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Existing detection methods face a huge challenge in identifying insulators with minor defects when targeting transmission line images with complex backgrounds. To ensure the safe operation of transmission lines, an improved YOLOv7 model is proposed to improve detection results. Firstly, the target boxes of the insulator dataset are clustered based on K-means++ to generate more suitable anchor boxes for detecting insulator-defect targets. Secondly, the Coordinate Attention (CoordAtt) module and HorBlock module are added to the network. Then, in the channel and spatial domains, the network can enhance the effective features of the feature-extraction process and weaken the ineffective features. Finally, the SCYLLA-IoU (SIoU) and focal loss functions are used to accelerate the convergence of the model and solve the imbalance of positive and negative samples. Furthermore, to optimize the overall performance of the model, the method of non-maximum suppression (NMS) is improved to reduce accidental deletion and false detection of defect targets. The experimental results show that the mean average precision of our model is 93.8%, higher than the Faster R-CNN model, the YOLOv7 model, and YOLOv5s model by 7.6%, 3.7%, and 4%, respectively. The proposed YOLOv7 model can effectively realize the accurate detection of small objects in complex backgrounds.

Objective This systematic review aims to evaluate the effectiveness of universal school-based transdiagnostic interventions in promoting the mental health of children and adolescents. It compares and discusses interventions targeting the prevention of mental disorders versus the promotion of mental health. Additionally, the roles of teachers and psychologists as intervention conductors are examined. Methods A comprehensive search of the Psycinfo, Pubmed, and Web of Science databases was conducted without any time restrictions to identify relevant literature on universal school-based transdiagnostic interventions promoting children and adolescents' mental health. Results and discussion The findings reveal that universal school-based transdiagnostic promotion/prevention programs have a small to medium overall effect size. These interventions demonstrate a broad coverage of different aspects of children and adolescents' mental health. However, the relative effectiveness of teacher-led versus psychologist-led interventions remains unclear. Interventions focused on preventing mental disorders exhibit a higher effect size, albeit on a narrower range of mental health aspects for children and adolescents. Significance This study enhances our understanding of universal school-based transdiagnostic interventions and their impact on children and adolescents' mental health. Further research is needed to elucidate the comparative efficacy of teacher-led and psychologist-led interventions and to explore the specific dimensions of mental health targeted by these interventions.

Grassland degradation received considerable concern because of its adverse impact on agronomic productivity and its capacity to provide goods and service. Climate change and human activities are commonly recognized as the two broad underlying drivers that lead to grassland degradation. In this study, a comprehensive method based on net primary productivity (NPP) was introduced to assess quantitatively the relative roles of climate change and human perturbations on worldwide grassland degradation from 2000 to 2010. The results revealed that at a global scale, 49.25 % of grassland ecosystems experienced degradation. Nearly 5 % of these grasslands experienced strong to extreme significant degradation. Climate change was the dominant cause that resulted in 45.51 % of degradation compared with 32.53 % caused by human activities. On the contrary, 39.40 % of grassland restoration was induced by human interferences, and 30.6 % was driven by climate change. The largest area of degradation and restoration both occurred in Asia. NPP losses ranged between 1.40 Tg C year⁻¹ (in North America) and 13.61 Tg C year⁻¹ (in Oceania) because of grassland degradation. Maximum NPP increase caused by restoration was 17.57 Tg C year⁻¹ (in North America). Minimum NPP was estimated at 1.59 Tg C year⁻¹ (in Europe). The roles of climate change and human activities on degradation and restoration were not consistent at continental level. Grassland ecosystems in the southern hemisphere were more vulnerable and sensitive to climate change. Therefore, climate change issues should be gradually integrated into future policies and plans for domestic grassland management and administration.

Climate variations and human activities, as two major driving forces, have profound impacts on alpine ecosystems. The Three-River Headwaters Region (TRHR) is located in the alpine region and is the source of three major rivers flowing to eastern China and Southeast Asia. Grassland is the dominant vegetation type in the TRHR and is fragile and sensitive to climate variations and human activities due to the alpine environment. Different types of grassland may have varying coping mechanisms with disturbances due to their unique environments and physiological functions. However, there is limited quantitative research on the response of different grassland types to climate variations and human activities in the TRHR. Therefore, the Carnegie–Ames–Stanford approach (CASA) was selected to simulate the net primary productivity (NPP) affected by climate (NPPC) and the actual NPP (NPPA) of steppes and meadows in the TRHR from 2001 to 2022, and the NPP affected by human activities (NPPH) was calculated by subtracting the NPPA from the NPPC. Results showed that the NPPA increased by 0.53 gC/m2/a during the study period, with the NPPA of steppes and meadows increasing by 0.55 gC/m2/a and 0.51 gC/m2/a, respectively. The regions dominated by climate variations, human activities, and the combined impact of the two accounted for 22.01%, 29.42%, and 48.57% of the NPPA changes. In terms of climate change, the impact of temperature and soil moisture on the NPP is equally important. It is worth noting that the alpine meadows (67.60%) contributed more to the increases in the NPPA than the steppes (32.40%). In addition, climate variations and human activities contributed more to the increased total NPPA of the meadows (20.54 GgC and 36.41 GgC) than that of the steppes (14.35 GgC and 10.20 GgC). The results clarify the quantitative evaluation system for the impact of human activities and climate change on different types of grasslands in the TRHR, providing guidance for the protection and management of these grasslands.

Recently, the preparation of porous carbon using biomass materials as carbon precursor has received extensive interests due to their wide range of sources and low cost. Herein, ultrasonic-assisted fabrication of porous carbon materials derived from agricultural waste had been successfully synthesized and further applied in solid-state supercapacitor. It is found that the adoption of ultrasonic-assisted method could deeply etch carbon materials to induce more porous structure to the resulted carbon materials. The presence of additional pore structures is beneficial for the transfer of electrolytes, providing more active sites and improving electrochemical performance. Compared with the samples without ultrasonic treatment, the activated sample exhibits a high specific surface area of 1281 m2/g, abundant porous structure and prominent specific capacitance of 197 F/g. The assembled symmetrical solid-state supercapacitor shows a high energy density of 18.43 μWh/cm2 at 120 μW/cm2 and predominant cycle stability with 86% capacitance retention even after 2500 cycles at high current density of 3 mA/cm2. The obtained results predicted that ultrasonic-assisted fabrication of porous carbon materials exhibits great application potential for flexible supercapacitors.

Background and aims Abandonment of agricultural land is a common type of land-use change worldwide. Nevertheless, there is currently no consensus on how soil aggregates and aggregate-associated organic carbon (C) vary with agricultural land abandonment on a global scale. Methods We synthesized the global responses and controlling factors of distribution, stability, and associated organic C concentration of soil water-stable aggregates under the influence of agricultural land abandonment using meta-analysis. Results On average, agricultural land abandonment significantly enhanced the mass proportion of large macroaggregates (LMA) and mean weight diameter (MWD) by 89.9% and 51.1%, respectively, while leading to a significant reduction in the proportion of silt-clay particles (SC) (−26.6%). By contrast, the proportions of both small macroaggregates (SMA) and microaggregates (MIA) showed no response to agricultural land abandonment. Overall, agricultural land abandonment significantly increased the aggregate-associated organic C concentrations by 23.3–24.8%, and the highest increase was observed for LMA. In most cases, the responses of soil aggregates to agricultural land abandonment did not differ significantly between subgroups of mean annual temperature, mean annual precipitation, soil texture, and abandonment duration (AD). We found that the dynamics of MWD and associated organic C concentrations were positively related to AD according to redundancy analysis. Conclusion Our findings suggested that the formation and C accrual of LMA, which could be improved with the increase of AD due to a more favorable environment for plant and microbial growth, played crucial roles in both soil structural rehabilitation and soil C sequestration during agricultural land abandonment.

As a typical sequence to sequence task, sign language production (SLP) aims to automatically translate spoken language sentences into the corresponding sign language sequences. The existing SLP methods can be classified into two categories: autoregressive and non-autoregressive SLP. The autoregressive methods suffer from high latency and error accumulation caused by the long-term dependence between current output and the previous poses. And non-autoregressive methods suffer from repetition and omission during the parallel decoding process. To remedy these issues in SLP, we propose a novel method named Pyramid Semi-Autoregressive Transformer with Rich Semantics (PSAT-RS) in this paper. In PSAT-RS, we first introduce a pyramid Semi-Autoregressive mechanism with dividing target sequence into groups in a coarse-to-fine manner, which globally keeps the autoregressive property while locally generating target frames. Meanwhile, the relaxed masked attention mechanism is adopted to make the decoder not only capture the pose sequences in the previous groups, but also pay attention to the current group. Finally, considering the importance of spatial-temporal information, we also design a Rich Semantics embedding (RS) module to encode the sequential information both on time dimension and spatial displacement into the same high-dimensional space. This significantly improves the coordination of joints motion, making the generated sign language videos more natural. Results of our experiments conducted on RWTH-PHOENIX-Weather-2014T and CSL datasets show that the proposed PSAT-RS is competitive to the state-of-the-art autoregressive and non-autoregressive SLP models, achieving a better trade-off between speed and accuracy.

A thin layer of silver was prepared on cellulose film (CF) surface via electroless plating to obtain high electromagnetic shielding effectiveness Ag/cellulose composite layer. The process is simple, efficient and low-cost. The developed film has a great advantage in electric conduction and electromagnetic interference (EMI) shielding. The identical deposit of thin silver layer was perfectly fabricated via the electroless plating on the CF surface. The fabricated thin silver layers were tested for electrical properties and EMI SE. The electrical and electromagnetic shielding properties of the thin silver layer were ideal when the activation concentration was 100 Mm (mmol/L). Herein, the resistance and conductivity of Ag/cellulose composite films can reach 0.35 Ω and 45 s/cm, respectively, and the EMI SE of Ag/cellulose composite films can be up to 67 dB ranging from 0.0003 to 3 GHz. The dielectric constant (ε′) of the Ag/cellulose composite film was between 6.5 and 7.5, which was stable throughout the test band ranging from 2 to 18 GHz. The permeability (µ′) of the Ag/cellulose composite film was around 1 ranging from 2 to 18 GHz.

The Tibetan Plateau (TP) serves as a vital ecological safeguard and water conservation region in China. In recent decades, substantial efforts have been made to promote vegetation greening across the TP; however, these interventions have added complexity to the local water balance and evapotranspiration (ET) processes. To investigate these dynamics, we apply the Priestley–Taylor Jet Propulsion Laboratory (PT-JPL) model to simulate ET components in the TP. Through model sensitivity experiments, we isolate the contribution of vegetation greening to ET variations. Furthermore, we analyze the role of climatic drivers on ET using a suite of statistical techniques. Based on satellite and climate data from 1982 to 2018, we found the following: (1) The PT-JPL model successfully captured ET trends over the TP, revealing increasing trends in total ET, canopy transpiration, interception loss, and soil evaporation at rates of 0.06, 0.39, 0.005, and 0.07 mm/year, respectively. The model’s performance was validated using eddy covariance observations from three flux tower sites, yielding R2 values of 0.81–0.86 and RMSEs ranging from 6.31 to 13.20 mm/month. (2) Vegetation greening exerted a significant enhancement on ET, with the mean annual ET under greening scenarios (258.6 ± 120.9 mm) being 2.9% greater than under non-greening scenarios (251.2 ± 157.2 mm) during 1982–2018. (3) Temperature and vapor pressure deficit were the dominant controls on ET, influencing 53.5% and 23% of the region, respectively, as identified consistently by both multiple linear regression and dominant factor analyses. These findings highlight the net influence of vegetation greening and offer valuable guidance for water management and sustainable ecological restoration efforts in the region.

Wetlands and meadows are two terrestrial ecosystems that are strikingly distinct in terms of hydrological conditions and biogeochemical characteristics. Wetlands generally feature saturated soils, high accumulation of organic matter, and hypoxic environments. They support unique microbial communities and play crucial roles as carbon sinks and nutrient retainers. In contrast, meadows are characterized by lower water supply, enhanced aeration, and accelerated turnover of organic matter. The transition from wetlands to meadows under global climate change and human activities has triggered severe ecological consequences in the Sanjiangyuan region, yet the mechanisms driving microbial network stability remain unclear. This study integrates microbial sequencing, soil physicochemical analyses, and structural equation modeling (SEM) to reveal systematic changes in microbial communities during wetland degradation. Key findings indicate: (1) critical soil parameter shifts (moisture: 48.5%→19.3%; SOM: −43.6%; salinity: +170%); (2) functional microbial restructuring with drought-tolerant Actinobacteria (+62.8%) and Ascomycota (+48.3%) replacing wetland specialists (Nitrospirota: −43.2%, Basidiomycota: −28.6%); (3) fundamental network reorganization from sparse wetland connections to hypercomplex meadow networks (bacterial nodes +344%, fungal edges +139.2%); (4) SEM identifies moisture (λ = 0.82), organic matter (λ = 0.68), and salinity (λ = −0.53) as primary drivers. Particularly, the collapse of methane-oxidizing archaea (−100%) and emergence of pathogenic fungi (+28.6%) highlight functional thresholds in degradation processes. These findings provide microbial regulation targets for wetland restoration, emphasizing hydrologic management and organic carbon conservation as priority interventions. Future research should assess whether similar microbial and network transitions occur in degraded wetlands across other alpine and temperate regions, to validate the broader applicability of these ecological thresholds. Restoration efforts should prioritize re-saturating soils, reducing salinity, and enhancing organic matter retention to stabilize microbial networks and restore essential ecosystem functions.