ABSTRACT
Background: Affected by the rapid spread of the COVID-19 pandemic, teachers have experienced extremely general anxiety or depression. This article takes ideological and political educators as an example to study the generalized anxiety problem in the context of the COVID-19 pandemic from a demographic perspective. The influencing factors are analyzed and mitigation strategies are proposed accordingly. Subjects and methods: A total of 231 ideological and political educators from different colleges or middle schools in Anhui Province of China were selected and the survey was carried out through online questionnaires. Using SPSS 26.0 as the tool, the Chi-square test and cross-analysis were conducted to study the influencing factors of anxiety of ideological and political educators. Results: The age factor was significantly correlated with anxiety at the 0.001 level (chi(2) = 33.067, P < 0.001). The gender factor was significantly correlated with anxiety at the 0.01 level (chi(2) = 11.591, P < 0.01). The highest educational level was associated with anxiety at the 0.01 level. There was a significant correlation at the 0.001 level (chi(2) = 22.653, P < 0.001). There was a significant correlation between physical health and anxiety at the 0.001 level (chi(2) = 22.653, P < 0.001). The degree of attention to the pandemic also significantly affected the level of individual anxiety (chi(2) = 46.430, P < 0.001). Conclusions: This study conducted a survey analysis of 231 ideological and political educators in different universities or middle schools in Anhui Province of China. The results show that factors such as age, gender, highest education, health, and attention to the pandemic will all affect the anxiety level of individuals. Therefore, educators should combine their own conditions and determine whether professional psychological counseling is needed according to the severity of anxiety.
ABSTRACT
The paper addresses the problem of efficiently planning routes for multiple ground vehicles used in goods delivery services. Given popularity of today's e-commerce, particularly under the COVID-19 pandemic conditions, goods delivery services have been booming than ever, dominated by small-scaled (electric) bikes and promised by autonomous vehicles. However, finding optimal routing paths for multiple delivery vehicles operating simultaneously in order to minimize transportation cost is a fundamental but challenging problem. In this paper, it is first proposed to exploit the mixed integer programming paradigm to model the delivery routing optimization problem (DROP) for multiple simultaneously-operating vehicles given their energy constraints. The routing optimization problem is then solved by the multi-chromosome genetic algorithm, where the number of delivery vehicles can be optimized. The proposed approach was evaluated in a realworld experiment in which goods were expected to be delivered from a depot to 26 suburb locations in Canberra, Australia. The obtained results demonstrate effectiveness of the proposed algorithm. © 2021 IEEE.
ABSTRACT
Droplet digital polymerase chain reaction (ddPCR) is a rapidly developing technology used for accurate, quantitative analysis of rare samples. However, ddPCR has only been implemented in research field but rarely in clinical trials due to its relatively high cost and negative user experiences compared with qPCR. We developed a novel programmable on-demand droplet generator based on a microfluidic adaptive printing system (MAP-ddPCR) to create a cost-effective ddPCR process. This process easily produces low-volume, spot-on-demand droplet dispensing and data analysis using simple equipment and workflow. Compared with the existing droplet generation systems that rely on surface-assistant, the proposed MAP system generates a variety of droplet arrays on regular non-surface-treated glass slides. This system directly processes PCR and performs data analysis without requiring a secondary droplets transfer. The static and independent properties of each droplet dramatically avoid cross-contamination during PCR, provide the opportunity to trace droplets in real-time and simplify the analysis. We demonstrated that the MAP-ddPCR produces reliable data using gradient concentrations of glyceraldehyde-3-phosphate dehydrogenase (GAPDH) in human genomic cDNA. These concentrations were further verified by quantitative PCR (qPCR). In addition, a very low viral load of SARS-CoV-2 was precisely detected and quantified by the MAP-ddPCR system. Finally, this system is affordable and simpler to integrate compared to other more expensive commercial digital PCR methods. Therefore, the proposed MAP-ddPCR system is expected to have a significant impact on market applications. © 2021 Elsevier B.V.
ABSTRACT
Based on the current situation and task of fighting COVID-19, and combined with emergency management mode of public health emergencies and participation of multi-times emergency rescue practices along with the case analysis and literature review and brain-storming, we constructed a basic framework of the emergency command system of public health emergencies in COVID-19 epidemic prevention and control background. The framework contained four modules: the response mechanism, the organizational structure, the emergency capacity, and the supervisory mechanism and the advantages and key points in implementing this emergency command system was discussed. © 2021, Editorial Board of Journal of Xi'an Jiaotong University (Medical Sciences). All right reserved.