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Dezhi Li

Other affiliations: Chinese Ministry of Education
Bio: Dezhi Li is an academic researcher from Southeast University. The author has contributed to research in topics: Resilience (network) & Greenhouse gas. The author has an hindex of 13, co-authored 36 publications receiving 542 citations. Previous affiliations of Dezhi Li include Chinese Ministry of Education.

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TL;DR: Wang et al. as mentioned in this paper investigated the effect of seven key driving factors on the construction industry's carbon emissions and evaluated the effectiveness of the construction emissions policy by using the Logarithmic Mean Divisia Index (LMDI) to decompose incremental emission changes.

152 citations

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TL;DR: Wang et al. as discussed by the authors provided a MCDM approach to assess and rank the resilience of 187 smart cities in China and found that the overall resilience of smart cities is at a relatively low level.

117 citations

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TL;DR: Wang et al. as mentioned in this paper proposed a hybrid Logarithmic Mean Divisia Index (LMDI) model that decomposes the change of total energy consumption (TEC) in the building sector to three different dimensions: 1) key influencing effects that include area effect, structure effect, population intensity, value intensity, and energy intensity; 2) three phases that include material production, construction, and operation; and 3) geographically distributed regions.

61 citations

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TL;DR: In this article, a prediction model was established by system dynamics, including direct CECI, indirect and operational CECIs, to accurately predict the peak of the peak carbon emission of the construction industry in China.
Abstract: China has become the world's largest carbon emitter, and its commitment to peak carbon emissions by 2030 is important for global development. The construction industry is one of China's biggest carbon emitters, and its peak has a direct impact on China's carbon commitment. Due to the regional heterogeneity of different provinces, the carbon emission of construction industry (CECI) at provincial level is of unique significance. To accurately predict the peak of provincial CECI, a prediction model was established by system dynamics, including direct CECI, indirect CECI and operational CECI. Taking Jiangsu province as an example, the single and multiple scenario settings with increasing R&D investment, promoting energy-saving buildings and implementing carbon trading from 2016 to 2030 was carried out, indicating that: 1) Without any carbon emission reduction measures, the CECI would maintain an annual growth rate of 5.58% to reach 530.61 million tons by 2030, and the indirect and operational CECI account for the majority of total with an average annual growth rate of 8.02% and 2.79% respectively. 2) All three measures had good carbon reduction effects, which would reduce the total CECI by 26.46% 21.68% and 10.68% respectively by 2030, but only when implemented simultaneously can CECI peak before 2030, 308.77 million tons at 2029. In the end, three policy implications was put forward. The framework presented in this paper provided a basis for the prediction of peak CECI in a province or state, which can help policy makers plan a more reasonable low-carbon development roadmap.

60 citations

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TL;DR: In this paper, a travel behavior-based Gaussian two-step floating catchment area (G2SFCA) method is proposed as a new method to assess accessibility for older adults with their travel behavior, and spatial disparities of accessibility with travel behavior are identified in five suburban districts and one central district by using Anselin Local Moran's I, and the lowaccessibility area in these six districts are confirmed as the weakness area lacking community-based services.

54 citations

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01 Jan 2020
TL;DR: Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future.
Abstract: Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.

4,408 citations

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TL;DR: In this article, the authors provide a systematic literature review on the theme of sustainable development from the perspective of eco-efficiency, with the adaptation of the knowledge development process intervention instrument -pro-Know-C.

223 citations

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TL;DR: Wang et al. as mentioned in this paper decompose changes in energy-related CO2 emissions into a population effect, economic output effect, industrial structure effect, energy intensity effect and carbon dioxide emission coefficient effect.

206 citations

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TL;DR: In this paper, a data envelopment analysis model was applied to eco-efficiency analysis using environmental pollution as an undesirable output, and a super-efficiency model was modified for ranking.

188 citations

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TL;DR: The findings highlight that although the techno driven approach may be more productive to identify, isolate and quarantine infected individuals, it also results in the suppression and censoring the citizen views.

175 citations