This paper focuses on the response of reticulated shell structures under oblique impact loads, with a departure from the traditional emphasis on vertical impact loads. These structures are typically utilised in large-span spaces such as iconic buildings and large venues. The study begins by establishing a numerical simulation method for reticulated shell structures subjected to oblique impact loads, which is then validated against existing experimental results. Building on this verified method, the research delves into the effects of varying impactor mass, velocity, and initial kinetic energy on the reticulated shell structure under oblique impacts, as well as the influence of different oblique impact angles. The study extensively examines the failure modes of the structure, node displacements in the structure, and variations in member stress under different impactor parameters. It further investigates how these parameters influence the maximum impact bearing capacity, impact duration, energy dissipation capability, and response forms of the structures, analyzing the reasons behind these effects. The findings offer valuable insights for further research and practical engineering design of reticulated shell structures.
Abstract Objective Cognitive dysfunction is a prevalent and intricate manifestation of schizophrenia (SCZ) that may be associated with distinct clinical factors and the presence of antioxidants, which relationship is unclear. The study aimed to investigate cognitive function and its influencing factors in Chinese patients with SCZ. Methods A group of 133 patients with SCZ and 120 healthy controls (HCs) were recruited. The MATRICS Consensus Cognitive Battery (MCCB) was utilized to evaluate cognitive ability, and the Positive and Negative Syndrome Scale (PANSS) was used to assess clinical symptoms. Levels of plasma superoxide dismutase (SOD), serum albumin (ALB) and uric acid (UA) were assessed. Results Compared with HCs, patients with SCZ exhibited lower cognitive performance as indicated by MCCB scores, including the dimensions of speed of processing, attention/vigilance, working memory, verbal learning, and visual learning. In the SCZ group, total PANSS scores were negatively associated with all MCCB dimensions (all p < 0.05), except for the attention/vigilance score. The PANSS-negative and PANSS-cognitive subscores were negatively associated with speed of processing, verbal learning, and visual learning scores (all p < 0.05). The PANSS-excited subscores showed a negative correlation with working memory and visual learning scores (all p < 0.05). ALB levels significantly decreased, and their UA and SOD levels were notably elevated compared to HCs (all p < 0.05). ALB levels and PANSS-negative factors were correlated with to speed of processing, working memory, and visual learning dimensions. SOD levels were independent contributors to the attention/vigilance dimension. Conclusions The cognitive function was decreased in SCZ. The degree of cognitive impairment was closely related to ALB, SOD levels and negative clinical symptoms.
Fuel cell hybrid electric vehicles (FCHEVs) have been become one promising way to cope with energy crisis and environmental pollution. Meantime, degradation of energy sources including fuel cell (FC) and battery is of importance to performance for energy management strategies (EMSs) of FCHEVs. However, how to realize trade-off between real-time optimization performance of EMSs and lifetime of energy sources still remains challenging. Therefore, based on exploratory decision-making deep deterministic policy gradient (EDM-DDPG) algorithm, a adaptive fuzzy-based hierarchical EMS is proposed considering degradation of both FC and battery. In the upper layer, an adaptive fuzzy filter allocates peak power to ultracapacitor to reduce the computational load of EDM-DDPG algorithm. To improve fuel consumption efficiency and extend lifetime of FC and battery, in the lower layer, degradation states of FC and battery are quantified in terms of hydrogen consumption within EDM-DDPG. Meanwhile, for enhancing convergence and optimization capabilities of the proposed algorithm, a novel exploratory decision-making mechanism is introduced by integrating loss values of energy and memory pool dynamics to adjust the exploration factor of EDM-DDPG algorithm. Finally, the simulation results demonstrate that the proposed hierarchical EMS can reduce the equivalent fuel consumption by 5.6% and improves the FC efficiency by 3.48%.
This study aimed to explore the psychiatric symptoms and associated risk and protective factors among religious adolescents after 2-month home confinement against coronavirus disease-2019 (COVID-19) in China.
Buildings such as office blocks, individual houses and department stores have walls constructed from dielectric layers. It is important to characterize the properties of radio propagation through multilayered dielectric structures. In this work, plane wave incidence on dielectric layers is treated by using transmission-line theory. Transmission and reflection properties of plane wave for double layers in the UHF and SHF bands for wireless LAN arc presented and the results of different parameters arc compared. Thus, it will provide a guideline to design and deploy wireless LANs in communication environments.
The projected area of the switch connector can reflect the product quality of the component. In order to accurately determine the quality of the switch connector, it is necessary to calculate the projected area of the product. This article proposes a switch connector image segmentation model based on an improved DeepLabV3+ network to achieve precise segmentation of switch connectors in images. This network uses the MobileNetV2 network pre trained using the PASCAL VOC public dataset as the backbone network for feature extraction of images, and then uses this network to connect with the improved DeepLabV3+ network as the final segmentation network. The improved DeepLabV3+ network uses the sum of Dice Loss and cross entropy loss function on the basic DeepLabV3+ network to replace the original method that only uses one cross entropy loss function, so as to alleviate the adverse effects caused by the imbalance between foreground and background in the samples; At the same time, ECA module is also added as an attention mechanism module to enhance the feature representation of the model, thereby improving the segmentation performance of the model. The experiment shows that the segmentation results of this model reach 95.17% in average intersection to union ratio (MIOU) which is 1.30 percentage points higher than the original DeepLabV3+ model, and the frame rate is 12.04% higher. At the same time, the network model in this paper also reduces the parameter quantity and computational cost by 89.38% and 83.58% compared to the original model, respectively. The method proposed in this article can effectively perform product quality inspection on industrial parts with multiple sizes, types, complex shapes and characteristics in complex industrial scenarios, achieving automated and intelligent quality inspection for factory production, while improving quality inspection efficiency and reducing labor costs.
Abstract Objective Cognitive dysfunction is a prevalent and intricate manifestation of schizophrenia (SCZ) that may be associated with distinct clinical factors and the presence of antioxidants, which relationship is unclear. The study aimed to investigate cognitive function and its influencing factors in Chinese patients with SCZ. Methods A group of 133 patients with SCZ and 120 healthy controls (HCs) were recruited. The MATRICS Consensus Cognitive Battery (MCCB) was utilized to evaluate cognitive ability, and the Positive and Negative Syndrome Scale (PANSS) was used to assess clinical symptoms. Levels of plasma superoxide dismutase (SOD), serum albumin (ALB) and uric acid (UA) were assessed. Results Compared with HCs, patients with SCZ exhibited lower cognitive performance as indicated by MCCB scores, including the dimensions of speed of processing, attention/vigilance, working memory, verbal learning, and visual learning. In the SCZ group, total PANSS scores were negatively associated with all MCCB dimensions (all p < 0.05), except for the attention/vigilance score. The PANSS-negative and PANSS-cognitive subscores were negatively associated with speed of processing, verbal learning, and visual learning scores (all p < 0.05). The PANSS-excited subscores showed a negative correlation with working memory and visual learning scores (all p < 0.05). ALB levels significantly decreased, and their UA and SOD levels were notably elevated compared to HCs (all p < 0.05). ALB levels and PANSS-negative factors were correlated with to speed of processing, working memory, and visual learning dimensions. SOD levels were independent contributors to the attention/vigilance dimension. Conclusion The cognitive function was decreased in SCZ. The degree of cognitive impairment was closely related to ALB, SOD levels and negative clinical symptoms.
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