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ObjectiveTo analyze the mental health status and the influencing factors among the residents taking standardized residency training during the outbreak and stable period of COVID-19， so as to provide theoretical basis for their mental health education.MethodsOn February 8 to February 10 and April 11 to April 13， 2020， Symptom Checklist 90 （SCL-90）， Beck Srivastava Stress Inventory （BSSI） and Simplified Coping Style Questionnaire （SCSQ） were distributed in online chat groups involving all grades of residents taking standardized residency training in the Second Affiliated Hospital of Kunming Medical University. Through two rounds of questionnaire survey， non-probability sampling method was used to obtain survey samples， and their mental status were analyzed.ResultsA total of 159 valid questionnaires were collected in the first round， and 99 valid questionnaires in the second round. The first survey showed that the total score of SCL-90 was （117.69±37.74） and the detection rate of positive symptoms in SCL-90 was 25.8%， and mainly dominated by obsession， fear and interpersonal sensitivity. In the second survey， the results showed that the total score of SCL-90 was （127.19±51.44）， and the main positive symptoms included obsession， depression and interpersonal sensitivity， with a positive detection rate of 30.3 %. The first survey found that the mental health status had significant differences among residents of different grades （χ2=7.46， P

This study aimed to explore the relationship between areas of work–life and psychological reward satisfaction, and the role of psychological capital in that relationship. Participants were from four Chinese major public hospitals (n = 532; female = 88.7%; mean age = 22.36 years, SD = 1.58 years). The nurses completed validated measures including the Psychological Capital Questionnaire, the Areas of Work–life Scale, and the Psychological Reward Satisfaction Scale. Regression analysis results showed that areas of work–life significantly predicted high psychological reward satisfaction among new Chinese graduate nurses. Similarly, psychological capital significantly predicted high psychological reward satisfaction among new Chinese graduate nurses. Psychological capital partially mediated the relationship between areas of work–life and psychological reward satisfaction. These findings indicate a need for work–life interventions to increase new graduate nurses' psychological reward satisfaction through enhancing their psychological capital and optimising a person–job fit in six areas of work–life. [ABSTRACT FROM AUTHOR]

High performance computing (HPC) is renowned for its capacity to tackle complex problems. Meanwhile, quantum computing (QC) provides a potential way to accurately and efficiently solve quantum chemistry problems. The emerging field of quantum-centric high performance computing (QCHPC), which merges these two powerful technologies, is anticipated to enhance computational capabilities for solving challenging problems in quantum chemistry. The implementation of QCHPC for quantum chemistry requires interdisciplinary research and collaboration across multiple fields, including quantum chemistry, quantum physics, computer science and so on. This perspective provides an introduction to the quantum algorithms that are suitable for deployment in QCHPC, focusing on conceptual insights rather than technical details. Parallel strategies to implement these algorithms on quantum-centric supercomputers are discussed. We also summarize high performance quantum emulating simulators, which are considered a viable tool to explore QCHPC. We conclude with challenges and outlooks in this field. [ABSTRACT FROM AUTHOR]

Carbon nanotube (CNT) polymer composites have broad application prospects in thermal management as electrothermal heaters. Nevertheless, challenge remains in achieving high electrical conductivity for the composites due to the contradiction between CNTs and insulated polymers. To address this issue, herein, innovative use of interface strategy approach by constructing synergistic nanomaterial networks on carboxyl CNTs yarn winding composites for improving the interfacial adhesion and electrical performance. In the work, carboxyl CNTs yarn/CNTs‐graphene oxide (GO) polyvinyl alcohol (PVA) composites (C‐CY‐HP‐C) were proposed and manufactured via filament winding process. The as‐constructed C‐CY‐HP‐C demonstrated a remarkable interfacial shear strength of 2057.16 N mm−1, which was 53.59% higher than that of control CNTs yarn/PVA winding composites. In addition, the C‐CY‐HP‐C achieved an attractive electrical conductivity of 346.39 S cm−1 owing to the electronic transmission channels were formed. Notably, the superior electrical conductivity facilitated a rapid‐response of electrothermal performance for the C‐CY‐HP‐C. It reached a steady‐state temperature of 229.9°C within 10 s when the voltage was 1.2 V. Concurrently, it exhibited an impressive heating rate of 10.8°C min−1 at an ambient temperature of −20°C as the battery surface heater. These findings shed light on the development of technique for battery preheating system based on CNTs yarn/polymer composites. [ABSTRACT FROM AUTHOR]

In this paper, the digital beamforming algorithm for horizontally polarized directional antenna array in narrowband multipath environment is studied. Because the steering vector of directional antenna arrays is complex and cannot be modeled exactly, blind beamforming algorithm is usually used for directional antenna arrays. As the existing blind beamforming algorithms require much prior information, work poorly for weak signals, have limited applications, and need high computational complexity, this paper designs a multi-polarization heterogeneous array cooperative processing scheme, and proposes a new multipath strengthening beamforming algorithm based on adaptive loading projection. The heterogeneous array consists of vertical polarization omnidirectional antenna array and horizontal polarization directional antenna array. The new algorithm utilizes the respective advantages of the two polarization arrays. This algorithm combines the methods of spatial smoothing, sampling matrix inversion, and spatial projection, and further improves the robustness of waveform estimation through adaptive loading processing. The algorithm requires less computation and less prior information, and has strong adaptability to non-ideal conditions. The implementation process and error analysis of the new algorithm are deduced, and effectiveness of the new algorithm is verified through computer simulations.