In December 2019, an outbreak of coronavirus disease 2019 (COVID-19) was identified in Wuhan, China. The World Health Organization (WHO) declared this outbreak a significant threat to international ...health. COVID-19 is highly infectious and can lead to fatal comorbidities especially acute respiratory distress syndrome (ARDS). Thus, fully understanding the characteristics of COVID-19-related ARDS is conducive to early identification and precise treatment. We aimed to describe the characteristics of COVID-19-related ARDS and to elucidate the differences from ARDS caused by other factors. COVID-19 mainly affected the respiratory system with minor damage to other organs. Injury to the alveolar epithelial cells was the main cause of COVID-19-related ARDS, and endothelial cells were less damaged with therefore less exudation. The clinical manifestations were relatively mild in some COVID-19 patients, which was inconsistent with the severity of laboratory and imaging findings. The onset time of COVID-19-related ARDS was 8-12 days, which was inconsistent with ARDS Berlin criteria, which defined a 1-week onset limit. Some of these patients might have a relatively normal lung compliance. The severity was redefined into three stages according to its specificity: mild, mild-moderate, and moderate-severe. HFNO can be safe in COVID-19-related ARDS patients, even in some moderate-severe patients. The more likely cause of death is severe respiratory failure. Thus, the timing of invasive mechanical ventilation is very important. The effects of corticosteroids in COVID-19-related ARDS patients were uncertain. We hope to help improve the prognosis of severe cases and reduce the mortality.
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bstract
In this paper, we promote the convex cone method of positive bounds from tree level to loop level. This method is general and can be applied to obtain leading
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positivity bounds on the ...forward scattering process in the standard model effective field theory. To obtain the loop level bounds, the original tree level bounds are modified by loop corrections, which involve low dimensional coefficients. New positivity bounds being valid at one loop level on the four-Higgs scattering have been provided. We study some specific ultraviolet models to check the validity of the new bounds. In addition, the renormalisation group effect on positivity is explored. We point out that as long as the new bounds are satisfied at the cutoff scale Λ, they will also be satisfied at all scales below Λ.
Research Summary
How should firms respond to technological discontinuities in order to achieve greater performance? In contrast to most studies that advocate a timely transition from the old to the ...new technology, this paper posits that in markets where a discontinuous technology exposes customers' latent preference heterogeneity for certain old technology attributes, firms may ultimately experience a performance surge by adhering to the old technology during technological change. Explicitly, I theorize a U‐shaped relationship within such a market between competitors' increasing adoption of the new technology and the performance of firms that stick with the old technology. This prediction is thoroughly examined using comprehensive data from the traditional Chinese medicine industry in China during the 1990s and receives robust empirical support.
Managerial Summary
In some markets, the rise of a discontinuous technology, besides posing a substitute threat to the old technology, further exposes niche segments where customers continue to favor the old technology. This paper predicts that within such a market, as competitors increasingly adopt the new technology for varied motives, firms sticking with the old technology may see their performance declining before rebounding and potentially reaching new heights. Analyses using archival data from the traditional Chinese medicine industry in China during the 1990s provide robust support for this prediction. The arguments and findings of this paper offer an “existence proof” that when confronted with a technological discontinuity, adhering to the old technology may also represent an effective strategy that ultimately improves firm performance.
Inspired by the swimming of natural microorganisms, synthetic micro‐/nanomachines, which convert energy into movement, are able to mimic the function of these amazing natural systems and help ...humanity by completing environmental and biological tasks. While offering autonomous propulsion, conventional micro‐/nanomachines usually rely on the decomposition of external chemical fuels (e.g., H2O2), which greatly hinders their applications in biologically relevant media. Recent developments have resulted in various micro‐/nanomotors that can be powered by biocompatible fuels. Fuel‐free synthetic micro‐/nanomotors, which can move without external chemical fuels, represent another attractive solution for practical applications owing to their biocompatibility and sustainability. Here, recent developments on fuel‐free micro‐/nanomotors (powered by various external stimuli such as light, magnetic, electric, or ultrasonic fields) are summarized, ranging from fabrication to propulsion mechanisms. The applications of these fuel‐free micro‐/nanomotors are also discussed, including nanopatterning, targeted drug/gene delivery, cell manipulation, and precision nanosurgery. With continuous innovation, future autonomous, intelligent and multifunctional fuel‐free micro‐/nanomachines are expected to have a profound impact upon diverse biomedical applications, providing unlimited opportunities beyond one's imagination.
Fuel‐free synthetic micro‐/nanomachines powered by external stimuli are able to swim efficiently in biologically relevant environments. Tremendous progress made in the past decade to develop different synthesis strategies for designing and fabricating fuel‐free micro‐/nanomotors with different functionalities is reviewed. These artificial nanomachines can achieve predetermined tasks in biomedical applications.
The Internet of Things is a paradigm where everyday objects can be equipped with identifying, sensing, networking and processing capabilities that will allow them to communicate with one another and ...with other devices and services over the Internet to accomplish some objective. Ultimately, IoT devices will be ubiquitous, context-aware and will enable ambient intelligence. This article reports on the current state of research on the Internet of Things by examining the literature, identifying current trends, describing challenges that threaten IoT diffusion, presenting open research questions and future directions and compiling a comprehensive reference list to assist researchers.
Rapid advances in industrialisation and informatisation methods have spurred tremendous progress in developing the next generation of manufacturing technology. Today, we are on the cusp of the Fourth ...Industrial Revolution. In 2013, amongst one of 10 'Future Projects' identified by the German government as part of its High-Tech Strategy 2020 Action Plan, the Industry 4.0 project is considered to be a major endeavour for Germany to establish itself as a leader of integrated industry. In 2014, China's State Council unveiled their ten-year national plan, Made-in-China 2025, which was designed to transform China from the world's workshop into a world manufacturing power. Made-in-China 2025 is an initiative to comprehensively upgrade China's industry including the manufacturing sector. In Industry 4.0 and Made-in-China 2025, many applications require a combination of recently emerging new technologies, which is giving rise to the emergence of Industry 4.0. Such technologies originate from different disciplines including cyber-physical Systems, IoT, cloud computing, Industrial Integration, Enterprise Architecture, SOA, Business Process Management, Industrial Information Integration and others. At this present moment, the lack of powerful tools still poses a major obstacle for exploiting the full potential of Industry 4.0. In particular, formal methods and systems methods are crucial for realising Industry 4.0, which poses unique challenges. In this paper, we briefly survey the state of the art in the area of Industry 4.0 as it relates to industries.
How to achieve reliable and accurate positioning performance using low-cost sensors is one of the main challenges for land vehicles. This paper proposes a novel fusion positioning strategy for land ...vehicles in GPS-denied environments, which enhances the positioning performance simultaneously from the sensor and methodology levels. It integrates multiple complementary low-cost sensors not only incorporating GPS and microelectromechanical-based inertial measurement unit, but also a "virtual" sensor, i.e., a sliding-mode observer (SMO). The SMO is first synthesized based on nonlinear vehicle dynamics model to estimate vehicle state information robustly. Then, a federated Kalman filter (FKF) is designed to fuse all sensor information, which can easily isolate and accommodate such sensor failures as GPS ones due to its decentralized filtering architecture. Further, a hybrid global estimator (HGE) is constructed by augmenting the FKF with a grey predictor, which has the advantages of dealing with the systems with uncertain or insufficient information. The HGE works in the update mode when there is no GPS failure, whereas it switches to the prediction mode in case of GPS outage to realize accurate and reliable positioning. The experimental results validate the effectiveness and reliability of the proposed strategy.
As one of the most critical approaches to resolve the energy crisis and environmental concerns, carbon dioxide (CO2) photoreduction into value‐added chemicals and solar fuels (for example, CO, HCOOH, ...CH3OH, CH4) has attracted more and more attention. In nature, photosynthetic organisms effectively convert CO2 and H2O to carbohydrates and oxygen (O2) using sunlight, which has inspired the development of low‐cost, stable, and effective artificial photocatalysts for CO2 photoreduction. Due to their low cost, facile synthesis, excellent light harvesting, multiple exciton generation, feasible charge‐carrier regulation, and abundant surface sites, semiconductor quantum dots (QDs) have recently been identified as one of the most promising materials for establishing highly efficient artificial photosystems. Recent advances in CO2 photoreduction using semiconductor QDs are highlighted. First, the unique photophysical and structural properties of semiconductor QDs, which enable their versatile applications in solar energy conversion, are analyzed. Recent applications of QDs in photocatalytic CO2 reduction are then introduced in three categories: binary II–VI semiconductor QDs (e.g., CdSe, CdS, and ZnSe), ternary I–III–VI semiconductor QDs (e.g., CuInS2 and CuAlS2), and perovskite‐type QDs (e.g., CsPbBr3, CH3NH3PbBr3, and Cs2AgBiBr6). Finally, the challenges and prospects in solar CO2 reduction with QDs in the future are discussed.
Carbon dioxide (CO2) photoreduction is regarded as an attractive pathway to produce value‐added chemicals and fuels. Recent advances in CO2 photoreduction via semiconductor quantum dots (QDs) in three categories are reviewed: II–VI, I–III–VI, and perovskite‐type QDs. Additionally, current challenges and prospects for QD‐photocatalyzed CO2 reduction are discussed.
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•Cytokine storm formed in severe COVID-19 cases indicates the involvement of the NLRP3 inflammasome in COVID-19.•SARS-CoV-2 infection activates the NLRP3 inflammasome via intricate ...molecular mechanisms, such as viroporins, ion flux, etc.•The NLRP3 inflammasome contributes to the development of respiratory, cardiovascular and neurological symptoms in COVID-19.•Inhibitors targeting the NLRP3 inflammasome and its downstream pathways provide novel therapeutic strategies for COVID-19.
Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), exhibits a wide spectrum of clinical presentations, ranging from asymptomatic cases to severe pneumonia or even death. In severe COVID-19 cases, an increased level of proinflammatory cytokines has been observed in the bloodstream, forming the so-called “cytokine storm”. Generally, nucleotide-binding oligomerization domain-like receptor containing pyrin domain 3 (NLRP3) inflammasome activation intensely induces cytokine production as an inflammatory response to viral infection. Therefore, the NLRP3 inflammasome can be a potential target for the treatment of COVID-19. Hence, this review first introduces the canonical NLRP3 inflammasome activation pathway. Second, we review the cellular/molecular mechanisms of NLRP3 inflammasome activation by SARS-CoV-2 infection (e.g., viroporins, ion flux and the complement cascade). Furthermore, we describe the involvement of the NLRP3 inflammasome in the pathogenesis of COVID-19 (e.g., cytokine storm, respiratory manifestations, cardiovascular comorbidity and neurological symptoms). Finally, we also propose several promising inhibitors targeting the NLRP3 inflammasome, cytokine products and neutrophils to provide novel therapeutic strategies for COVID-19.
Rotating machinery fault diagnosis problems have been well-addressed when sufficient supervised data of the tested machine are available using the latest data-driven methods. However, it is still ...challenging to develop effective diagnostic method with insufficient training data, which is highly demanded in real-industrial scenarios, since high-quality data are usually difficult and expensive to collect. Considering the underlying similarities of rotating machines, data mining on different but related equipments potentially benefit the diagnostic performance on the target machine. Therefore, a novel transfer learning method for diagnostics based on deep learning is proposed in this article, where the diagnostic knowledge learned from sufficient supervised data of multiple rotating machines is transferred to the target equipment with domain adversarial training. Different from the existing studies, a more generalized transfer learning problem with different label spaces of domains is investigated, and different fault severities are also considered in fault diagnostics. The experimental results on four datasets validate the effectiveness of the proposed method, and show it is feasible and promising to explore different datasets to improve diagnostic performance.
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