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In this paper, preliminary investigation was conducted to evaluate the potential ecological risk of heavy metals contamination in cemetery soils. Necrosol samples were collected from within and around the vicinity of the largest mass grave in Rwanda and analyzed for heavy metal concentrations using total digestion–inductively coupled plasma mass spectrometry and instrumental neutron activation analysis. Based on the concentrations of As, Cu, Cr, Pb, and Zn, the overall contamination degree (Cdeg) and potential ecological risks status (RI) of the necrosols were determined. The preliminary results revealed that the associated cemetery soils are only contaminated to a low degree. On the other hand, assessment of the potential ecological risk index (RI) revealed that cumulative heavy metal content of the soil do not pose any significant ecological risks. These findings, therefore, suggest that, while cemetery soils may be toxic due to the accumulation of certain heavy metals, their overall ecological risks may be minimal and insignificant.
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Agglomerated cork is a known material by its contribution to the sustainment of the environment, not only because it is a wholly natural material, without chemical additives, but also because its industrial process of production results from the lowest quality residues of cork or industrial waste material, unsuitable for other applications. It is a reusable material, which means, the cork facade elements can be converted into a new agglomerated material, demonstrating a huge potential for adaptation to existing buildings following a reversible process. It is durable, lightweight, water resistant, low-cost material, some of the properties that may qualify it as suitable for application in large surfaces of vertical construction façades. The aim of this article is to analyze the mechanical, thermal and acoustic characteristics of cork composites against site-specific climatic conditions of subtropical climates and its suitability as an external coating system for residential buildings with the goal to reduce the energy consumption for cooling the inner environment. In high-density cities like Guangzhou, Shenzhen and Hong Kong the majority of the buildings starting from the 1960s until early 21st century (Brach & Song 2006), did not integrate thermal insulation systems into external walls, producing a high level of heat transfer through the external façade from the outside environment during spring and summer seasons. Due to the extremely fast urban growth of the modern Chinese city, little importance is given to the quality of the external walls in current residential building construction. For at least during six months each year the consumption of energy due to air conditioning in Guangdong province is extremely high. The study concluded that substantial energy could be saved by implementing an external coating upgrade to existing buildings. Additionally, this study details the result obtained through software for energy simulations (Design Builder, ENVI-met) demonstrating the potential of this project to produce homogeneous and comfortable inside temperatures, which cools the indoor ambient temperature in summer time.
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With the fifth generation (5G) communication technology, the mobile multiuser networks have developed rapidly. In this paper, the performance analysis of mobile multiuser networks which utilize decode-and-forward (DF) relaying is considered. We derive novel outage probability (OP) expressions. To improve the OP performance, we study the power allocation optimization problem. To solve the optimization problem, we propose an intelligent power allocation optimization algorithm based on grey wolf optimization (GWO). We compare the proposed GWO approach with three existing algorithms. The experimental results reveal that the proposed GWO algorithm can achieve a smaller OP, thus improving system efficiency. Also, compared with other channel models, the OP values of the 2-Rayleigh model are increased by 81.2% and 66.6%, respectively.
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COVID-19 has hit the world unprepared, as the deadliest pandemic of the century. Governments and authorities, as leaders and decision makers fighting the virus, enormously tap into the power of artificial intelligence and its predictive models for urgent decision support. This book showcases a collection of important predictive models that used during the pandemic, and discusses and compares their efficacy and limitations. Readers from both healthcare industries and academia can gain unique insights on how predictive models were designed and applied on epidemic data. Taking COVID19 as a case study and showcasing the lessons learnt, this book will enable readers to be better prepared in the event of virus epidemics or pandemics in the future.
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Following the World Health Organization proclaims a pandemic due to a disease that originated in China and advances rapidly across the globe, studies to predict the behavior of epidemics have become increasingly popular, mainly related to COVID-19. The critical point of these studies is to discuss the disease's behavior and the progression of the virus's natural course. However, the prediction of the actual number of infected people has proved to be a difficult task, due to a wide range of factors, such as mass testing, social isolation, underreporting of cases, among others. Therefore, the objective of this work is to understand the behavior of COVID-19 in the state of Ceará to forecast the total number of infected people and to aid in government decisions to control the outbreak of the virus and minimize social impacts and economics caused by the pandemic. So, to understand the behavior of COVID-19, this work discusses some forecast techniques using machine learning, logistic regression, filters, and epidemiologic models. Also, this work brings a new approach to the problem, bringing together data from Ceará with those from China, generating a hybrid dataset, and providing promising results. Finally, this work still compares the different approaches and techniques presented, opening opportunities for future discussions on the topic. The study obtains predictions with R2 score of 0.99 to short-term predictions and 0.93 to long-term predictions.
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As an incomparable implication of industrial culture, the industrial heritage has a wide range of historical, technological, social, architectural or scientific values. With the process of large-scale contemporary urban revitalization, abandoned industrial buildings and areas always become the targets of urban renewal and redevelopment due to the ongoing transformation on structural changes of economy and adjustments of plot usage. Although the research and discussion on preservation of industrial heritage have been launched in the fields of theory and practice in China, many former industrial areas and buildings are still undergoing extreme threats and irreversible damages. Taking Iec Long Fireworks Factory which is the only well preserved survivor of industrial heritage in Macao as a case study, this paper presents its historic background, present challenges and future envisions of development. Based on group investigations and SWOT analysis, integrated strategies are proposed to preserve and revitalize the old factory ruins and their landscape settings. The conclusions show the significance to preserve and reuse industrial heritage opened for the urban renewal, which also could be a good contribution for sustainability of history and culture, environment, society and tourism.
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"In 2021/2022 academic year, there are 2,244 SEN students in Macau and its growth rate is 36% in ten years. However, at the present, there are 38 schools providing the related education to them. Admittedly, this is an unbalanced supply and demand. In fact, the teachers who work at inclusive education schools are bearing all responsibility to teach SEN students and their mental health is worth to attention. Moreover, there are 1,224 SEN students in primary (2021/2022 academic year), it accounting for 55% of all. That is, the numbers of their teachers are the most and they are representative. Therefore, exploring primary teachers’ burnout at inclusive education schools becomes the topic of this study, even more important, it is including to compare normal and resource teachers. This topic is rarer currently in Macau. On the one hand, emotional exhaustion, depersonalization and (reduced) personal accomplishment are dimensions of burnout (Maslach et al., 1996). These become the dependent variables of this study. According Ecological Systems Theory (Bronfenbrenner, 1979) and the factors of self-efficacy in inclusive education (Sharma et al., 2012), the following hypotheses are provided to guide this study: (1) normal teachers’ emotional exhaustion, depersonalization and reduced personal accomplishment are higher than those in resource teachers; (2) teachers’ attitudes into inclusive education, (3) teachers’ self-efficacy to use inclusive instruction (SEII), (4) teachers’ self-efficacy in collaboration (SEC) and (5) teachers’ self-efficacy in v managing behavior (SEMB) both are negatively related to emotional exhaustion, depersonalization and reduced personal accomplishment; (6) teachers’ stress of Covid19 is positively related to emotional exhaustion, depersonalization and reduced personal accomplishment. On the other hand, quantitative methodology, and snowball sampling are used in this research. At last, 132 responds are collected, including 100 normal teachers and 32 resource teachers. They are from 48 inclusive education schools in Macau. All data were analyzed by SPSS 25.0. The results of this study are followed: (1) teachers’ emotional exhaustion level is middle, their depersonalization and reduced personal accomplishment levels both are low; (2) resource teachers’ emotional exhaustion and depersonalization are higher than normal teachers; (3) teachers’ attitudes into inclusive education negatively related to depersonalization but positively related to reduced personal accomplishment; (4) in the factors of self-efficacy, only SEII is negatively related to reduced personal accomplishment; (5) teachers’ stress of Covid-19 is positively related to emotional exhaustion, depersonalization and reduced personal accomplishment."
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