Nankai University

About: Nankai University is a education organization based out in Tianjin, China. It is known for research contribution in the topics: Catalysis & Adsorption. The organization has 42964 authors who have published 51866 publications receiving 1127896 citations. The organization is also known as: Nánkāi Dàxué.

Prevalence and socio-demographic correlates of psychological health problems in Chinese adolescents during the outbreak of COVID-19.

Abstract: Psychological health problems, especially emotional disorders, are common among adolescents. The epidemiology of emotional disorders is greatly influenced by stressful events. This study sought to assess the prevalence rate and socio-demographic correlates of depressive and anxiety symptoms among Chinese adolescents affected by the outbreak of COVID-19. We conducted a cross-sectional study among Chinese students aged 12-18 years during the COVID-19 epidemic period. An online survey was used to conduct rapid assessment. A total of 8079 participants were involved in the study. An online survey was used to collect demographic data, assess students' awareness of COVID-19, and assess depressive and anxiety symptoms with the Patient Health Questionnaire (PHQ-9) and the Generalized Anxiety Disorder (GAD-7) questionnaire, respectively. The prevalence of depressive symptoms, anxiety symptoms, and a combination of depressive and anxiety symptoms was 43.7%, 37.4%, and 31.3%, respectively, among Chinese high school students during the COVID-19 outbreak. Multivariable logistic regression analysis revealed that female gender was the higher risk factor for depressive and anxiety symptoms. In terms of grades, senior high school was a risk factor for depressive and anxiety symptoms; the higher the grade, the greater the prevalence of depressive and anxiety symptoms. Our findings show there is a high prevalence of psychological health problems among adolescents, which are negatively associated with the level of awareness of COVID-19. These findings suggest that the government needs to pay more attention to psychological health among adolescents while combating COVID-19.

A bioinspired flexible organic artificial afferent nerve

Abstract: The distributed network of receptors, neurons, and synapses in the somatosensory system efficiently processes complex tactile information. We used flexible organic electronics to mimic the functions of a sensory nerve. Our artificial afferent nerve collects pressure information (1 to 80 kilopascals) from clusters of pressure sensors, converts the pressure information into action potentials (0 to 100 hertz) by using ring oscillators, and integrates the action potentials from multiple ring oscillators with a synaptic transistor. Biomimetic hierarchical structures can detect movement of an object, combine simultaneous pressure inputs, and distinguish braille characters. Furthermore, we connected our artificial afferent nerve to motor nerves to construct a hybrid bioelectronic reflex arc to actuate muscles. Our system has potential applications in neurorobotics and neuroprosthetics.

Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions

Abstract: Although using convolutional neural networks (CNNs) as backbones achieves great successes in computer vision, this work investigates a simple backbone network useful for many dense prediction tasks without convolutions. Unlike the recently-proposed Transformer model (e.g., ViT) that is specially designed for image classification, we propose Pyramid Vision Transformer~(PVT), which overcomes the difficulties of porting Transformer to various dense prediction tasks. PVT has several merits compared to prior arts. (1) Different from ViT that typically has low-resolution outputs and high computational and memory cost, PVT can be not only trained on dense partitions of the image to achieve high output resolution, which is important for dense predictions but also using a progressive shrinking pyramid to reduce computations of large feature maps. (2) PVT inherits the advantages from both CNN and Transformer, making it a unified backbone in various vision tasks without convolutions by simply replacing CNN backbones. (3) We validate PVT by conducting extensive experiments, showing that it boosts the performance of many downstream tasks, e.g., object detection, semantic, and instance segmentation. For example, with a comparable number of parameters, RetinaNet+PVT achieves 40.4 AP on the COCO dataset, surpassing RetinNet+ResNet50 (36.3 AP) by 4.1 absolute AP. We hope PVT could serve as an alternative and useful backbone for pixel-level predictions and facilitate future researches. Code is available at this https URL.

A high-performance supercapacitor-battery hybrid energy storage device based on graphene-enhanced electrode materials with ultrahigh energy density

Abstract: In pursuing higher energy density with no sacrifice of power density, a supercapacitor-battery hybrid energy storage device—combining an electrochemical double layer capacitance (EDLC) type positive electrode with a Li-ion battery type negative electrode—has been designed and fabricated. Graphene is introduced to both electrodes: an Fe3O4/graphene (Fe3O4/G) nanocomposite with high specific capacity as negative electrode material, and a graphene-based three-dimensional porous carbon material (3DGraphene) with high surface area (∼3355 m2 g−1) as positive electrode material. The Fe3O4/G nanocomposite shows a high reversible specific capacity exceeding 1000 mA h g−1 at 90 mA g−1 and remaining at 704 mA h g−1 at 2700 mA g−1, as well as excellent rate capability and improved cycle stability. Meanwhile the 3DGraphene positive electrode also displays great electrochemical performance. With these two graphene-enhanced electrode materials and using the best recommended industry evaluation method, the hybrid supercapacitor Fe3O4/G//3DGraphene demonstrates an ultrahigh energy density of 147 W h kg−1 (power density of 150 W kg−1), which also remains of 86 W h kg−1 even at high power density of 2587 W kg−1, so far the highest value of the reported hybrid supercapacitors. Furthermore, the energy density of the hybrid supercapacitor is comparable to lithium ion batteries, and the power density also reaches that of symmetric supercapacitors, indicating that the hybrid supercapacitor could be a very promising novel energy storage system for fast and efficient energy storage in the future.

Transition-Metal-Free Coupling Reactions

Abstract: Beijing National Laboratory of Molecular Sciences (BNLMS) and Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, College of Chemistry and Green Chemistry Center, Peking University, 202 Chengfu Road, 098#, Beijing 100871, China State Key Laboratory of Organometallic Chemistry, Chinese Academy of Sciences, 345 Lingling Road, Shanghai 200032, China State Key Laboratory of Elemento-Organic Chemistry, Nankai University, Tianjin 200060, China