Sustainable Cities and Society最新文献_第3页

Identifying the integrated visual characteristics of greenway landscape: A focus on human perception 确定绿道景观的综合视觉特征：关注人类感知

IF 11.7 1区工程技术

Sustainable Cities and Society Pub Date : 2023-09-01 DOI: 10.1016/j.scs.2023.104937

Wenping Liu, Xuyu Hu, Ziliang Song, Xionggang Yuan

引用次数: 0

The use of Google Community Mobility Reports to model residential waste generation behaviors during and after the COVID-19 lockdown 使用谷歌社区移动报告来模拟 COVID-19 封锁期间和之后的居民废物产生行为

IF 11.7 1区工程技术

Sustainable Cities and Society Pub Date : 2023-09-01 DOI: 10.1016/j.scs.2023.104926

Tanvir Mahmud, K. T. W. Ng, Sagar Ray, Linxiang Lyu, Chunjiang An

引用次数: 0

Exploring the nexus between social vulnerability, built environment, and the prevalence of COVID-19: A case study of Chicago. 探索社会脆弱性、建筑环境与 COVID-19 发病率之间的关系：芝加哥案例研究。

IF 11.7 1区工程技术

Sustainable Cities and Society Pub Date : 2021-12-01 Epub Date: 2021-08-20 DOI: 10.1016/j.scs.2021.103261

Shakil Bin Kashem, Dwayne M Baker, Silvia R González, C Aujean Lee

{"title":"Exploring the nexus between social vulnerability, built environment, and the prevalence of COVID-19: A case study of Chicago.","authors":"Shakil Bin Kashem, Dwayne M Baker, Silvia R González, C Aujean Lee","doi":"10.1016/j.scs.2021.103261","DOIUrl":"10.1016/j.scs.2021.103261","url":null,"abstract":"COVID-19 has significantly and unevenly impacted the United States, disproportionately affecting socially vulnerable communities. While epidemiologists and public health officials have suggested social distancing and shelter-in-place orders to halt the spread of this virus, the ability to comply with these guidelines is dependent on neighborhood, household, and individual characteristics related to social vulnerability. We use structural equation modeling and multiple data sources, including anonymized mobile phone location data from SafeGraph, to examine the effects of different social vulnerability and built environment factors on COVID-19 prevalence over two overlapping time periods (March to May and March to November of 2020). We use Chicago, Illinois as a case study and find that zip codes with low educational attainment consistently experienced higher case rates over both periods. Though population density was not significantly related to the prevalence in any period, movement of people made a significant contribution only during the longer time period. This finding highlights the significance of analyzing different timeframes for understanding social vulnerability. Our results suggest social vulnerability played an influential role in COVID-19 prevalence, highlighting the needs to address socioeconomic barriers to pandemic recovery and future pandemic response.","PeriodicalId":22307,"journal":{"name":"Sustainable Cities and Society","volume":"75 ","pages":"103261"},"PeriodicalIF":11.7,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8459204/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10391230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Discovering optimal strategies for mitigating COVID-19 spread using machine learning: Experience from Asia. 利用机器学习发现缓解COVID-19传播的最佳策略:来自亚洲的经验。

IF 11.7 1区工程技术

Sustainable Cities and Society Pub Date : 2021-12-01 DOI: 10.1016/j.scs.2021.103254

Yue Pan, Limao Zhang, Zhenzhen Yan, May O Lwin, Miroslaw J Skibniewski

{"title":"Discovering optimal strategies for mitigating COVID-19 spread using machine learning: Experience from Asia.","authors":"Yue Pan, Limao Zhang, Zhenzhen Yan, May O Lwin, Miroslaw J Skibniewski","doi":"10.1016/j.scs.2021.103254","DOIUrl":"https://doi.org/10.1016/j.scs.2021.103254","url":null,"abstract":"To inform data-driven decisions in fighting the global pandemic caused by COVID-19, this research develops a spatiotemporal analysis framework under the combination of an ensemble model (random forest regression) and a multi-objective optimization algorithm (NSGA-II). It has been verified for four Asian countries, including Japan, South Korea, Pakistan, and Nepal. Accordingly, we can gain some valuable experience to better understand the disease evolution, forecast the prevalence of the disease, which can provide sustainable evidence to guide further intervention and management. Random forest with a proper rolling time-window can learn the combined effects of environmental and social factors to accurately predict the daily growth of confirmed cases and daily death rate on a national scale, which is followed by NSGA-II to find a range of Pareto optimal solutions for ensuring the minimization of the infection rate and mortality at the same time. Experimental results demonstrate that the predictive model can alert the local government in advance, allowing the accused time to put forward relevant measures. The temperature in the category of environment and the stringency index belonging to the social factor are identified as the top 2 important features to exert a greater impact on the virus transmission. Moreover, optimal solutions provide references to design the best control strategies towards pandemic containment and prevention that can accommodate the country-specific circumstance, which are possible to decrease the two objectives by more than 95%. In particular, appropriate adjustment of social-related features needs to take priority over others, since it can bring about at least 1.47% average improvement of two objectives compared to environmental factors.","PeriodicalId":22307,"journal":{"name":"Sustainable Cities and Society","volume":"75 ","pages":"103254"},"PeriodicalIF":11.7,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.scs.2021.103254","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10450231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 18

Passenger exposure to respiratory aerosols in a train cabin: Effects of window, injection source, output flow location. 乘客在火车车厢内接触呼吸道气溶胶的情况：窗户、注入源和输出流位置的影响。

IF 11.7 1区工程技术

Sustainable Cities and Society Pub Date : 2021-12-01 Epub Date: 2021-08-19 DOI: 10.1016/j.scs.2021.103280

Mahdi Ahmadzadeh, Mehrzad Shams

{"title":"Passenger exposure to respiratory aerosols in a train cabin: Effects of window, injection source, output flow location.","authors":"Mahdi Ahmadzadeh, Mehrzad Shams","doi":"10.1016/j.scs.2021.103280","DOIUrl":"10.1016/j.scs.2021.103280","url":null,"abstract":"Nowadays the use of public transportation (PT) has been identified as high risk as due to the transfer of particles carrying the coronavirus from an infected passenger to others. This study puts forward a new computational framework for predicting the spread of droplets produced while the infected passenger talking inside the cabin of a train during various scenarios, including the changes in the outflows' location and the infected passenger's position. CFD was used to conduct the study, using the Euler-Lagrange approach to capture the transmission of particles, and Reynolds-averaged Navier-Stokes equations (RANS) to compute the airflow field. The results revealed that opening the window reduces the duration of particles inside the domain. So that when the window is open, the particle's shelf time can decrease to 25 percent comparing with closed mode. It was found that the passenger sitting next to the infected passenger encountered the highest infection risk. The conclusions made in this work show that the most desirable situation is obtained when the infected passenger is sitting next to the exits, whether the window is closed or open. The results of this paper offer comprehensive insights into how to keep indoor environments safe against infection aerosols.","PeriodicalId":22307,"journal":{"name":"Sustainable Cities and Society","volume":"75 ","pages":"103280"},"PeriodicalIF":11.7,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8459195/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10391231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

What determines urban resilience against COVID-19: City size or governance capacity? 是什么决定了城市抵御 COVID-19 的能力？城市规模还是治理能力？

IF 11.7 1区工程技术

Sustainable Cities and Society Pub Date : 2021-12-01 Epub Date: 2021-08-28 DOI: 10.1016/j.scs.2021.103304

Zhen Chu, Mingwang Cheng, Malin Song

{"title":"What determines urban resilience against COVID-19: City size or governance capacity?","authors":"Zhen Chu, Mingwang Cheng, Malin Song","doi":"10.1016/j.scs.2021.103304","DOIUrl":"10.1016/j.scs.2021.103304","url":null,"abstract":"This study analyzed the effects of urban governance and city size on COVID-19 prevention and control measures. Based on real-time data in 276 prefecture-level Chinese cities, we used the ordinary least squares plus robust standard error strategy. It was found that: (1) despite the non-significant effect of city size, urban governance capacity was an important factor affecting the prevention and control of the COVID-19 pandemic; urban governance capacity was particularly significant in the late control of the pandemic, but not significant in the early prevention; for every unit increase of urban governance capacity, the number of recovered COVID-19 cases per capita increased by 2.4%. Moreover, (2) the influence mechanism of anti-pandemic measures in cities could be divided into the workforce, financial, and material effects, and their contribution rates were 26.15%, 32.55%, and 37.20%, respectively; namely, the effective/timely assistance from Chinese central government regarding the workforce, financial, and material resources in key pandemic areas and nationwide played a major role in pandemic control. Additionally, (3) cities with a high level of smart city construction were more capable of enhancing the pandemic prevention and control effect, indicating that smart city construction is conducive to enhanced coping with public crises.","PeriodicalId":22307,"journal":{"name":"Sustainable Cities and Society","volume":"75 ","pages":"103304"},"PeriodicalIF":11.7,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8437392/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10395362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An evaluative model for assessing pandemic resilience at the neighborhood level: The case of Tehran. 在社区一级评估大流行病适应能力的评价模型：德黑兰案例。

IF 11.7 1区工程技术

Sustainable Cities and Society Pub Date : 2021-12-01 Epub Date: 2021-09-28 DOI: 10.1016/j.scs.2021.103410

Azadeh Lak, Pantea Hakimian, Ayyoob Sharifi

{"title":"An evaluative model for assessing pandemic resilience at the neighborhood level: The case of Tehran.","authors":"Azadeh Lak, Pantea Hakimian, Ayyoob Sharifi","doi":"10.1016/j.scs.2021.103410","DOIUrl":"10.1016/j.scs.2021.103410","url":null,"abstract":"The spread of the COVID-19 virus, which has caused abundant mortalities in human settlements, has drawn the attention of urban planners and policy-makers to the necessity of improving resilience to future pandemics. In this study, a set of indicators related to pandemic resilience were identified and used to develop a composite multi-dimensional pandemic resilience index for Tehran's neighborhoods. The physical, infrastructural, socio-economic, and environmental dimensions of pandemic resilience were defined considering the conditions of 351 neighborhoods through the exploratory factor analysis method. Accordingly, the pandemic resilience (PR) score of the neighborhoods was calculated. Furthermore, the Pearson correlation analysis was used to validate the PR scores by examining the correlation between the neighborhood PR scores and the number of confirmed cases. For this purpose, we used a sample consisting of 43,000 confirmed COVID-19 patients in the first five months of its spread. The test shows a statistically significant negative correlation between neighborhoods' resilience score and the cumulative number of confirmed patients in the neighborhoods (r= -.456, P<0.001). This study also tries to develop a new model to better understand health determinants of pandemic resilience. The proposed model can inform planners and policymakers to take appropriate measures to create more pandemic-resilient urban neighborhoods.","PeriodicalId":22307,"journal":{"name":"Sustainable Cities and Society","volume":"75 ","pages":"103410"},"PeriodicalIF":11.7,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8487762/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10389994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

On the Critical Role of Human Feces and Public Toilets in the Transmission of COVID-19: Evidence from China. 人类粪便和公共厕所在 COVID-19 传播中的关键作用：来自中国的证据

IF 11.7 1区工程技术

Sustainable Cities and Society Pub Date : 2021-12-01 Epub Date: 2021-09-11 DOI: 10.1016/j.scs.2021.103350

Qiuyun Wang, Lu Liu

{"title":"On the Critical Role of Human Feces and Public Toilets in the Transmission of COVID-19: Evidence from China.","authors":"Qiuyun Wang, Lu Liu","doi":"10.1016/j.scs.2021.103350","DOIUrl":"10.1016/j.scs.2021.103350","url":null,"abstract":"The surprising spread speed of the COVID-19 pandemic creates an urgent need for investigating the transmission chain or transmission pattern of COVID-19 beyond the traditional respiratory channels. This study therefore examines whether human feces and public toilets play a critical role in the transmission of COVID-19. First, it develops a theoretical model that simulates the transmission chain of COVID-19 through public restrooms. Second, it uses stabilized epidemic data from China to empirically examine this theory, conducting an empirical estimation using a two-stage least squares (2SLS) model with appropriate instrumental variables (IVs). This study confirms that the wastewater directly promotes the transmission of COVID-19 within a city. However, the role of garbage in this transmission chain is more indirect in the sense that garbage has a complex relationship with public toilets, and it promotes the transmission of COVID-19 within a city through interaction with public toilets and, hence, human feces. These findings have very strong policy implications in the sense that if we can somehow use the ratio of public toilets as a policy instrument, then we can find a way to minimize the total number of infections in a region. As shown in this study, pushing the ratio of public toilets (against open defecation) to the local population in a city to its optimal level would help to reduce the total infection in a region.","PeriodicalId":22307,"journal":{"name":"Sustainable Cities and Society","volume":"75 ","pages":"103350"},"PeriodicalIF":11.7,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8433098/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10395361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Spatiotemporal patterns of the COVID-19 control measures impact on industrial production in Wuhan using time-series earth observation data. 利用时间序列地球观测数据研究 COVID-19 控制措施对武汉工业生产影响的时空模式。

IF 11.7 1区工程技术

Sustainable Cities and Society Pub Date : 2021-12-01 Epub Date: 2021-09-25 DOI: 10.1016/j.scs.2021.103388

Ya'nan Zhou, Li Feng, Xin Zhang, Yan Wang, Shunying Wang, Tianjun Wu

{"title":"Spatiotemporal patterns of the COVID-19 control measures impact on industrial production in Wuhan using time-series earth observation data.","authors":"Ya'nan Zhou, Li Feng, Xin Zhang, Yan Wang, Shunying Wang, Tianjun Wu","doi":"10.1016/j.scs.2021.103388","DOIUrl":"10.1016/j.scs.2021.103388","url":null,"abstract":"Understanding the spatiotemporal patterns of the COVID-19 impact on industrial production could improve the estimation of the economic loss and sustainable work resumption policies in cities. In this study, assuming and checking a correlation between the land surface temperature (LST) and industrial production, we applied the BFAST algorithm and linear regression models on multi-temporal MODIS data to derive monthly time-series deviation of LST with a spatial resolution of 1 × 1 km, to quantificationally explore the fine-scale spatiotemporal patterns of the COVID-19 control measures impact on industrial production, within Wuhan city. The results demonstrate that (1) the trend of time-series LST could partly reflect the impact of the COVID-19 pandemic on industrial production, and the year-around industrial production was less than expectations, with a fall of 14.30%; (2) the most serious COVID-19 impact on industrial production appeared in Mar. and Apr., then, after the lifting of lockdown, some regions (approximate 4.90%) firstly returned to expected levels in Jun, and almost all regions (98.49%) have completed the resumption of work and production before Nov.; (3) the southwest and south-central had more serious impact of the COVID-19 pandemic, approximate twice as much as that in the north and suburban, in Wuhan. The results and findings elaborated the spatiotemporal distribution and their changes during 2020 within Wuhan, which could provide a beneficial support for assessment of the COVID-19 pandemic and implementation of resumption plans for sustainable development.","PeriodicalId":22307,"journal":{"name":"Sustainable Cities and Society","volume":"75 ","pages":"103388"},"PeriodicalIF":11.7,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8482229/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10450806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Deep transfer learning for COVID-19 detection and infection localization with superpixel based segmentation. 基于超像素分割的COVID-19检测和感染定位深度迁移学习。

IF 11.7 1区工程技术

Sustainable Cities and Society Pub Date : 2021-12-01 DOI: 10.1016/j.scs.2021.103252

N B Prakash, M Murugappan, G R Hemalakshmi, M Jayalakshmi, Mufti Mahmud

{"title":"Deep transfer learning for COVID-19 detection and infection localization with superpixel based segmentation.","authors":"N B Prakash, M Murugappan, G R Hemalakshmi, M Jayalakshmi, Mufti Mahmud","doi":"10.1016/j.scs.2021.103252","DOIUrl":"https://doi.org/10.1016/j.scs.2021.103252","url":null,"abstract":"The evolution the novel corona virus disease (COVID-19) as a pandemic has inflicted several thousand deaths per day endangering the lives of millions of people across the globe. In addition to thermal scanning mechanisms, chest imaging examinations provide valuable insights to the detection of this virus, diagnosis and prognosis of the infections. Though Chest CT and Chest X-ray imaging are common in the clinical protocols of COVID-19 management, the latter is highly preferred, attributed to its simple image acquisition procedure and mobility of the imaging mechanism. However, Chest X-ray images are found to be less sensitive compared to Chest CT images in detecting infections in the early stages. In this paper, we propose a deep learning based framework to enhance the diagnostic values of these images for improved clinical outcomes. It is realized as a variant of the conventional SqueezeNet classifier with segmentation capabilities, which is trained with deep features extracted from the Chest X-ray images of a standard dataset for binary and multi class classification. The binary classifier achieves an accuracy of 99.53% in the discrimination of COVID-19 and Non COVID-19 images. Similarly, the multi class classifier performs classification of COVID-19, Viral Pneumonia and Normal cases with an accuracy of 99.79%. This model called the COVID-19 Super pixel SqueezNet (COVID-SSNet) performs super pixel segmentation of the activation maps to extract the regions of interest which carry perceptual image features and constructs an overlay of the Chest X-ray images with these regions. The proposed classifier model adds significant value to the Chest X-rays for an integral examination of the image features and the image regions influencing the classifier decisions to expedite the COVID-19 treatment regimen.","PeriodicalId":22307,"journal":{"name":"Sustainable Cities and Society","volume":"75 ","pages":"103252"},"PeriodicalIF":11.7,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.scs.2021.103252","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10381229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 24