Modeling of the resilient supply chain system from a perspective of production design changes

Building an effective resilient supply chain system (RSCS) is critical and necessary to reduce the risk of supply chain disruptions in unexpected scenarios such as COVID-19 pandemic and trade wars. To overcome the impact of insufficient raw material supply on the supply chain in mass disruption scenarios, this study proposes a novel RSCS considering product design changes (PDC). An RSCS domain model is first developed from the perspective of PDC based on a general conceptual framework, i.e., function-context-behavior-principle-state-structure (FCBPSS), which can portray complex systems under unpredictable situations. Specifically, the interaction among the structure, state and behavior of the infrastructure system and substance system is captured, and then a quantitative analysis of the change impact process is presented to evaluate the resilience of both the product and supply chain. Next, a case study is conducted to demonstrate the PDC strategy and to validate the feasibility and effectiveness of the RSCS domain model. The results show that the restructured RSCS based on the proposed strategy and model can remedy the huge losses caused by the unavailability of raw materials.

Exploring the consequence of information communication technology-enabled work during non-working hours: a stress perspective

PurposeThis study aims to examine the impact of information communication technology-enabled work during non-working hours (ICT-enabled WNWHs), as a source of stress, on employee behavioral outcomes -in-role job performance, organizational citizenship behaviors (OCBs) that benefit organizations and OCBs that benefit individuals, through emotional responses - work exhaustion, nonwork exhaustion and organization-based self-esteem. As the coronavirus disease 2019 (COVID-19) lockdowns demonstrated that employees frequently engage in ICT-enabled WNWHs, studying stress induced by ICT-enabled WNWHs is essential for understanding employee adaptation to the work-from-home trend that emerged from COVID-19 lockdowns.Design/methodology/approachA quantitative survey comprising 1,178 employees in China was conducted, and the data reliability and validity were confirmed. Partial least squares structural equation modeling analysis was employed to test the hypotheses.FindingsThe study results empirically proved that, although ICT-enabled WNWHs had significant effects on employee behavioral outcomes, the related emotional responses were the mediators of the stress transmission mechanism that directly affected employee behavioral outcomes. Notably, work exhaustion and organization-based self-esteem partially mediate the stress transmission mechanism, while nonwork exhaustion exerts a full mediating effect.Originality/valueThis study proposes the stress transmission mechanism of ICT-enabled WNWHs and delineates emotional responses regarding the work environment attributes of ICT-enabled WNWHs, an approach rarely seen in prior IS studies. To our best knowledge, this study is the first to identify and empirically demonstrate organization-based self-esteem as one among the emotional responses to ICT-enabled WNWHs. Furthermore, it expands understanding of the holistic impacts of ICT-enabled WNWHs, which is lacking in information systems (IS) literature.

Patient behavior detection based on time-frequency fusion of FMCW radar

This paper proposes a novel time-frequency feature fusion method to recognise patients' behaviours based on the Frequency Modulated Continuous Wave (FMCW) radar system, which can locate patients as well as recognise their current actions and thus is expected to solve the shortage of medical staff caused by the novel coronavirus pneumonia (COVID-19). To recognise the patient's behaviour, the FMCW radar is utilised to acquire point clouds reflected by the human body, and the micro-Doppler spectrogram is generated by human motion. Then features are extracted and fused from the time-domain information of point clouds and the frequency-domain information of the micro-Doppler spectrogram respectively. According to the fused features, the patient's behaviour is recognised by a Bayesian optimisation random forest algorithm, where the role of Bayesian optimisation is to select the best hyper-parameters for the random forest, i.e. the number of random forest decision trees, the depth of leaves, and the number of features. The experimental results show that an average accuracy of 99.3% can be achieved by using the time-frequency fusion with the Bayesian optimisation random forest model to recognise six actions.

Assessing the Impact of the Digital Economy on Green Total Factor Energy Efficiency in the Post-COVID-19 Era

Digital transformation in the energy sector is an essential tool for promoting the construction of a clean energy system in the post-COVID-19 era. Under the background of digital China strategy and sustainable energy transformation in the post-COVID-19 era, it is meaningful to investigate the relationship between the digital economy and green total factor energy efficiency (GTFEE) to better drive the development of the digital economy and improve GTFEE. For this purpose, this study estimates deeply the impact of the digital economy on GTFEE by applying ordinary least squares (OLS), panel vector autoregression (PVAR), panel threshold, and mediation effect models based on panel data of 30 Chinese provinces from 2006 to 2018. The statistical results indicate that digital economy is conducive to improving GTFEE. Digital economy can significantly contribute to GTFEE by improving economic growth level, urbanization level, R&D investment, and human capital. The most interesting finding was that there is also a non-linear relationship between digital economy and GTFEE. The effect of digital economy on GTFEE is shown to be first promoted and then inhibited as digital economy level continues to increase. Further, the positive impact of the digital economy on GTFEE is strengthened with increasing levels of economic growth, urbanization, R&D input, and human capital. Finally, A positive correlation was found between digital economy and GTFEE in the eastern and central regions, but insignificantly in other regions.

The clinical warning index of severe COVID-19: discussion based on the clinical features and outcomes of 4 patients.

OBJECTIVE: Coronavirus disease 2019 (COVID-19) is spreading worldwide. The onset of severe COVID-19 could lead to multiple organ damage and even death. It is worth paying attention to the warning index of the onset for severe COVID-19 so that patients can be identified and monitored carefully. PATIENTS AND METHODS: The report is a retrospective study that describes and analyzes the clinical features during the treatment of COVID-19. Four patients with COVID-19 were involved in this study, who were father-and-son pairs from two families. All patients were treated with the same combination of anti-microbial and anti-viral agents for 10-14 days, adjusting for the disease status. The primary outcome measure was SARS-CoV-2 detection using RT-qPCR with oropharyngeal swabs. Chest CT imaging served as a secondary outcome measure. RESULTS: One of the four patients progressed to severe disease, while the remaining patients recovered with the same treatment. A persistent decrease in the lymphocyte ratio and increase in the C-reactive protein (CRP) level were observed in the severe patient, along with other typical symptoms of COVID-19. CONCLUSIONS: The cases we described indicate that blood cell and CRP tests could be useful risk warnings of severe onset of COVID-19.

Clinical features of 17 patients with 2019-nCoV.

OBJECTIVE: This study aims to discuss the unique clinical features of patients with 2019-nCoV in Zhengzhou City to provide references for clinical diagnosis and treatment. PATIENTS AND METHODS: Seventeen patients with 2019-nCoV in Zhengzhou People's Hospital from February to March 2020 were collected. Their epidemiology, clinical symptoms, laboratory examinations, and chest CT images were reviewed. All 17 patients were aged between 12-83 years, with an average age of 47 years, and consisted of 10 males (58.8%) and 7 females (41.2%). Two patients had histories of living or traveling in Wuhan, and 9 patients were attacked locally. The 6 remaining patients were unknown about incidence reasons. RESULTS: The average incubation period was 10 days, and the average time of the course of the disease was 9 days. Among the participants, 12 patients had fever as the first symptoms and 5 patients had normal body temperature. One patient was symptom-free carrier, and one patient had serious symptoms. One patient developed from mild symptoms to severe symptoms, and 14 patients had mild symptoms. Moreover, 7 patients had complications of cardiovascular and cerebrovascular diseases and hypertension, 1 patient was in the advanced stage of squamous cell lung carcinoma, and 1 patient had diabetes mellitus, renal failure, and late-stage uremia. According to novel coronavirus nucleic acid test, 8 patients were positive, accounting for 47.1%. All patients were negative in the novel coronavirus IgM antibody test and negative in other common respiratory pathogen detection. All 17 patients had ground glass-like high-density shadow or stripped high-density shadow on lung CT images, accompanied with many affected lesions on two lungs. The average stay in hospital was 10 days, and the average time of the course of the disease was 9 days. After hospitalization, 15 patients were discharged from the hospital upon recovery, 1 patient was transferred to superior hospital for continuous treatment, and 1 patient died. Patients with 2019-nCoV in Zhengzhou People's Hospital were mainly attacked in local areas, and most of them had mild symptoms. The positive rate of the nucleic acid test was 47.1%. CONCLUSIONS: The main clinical characteristics are increased neutrophil granulocytes, increased C-reactive proteins, decreased lymphocytes, ground glass-like or stripped lesions on lung CT image, common complications of cardiovascular and cerebrovascular diseases, and favorable prognosis.

Rationality Analysis of the Treatment of Coronavirus Disease 2019 (COVID-19) with Reduning Injection

OBJECTIVE: To evaluate the safety and rationality of Reduning injection in the treatment of COVID-19. METHODS: Through consulting, summarizing and analyzing literatures, the rapid HTA evaluation of Reduning was carried out, and its pharmacological rationality and drug monitoring for COVID-19 were discussed. RESULTS: Literature analysis indicated that COVID-19 belongs to the pestilence of TCM. It was characterized by “dampness, heat, deficiency, toxin and stasis”, and its clinical manifestations involved inflammatory factor storm, immune system damage, etc. Reduning injection was approved to the treatment of influenza, cough and respiratory tract infections caused by exopathic wind-heat, and a typical drug for heat-clearing and detoxifying. CONCLUSION: The rapid HTA evaluation showed that Reduning injection has good safety, effectiveness and economy. The mechanisms of Reduning in antipyretic and anti-inflammatory, immune regulation and anti-virus suggest the rationality of Reduning in treating COVID-19, but drug monitoring should be done well in the use process.