In clinical settings, physicians tend to use corticosteroids in the most critically ill patients. ...selection bias and confounders in observational studies might contribute to any observed increased ...mortality in patient groups treated with corticosteroids. Inconclusive clinical evidence should not be a reason for abandoning corticosteroid use in 2019-nCoV pneumonia. ...there are studies supporting the use of corticosteroids at low-to-moderate dose in patients with coronavirus infection. According to the expert consensus statement, the following basic principles should be followed when using corticosteroids: (1) the benefits and harms should be carefully weighed before using corticosteroids; (2) corticosteroids should be used prudently in critically ill patients with 2019-nCoV pneumonia; (3) for patients with hypoxaemia due to underlying diseases or who regularly use corticosteroids for chronic diseases, further use of corticosteroids should be cautious; and (4) the dosage should be low-to-moderate (≤0·5–1 mg/kg per day methylprednisolone or equivalent) and the duration should be short (≤7 days).
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ
Due to the distributed characteristics of federated learning (FL), the vulnerability of the global model and the coordination of devices are the main obstacle. As a promising solution of ...decentralization, scalability, and security, leveraging the blockchain in FL has attracted much attention in recent years. However, the traditional consensus mechanisms designed for blockchain-like proof of work (PoW) would cause extreme resource consumption, which reduces the efficiency of FL greatly, especially when the participating devices are wireless and resource-limited. In order to address device asynchrony and anomaly detection in FL while avoiding the extra resource consumption caused by blockchain, this article introduces a framework for empowering FL using direct acyclic graph (DAG)-based blockchain systematically (DAG-FL). Accordingly, DAG-FL is first introduced from a three-layer architecture in detail, and then, two algorithms DAG-FL Controlling and DAG-FL Updating are designed running on different nodes to elaborate the operation of the DAG-FL consensus mechanism. After that, a Poisson process model is formulated to discuss that how to set deployment parameters to maintain DAG-FL stably in different FL tasks. The extensive simulations and experiments show that DAG-FL can achieve better performance in terms of training efficiency and model accuracy compared with the typical existing on-device FL systems as the benchmarks.
The present study proposes a new mechanism to cause a strong electron heating in the magnetic islands ejected from the reconnection current layer. A large‐scale full kinetic simulation in ...three‐dimensional system demonstrates that the electrons are effectively accelerated by the non‐ideal electric field generated through the electromagnetic turbulence excited in the magnetic islands. It is found that the high‐energy electrons are efficiently scattered by the turbulence, resulting in the strong electron heating. The existence of turbulence and the associated non‐ideal electric field in the magnetic islands is consistent with recent satellite observations in the Earth’s magnetosphere.
Plain Language Summary
Observed velocity distribution of space plasmas often contains high‐energy components overlapping the ambient thermal component, implying the existence of local explosive processes producing energetic particles. Magnetic reconnection is one of such the processes, converting the magnetic field energy into plasma kinetic energies. In this study, we propose a new mechanism to cause a strong electron heating in the magnetic islands generated during magnetic reconnection. By means of a large‐scale computer simulation, where both electrons and ions are treated as particles, we found that the electrons are effectively accelerated by turbulence‐induced electric field. The high‐energy electrons are efficiently scattered by the turbulence, resulting in the strong electron heating. The existence of turbulence and the associated induction electric field is consistent with recent satellite observations in the Earth’s magnetosphere.
Key Points
We propose a new mechanism to accelerate electrons in the magnetic islands via turbulence‐induced electric field
The accelerated electrons are efficiently scattered by the electromagnetic turbulence, resulting in strong electron heating
The existence of non‐ideal electric field and turbulence in the magnetic islands is consistent with satellite observations
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Zika virus (ZIKV) infection during pregnancy leads to devastating fetal outcomes, including intrauterine growth restriction and microcephaly. Greater understanding of mechanisms underlying ZIKV ...maternal-fetal transmission is needed to develop new therapeutic interventions. Here, we define an important role for the autophagy pathway in ZIKV vertical transmission. ZIKV infection induced autophagic activity in human trophoblasts and pharmacological inhibition limited ZIKV infectivity. Furthermore, deficiency in an essential autophagy gene,
, in mice limited ZIKV vertical transmission and placental and fetal damage and overall improved placental and fetal outcomes. This protection was due to a placental trophoblast cell-autonomous effect of autophagic activity, not to alterations in systemic maternal ZIKV infection. Finally, an autophagy inhibitor, hydroxychloroquine, approved for use in pregnant women, attenuated placental and fetal ZIKV infection and ameliorated adverse placental and fetal outcomes. Our study reveals new insights into the mechanism of ZIKV vertical transmission and suggests that an autophagy-based therapeutic warrants possible evaluation in humans to diminish the risks of ZIKV maternal-fetal transmission.
Since the outbreak of coronavirus disease 2019 (COVID-19), clinicians have tried every effort to understand the disease, and a brief portrait of its clinical features have been identified. In ...clinical practice, we noticed that many severe or critically ill COVID-19 patients developed typical clinical manifestations of shock, including cold extremities and weak peripheral pulses, even in the absence of overt hypotension. Understanding the mechanism of viral sepsis in COVID-19 is warranted for exploring better clinical care for these patients. With evidence collected from autopsy studies on COVID-19 and basic science research on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and SARS-CoV, we have put forward several hypotheses about SARS-CoV-2 pathogenesis after multiple rounds of discussion among basic science researchers, pathologists, and clinicians working on COVID-19. We hypothesise that a process called viral sepsis is crucial to the disease mechanism of COVID-19. Although these ideas might be proven imperfect or even wrong later, we believe they can provide inputs and guide directions for basic research at this moment.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ
Graphite anodes show great potential for potassium storage, however, their capacity fades quickly owing to substantial interlayer expansion/shrinkage (i.e., up to 60%) induced structural degradation. ...Here, Ti3C2Tx MXene nanosheets are used as a fast electron/potassium‐ion dual‐function conductor to construct the framework of all‐integrated graphite nanoflake (GNF)/MXene (GNFM) electrodes. The continuous MXene framework constructs a 3D channel for fast electron/potassium‐ion transfer and endows GNFM electrodes with a high structural stability. Owing to this unique MXene framework, GNFM electrodes exhibit much enhanced potassium storage performances than that of the conventional polymer‐bonded electrodes even at high mass loadings. Moreover, GNFM electrodes also show impressive cyclability in non‐flammable electrolytes and are further used as anodes to assemble novel non‐flammable potassium‐ion capacitors that show an excellent cyclability and high energy/power densities (113.1 Wh kg–1 and 12.2 kW kg–1). New insights into phase transition mechanism in GNFM electrodes are verified by operando XRD. Density functional theory calculations demonstrate that MXene can promote electron transfer and potassium diffusion in the heterointerface between GNF and MXene. Therefore, the results demonstrate that all‐integrated GNFM electrodes designed with MXene as multifunctional frameworks provide a new paradigm for producing efficient potassium storage anodes.
Ti3C2Tx MXene nanosheets are used as a fast electron/potassium‐ion dual‐conductor to construct the framework of all‐integrated graphite nanoflake/MXene (GNFM) electrodes with improved electrochemical performances by exploiting unique MXene properties such as 2D morphology, metallic conductivity, and good flexibility. All‐integrated GNFM electrodes designed with MXene as multifunctional frameworks provide a new paradigm for producing efficient potassium storage anodes.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Blockchain has been regarded as a promising technology for IoT, since it provides significant solutions for decentralized networks that can address trust and security concerns, high maintenance cost ...problems, and so on. The decentralization provided by blockchain can be largely attributed to the use of a consensus mechanism, which enables peer-to-peer trading in a distributed manner without the involvement of any third party. This article starts by introducing the basic concept of blockchain and illustrating why a consensus mechanism plays an indispensable role in a blockchain enabled IoT system. Then we discuss the main ideas of two famous consensus mechanisms, PoW and PoS, and list their limitations in IoT. Next, two mainstream DAG based consensus mechanisms, the Tangle and Hashgraph, are reviewed to show why DAG consensus is more suitable for IoT system than PoW and PoS. Potential issues and challenges of DAG based consensus mechanisms to be addressed in the future are discussed in the last section.
Recent magnetospheric observations and three‐dimensional (3D) kinetic simulations have shown that plasma wave activities are significantly enhanced around the reconnection x‐line, implying that the ...reconnection process is fully 3D. However, how the turbulence affects the local reconnection process has been poorly understood so far. We find by means of large‐scale particle‐in‐cell simulation in 3D system that the local reconnection rate can be significantly enhanced, reaching 0.4, which is much larger than theoretical predictions for two‐dimensional (2D) reconnection. The large reconnection rate is associated with large energy conversion rate and strong electron acceleration. The enhancement of the reconnection rate is caused by local increases of electron momentum transport and pressure gradient force induced by turbulence, which can not occur in 2D system. The result is expected to give better interpretations to in‐situ satellite observations where magnetic reconnection proceeds in 3D system.
Plain Language Summary
Magnetic reconnection is an important process in space physics to convert the magnetic field energy into particle kinetic energy. In this study, we investigate reconnection rate, a physical quantity that measures the speed of magnetic reconnection by using fully kinetic simulation, in which both electrons and ions are particles. We find very fast local reconnection processes in three‐dimensional system that far exceeds expectation. It indicates that magnetic reconnection is a three‐dimensional process. The high reconnection rate comes from the electrons rather than ions. And the main reason is the increasing of electron momentum transport and pressure gradient caused by strong turbulence, leading to a strong magnetic reconnection process in the current sheet.
Key Points
Magnetic reconnection can be strongly intensified in turbulent current sheet with the local reconnection rate exceeding 0.4
High reconnection rate is caused by local enhancements of electron momentum transport and pressure gradient force induced by turbulence
Reconnection process is essentially 3D, suggesting that local satellite observations may be insufficient in capturing the global process
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Direct Acyclic Graph (DAG)-based ledger and the corresponding consensus algorithm has been identified as a promising technology for Internet of Things (IoT). Compared with Proof-of-Work (PoW) and ...Proof-of-Stake (PoS) that have been widely used in blockchain, the consensus mechanism designed on DAG structure (simply called as DAG consensus) can overcome some shortcomings such as high resource consumption, high transaction fee, low transaction throughput and long confirmation delay. However, the theoretic analysis on the DAG consensus is an untapped venue to be explored. To this end, based on one of the most typical DAG consensuses, Tangle, we investigate the impact of network load on the performance and security of the DAG-based ledger. Considering unsteady network load, we first propose a Markov chain model to capture the behavior of DAG consensus process under dynamic load conditions. The key performance metrics, i.e., cumulative weight and confirmation delay are analysed based on the proposed model. Then, we leverage a stochastic model to analyse the probability of a successful double-spending attack in different network load regimes. The results can provide an insightful understanding of DAG consensus process, e.g., how the network load affects the confirmation delay and the probability of a successful attack. Meanwhile, we also demonstrate the trade-off between security level and confirmation delay, which can act as a guidance for practical deployment of DAG-based ledgers.
The efficient handling of wastewater pollutants is a must, since they are continuously defiling limited fresh water resources, seriously affecting the terrestrial, aquatic, and aerial flora and ...fauna. Our vision is to undertake an exhaustive examination of current research trends with a focus on nanomaterials (NMs) to considerably improve the performance of classical wastewater treatment technologies, e.g. adsorption, catalysis, separation, and disinfection. Additionally, NM-based sensor technologies are considered, since they have been significantly used for monitoring water contaminants. We also suggest future directions to inform investigators of potentially disruptive NM technologies that have to be investigated in more detail. The fate and environmental transformations of NMs, which need to be addressed before large-scale implementation of NMs for water purification, are also highlighted.
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