42% under the same conditions. Multi-characterization analyses, including XRD, TEM, and H2-TPR, revealed significant aggregation of highly dispersed Ni species in NiO/Al2O3 at higher reduction temperatures. The emergence of XRD characteristic peaks and the (111) crystal face of metallic Ni (Ni0) became apparent at 700 °C. More importantly, the XPS test inferred that the increasement of hydrogen-rich gas production was ascribed to the appropriate Ni0/Ni2+ ratio, and the highest hydrogen yield of 41.50% was achieved as the Ni0/Ni2+ ratio reached about 1.57. This work not only provides an effective solution for the consumption of waste textiles, but also converts it into high value-added hydrogen-rich gas. [ABSTRACT FROM AUTHOR]

The rectangular cartogram is a geospatial visualization method that blends the characteristics of maps and charts. By simplifying geographic regions into rectangles and using the area of each rectangle to represent statistical data, it enables efficient geovisualization. This paper summarizes and analyzes the advantages and limitations of two main approaches used in current rectangular cartogram construction algorithms. To address the issues of high computational cost and inadequate preservation of adjacency and relative positional relationships in existing algorithms, we propose and implement a new rectangular cartogram construction algorithm. This algorithm simplifies the layout computation process while ensuring that the adjacency and relative positional relationships between regions during the layout generation process have only minor errors. In adjusting rectangle areas to match attribute values, the algorithm adopts a "region-by-region placement" strategy, ensuring that errors in area accuracy remain within a small range, while also keeping errors in adjacency and relative positional relationships minimal. Finally, by comparing the results of our algorithm with those of existing algorithms using real-world data with varying distribution characteristics, we demonstrate its effectiveness. The results show that the proposed algorithm not only improves computational efficiency but also effectively displays the adjacency and relative positional relationships between regions. [ABSTRACT FROM AUTHOR]

This study aims to explore the effect of microstructural parameters on the notch fatigue damage behavior of the TC21 alloy. Different levels of lamellar microstructures were achieved through distinct aging temperatures of 550 °C, 600 °C, and 650 °C. The findings reveal that increasing aging temperature primarily contributes to the augmentation of α colony (αc) thickness, grain boundaries α phase (GBα) thickness, and α fine (αfine) size alongside a reduction in α lath (αlath) thickness and αfine content. The notch alters stress distribution and relaxation effects at the root, enhancing notched tensile strength while weakening plasticity. Moreover, the increased thickness of GBα emerges as a critical factor leading to the increase area of intergranular cleavage fracture. It is noteworthy that more thickness αlath and smaller αfine facilitate deformation coordination and enhance dislocation accumulation at the interface, leading to a higher propensity for micro-voids and micro-cracks to propagate along the interface. Conversely, at elevated aging temperatures, thinner αlath and larger αfine are more susceptible to fracture, resulting in the liberation of dislocations at the interface. The reduction in αlath thickness is crucial for triggering the initiation of multi-system dislocations at the interface, which promotes the development of persistent slip bands (PSBs) and dislocation nets within αlath. This phenomenon induces inhomogeneous plastic deformation and localized hardening, fostering the formation of micro-voids and micro-cracks. [ABSTRACT FROM AUTHOR]

The majority of the world's forests are located at landscape edges and are highly fragmented; the plantations on the Loess Plateau are no exception, experiencing pronounced edge effects. However, edge effects are often overlooked in assessments of carbon storage and biodiversity, and the extent and impact of these effects on Loess Plateau plantations remain inadequately understood. The objective of this study is to reveal how edge effects influence biodiversity and species composition and to examine their long-term impacts on ecosystem structure and function. Furthermore, it aims to explore the mechanisms underlying edge effects in plantation systems. Examining these effects is essential for guiding forest management practices and formulating effective biodiversity conservation strategies, thereby providing scientific insights to support the ecological restoration and sustainable management of plantations. In this study, we classified 44 sample plots into four groups according to their distances from the plantation edges to compare and analyze species composition. Additionally, we evaluated the intensity and range of edge effects on stand structure, species diversity, and carbon storage. The Shannon index of understory vegetation was used as the dependent variable, with canopy cover, edge distance, and stand density as independent variables. We used multiple linear regression to examine the effects of these factors on the Shannon index of understory vegetation (shrubs, herbs, and trees). The key findings were as follows: (1) Tree height did not exhibit edge effects across any distance range, while the Shannon index, species richness, and carbon storage showed edge effects within 54 m from the edge. Diameter at breast height (DBH), stand density, and canopy cover exhibited edge effects within 0–83 m from the edge. (2) The significance values for edge distance and canopy cover in the linear regression with the Shannon index were 0.99 and 0.51, respectively, showing no significant correlation. In contrast, stand density had a significant positive effect on the Shannon index (p = 0.03). (3) Notable differences in understory species composition were observed between the outermost and innermost groups of the plantation. Climatic conditions on the Loess Plateau exert a dominant influence on understory plants, altering species composition and abundance. High stand density appeared to moderate the microclimate, contributing to a higher understory Shannon index, but reducing carbon storage. Our findings suggest that the edge effects of plantation forests on the Loess Plateau exert varying degrees of influence on different indicators. Management decisions should be guided by the specific silvicultural objectives, whether the manager's goals are to optimize biomass accumulation, enhance species recovery, or achieve a balance between these two goals. [ABSTRACT FROM AUTHOR]

To address prominent issues in the spring soil removal process for wine grapes in northern China, such as incomplete soil clearing, vine damage, and low operational efficiency, a dual-sided soil removal machine combining scraping, rotary, and vibration functions was designed and developed. The machine primarily consists of a gantry frame, rotary soil components, scraping components, and vibrating components. Using EDEM 2020 discrete element software analysis and Design-Expert 13 orthogonal experiments, a three-factor, three-level orthogonal simulation experiment was conducted, with rotary soil component speed, scraping component angle, and vibrating component frequency as test factors and soil removal rate as the evaluation index. The optimal operating parameters were determined: rotary soil component speed at 720.6 r/min, scraping component angle at 42.4°, and vibrating component frequency at 179.1 Hz, yielding a soil removal efficiency (K value) of 83.48% and the best simulation results. A physical prototype was manufactured, and field experiments were conducted, resulting in an actual soil removal rate of 76.81%, with a deviation of 7.09% from the simulation results. The field test results were consistent with the simulation data, and the exposed vines in the field after soil removal met the operational requirements for actual production. The research outcomes of this machine provide a reference for the further development of dual-sided soil removal equipment for wine grape vines. [ABSTRACT FROM AUTHOR]

Citrus huanglongbing (HLB) is one of the most severe diseases affecting the citrus industry, with Diaphorina citri (Hemiptera: Liviidae) serving as its primary natural vector. To understand the genetic diversity and population structure of D. citri in the context of HLB diffusion, we analyzed 13 populations from the HLB diffusion frontier and 25 populations from epidemic areas in China. The HLB diffusion frontier areas refer to the peripheral regions of HLB distribution in China, including the western Zhejiang, southern Jiangsu, northern Jiangxi, northern Hunan, and eastern Sichuan provinces. In contrast, the HLB epidemic areas represent regions in China where HLB is actively widespread and causing significant impacts. We utilized mitochondrial genes (COI, ND5, and Cytb) of D. citri and housekeeping genes (dnaQ, rpoC, and argH) of its endosymbiont Candidatus Carsonella ruddii (Ca. C. ruddii) for this analysis. Our findings revealed that the D. citri and Ca. C. ruddii in different regions showed low haplotype diversity and nucleotide diversity. While the genetic variation in D. citri populations primarily occurred within populations, the endosymbiont showed contrasting patterns in the HLB epidemic areas. We identified three dispersal paths: (1) migration of the Yunnan population to Sichuan, Guizhou, and Guangxi; (2) movement of the Guangdong population to Fujian, Jiangxi, and Zhejiang; and (3) dispersal of the Guangdong population to Hunan and Guangxi. Our study suggests that D. citri populations at the HLB diffusion frontier are predominantly transmitted from neighboring epidemic areas. [ABSTRACT FROM AUTHOR]

Quadruped robots, with their biomimetic structure, are capable of stable locomotion in complex terrains and are vital in rescue, exploration, and military applications. However, developing multi-modal robots that feature simple motion control while adapting to diverse amphibious environments remains a significant challenge. These robots need to excel at obstacle-crossing, waterproofing, and maintaining stability across various locomotion modes. To address these challenges, this paper introduces a novel leg–fin integrated propulsion mechanism for a bionic quadruped robot, utilizing rapidly advancing soft materials and integrated molding technologies. The robot's motion is modeled and decomposed using an improved central pattern generator (CPG) control network. By leveraging the control characteristics of the CPG model, global control of the single-degree-of-freedom drive mechanism is achieved, allowing smooth transitions between different motion modes. The design is verified through simulations conducted in the Webots environment. Finally, a physical prototype of the quadruped compliant robot is constructed, and experiments are carried out to test its walking, turning, and obstacle-crossing abilities in various environments. The experimental results demonstrate that the robot shows a significant speed advantage in regions where land and water meet, reaching a maximum speed of 1.03 body lengths per second (bl/s). [ABSTRACT FROM AUTHOR]

Sepsis is a life-threatening condition resulting from a dysregulated host response to infection. Currently, there is no effective therapy for sepsis due to an incomplete understanding of its pathogenesis. Scavenger receptor BI (SR-BI) is a high-density lipoprotein (HDL) receptor that plays a key role in HDL metabolism by modulating the selective uptake of cholesteryl ester from HDL. Recent studies, including those from our laboratory, indicate that SR-BI protects against sepsis through multiple mechanisms: (1) preventing nitric oxide-induced cytotoxicity; (2) promoting hepatic lipopolysaccharide (LPS) clearance and regulating cholesterol metabolism in the liver; (3) inhibiting LPS-induced inflammatory signaling in macrophages; and (4) mediating the uptake of cholesterol from HDL for inducible glucocorticoid (iGC) synthesis in the adrenal gland, which controls systemic inflammatory response. In this article, we review the roles of SR-BI in sepsis. [ABSTRACT FROM AUTHOR]

We observed tunable characteristics of optical frequency combs (OFCs) generated from InGaAs/GaAs double quantum wells (DQWs) asymmetric waveguide two-section mode-locked lasers (TS-MLLs). This involves an asymmetric waveguide mode-locked semiconductor laser (AWML-SL) operating at a center wavelength of net modal gain of approximately 1.06 µm, which indicates a stable pulse shape, with the power-current(P-I) characteristic curve revealing a small difference between forward and reverse drive currents in the gain region. Under different operating conditions, the laser exhibits the characteristics of OFCs. And the pulse interval in the timing and the peak interval in the frequency domain show a periodic alternating change trend with the increase in the gain current. This tunable characteristic is reported for the first time. The study demonstrates the feasibility of generating tunable optical combs using a monolithic integrated two-section mode-locked semiconductor laser (MI-TS-MLL). This has important reference value for the application of OFCs generated from MI-TS-MLLs or integrated optical chips. [ABSTRACT FROM AUTHOR]

Herein, we report the first example of molybdenum-catalyzed (E)-Selective anti-Markovnikov hydrosilylation of alkynes. The reaction operates effectively with the utilization of minute amounts of the inexpensive, bench-stable pre-catalyst and ligand under mild conditions. Moreover, this molybdenum-catalyzed hydrosilylation process features the advantages of simple operation, excellent selectivity, and broad functional groups tolerance. [ABSTRACT FROM AUTHOR]

The corrosion resistance of nickel–titanium nitride (Ni/TiN) composites is significantly influenced by the operation parameters during the jet pulse electrodeposition (JPE) process. The effect of current density, jet rate, TiN concentration, and duty cycle impact on the anti-corrosion property of Ni/TiN composites were investigated and optimized using the response surface method (RSM). After the optimization of the operation parameters, the corrosion current of Ni/TiN composites decreased from 9.52 × 10−5 A/cm2 to 4.63 × 10−5 A/cm2. The corrosion current of Ni/TiN composites decreased initially and then increased with an increase in current density, jet rate, TiN concentration, and duty cycle. During the jet electrodeposition process, the influence of the duty cycle on the corrosion current of Ni/TiN composites was comparatively insignificant, whereas the concentration of TiN had a significant effect on the corrosion current. The error rate between the predicted value and the measured result from the corrosion current of Ni/TiN composites was only 0.64%, indicating the high accuracy of fitting the model. Furthermore, X-ray diffraction (XRD) patterns and scanning electron microscope (SEM) images revealed that the optimized Ni/TiN composites comprised significant Ti content, fine nickel gain, and a compact, smooth structure. In addition, the electrochemical measured results demonstrated that the optimized Ni/TiN composites possessed a low self-corrosion current and high self-corrosion potential. These findings show that the optimized composites have a substantially greater corrosion resistance compared to two other unoptimized Ni/TiN composites. [ABSTRACT FROM AUTHOR]

Quantum heat engines (QHEs) are established by applying the principles of quantum thermodynamics to small−scale systems, which leverage quantum effects to gain certain advantages. In this study, we investigate the quantum Otto cycle by employing the dipole−dipole coupled polar molecules as the working substance of QHE. Here, the molecules are considered to be trapped within an optical lattice and located in an external electric field. We analyze the work output and the efficiency of the quantum Otto heat engine (QOHE) as a function of various physical parameters, including electric field strength, dipole−dipole interaction and temperatures of heat baths. It is found that by adjusting these physical parameters the performance of the QOHE can be optimized effectively. Moreover, we also examine the influences of the entanglement and relative entropy of coherence for the polar molecules in thermal equilibrium states on the QOHE. Our results demonstrate the potential of polar molecules in achieving QHEs. [ABSTRACT FROM AUTHOR]

In architectural heritage research, rituals and human activities are often overlooked but are crucial for maintaining authenticity and reflecting various cultural values. In the Tibetan-Yi Corridor, one of China's most renowned heritage routes, rituals and behaviours around the central pillar or fire pit reflect the shared culture and history of Di-Qiang ethnic groups, serving as critical indicators in studying their origins. A scientific method linking physical spaces with intangible cultural information is essential to preserve these rituals or activities and understand their interactions with architectural spaces. This study introduces a method utilising HBIM technology to document and analyse the 3D structures of Di-Qiang ethnic architecture and the rituals. It deconstructs rituals into bodily movements represented within the BIM space to simulate the behaviours of various roles. This method visualises ritual types and critical information by encoding different rituals and movements through geometric shapes, sizes, and colours, effectively linking architectural spaces with intangible cultural elements. The study's two main contributions are (i) the HBIM archival method for Di-Qiang ethnic architecture, standardising geometric modelling and semantic information recording to digitise Di-Qiang architectural heritage, and forming a foundational 3D model library and semantic database; and (ii) the 3D representation method for ritual movements, which offers a way to manage intangible cultural information and spatially assess cultural behaviours, and evaluates the authenticity and quality of architectural heritage by analysing bodily rituals in space. This approach introduces a novel method for documenting and researching intangible heritage in cultural studies. Additionally, the digital technology-based research method offers a convenient platform for integrating and connecting digital heritage with digital humanities in the future. [ABSTRACT FROM AUTHOR]

To improve the regulatory capacity of distributed resources within the park and enhance the flexibility of market transactions, this paper introduces a distributed dispatch and profit allocation method grounded in cooperative game theory and the generalized Nash bargaining framework. Initially, models for individual park equipment are established. Subsequently, a distributed dispatch model is constructed, followed by the development of a profit allocation strategy based on contribution levels, using the generalized Nash bargaining method. The model is solved using the alternating direction method of multipliers. The results show that the proposed approach achieves fast convergence, optimizes resource sharing and mutual support within the park, lowers operational costs, ensures a fairer distribution of profits, and promotes increased cooperation among park entities. [ABSTRACT FROM AUTHOR]

This review summarizes the latest progress in enzyme preparation, including enzyme design and modification technology, exploration of new enzyme sources, and application of enzyme preparation in food processing, detection, and preservation. The directed evolution technology improved the stability and catalytic efficiency of enzymes, while enzyme immobilization technology enhanced reusability and industrial applicability. Extremozymes and biomimetic enzymes exhibit excellent performance under harsh conditions. In food processing, enzyme preparation can improve food quality and flavor. In food detection, enzymes combined with immune detection and biosensors realize rapid detection of allergens, pollutants, and pesticide residues. In food preservation, enzymes enhance food quality by extending shelf life and inhibiting microbial growth. In the future, enzyme engineering will be combined with computer-aided design, artificial intelligence, and new material technology to promote intelligent enzyme design and multifunctional enzyme preparation development and help the technological upgrading and sustainable development of the food industry and green chemistry. [ABSTRACT FROM AUTHOR]

Age-related macular degeneration (AMD) is a leading cause of vision loss in the elderly, significantly diminishing quality of life. Currently, there is no available treatment to reverse retinal degeneration and neuronal loss, prompting a focus on interventions that slow the progression of intermediate AMD and geographic atrophy. Berries are rich in bioactive compounds, including flavonoids, anthocyanins, carotenoids, and resveratrol, known for their antioxidant, anti-inflammatory, and anti-angiogenic properties. Preclinical studies suggest that extracts from various berries, such as aronia, honeysuckle, black currant, goji, and bilberry, can improve retinal health by reducing oxidative stress and inflammation. Although clinical trials are limited, emerging evidence indicates that dietary intake of these compounds may enhance visual function and slow the progression of AMD. This review summarizes findings from both animal studies and clinical trials to identify specific berries that have been validated to prevent or delay AMD progression, as well as those with potential therapeutic value. Furthermore, we examine the key phytochemicals present in these berries, their mechanisms of action on macular degeneration, and their distinct properties for therapeutic application. A deeper understanding of these characteristics could enable the rational appliance of berries, especially wolfberry, and berry-derived components, such as carotenoids and anthocyanins, to optimize better therapeutic outcomes in AMD management. [ABSTRACT FROM AUTHOR]

Soil nutrient buildup is a key process in nutrient-poor arid and semiarid regions. However, our knowledge of the factors that control soil nutrient buildup in these systems is still limited. An experiment was set up and carried out for five and a half years in order to investigate how precipitation and other site factors control soil nutrient buildup. Topsoil carbon (C), nitrogen (N), phosphorus (P), and potassium (K) derived from litter (soil nutrient buildup) were tracked twice a year at two sites differing in terms of climate and soils (Urat: arid and Naiman: semiarid, both in Inner Mongolia). Precipitation was manipulated at both sites to include seven precipitation levels: three reduced levels (−20, −40, and −60% with respect to the background), background (control), and three enhanced levels (+20, +40, and +60% with respect to the background). The dynamic buildup (i.e., amount of nutrients released among consecutive samplings) for all nutrients was controlled by precipitation (nonlinearly), site effects (lower buildup at the site dominated by aeolian pedogenesis), and seasonality (higher under warm conditions). However, the considered nutrients differed in the factor that most determined their buildup. Through studying the concurrent dynamics of litter decomposition and soil nutrient buildup, we can foresee that changes in precipitation and land degradation are most likely to affect the soil nutrient pools in these ecosystems. [ABSTRACT FROM AUTHOR]

Background: Mirabilis himalaica, distributed in the high-altitude, arid, and semi-arid regions of Xizang, exhibits great tolerance to drought, which is rich in rotenoids and other secondary metabolites. It is still unknown, though, how drought stress influences rotenoid synthesis in M. himalaica. Methods: In this study, the calli of M. himalaica were subjected to 5% PEG6000 for 0, 20, and 40 h and divided into control group (CK), mild-drought-treated group (M), and high-drought-treated group (H), respectively. We then analyzed the relative content of three main rotenoids in M. himalaica using high-performance liquid chromatography–electrospray ionization–tandem mass spectrometry (HPLC-ESI-MS/MS). Results: Our findings demonstrated that the content of rotenoids was significantly reduced under drought stress. Transcriptome analysis subsequently revealed 14,525 differentially expressed genes (DEGs) between the different treatments. Furthermore, these DEGs exhibited enrichment in pathways associated with isoflavone biosynthesis and hormone signaling pathways. Key genes with decreased expression patterns during drought stress were also found to be involved in rotenoid accumulation and drought-responsive phytohormone signaling, including abscisic acid (ABA), auxin (IAA), and jasmonic acid (JA). Conclusions: These findings elucidate the molecular processes of drought resistance in M. himalaica and shed light on the relationship between rotenoid production and drought stress in M. himalaica. [ABSTRACT FROM AUTHOR]

Sustainable design concepts are design concepts that the United Nations and China have been promoting that aim to achieve environmental sustainability, social sustainability, and economic sustainability. In recent years, with the rise of intelligent drying wardrobes, more and more scholars have applied the concept of sustainable design to the theoretical research and design practices of intelligent drying wardrobes. But most of them focus on the research and practice of a certain functional module, while less focus on end users. This study examines users' perceptions of the functional modules of intelligent drying wardrobes through a questionnaire. It focuses on environmental, social, and economic sustainability. The research also measures users' satisfaction and the importance of these modules using IPA. From the perspective of end users, the results show that social sustainability is the best option, followed by economic sustainability and environmental sustainability. From the enterprise point of view, the high priority of social sustainability in terms of user's needs is highlighted. However, in response to sustainable development policy, environmental sustainability is taken as the second most important guiding factor for the development of intelligent drying wardrobe functional modules. This paper fills the current research gap on the differences in users' perceptions of intelligent drying wardrobe design modules and prioritizes users' perception decisions on functional modules from the perspective of sustainability, so as to provide some reference for enterprise production. [ABSTRACT FROM AUTHOR]

During the ignition process of a solid rocket motor, the pressure changes dramatically and the ignition process is very complex as it includes multiple reactions. Successful completion of the ignition process is essential for the proper operation of solid rocket motors. However, the measurement of pressure becomes extremely challenging due to several issues such as the enormity and high cost of conducting tests on solid rocket motors. Therefore, it needs to be investigated using numerical calculations and other methods. Currently, the fundamental theories concerning the ignition process have not been fully developed. In addition, numerical simulations require significant simplifications. To address these issues, this study proposes a solid rocket motor pressure prediction method based on bidirectional long short-term memory (CBiLSTM) combined with adaptive Gaussian noise (AGN). The method utilizes experimental pressure data and simulated pressure data as inputs for co-training to predict pressure data under new operating conditions. By comparison, the AGN-CBiLSTM method has a higher prediction accuracy with a percentage error of 3.27% between the predicted and actual data. This method provides an effective way to evaluate the performance of solid rocket motors and has a wide range of applications in the aerospace field. [ABSTRACT FROM AUTHOR]

As the imaging distance and focal length of photoelectric systems increase, the requirements for line-of–sight stabilization of optical inertial stabilized platforms (ISPs) become higher. Disturbance rejection directly determines the stability accuracy of optical inertial stabilized platforms. However, the accurate observation and suppression of wide-band and rapidly changing disturbances remains a challenge in current engineering applications. This paper proposes a robust extended sliding mode observer (ESMO) method to improve disturbance estimation performance. First, the linear extended state observer (LESO) is designed by taking the total disturbances as extended states. Then, a sliding mode observer (SMO) is incorporated in the extended states of the extended observer, forming a robust ESMO. Subsequently, the robustness and convergence characteristics of the proposed method are mathematically proved, revealing that it operates robustly without knowing the disturbance's upper bound and offers faster dynamics and higher accuracy than the LESO. Finally, a series of simulation experimental tests are performed to demonstrate the effectiveness of the proposed method. The proposed method observes wide-band and rapidly changing disturbances utilizing the rapidly switching characteristic of the SMO and smooths the jitter of the SMO by cascading sliding mode estimation to the differentiation term of extended observation, achieving the integral effect of the reaching law. Meanwhile, this method only requires adjusting two parameters, making it suitable for engineering applications. It can be effectively used in optical inertial stabilized platform control systems for disturbance estimation and compensation. [ABSTRACT FROM AUTHOR]

Aiming at the uncertainty problem caused by the time-varying modeling parameters associated with ship speed in the course tracking control of underactuated surface vessels (USVs), this paper proposes a control algorithm based on the dynamic neural fuzzy model (DNFM). The DNFM simultaneously adjusts the structure and parameters during learning and fully approximates the inverse dynamics of ships. Online identification and modeling lays the model foundation for ship motion control. The trained DNFM, serving as an inverse controller, is connected in parallel with the fractional-order PIλDμ controller to be used for the tracking control of the ship's course. Moreover, the weights of the model can be further adjusted during the course tracking. Taking the actual ship data of a 5446 TEU large container ship, simulation experiments are conducted, respectively, for course tracking, course tracking under wind and wave interferences, and comparison with five different controllers. This proposed controller can overcome the influence of the uncertainty of modeling parameters, tracking the desired course quickly and effectively. [ABSTRACT FROM AUTHOR]

HIF-1α plays a crucial regulatory role in vascular calcification (VC), primarily influencing the osteogenic differentiation of VSMCs through oxygen-sensing mechanisms. Under hypoxic conditions, the stability of HIF-1α increases, avoiding PHD and VHL protein-mediated degradation, which promotes its accumulation in cells and then activates gene expressions related to calcification. Additionally, HIF-1α modulates the metabolic state of VSMCs by regulating the pathways that govern the switch between glycolysis and oxidative phosphorylation, thereby further advancing the calcification process. The interaction between HIF-1α and other signaling pathways, such as nuclear factor-κB, Notch, and Wnt/β-catenin, creates a complex regulatory network that serves as a critical driving force in VC. Therefore, a deeper understanding of the role and regulatory mechanism of the HIF-1α signaling during the development and progression of VC is of great significance, as it is not only a key molecular marker for understanding the pathological mechanisms of VC but also represents a promising target for future anti-calcification therapies. [ABSTRACT FROM AUTHOR]

Ensuring safety at sea has become a primary focus of marine monitoring, driving the increasing adoption of ship detection technology in the maritime industry. Detecting small ship targets in SAR images presents challenges, as they occupy only a small portion of the image and exhibit subtle features, reducing detection efficiency. To address these challenges, we propose the HCA-RFLA algorithm for ship detection in SAR remote sensing. To better capture small targets, we design a hierarchical collaborative attention (HCA) mechanism that enhances feature representation by integrating multi-level features with contextual information. Additionally, due to the scarcity of positive samples for small targets under IoU and center sampling strategies, we propose a label assignment strategy based on Gaussian receptive fields, known as RFLA. RFLA assigns positive samples to small targets based on the Gaussian distribution between feature points and ground truth, increasing the model's sensitivity to small samples. The HCA-RFLA was experimentally validated using the SSDD, HRSID, and SSD datasets. Compared to other state-of-the-art methods, HCA-RFLA improves detection accuracy by 6.2%, 4.4%, and 3.6%, respectively. These results demonstrate that HCA-RFLA outperforms existing algorithms in SAR remote sensing ship detection. [ABSTRACT FROM AUTHOR]

Non-noble metals catalyzed carbonylative reactions serve as straightforward and sustainable methods for the synthesis of functionalized carbonyl-containing compounds. Herein, a low-valent-tungsten-catalyzed reaction that enables the coupling of aryl iodides and alcohols or phenols was disclosed, employing the readily available W(CO)6 as the effective catalyst and PPh3 as ligand. Under the optimal reaction conditions, aryl iodides smoothly underwent carbonylative coupling reactions with alcohols or phenols, processing the feature of broad substrate scope and good functional groups tolerance. Furthermore, this conversion can be carried out on a gram scale, showcasing significant promise in the synthesis of pharmaceutical or biologically active compounds. [ABSTRACT FROM AUTHOR]

Object detection is a fundamental task in computer vision. Recently, deep-learning-based object detection has made significant progress. However, due to large variations in target scale, the predominance of small targets, and complex backgrounds in remote sensing imagery, remote sensing object detection still faces challenges, including low detection accuracy, poor real-time performance, high missed detection rates, and high false detection rates in practical applications. To enhance remote sensing target detection performance, this study proposes a new model, the remote sensing detection transformer (RS-DETR). First, we incorporate cascaded group attention (CGA) into the attention-driven feature interaction module. By capturing features at different levels, it enhances the interaction between features through cascading and improves computational efficiency. Additionally, we propose an enhanced bidirectional feature pyramid network (EBiFPN) to facilitate multi-scale feature fusion. By integrating features across multiple scales, it improves object detection accuracy and robustness. Finally, we propose a novel bounding box regression loss function, Focaler-GIoU, which makes the model focus more on difficult samples, improving detection performance for small and overlapping targets. Experimental results on the satellite imagery multi-vehicles dataset (SIMD) and the high-resolution remote sensing object detection (TGRS-HRRSD) dataset show that the improved algorithm achieved mean average precision (mAP) of 78.2% and 91.6% at an intersection over union threshold of 0.5, respectively, which is an improvement of 2.0% and 1.5% over the baseline model. This result demonstrates the effectiveness and robustness of our proposed method for remote sensing image object detection. [ABSTRACT FROM AUTHOR]

Photovoltaic panel defect detection presents significant challenges due to the wide range of defect scales, diverse defect types, and severe background interference, often leading to a high rate of false positives and missed detections. To address these challenges, this paper proposes the LEM-Detector, an efficient end-to-end photovoltaic panel defect detector based on the transformer architecture. To address the low detection accuracy for Crack and Star crack defects and the imbalanced dataset, a novel data augmentation method, the Linear Feature Augmentation (LFA) module, specifically designed for linear features, is introduced. LFA effectively improves model training performance and robustness. Furthermore, the Efficient Feature Enhancement Module (EFEM) is presented to enhance the receptive field, suppress redundant information, and emphasize meaningful features. To handle defects of varying scales, complementary semantic information from different feature layers is leveraged for enhanced feature fusion. A Multi-Scale Multi-Feature Pyramid Network (MMFPN) is employed to selectively aggregate boundary and category information, thereby improving the accuracy of multi-scale target recognition. Experimental results on a large-scale photovoltaic panel dataset demonstrate that the LEM-Detector achieves a detection accuracy of 94.7% for multi-scale defects, outperforming several state-of-the-art methods. This approach effectively addresses the challenges of photovoltaic panel defect detection, paving the way for more reliable and accurate defect identification systems. This research will contribute to the automatic detection of surface defects in industrial production, ultimately enhancing production efficiency. [ABSTRACT FROM AUTHOR]

The enhancement of the carbon trading mechanism signifies a gradual transition in China's environmental regulatory framework, shifting from a command and control approach to a market-based incentive model. Despite the significance of this shift, existing research has insufficiently explored the impact of market-oriented environmental policies on consumption-based emissions. This study leverages the carbon trading policies implemented in 2013 as a quasi-natural experiment, combined with a precise measurement of urban and rural household carbon emissions (HCE) during 2005–2021. Employing a difference-in-differences method, we evaluate the heterogeneous impact of these policies on urban and rural HCE. The results demonstrate a significantly negative effect of the policies on indirect HCE, a conclusion that remains robust across various placebo and robustness tests. Furthermore, we identify the transmission mechanisms through which carbon trading policies affect the reduction in HCE. The results indicate that the policy has a significant negative impact on indirect HCE, with a notable urban–rural difference. The effect of the policy is −0.829 for urban areas and −0.365 for rural areas, a conclusion that remains robust across various placebo and robustness checks. Additionally, we identified two transmission mechanisms through which carbon trading policies operate: financial deepening and employment effects. Lastly, we found that carbon trading policies can reduce carbon inequality between urban and rural areas by 46.8%. [ABSTRACT FROM AUTHOR]

Pokkah boeng disease (PBD), which is caused by Fusarium verticillioides, is a major sugarcane disease in Southeast Asian countries. Breeding varieties to become resistant to F. verticillioides is the most effective approach for minimizing the damage caused by PBD, and identifying genes mediating resistance to PBD via molecular techniques is essential. The production of reactive oxygen species (ROSs) is one of a cell's first responses to pathogenic infections. Plant peroxisomes play roles in several metabolic processes involving ROSs. In this study, seedlings of YT94/128 and GT37 inoculated with F. verticillioides were used to identify PBD resistance genes. The cells showed a high degree of morphological variation, and the cell walls became increasingly degraded as the duration of the infection increased. There was significant variation in H2O2 accumulation over time. Catalase, superoxide dismutase, and peroxidase activities increased in both seedlings. Analysis of differentially expressed genes (DEGs) revealed that peroxidase-metabolism-related genes are mainly involved in matrix protein import and receptor recycling, adenine nucleotide transport, peroxisome division, ROS metabolism, and processes related to peroxisomal membrane proteins. The expression levels of SoCATA1 and SoSOD2A2 gradually decreased after sugarcane infection. F. verticillioides inhibited the expressions of C5YVR0 and C5Z4S4. Sugarcane infection by F. verticillioides disrupts the balance of intracellular ROSs and increases the cell membrane's lipid peroxidation rate. Defense-related enzymes play a key regulatory role in maintaining a low, healthy level of ROSs. The results of this study enhance our understanding of the mechanism through which peroxisomes mediate the resistance of sugarcane to PBD and provide candidate genes that could be used to breed varieties with improved traits via molecular breeding. [ABSTRACT FROM AUTHOR]

With the rapid development of multimedia services and smart devices, 360-degree video has enhanced the user viewing experience, ushering in a new era of immersive human–computer interaction. These technologies are increasingly integrating everyday life, including gaming, education, and healthcare. However, the uneven spatiotemporal distribution of wireless resources presents significant challenges for the transmission of ultra-high-definition 360-degree video streaming. To address this issue, this paper proposes a multi-layer non-uniform coding-based adaptive transmission method for 360° video (MNCATM). This method optimizes video caching and transmission by dividing non-uniform tiles and leveraging users' dynamic field of view (FoV) information and the multi-bitrate characteristics of video content. First, the video transmission process is formalized and modeled, and an adaptive transmission optimization framework for a non-uniform video is proposed. Based on this, the optimization problem required by the paper is summarized, and an algorithm is proposed to solve the problem. Simulation experiments demonstrate that the proposed method, MNCATM, outperforms existing transmission schemes in terms of bandwidth utilization and user quality of experience (QoE). MNCATM can effectively utilize network bandwidth, reduce latency, improve transmission efficiency, and maximize user experience quality. [ABSTRACT FROM AUTHOR]

The extraction process of crude polysaccharides from Agrocybe aegerita was optimized, and the antioxidant and anti-aging effects of the crude polysaccharides were evaluated. The optimal extraction parameters for the polysaccharide were identified using the response surface methodology. The DPPH, hydroxy radical, and superoxide anion radical scavenging capacities were evaluated to determine the antioxidant properties of the AAPs. The effects of the AAPs on the lifespan, head-swing frequency, swallowing frequency, body-bending frequency, and stress resistance of Caenorhabditis elegans were determined. The optimal extraction conditions included a solid-to-liquid ratio that resulted in an extraction solution concentration of 0.034 g/mL, an extraction temperature of 92.64 °C, and an extraction time of 2.82 h. Under these conditions, the yield of the AAPs was 11.325% ± 0.996%. The IC50 of the AAPs for superoxide anion radical scavenging was 4.693 mg/mL. The AAPs reached their maximum activity at concentrations of about 2 mg/mL for DPPH and 5 mg/mL for the hydroxyl radical. The AAPs could prolong the lifespan and improve locomotion and the stress resistance of C. elegans. Our findings illustrate the potential of AAPs as an anti-aging and antioxidant agent, highlighting the use of this natural compound in the fields of food and pharmacology. [ABSTRACT FROM AUTHOR]

Research on the carrying capacity of land resources and their outputs to population size will be able to better serve the ecological governance of food security. This paper analyzes the population carrying capacity level of southern Xinjiang by using the population carrying capacity model of land resources, and ANOVA analyzes the significance difference between the newly added arable land and the original arable land. At the same time, the demand of cultivated land development is discussed. The results showed that the sown area of grain crops in all the prefectures showed an overall increase from 2009 to 2019. The population carrying scale is more optimistic under subsistence and well-off conditions. From 2009 to 2019, cropland in Aksu region increased the most, followed by Kashgar region, with both regions exceeding 300,000 ha. ANOVA results show that the new arable land is comprehensively lower than the original arable land in terms of quality grade and agricultural output, and salinization and desertification are more serious than on the original arable land. At the same time, the subsistence type requires the least amount of arable land development while the affluent type requires the most. Therefore, we should adapt to local conditions and develop modern agriculture scientifically and reasonably. [ABSTRACT FROM AUTHOR]

The production of waste textiles has increased rapidly in the past two decades along with the rapid development of the economy, the majority of which has been either landfilled or incinerated, resulting in energy loss and environmental pollution. Microwave pyrolysis, which can transform heterogeneous and complex waste feedstocks into value-added products, is considered one of the most competitive technologies for processing waste textiles. However, achieving selective product formation during the microwave pyrolysis of waste textiles remains a significant challenge. Herein, sodium acetate, potassium acetate, and nickel acetate were introduced into waste textiles through an impregnation method as raw materials to improve the pyrolysis efficiency. The optimized process parameters indicated that nickel acetate had the most favorable promotional effect of the three acetates. Notably, the waste textiles containing 1.0% Ni exhibited the highest gas production rate, with the hydrogen-containing combustible gas reaching 81.1% and 61.0%, respectively. Using X-ray diffraction (XRD), transmission electron microscopy (TEM), Fourier transform infrared spectroscopy (FTIR), and Raman spectroscopy to characterize the waste textiles before and after pyrolysis, it was found that nickel acetate was converted into metallic nickel (Ni0) during microwave pyrolysis. This active site significantly enhanced the pyrolysis process, and as the gas yield increased, the disorder of the resulting pyrolytic carbon also rose. The proposed Ni0-enhanced microwave pyrolysis mediated by nickel acetate offers a novel method for the efficient disposal and simultaneous resource recovery of waste textiles. [ABSTRACT FROM AUTHOR]

The GF-7 satellite, China's inaugural sub-meter-level stereoscopic mapping satellite, has been deployed for a wide range of applications, including natural resource investigation, environmental monitoring, fundamental surveying, and the development of global geospatial information resources. The satellite's stable platform and reliable imaging systems are crucial for achieving high-quality imaging and precise attitude measurements. However, the satellite's operation is affected by both internal and external factors, which induce vibrations in the satellite platform, thereby affecting image quality and mapping accuracy. To address this challenge, this paper proposes a novel method for constructing a satellite platform vibration model based on geographic location information. The model is developed by integrating composite data from star sensors and gyroscopes (gyro) with subsatellite point location data. The experimental methodology involves the composite processing of gyro data and star sensor optical axis angles, integration of the processed data through time-matching and normalization, and denoising of the integrated data, followed by trigonometric fitting to capture the periodic characteristics of platform vibrations. The positions of the satellite substellar points are determined from the satellite orbit data. A rigorous geometric imaging model is then used to construct a vibration model with geographic location correlation in combination with the satellite subsatellite point positions. The experimental results demonstrate the following: (1) Over the same temporal range, there is a significant convergence in the waveform similarities between the gyro data and the star sensor optical axis angles, indicating a strong correlation in the jitter information; (2) The platform vibration exhibits a robust correlation with the satellite's geographic location along its orbit. Specifically, the model reveals that the GF-7 satellite experiences the maximum vibration amplitude between 5° S and 20° S latitude during its ascending phase, and the minimum vibration amplitude between 5° N and 20° N latitude during the descending phase. The model established in this study offers theoretical support for optimizing satellite attitude and mitigating platform vibrations. [ABSTRACT FROM AUTHOR]