Unprecedented measures have been adopted to control the rapid spread of the ongoing COVID-19 epidemic in China. People's adherence to control measures is affected by their knowledge, attitudes, and ...practices (KAP) towards COVID-19. In this study, we investigated Chinese residents' KAP towards COVID-19 during the rapid rise period of the outbreak. An online sample of Chinese residents was successfully recruited via the authors' networks with residents and popular media in Hubei, China. A self-developed online KAP questionnaire was completed by the participants. The knowledge questionnaire consisted of 12 questions regarding the clinical characteristics and prevention of COVID-19. Assessments on residents' attitudes and practices towards COVID-19 included questions on confidence in winning the battle against COVID-19 and wearing masks when going out in recent days. Among the survey completers (n=6910), 65.7% were women, 63.5% held a bachelor degree or above, and 56.2% engaged in mental labor. The overall correct rate of the knowledge questionnaire was 90%. The majority of the respondents (97.1%) had confidence that China can win the battle against COVID-19. Nearly all of the participants (98.0%) wore masks when going out in recent days. In multiple logistic regression analyses, the COVID-19 knowledge score (OR: 0.75-0.90, P<0.001) was significantly associated with a lower likelihood of negative attitudes and preventive practices towards COVID-2019. Most Chinese residents of a relatively high socioeconomic status, in particular women, are knowledgeable about COVID-19, hold optimistic attitudes, and have appropriate practices towards COVID-19. Health education programs aimed at improving COVID-19 knowledge are helpful for Chinese residents to hold optimistic attitudes and maintain appropriate practices. Due to the limited sample representativeness, we must be cautious when generalizing these findings to populations of a low socioeconomic status.
With the development of radiotherapeutic oncology, computer technology and medical imaging technology, radiation therapy has made great progress. Research on the impact and the specific mechanism of ...radiation on tumors has become a central topic in cancer therapy. According to the traditional view, radiation can directly affect the structure of the DNA double helix, which in turn activates DNA damage sensors to induce apoptosis, necrosis, and aging or affects normal mitosis events and ultimately rewires various biological characteristics of neoplasm cells. In addition, irradiation damages subcellular structures, such as the cytoplasmic membrane, endoplasmic reticulum, ribosome, mitochondria, and lysosome of cancer cells to regulate various biological activities of tumor cells. Recent studies have shown that radiation can also change the tumor cell phenotype, immunogenicity and microenvironment, thereby globally altering the biological behavior of cancer cells. In this review, we focus on the effects of therapeutic radiation on the biological features of tumor cells to provide a theoretical basis for combinational therapy and inaugurate a new era in oncology.
Convolutional neural networks (CNNs) are the heart of deep learning applications. Recent works PRIME 1 and ISAAC 2 demonstrated the promise of using resistive random access memory (ReRAM) to perform ...neural computations in memory. We found that training cannot be efficiently supported with the current schemes. First, they do not consider weight update and complex data dependency in training procedure. Second, ISAAC attempts to increase system throughput with a very deep pipeline. It is only beneficial when a large number of consecutive images can be fed into the architecture. In training, the notion of batch (e.g. 64) limits the number of images can be processed consecutively, because the images in the next batch need to be processed based on the updated weights. Third, the deep pipeline in ISAAC is vulnerable to pipeline bubbles and execution stall. In this paper, we present PipeLayer, a ReRAM-based PIM accelerator for CNNs that support both training and testing. We analyze data dependency and weight update in training algorithms and propose efficient pipeline to exploit inter-layer parallelism. To exploit intra-layer parallelism, we propose highly parallel design based on the notion of parallelism granularity and weight replication. With these design choices, PipeLayer enables the highly pipelined execution of both training and testing, without introducing the potential stalls in previous work. The experiment results show that, PipeLayer achieves the speedup of 42.45x compared with GPU platform on average. The average energy saving of PipeLayer compared with GPU implementation is 7.17x.
The increasing demands of energy storage require the significant improvement of current Li‐ion battery electrode materials and the development of advanced electrode materials. Thus, it is necessary ...to gain an in‐depth understanding of the reaction processes, degradation mechanism, and thermal decomposition mechanisms under realistic operation conditions. This understanding can be obtained by in situ/operando characterization techniques, which provide information on the structure evolution, redox mechanism, solid‐electrolyte interphase (SEI) formation, side reactions, and Li‐ion transport properties under operating conditions. Here, the recent developments in the in situ/operando techniques employed for the investigation of the structural stability, dynamic properties, chemical environment changes, and morphological evolution are described and summarized. The experimental approaches reviewed here include X‐ray, electron, neutron, optical, and scanning probes. The experimental methods and operating principles, especially the in situ cell designs, are described in detail. Representative studies of the in situ/operando techniques are summarized, and finally the major current challenges and future opportunities are discussed. Several important battery challenges are likely to benefit from these in situ/operando techniques, including the inhomogeneous reactions of high‐energy‐density cathodes, the development of safe and reversible Li metal plating, and the development of stable SEI.
Recent developments of the five important in situ/operando characterization categories for lithium battery research are summarized, including X‐ray, electron, neutron, optical, and scanning probe techniques. For each technique, the operating principles and in situ cell design are described in detail, including representative studies of typical electrode materials and related processes summarized in tables for easy comparison and cross reference.
The azo linkage is a prominent chemical motif which has found numerous applications in materials science, pharmaceuticals, and agrochemicals. Described herein is a sustainable ...heterogeneous‐gold‐catalyzed synthesis of azo arenes. Available nitroarenes are deoxygenated and linked selectively by the formation of NN bonds using molecular H2 without any external additives. As a result of a unique and remarkable synergy between the metal and support, a facile surface‐mediated condensation of nitroso and hydroxylamine intermediates is enabled, and the desired transformation proceeds in a highly selective manner under mild reaction conditions. The protocol tolerates a large variety of functional groups and offers a general and versatile method for the environmentally friendly synthesis of symmetric or asymmetric aromatic azo compounds.
Game of rates: A general approach for the chemoselective hydrogenative coupling of nitroarenes to give the corresponding azo compounds, using a heterogeneous gold catalyst, has been developed. As a result of the remarkable synergy between the metal and support, a facile condensation of transient nitroso and hydroxylamine intermediates proceeds. The desired transformation is highly selective under mild reaction conditions.
The development of economical, efficient and stable non-noble metal catalysts plays a key role in electrocatalytic hydrogen evolution. NiCo2S4 has been proved to be an efficient non-noble catalyst, ...to further improve its electrocatalytic performance is a meaningful work. In this paper, the effects of Fe doping on electrochemical performance of NiCo2S4 is investigated. The Fe-doped NiCo2S4 catalyst is prepared by a facile solvothermal method with metal-organic-framework (MOF, ZIF-67) as template, and it exhibits an improved hydrogen evolution reaction (HER) performance with an overpotential of 181 mV at 10 mA cm−2, a Tafel slope of 125 mV dec−1 compared with that of NiCo2S4 (252 mV overpotential and 149 mV dec−1 Tafel slope). The combination of improved conductivity, mesopores architecture retained with the ZIF-67 template, which result the reduced internal resistance, enhanced charge transportation as well as large electrochemical double-layer capacitance. This work provides an effective and synergistic strategy for fabricating NiCo2S4-based catalysts toward electrochemical water splitting.
•Fe-doped NiCo2S4 catalyst was synthesized by using ZIF-67 as a template.•The conductivity of NiCo2S4 is increased by Fe doping.•Mesopores architecture of the Fe-doped NiCo2S4 is retained with the template.•The Fe-doped NiCo2S4 catalyst presents an improved HER activity and stability.
Abstract
India‐Asia collision is generally believed to have collided since 55 ± 5 Ma, with a total amount of convergence of 2900–4400 km. Besides the overriding Tibetan lithospheric shortening, a ...large amount of convergence has to be accommodated by the subducting plate of Greater India. Three typical India‐Asia collision models have been proposed, including the Greater Indian Continent (GIC) model, Intra‐Oceanic Arc model and Greater Indian Oceanic Basin model. In this study, a large‐scale 2D numerical model, driven by the reconstruction‐based India‐Asia convergence rate, have been conducted to evaluate these three major models. The model results indicate that the one‐stage GIC model favours later initial collision at ≤50 Ma. For the two‐stage collision, the large amount of convergence can be easily accommodated by modifying the length of oceanic subduction after the first stage of continental collision. This study provides systematic numerical constraints for the favourable conditions of each model.
The pursuit of high‐power factor and low lattice thermal conductivity simultaneously in thermoelectric research is longstanding. Herein, great success has been achieved in SnTe‐based materials by ...employing a proposed strategy of entropy engineering involving vacancies, thus leveraging the promising cocktail effect. Significant band convergence and flatness effects have given rise to exceptionally high density of state carrier effective mass and Seebeck coefficients. These effects have also led to the theoretical optimal carrier concentration closely aligning with the actual carrier concentration. Furthermore, the entropy engineering involving vacancies has induced pronounced lattice disorder and a wealth of nanostructures, facilitating multi‐scale phonon scattering. Consequently, impressive thermoelectric performance is realized in AgSb3Pb2Ge2Sn6Te15: room‐temperature ZT of ≈0.4, peak ZT of ≈1.3 at 623 K, and average ZT of ≈1.0 (300–773 K). A thermoelectric module, comprising this p‐type material and the homemade n‐type PbTe, is assembled, demonstrating a competitive conversion efficiency of 9.3% at a temperature difference of 478 K. This work not only provides valuable insights into the modulation of electron/phonon transports but also establishes an effective paradigm of entropy engineering involving vacancies.
Unlike the exclusive implementation of entropy engineering or vacancy engineering in SnTe‐based materials, a strategy of entropy engineering involving vacancies is proposed in this work to leverage a promising cocktail effect. The approach results in the simultaneous attainment of high power factor and low lattice thermal conductivity, culminating in extraordinary thermoelectric performance at low‐medium temperatures.
Abstract
The solid‐state battery (SSB) is a promising direction to address the inherent safety problems in commercial batteries and energy storage systems. However, the development of SSBs is still ...hider of the low ionic conductivity of solid‐state electrolytes. Based on a machine learning (ML) method, a cobalt‐doping strategy was developed for the Na
3.2
Zr
2
Si
2.2
P
0.8
O
12
(NASICON) compound by training on NASICON‐type solid electrolyte data. The cobalt‐doping strategy efficiently improves the NASICONs’ ionic conductivity to ~2.63 mS/cm with low activation energy at ~0.245 eV. The grain‐boundary ionic conductivity reaches ~11.00 mS/cm without extra densification of the pellet. The NASICON's structures were studied by the Rietveld and the bond‐valence methods. The calculations and observed structural transitions confirm that the cobalt‐doping strategy promotes the structural transition and adjusts the structure to a better performance state. The doping strategy predicted by the ML model is consistent with our experimental results, providing very useful guidance for improving ionic conductivity of NASICON electrolytes.
Root zone microbial structure is particularly complex in plants with rhizosheaths, and greater understanding of the rhizosheath may play an important role in the future development of sustainable ...agricultural practices. However, one important reason to focus study on rhizosheath microbial structure is that there is no definite method for rhizosheath separation. The aim of this study was to explore rhizosheath isolation methods and the diversity characteristics of microorganisms around the rhizosphere. In this study, we isolated the rhizosheath of Stipa grandis, a dominant species in desert steppe, and the microorganisms in the roots, root epidermis, rhizosheath and rhizosphere soil were extracted and sequenced by 16S rRNA and ITS. The alpha diversity index of bacteria in Stipa grandis rhizosphere soil was the greatest, followed by rhizosheath, and the alpha diversity index of endophytic bacteria in root system was the smallest. The alpha diversity index of fungi in the rhizosheath and rhizosphere soil were significantly higher than that in the root epidermis and root system. There were significant differences in bacterial community structure between the root epidermis, endophytic bacteria, rhizosheath and rhizosphere soil. Unlike bacterial community structure, the community structure of fungi in the root epidermis was similar that of endophytic fungi, but significantly different from those in rhizosheath and rhizosphere soil. This study demonstrated a feasible method for separating plant rhizosheath and root epidermis. We suggest that the root epidermis can act as the interface between the host plant root and the external soil environment. We will have to re-examine the biological and ecological significance of rhizosheath and microorganisms in rhizosheath, as well as the mechanism explaining the close relationship of the rhizosheath and the plant root epidermis. This study provides theoretical and technical guidance for the isolation of the plant rhizosheath and the study of microorganisms in plant rhizosheath.
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