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  • Sedrez, Maycon  (5)
  • English  (5)
  • 2020-2024  (5)
  • 1
    In: Heliyon, Elsevier BV, Vol. 9, No. 3 ( 2023-03), p. e13879-
    Type of Medium: Online Resource
    ISSN: 2405-8440
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2023
    detail.hit.zdb_id: 2835763-2
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  • 2
    In: Scientific Reports, Springer Science and Business Media LLC, Vol. 12, No. 1 ( 2022-02-04)
    Abstract: With evidence-based measures, COVID-19 can be effectively controlled by advanced data analysis and prediction. However, while valuable insights are available, there is a shortage of robust and rigorous research on what factors shape COVID-19 transmissions at the city cluster level. Therefore, to bridge the research gap, we adopted a data-driven hierarchical modeling approach to identify the most influential factors in shaping COVID-19 transmissions across different Chinese cities and clusters. The data used in this study are from Chinese officials, and hierarchical modeling conclusions drawn from the analysis are systematic, multifaceted, and comprehensive. To further improve research rigor, the study utilizes SPSS, Python and RStudio to conduct multiple linear regression and polynomial best subset regression (PBSR) analysis for the hierarchical modeling. The regression model utilizes the magnitude of various relative factors in nine Chinese city clusters, including 45 cities at a different level of clusters, to examine these aspects from the city cluster scale, exploring the correlation between various factors of the cities. These initial 12 factors are comprised of ‘Urban population ratio’, ‘Retail sales of consumer goods’, ‘Number of tourists’, ‘Tourism Income’, ‘Ratio of the elderly population ( 〉  60 year old) in this city’, ‘population density’, ‘Mobility scale (move in/inbound) during the spring festival’, ‘Ratio of Population and Health facilities’, ‘Jobless rate (%)’, ‘The straight-line distance from original epicenter Wuhan to this city’, ‘urban per capita GDP’, and ‘the prevalence of the COVID-19’. The study’s results provide rigorously-tested and evidence-based insights on most instrumental factors that shape COVID-19 transmissions across cities and regions in China. Overall, the study findings found that per capita GDP and population mobility rates were the most affected factors in the prevalence of COVID-19 in a city, which could inform health experts and government officials to design and develop evidence-based and effective public health policies that could curb the spread of the COVID-19 pandemic.
    Type of Medium: Online Resource
    ISSN: 2045-2322
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 2615211-3
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  • 3
    In: Sustainability, MDPI AG, Vol. 14, No. 12 ( 2022-06-09), p. 7075-
    Abstract: This research studies the data on air quality and construction activities from 29 January 2020 to 30 April 2020. The analysis focuses on three sample districts of Hangzhou’s Xiacheng, Gongshu, and Xiaoshan districts. The samples, respectively, represent low-level, mid-level, and high-level districts in the scale of construction projects. The correlative relationships are investigated, respectively, in the periods of ‘pandemic lockdown (29 January 2020–20 February 2020)’ and ‘after pandemic lockdown (21 February 2020–30 April 2020)’. The correlative equations are obtained. Based on the guideline values of air parameters provided by the Chinese criteria and standards, the recommended maximum scales of construction projects are defined. The numbers of construction sites are 16, 118, and 311 for the Xiacheng, Gongshu, and Xiaoshan districts during the imposed lockdown period, respectively, and 19, 88, 234, respectively, after the lockdown period. Because the construction site is only one influential factor on the air quality, and the database is not large enough, there are some limitations in the mathematical model and the management plan. Possible problem solving techniques and future studies are introduced at the end of the research study.
    Type of Medium: Online Resource
    ISSN: 2071-1050
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2518383-7
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  • 4
    In: Sustainability, MDPI AG, Vol. 13, No. 10 ( 2021-05-12), p. 5395-
    Abstract: The COVID-19 pandemic has spread rapidly all over the world, affecting many countries to varying degrees. In this study, an in-depth analysis of the factors influencing the spread of COVID-19 is offered mainly through big data in the European Union (EU) context. In doing so, the data of the first wave of the pandemic are assessed. Afterward, we evaluate the impacts of the COVID-19 spread in specific countries and regions. Based on the existing literature, mobility is recognized as a significant direct factor affecting disease transmission. The same applies to the case of COVID-19. However, compared with the analysis of mobility itself, this paper explores more profound reasons that affect mobility, ranging from policy and economy to geographical and transportation factors. Specifically, this paper studies nine EU countries based on their population density and the degree of impact of the epidemic in the first six months (February to July 2020) of the pandemic. Our study aims to illustrate how policies, economies, and geographical locations (including transportation factors) directly or indirectly affect the spread of the novel coronavirus by applying the SEIR model to analyze all selected countries’ big data. The key findings of this research are: (1) the timeliness of relevant policies and the effectiveness of government implementation indirectly limit the spread of the epidemic by reducing population mobility; (2) a better medical level would contribute to detect, isolate, and treat patients, and help control the epidemic; and (3) the large land borders and developed transportation between countries exacerbate the spread of the COVID-19. The paper contributes to ongoing research on COVID-19 by addressing the above points.
    Type of Medium: Online Resource
    ISSN: 2071-1050
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2518383-7
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  • 5
    Online Resource
    Online Resource
    MDPI AG ; 2021
    In:  Sustainability Vol. 13, No. 9 ( 2021-04-26), p. 4853-
    In: Sustainability, MDPI AG, Vol. 13, No. 9 ( 2021-04-26), p. 4853-
    Abstract: Urban areas around the world are increasingly facing environmental challenges such as water scarcity, water pollution, and water-related disasters, which demands sustainable design solutions for cities. Efforts to introduce sustainable methods in architectural education are noteworthy since the early 1990s. However, Water Sensitive Design (WSD) has not been fully integrated to architectural education. WSD is an interdisciplinary approach that considers the water cycle as the primary element of design strategies, integrating the site’s ecological and social aspects to structure water management. The main objective of this study is to identify cases introducing WSD in an architecture design studio revealing its pedagogical approaches, comparing and discussing with a WSD-focused design studio. This study adapts on an exploratory and descriptive research, analyzing the literature on the topic of WSD in architectural education and documenting a graduate-level architectural design studio that proposes the development of water-oriented masterplan. The results suggest that WSD, as interdisciplinary method, can be incorporated into the design studio as the topic due to its tangible tools and strategies towards water. It also fits the proposal of a design studio to integrate knowledge from diverse disciplines. This unique study presents a comprehensive WSD introduction in an architectural design case and indicative pedagogical methods, contributing to the development of an approach for future related works.
    Type of Medium: Online Resource
    ISSN: 2071-1050
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2518383-7
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