Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmissible and pathogenic coronavirus that emerged in late 2019 and has caused a pandemic of acute respiratory disease, ...named 'coronavirus disease 2019' (COVID-19), which threatens human health and public safety. In this Review, we describe the basic virology of SARS-CoV-2, including genomic characteristics and receptor use, highlighting its key difference from previously known coronaviruses. We summarize current knowledge of clinical, epidemiological and pathological features of COVID-19, as well as recent progress in animal models and antiviral treatment approaches for SARS-CoV-2 infection. We also discuss the potential wildlife hosts and zoonotic origin of this emerging virus in detail.
Severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) are two highly transmissible and pathogenic viruses that emerged in humans at the ...beginning of the 21st century. Both viruses likely originated in bats, and genetically diverse coronaviruses that are related to SARS-CoV and MERS-CoV were discovered in bats worldwide. In this Review, we summarize the current knowledge on the origin and evolution of these two pathogenic coronaviruses and discuss their receptor usage; we also highlight the diversity and potential of spillover of bat-borne coronaviruses, as evidenced by the recent spillover of swine acute diarrhoea syndrome coronavirus (SADS-CoV) to pigs.
There is a shred of evidence of environmental degradation in the form of carbon emissions to behave differently when tested with different macroeconomic variables. This paper aims to examine the ...long-run and short-run association between natural resource rent, financial development, and urbanization on carbon emission from the context of the USA during 1995–2015 with the help of a contemporary and innovative approach named quantile autoregressive distributed lagged model (QARDL). The stated approach is applied due to the fact that non-linearity is observed for the study variables. The findings indicated that the higher financial development (0.304), natural resource rent (0.102), and urbanization (0.489) have a positive impact on the environmental degradation in the region of USA during long-run estimation in the stated quantiles of the study. This would indicate that higher financial development, urbanization, and natural resources are putting more environmental pressure on the economy of the USA. Similarly, the findings under short-run estimation confirm that past and lagged values of carbon emission, financial development, natural resource rent, and urbanization are significantly determining the current values of the carbon emission. For this reason, it is suggested that the government requires some immediate steps of the USA to control the harmful effect of such financial development, more urbanization, and higher natural resource rent as well. This would indicate the reflection of some green strategies in all three explanatory variables to generate some fruitful environmental outcomes.
Bat Coronaviruses in China Fan, Yi; Zhao, Kai; Shi, Zheng-Li ...
Viruses,
03/2019, Letnik:
11, Številka:
3
Journal Article
Recenzirano
Odprti dostop
During the past two decades, three zoonotic coronaviruses have been identified as the cause of large-scale disease outbreaks⁻Severe Acute Respiratory Syndrome (SARS), Middle East Respiratory Syndrome ...(MERS), and Swine Acute Diarrhea Syndrome (SADS). SARS and MERS emerged in 2003 and 2012, respectively, and caused a worldwide pandemic that claimed thousands of human lives, while SADS struck the swine industry in 2017. They have common characteristics, such as they are all highly pathogenic to humans or livestock, their agents originated from bats, and two of them originated in China. Thus, it is highly likely that future SARS- or MERS-like coronavirus outbreaks will originate from bats, and there is an increased probability that this will occur in China. Therefore, the investigation of bat coronaviruses becomes an urgent issue for the detection of early warning signs, which in turn minimizes the impact of such future outbreaks in China. The purpose of the review is to summarize the current knowledge on viral diversity, reservoir hosts, and the geographical distributions of bat coronaviruses in China, and eventually we aim to predict virus hotspots and their cross-species transmission potential.
A large number of SARS-related coronaviruses (SARSr-CoV) have been detected in horseshoe bats since 2005 in different areas of China. However, these bat SARSr-CoVs show sequence differences from SARS ...coronavirus (SARS-CoV) in different genes (S, ORF8, ORF3, etc) and are considered unlikely to represent the direct progenitor of SARS-CoV. Herein, we report the findings of our 5-year surveillance of SARSr-CoVs in a cave inhabited by multiple species of horseshoe bats in Yunnan Province, China. The full-length genomes of 11 newly discovered SARSr-CoV strains, together with our previous findings, reveals that the SARSr-CoVs circulating in this single location are highly diverse in the S gene, ORF3 and ORF8. Importantly, strains with high genetic similarity to SARS-CoV in the hypervariable N-terminal domain (NTD) and receptor-binding domain (RBD) of the S1 gene, the ORF3 and ORF8 region, respectively, were all discovered in this cave. In addition, we report the first discovery of bat SARSr-CoVs highly similar to human SARS-CoV in ORF3b and in the split ORF8a and 8b. Moreover, SARSr-CoV strains from this cave were more closely related to SARS-CoV in the non-structural protein genes ORF1a and 1b compared with those detected elsewhere. Recombination analysis shows evidence of frequent recombination events within the S gene and around the ORF8 between these SARSr-CoVs. We hypothesize that the direct progenitor of SARS-CoV may have originated after sequential recombination events between the precursors of these SARSr-CoVs. Cell entry studies demonstrated that three newly identified SARSr-CoVs with different S protein sequences are all able to use human ACE2 as the receptor, further exhibiting the close relationship between strains in this cave and SARS-CoV. This work provides new insights into the origin and evolution of SARS-CoV and highlights the necessity of preparedness for future emergence of SARS-like diseases.
Exposure correction is one of the fundamental tasks in image processing and computational photography. While various methods have been proposed, they either fail to produce visually pleasing results, ...or only work well for limited types of image (e.g., underexposed images). In this paper, we present a novel automatic exposure correction method, which is able to robustly produce high‐quality results for images of various exposure conditions (e.g., underexposed, overexposed, and partially under‐ and over‐exposed). At the core of our approach is the proposed dual illumination estimation, where we separately cast the under‐and over‐exposure correction as trivial illumination estimation of the input image and the inverted input image. By performing dual illumination estimation, we obtain two intermediate exposure correction results for the input image, with one fixes the underexposed regions and the other one restores the overexposed regions. A multi‐exposure image fusion technique is then employed to adaptively blend the visually best exposed parts in the two intermediate exposure correction images and the input image into a globally well‐exposed image. Experiments on a number of challenging images demonstrate the effectiveness of the proposed approach and its superiority over the state‐of‐the‐art methods and popular automatic exposure correction tools.
The nexus between economic growth (EG) and carbon emission has been examined extensively, specifically in consumption-based CO
2
. However, the role of human capital, green energy, and sustainable ...economic growth in determining the carbon emission is yet to be explored specifically from emerging economies. This study aimed to examine the impact of human capital index, green energy, EG in terms of GDP, and square of GDP on carbon emission for long-short run with the help of CS-ARDL. The data for study variables was collected from 1995 to 2018. The study findings confirmed that there exists CSD, cointegration, and slope heterogeneity among the study variables. In contrast, the output through CS-ARDL indicated that the main reason for higher carbon emission in the targeted economies are economic growth under long-short run estimation. Additionally, the role of green energy and human capital index is also constructive in lowering the environmental degradation for both long-run and short-run estimation. Finally, some policy implications are also convassed at the end of the research.
At the provincial level, there is a research gap in discussing the causality and internal mechanism between ICT development and wages of workers. The study utilizes the province-level balanced panel ...data over the period 2006–2021 in China, clarifies the impact and internal mechanism of ICT development on wages of workers, and uses the DID method to identify the causality between the two. This study found that there is a positive correlation between ICT development and workers’ wages, and skill level is a mediate transmission channel. Moreover, ICT development has a positive impact on workers’ wages in the central and western regions. Besides, compared to low-wage workers, high-wage workers gain more information dividends. The findings of this study have reference significance for policymakers. First, for the central and western provinces in China, it is necessary to actively develop the ICT industry, cultivate high-tech enterprises, and improve local ICT development levels. Second, we should improve the skill level of workers and enhance their competitive advantage in employment. Third, each province should continue to expand the enrollment scale of higher education institutions, and improve the quality of labor force.
The challenge of person re-identification (re-id) is to match individual images of the same person captured by different nonoverlapping camera views against significant and unknown cross-view feature ...distortion. While a large number of distance metric/ subspace learning models have been developed for re-id, the cross-view transformations they learned are view-generic and thus potentially less effective in quantifying the feature distortion inherent to each camera view. Learning view-specific feature transformations for re-id (i.e., view-specific re-id), an under-studied approach, becomes an alternative resort for this problem. In this work, we formulate a novel view-specific person re-identification framework from the feature augmentation point of view, called Camera coRrelation Aware Feature augmenTation (CRAFT). Specifically, CRAFT performs cross-view adaptation by automatically measuring camera correlation from cross-view visual data distribution and adaptively conducting feature augmentation to transform the original features into a new adaptive space. Through our augmentation framework, view-generic learning algorithms can be readily generalized to learn and optimize view-specific sub-models whilst simultaneously modelling view-generic discrimination information. Therefore, our framework not only inherits the strength of view-generic model learning but also provides an effective way to take into account view specific characteristics. Our CRAFT framework can be extended to jointly learn view-specific feature transformations for person re-id across a large network with more than two cameras, a largely under-investigated but realistic re-id setting. Additionally, we present a domain-generic deep person appearance representation which is designed particularly to be towards view invariant for facilitating cross-view adaptation by CRAFT. We conducted extensively comparative experiments to validate the superiority and advantages of our proposed framework over state-of-the-art competitors on contemporary challenging person re-id datasets.
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