To mitigate the grassland degradation in the Mongolian Plateau (MP), both China and Mongolia governments have carried out a series of new policies and ecological projects. However, the effect of such ...restoration measures on the productivity of grassland in the MP under different political systems remains unclear. Here we study the effects of land use and land cover change, human activities and climate change on the net primary productivity (NPP) of grassland in Mongolia (MG) and Inner Mongolia (IM) from 2001 to 2014. Results showed that the area of grassland increased in both MG and IM, accounted for 4.45 × 104 and 10.31 × 104 km2, respectively. The extended grassland contributed 4.34 × 108 Gg C (Gg = 109 g) to the total NPP, while the loss of grassland led to a decrease of 0.19 × 108 Gg C. The total NPP of grasslands in 2014 increased about 17.88% and 30.49% respectively in MG and IM since 2001. Specifically, IM exhibited a higher increase in land converted NPP than MG. The area of grassland restoration in IM and MG accounted for 90.21% and 81.45%, respectively, indicating that the grassland of the MP was restored. Although human activity was the dominant factor on grassland degradation, which was accounted for 9.79% and 18.55% in IM and MG, it has a positive effect on most of the grassland NPP in the MP. Overall, policy measures and ecological projects in IM brought a more positive effect compared with that in MG.
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•Land use and cover change (LUCC) as one of driving factors was quantified.•Inner Mongolia had a higher increase of land conversion NPP than Mongolia.•Grasslands in most areas of the Mongolian Plateau show a recovery trend.•Human activities are still the dominant factor in promoting degradation in the MP.
Human trajectory prediction is challenging and critical in various applications (e.g., autonomous vehicles and social robots). Because of the continuity and foresight of the pedestrian movements, the ...moving pedestrians in crowded spaces will consider both spatial and temporal interactions to avoid future collisions. However, most of the existing methods ignore the temporal correlations of interactions with other pedestrians involved in a scene. In this work, we propose a Spatial-Temporal Graph Attention network (STGAT), based on a sequence-to-sequence architecture to predict future trajectories of pedestrians. Besides the spatial interactions captured by the graph attention mechanism at each time-step, we adopt an extra LSTM to encode the temporal correlations of interactions. Through comparisons with state-of-the-art methods, our model achieves superior performance on two publicly available crowd datasets (ETH and UCY) and produces more "socially" plausible trajectories for pedestrians.
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.
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.
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.
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 m
2
/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/cm
2
at 120 μW/cm
2
and predominant cycle stability with 86% capacitance retention even after 2500 cycles at high current density of 3 mA/cm
2
. The obtained results predicted that ultrasonic-assisted fabrication of porous carbon materials exhibits great application potential for flexible supercapacitors.
Utilizing a photoelectrochemical (PEC) fuel cell to replace difficult water oxidation with facile oxidation of organic wastes is regarded as an effective method to improve the H2 production ...efficiency. However, in most reported PEC fuel cells, their PEC activities are still low and the energy in organic fuels cannot be effectively utilized. Here, a unique BiVO4 PEC fuel cell is successfully developed by utilizing the low‐cost biomass, tartaric acid, as an organic fuel. Thanks to the strong complexation between BiVO4 and tartaric acid, a bridge for the charge and energy transfer is successfully constructed, which not only improves the photoelectric conversion efficiency of BiVO4, but also effectively converts the chemical energy of biomass into H2. Remarkably, under AM1.5G illumination, the optimal nanoporous BiVO4 photoanode exhibits a high current density of 13.54 mA cm−2 at 1.23 V vs reversible hydrogen electrode (RHE) for H2 production, which is higher than that of previously reported PEC water splitting systems or PEC fuel cell systems. This work opens a new path for solving the low PEC H2 production efficiency and provides a new idea for improving the performances and energy conversion efficiency in traditional PEC fuel cells.
A unique BiVO4 photoelectrochemical fuel cell is successfully developed by utilizing the low‐cost tartaric acid biomass as an organic fuel. The strong complexation between BiVO4 and tartaric acid provides a bridge for charge and energy transfer. The optimal BiVO4 photoanode exhibits a remarkable current density of 13.54 mA cm−2 at 1.23 V versus reversible hydrogen electrode under AM1.5G.
Quantifying the driving force is significant to understand the impact of climate variation and human activities on grassland degradation. In this study, we selected net primary productivity (NPP) as ...an indicator to quantitatively assess the relative roles of climate variation and human activities in China, Mongolia, Pakistan and Uzbekistan from 2000 to 2013. The results showed that 1.9% of grassland areas experienced degradation in Uzbekistan. By contrast, 29.6%, 16%, and 32.5% of grassland areas underwent restoration in China, Mongolia and Pakistan, respectively. Furthermore, 83.9%, 85.1%, 6.7% of restored grassland areas were influenced by climate variation and 65%, 79.1%, 11.6% of degraded areas were affected by human activities in Mongolia, Pakistan and Uzbekistan, respectively. The NPP variation also could be calculated to evaluate the impacts of these factors and results were consistent with the findings based on area. Therefore, climate variation dominated grassland restoration, human activities dominated degradation in Mongolia and Pakistan, and Uzbekistan was just the opposite. In China, 38.5% of the grassland restoration areas was caused by climate variations compared with 38% induced by human activities. On the contrary, 37.4% of grassland degradation was caused by climate variation and 30% resulted from human activities. In addition, the results based on NPP variation revealed that 39.2% of restored grassland areas were influenced by human activities and 38.2% of degraded areas were affected by climate variation. Therefore, climate variation dominated grassland degradation and the driving force of restoration was determined by the effectiveness of environmental protection programs.
•NPP was used to assess the relative role of driving factor in grassland degradation.•Climate variation benefits the restoration, human activities promote degradation.•Contributions of the two factors varied greatly in these four countries.•Environmental protect programs are beneficial to the grassland restoration.
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.
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.
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.
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.
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