The SiO x /C composite, as a form of silicon-based materials, has been considered as an attractive alternative anode for next-generation lithium-ion batteries. The porous SiO 0.71 C 1.95 N 0.47 anode material exhibiting robust Si−O skeletons wrapped by carbon layers is successfully prepared and delivers an initial capacity of over 1700 mAh g −1 with an initial coulombic efficiency of 69.4% and favorable cycle life. Both Si (2p) X-ray photoelectron spectroscopy (XPS) and 29 Si nuclear magnetic resonance (NMR) demonstrate the existence of SiO 4 and SiO 3 C units as main lithium storage sites in the original state. The XPS curve moved toward the direction of the binding energy decreasing with NMR spectra shifting to a high field after the first lithiation process. The massive capacity loss during the first discharge and charge cycle results from the formation of irreversible Li silicate (Li 2 SiO 4 ). The fluctuation of the charge and discharge capacity, including a persistent decline during the first 30 cycles and a continuous elevation in the following 400 cycles, could be attributed to the participated degree of reversible Li silicate (Li 2 SiO 3 and Li 2 Si 2 O 5 ) in the delithiation process. The Si−O skeletons are gradually corroded and ultimately destroyed in the final 400 cycles, leading to the sharp drop of the cycling performance of the half-cell.
For massive crowds, users often have the need for interactive roaming. A good roaming effect can make the user feel immersed in the crowd, and the scenes need to be populated with crowds of people that make the environment both alive and believable. This paper proposes a method of efficiency control for massive crowd rendering. First, we devise a state machine mechanism based on self-feedback, which can dynamically adjust the accuracy of crowd model rendering according to the relationship between the speed of the system rendering and the speed the users expect. Second, we propose a movement frequency update method to perform the frequency of motion update based on the distance between the individual and the viewpoint. In addition, we propose a variable precision point sampling drawing strategy to render the individual with different sampling precision. The state machine system in this paper effectively integrates two core technologies for dynamically controlling the accuracy of the model, ensuring visual efficiency, improving the rendering efficiency, and satisfying the fluency of users’ roaming interaction.
Objective: To assess situation of Inpatient mental health screening and suicide prevention of standard operating procedure (SOP). Methods: We invest 306 people to join our study from August 2017 to July 2019, the participants contain 128 patients, 128 healthy people and 50 medical workers. The information is collected by interview and questionnaire, that includes basic information of participants, depression assessment, anxiety assessment and medical workers' suicide prevention cognition score. The questionnaires include simple questionnaire, Self-Rating Anxiety Scale (SAS) and Self-rating depression scale (SDS). Result: In SAS research and SDS research, patient group has higher score than that of healthy people group, that patients were more anxious and depressed than healthy people in this mental health research. And the situation between patient group and healthy people group have big different as the results are statistical significance (p<0.001). In medical workers' suicide prevention cognition test, the test accuracy rates only have approximately 60% in those 3 domains, so medical workers' knowledge of suicide prevention of standard operating procedure (SOP) is far from enough in hospitalization. In particular, suicide prevention measures part has better performance than that of basic knowledge of suicide part (7 out of 12 vs 5 out of 8). Conclusion: The suicide prevention is a serious problem in hospitalized patient, the inpatients have serious mental health problem and medical workers lack related knowledge and skills.
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