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Institution

Xi'an Jiaotong-Liverpool University

EducationSuzhou, China
About: Xi'an Jiaotong-Liverpool University is a education organization based out in Suzhou, China. It is known for research contribution in the topics: Population & Photovoltaic system. The organization has 2026 authors who have published 4366 publications receiving 53673 citations. The organization is also known as: Xī’ān Jiāotōng Lìwùpǔ Dàxúe & XJTLU.


Papers
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Journal ArticleDOI
TL;DR: The COVID-19 pandemic was associated with mild stressful impact in a sample of local Chinese residents aged ≥18 years in Liaoning Province, mainland China, even though the pandemic is still ongoing.
Abstract: Our study aimed to investigate the immediate impact of the COVID-19 pandemic on mental health and quality of life among local Chinese residents aged ≥18 years in Liaoning Province, mainland China. An online survey was distributed through a social media platform between January and February 2020. Participants completed a modified validated questionnaire that assessed the Impact of Event Scale (IES), indicators of negative mental health impacts, social and family support, and mental health-related lifestyle changes. A total of 263 participants (106 males and 157 females) completed the study. The mean age of the participants was 37.7 ± 14.0 years, and 74.9% had a high level of education. The mean IES score in the participants was 13.6 ± 7.7, reflecting a mild stressful impact. Only 7.6% of participants had an IES score ≥26. The majority of participants (53.3%) did not feel helpless due to the pandemic. On the other hand, 52.1% of participants felt horrified and apprehensive due to the pandemic. Additionally, the majority of participants (57.8–77.9%) received increased support from friends and family members, increased shared feeling and caring with family members and others. In conclusion, the COVID-19 pandemic was associated with mild stressful impact in our sample, even though the COVID-19 pandemic is still ongoing. These findings would need to be verified in larger population studies.

933 citations

Journal ArticleDOI
Jens Kattge1, Gerhard Bönisch2, Sandra Díaz3, Sandra Lavorel  +751 moreInstitutions (314)
TL;DR: The extent of the trait data compiled in TRY is evaluated and emerging patterns of data coverage and representativeness are analyzed to conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements.
Abstract: Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

882 citations

Journal ArticleDOI
TL;DR: The state-of-the-art communication technologies and smart-based applications used within the context of smart cities are described and a future business model of big data for smart cities is proposed, and the business and technological research challenges are identified.

774 citations

Journal ArticleDOI
TL;DR: It is proposed that this requires a transition from the clinic-centric treatment to patient-centric healthcare where each agent such as hospital, patient, and services are seamlessly connected to each other, and needs a multi-layer architecture.

725 citations

Journal ArticleDOI
TL;DR: SARS-CoV-2 itself is not a recombinant of any sarbecoviruses detected to date, and its receptor-binding motif appears to be an ancestral trait shared with bat viruses and not one acquired recently via recombination.
Abstract: There are outstanding evolutionary questions on the recent emergence of human coronavirus SARS-CoV-2 including the role of reservoir species, the role of recombination and its time of divergence from animal viruses. We find that the sarbecoviruses—the viral subgenus containing SARS-CoV and SARS-CoV-2—undergo frequent recombination and exhibit spatially structured genetic diversity on a regional scale in China. SARS-CoV-2 itself is not a recombinant of any sarbecoviruses detected to date, and its receptor-binding motif, important for specificity to human ACE2 receptors, appears to be an ancestral trait shared with bat viruses and not one acquired recently via recombination. To employ phylogenetic dating methods, recombinant regions of a 68-genome sarbecovirus alignment were removed with three independent methods. Bayesian evolutionary rate and divergence date estimates were shown to be consistent for these three approaches and for two different prior specifications of evolutionary rates based on HCoV-OC43 and MERS-CoV. Divergence dates between SARS-CoV-2 and the bat sarbecovirus reservoir were estimated as 1948 (95% highest posterior density (HPD): 1879–1999), 1969 (95% HPD: 1930–2000) and 1982 (95% HPD: 1948–2009), indicating that the lineage giving rise to SARS-CoV-2 has been circulating unnoticed in bats for decades. In this manuscript, the authors address evolutionary questions on the emergence of SARS-CoV-2. They find that SARS-CoV-2 is not a recombinant of any sarbecoviruses detected to date, and that the bat and pangolin sequences most closely related to SARS-CoV-2 probably diverged several decades ago or possibly earlier from human SARS-CoV-2 samples.

716 citations


Authors

Showing all 2089 results

NameH-indexPapersCitations
Narayanaswamy Balakrishnan82134842669
Alan R. Fersht8216431666
Qingwen Li7134216936
Johannes M. H. Knops6819528859
Hui Li57125918731
Sai Gu5222610619
Tao Sun5272211105
Yuhui Shi5120834909
Victor Chang5039110184
Wouter Joosen4874610597
Stefan M.V. Freund48837215
Mu Wang461237282
Ming Xu451745767
Weisheng Lu442226070
Vernon J. Richardson431117769
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202333
2022102
2021797
2020669
2019626
2018502