The mean reversion/persistence of financial cycles: Empirical evidence for 24 countries worldwide

Research background: The globalization trend has inevitably enhanced the connectivity of global financial markets, making the cyclicality of financial activities and the spread of market imbalances have received widespread attention, especially after the global financial crisis. Purpose of the article: To reduce the negative effects of the contagiousness of the financial cycles, it is necessary to study the persistence of financial cycles and carve out the total connectedness, spillover paths, and sources of risks on a global scale. In addition, understanding the relationship between the financial cycle and economic development is an important way to prevent financial crises. Methods: This paper adopts the nonlinear smoothing transition autoregressive (STAR) model to extract cyclical and phase characteristics of financial cycles based on 24 countries during 1971Q1?2015Q4, covering developed and developing countries, the Americas, Europe, and Asia regions. In addition, the frequency connectedness approach is used to measure the connectedness of financial cycles and the relationship between the global financial cycle and the global economy. Findings & value added: The analysis reveals that aggregate financial cycles persist for 13.3 years for smoothed and 8.7 years for unsmoothed on average. The national financial cycles are asynchronous and exhibit more prolonged expansions and faster contractions. The connectedness of financial cycles is highly correlated with systemic crises and contributes to the persistence and harmfulness of shocks. It is mainly driven by short-term components and exhibits more pronounced interconnectedness within regions than across regions. During the financial crisis, the global financial cycle movements precede and are longer than the business fluctuations. Based on the study, some policy implications are presented. This paper emphasizes the impact of systemic crises on the persistence of financial cycles and their connectedness, which contributes to refining research related to the coping mechanisms of financial crises.

Incomplete pythagorean fuzzy preference relation for subway station safety management during COVID-19 pandemic.

Completing the Pythagorean fuzzy preference relations (PFPRs) based on additive consistency may exceed the defined domain. Therefore, we develop a group decision-making (GDM) method with incomplete PFPRs. Firstly, sufficient conditions for the expressibility of estimated preference values in PFPRs based on additive consistency are presented. Next, the correction algorithm is developed to correct the inexpressible elements in incomplete PFPRs. Then, a GDM method based on incomplete PFPRs is proposed to determine the objective weights of decision-makers. Finally, an example of subway station safety management during COVID-19 is selected to illustrate the applicability of the developed GDM method. The results show that the developed GDM method effectively identifies the crucial risk factor in subway station safety management and has better performance in terms of computational time complexity than the multiplicative consistency method.

Emerging research trends of total quality management in the COVID-19 pandemic: a dynamic evolution analysis

As the COVID-19 pandemic rages, the changing trends and emerging areas of total quality management (TQM) research before and after the COVID-19 pandemic are spotlighted, while the links between TQM and environmental social governance (ESG) are deeply discussed in this study. To explore the impact of the pandemic on TQM research, a comprehensive bibliometric analysis is conducted by collecting 1465 pre-pandemic and 76 post-pandemic publications from the WoS database. Further, the fundamental characteristics, conceptual structure and intellectual and social structure of TQM research are statistically analysed through bibliometric tools. Consequently, this article methodically sorts out the evolution, new research areas, primary sources, national collaboration networks and influential themes within an intricate and large TQM research system. The linkages between ESG and TQM are explored by focussing on some emerging topics after the outbreak such as sustainability and environmental management, which advances the innovative attempt towards the goal of cooperating sustainability. Finally, we offer some enlightening new perspectives on economic construction and social life during the pandemic to better cope with the negative effects of the pandemic.

Face detection for rail transit passengers based on single shot detector and active learning.

COVID-19 spreads rapidly among people, so that more and more people are wearing masks in rail transit stations. However, the current face detection algorithms cannot distinguish between a face wearing a mask and a face not wearing a mask. This paper proposes a face detection algorithm based on single shot detector and active learning in rail transit surveillance, effectively detecting faces and faces wearing masks. Firstly, we propose a real-time face detection algorithm based on single shot detector, which improves the accuracy by optimizing backbone network, feature pyramid network, spatial attention module, and loss function. Subsequently, this paper proposes a semi-supervised active learning method to select valuable samples from video surveillance of rail transit to retrain the face detection algorithm, which improves the generalization of the algorithm in rail transit and reduces the time to label samples. Extensive experimental results demonstrate that the proposed method achieves significant performance over the state-of-the-art algorithms on rail transit dataset. The proposed algorithm has a wide range of applications in rail transit stations, including passenger flow statistics, epidemiological analysis, and reminders of passenger who do not wear masks. Simultaneously, our algorithm does not collect and store face information of passengers, which effectively protects the privacy of passengers.

A look at the focus shift in innovation literature due to Covid-19 pandemic.

This study explores the problems related to the development of innovation research in the field of business and economics and the change in their characteristics following the coronavirus disease 2019 (COVID-19) pandemic. We compile a comprehensive bibliometric analysis of 17,277 pre-epidemic publications and 4,240 post-epidemic publications from the Web of Science. Using bibliometric methods and visualization tools, we present the changes in these publications following the COVID-19 pandemic, and identify the influential countries and regions, sources, and references, and obtain features of keywords over time. The results show that innovation research is rich in content, and involves a wide range; it has been focusing on emerging topics, such as those concerning low-carbon, innovation forms, and epidemic environments, following the COVID-19 pandemic. This study contributes to the body of knowledge on innovation, and helps to understand the features and structures of innovation research in business and economics.

Improvement of the C-glycosylation Step for the Synthesis of Remdesivir

The bulk supply of the antiviral C-nucleoside analogue remdesivir is largely hampered by a low-yielding Cglycosylation step in which the base is coupled to the pentose unit. Here, we disclose a significantly improved methodology for this critical transformation. By utilizing diisopropylamine as a cost-effective additive, the addition reaction furnishes an optimal yield of 75% of the desired ribofuranoside adduct, representing the highest yield obtained thus far for this key step. The method proved suitable for hectogram scale synthesis without column chromatographic operations.

Enhancing the filtration efficiency and wearing time of disposable surgical masks using TENG technology.

The COVID-19 pandemic has caused an unprecedented human and health crisis. And the shortage of protective equipment, especially the personal protective disposable surgical masks, has been a great challenge. Here, we developed an effective and simple scheme to prolong the lifetime of disposable surgical masks without changing their current structure, which is beneficial to solve the shortage of personal masks. After electrifying the meltblown PP filter by the new-developed single-electrode-based sliding triboelectric nanogenerator (TENG) charge replenishment (NGCR) technology, the processed filter is bipolar charged and has a filtration efficiency beyond 95% for the particulate matter (PM) ranging from PM0.3 to PM10.0. Further, we demonstrate the 80 °C dry heating is an effective decontamination method. This method is compatible with single-electrode-based sliding TENG charge replenishment technology. The 80 °C dry heating and the NGCR technology can make up an effective regeneration procedure for the mask. Even after ten cycles of simulated 4 h wearing process and such regeneration procedure, the filtration efficiency of the disposable surgical masks PM0.3 is still higher than 95%.

SARS-CoV-2 presented in the air of an intensive care unit (ICU).

As coronavirus disease 2019 (COVID-19) is spreading worldwide, there have been arguments regarding the aerosol transmission of its causative agent, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Moreover, some re-detectable positive (RP) patients have been reported. However, little attention has been given to the follow-up of recovered patients, and there is no environmental evidence to determine whether these patients continue to shed the virus after they test negative. Therefore, with an objective to test the hypothesis of airborne transmission of SARS-CoV-2, it is necessary to 1) determine whether SARS-CoV-2 particles are present in the indoor air and 2) determine whether recovered patients are still shedding virus, thus providing much-needed environmental evidence for the management of COVID-19 patients during the recovery period. In this study, surface and air samples were collected from an intensive care unit (ICU) containing one ready-for-discharge patient. All surface samples tested negative, but the air samples tested positive for SARS-CoV-2. This implies that SARS-CoV-2 particles may be shed in aerosol form for days after patients test negative. This finding may be one of the reasons for the observation of RP patients; therefore, there is a need for improved clinical and disease management guidelines for recovered COVID-19 patients.