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However, leaching from monolithic mortar samples complied with the regulatory limits, while Cr leaching exceeded the regulatory limits for all crushed mortar samples when using NaCl or Na2SO4. Both NaCl and Na2SO4 generally increased the heavy metal leaching yield from fly ash and mortar compared to leaching with acidified H2O. The results of the study suggest that environmental conditions should be taken into account when assessing leaching from cement-based materials with MSWI fly ash.The new Coronavirus, responsible for the COVID-19 disease, is the most discussed topic in the current days, and the forecast numbers of new cases and deaths are the most important source of data in governmental decision-making. The present work presents a prediction model with two different approaches concerning the input data, by using Artificial Neural Networks (ANN). The use of a substantial mitigation procedure adopted (mandatory use of masks) was experimented as an input to the network, in order to evaluate the improvement in the results. The ANN forecasting model was demonstrated to predict with higher accuracy within the next twenty days using the information about the mandatory use of face masks. The final results showed that the twenty days ahead forecasting was made with an error of 24,7% and 1,6% for the number of cumulative cases of infection and deaths for Brazil, and 37,9% and 33,8% for Portuguese time series, respectively.The global COVID-19 pandemic has been a part of our lives for the second year in a row and it has affected the activities of all economic entities across individual fields and industries. This article deals with research into the impact of the COVID-19 pandemic on construction companies in the Czech Republic. The research presented in this paper consists of several consecutive steps designing a research plan, performing data collection and analysis and compiling research results. Qualitative approaches to data collection and evaluation, especially in-depth interviews and the coding method, were used for contextual understanding and comprehension of the situation in the companies under research. Open questions (topics) related to the respondents' experience, perceptions and opinions were created as a part of the preparation process. selleckchem The aim was to obtain reliable and relevant answers to the questions asked. The research, which lasted for 5 months, involved 16 medium-scale and large companies from the Czech Republic. The aim of the research described in this article was to find out about the development of construction companies in the first half of 2021 and to specify their results in selected areas of activity.Extracting information and discovering patterns from a massive dataset is a hard task. In an epidemic scenario, this data has to be integrated providing organization, agility, transparency and, above all, it has to be free of any type of censorship or bias. The aim of this paper is to analyze how coronavirus contamination has evolved in Brazil applying unsupervised analysis algorithms to extract information and find characteristics between them. To achieve this goal we describe an implementation that uses data about Covid-19 spread in Brazilian states (26 states and the federal district), applying a Time Series Clustering technique based on a K-Means variation, using Dynamic Time Warping as a similarity metric. We used data reported by the Ministry of Health in Brazil, referring to deaths per 100k inhabitants, during 452 days from the first reported death in each state. Two analyzes were performed, one considering 3 clusters and the other with 6 clusters. Through these analysis, 3 patterns of responses to the pandemic can be observed, ranging from one of greater to lesser control of the pandemic, although in recent months all clusters showed a highly increase in the number of deaths. The identification of these patterns is important to highlight possible actions and events, as well as other characteristics that determine the correct or incorrect public decision-making in combating the Covid-19 pandemic.In strengthening eHealth in the Philippines to support the universal health care (UHC) law, the scaling up and full adoption of electronic medical record (EMR) systems was strategically scheduled and supposedly completed in 2020. The Covid-19 pandemic, however, delayed these strengthening efforts. We wanted to assess the status of EMR adoption in primary clinics of rural health units (RHUs) and understand the frequency of use, particularly during the pandemic. Through analyses of EMR usage logs from selected RHUs in 2020, we estimated frequency of EMR usage based on duration of use and tested if this was influenced by the performing RHU and pandemic event. We also determined the most frequent EMR activities through process maps and tested if there were differences in the conduct of these activities before and during the pandemic. Results showed that EMR use during work hours was significantly dependent on the performing RHU (p less then 0.001). High-performing RHUs used EMRs more than 3 hours/day while low-performing RHUs used the systems for less. The pandemic either significantly decreased or increased EMR use during work hours by around 5 hours/day in some RHUs (p less then 0.01). Process maps revealed that there were additional activities performed by RHUs during the pandemic. Except for Update Patient Profile and Add Patient EMR features, significant differences (p less then 0.01) were observed in accessing frequently used features before and during the pandemic. The results suggest some uneven level of utilization of EMRs at the primary care level which can impact readiness to support full implementation of the UHC law. The study shows the potential of using a more granular approach in studying adoption to help improve the quality of EMR use and contribute to improving health service delivery and financing.The COVID-19 pandemic has brought unprecedented challenges to public health and supply chain systems around the globe. Local farmers businesses were impacted by the lockdowns and they still face difficulties in commercializing their production while requests for social, economic and food support pile up at municipalities and non-governmental organisations (NGOs). Meanwhile, working from home, constraints to workout, business and social life, are impacting citizens' work-life balance, eating habits and impacting populations' physical and mental health globally. EatLOCAL proposes to address this issue by providing a service that is supported in an innovative digital platform that strengthens connections between suppliers, consumers, municipalities and NGOs working on food privation issues. Besides maximizing the opportunities for business to local farmers, this platform also creates a facilitated channel that promotes de access to fresh food by citizens and minimizes the social impact of the pandemic in most vulnerable groups.Brazil is a large developing country that requires attention to regionalized behaviors regarding the dissemination of COVID-19. To deal with this complexity, the COVID-19 Brazil observatory was developed. The Portal aims to monitor and analyze data from different sources. Therefore, with a detailed audit, we centralized this information on the evolution of the disease, allowing for territorial and temporal monitoring. The daily publication of numbers about COVID-19 allowed anyone to follow the current scenario in several Brazilian cities. With about 1,7 million accesses, the Portal offers clarity and an easy understanding of the pandemic data in the country.Instagram (IG) has been used as a health promotion tool by national and international sanitary authorities to tackle COVID-19. The profile of the World Health Organization (WHO) on IG contributed to spread and update information on the new coronavirus prevention This study focus attention on a non-pharmaceutical control measure (face mask in the community) and discusses the adaptation of health authorities from Portugal and Brazil to WHO guidelines on this topic, and how they passed them to citizens. A content analysis of posts from WHO, Portuguese National Health Service (NHS), and the Brazilian Ministry of Health (MH) profiles on IG was carried out, in the first 100 days of the pandemic. The sample is composed of 65 posts - WHO (12), NHS (36) and, MH (17). NHS highlights masks in 8,8% of posts and MH in 3,3%. WHO guidelines followed scientific evidence and prioritized the surgical masks, while NHS and MH adapted the guidelines to regional scenarios (community transmission and difficulty to social distancing) and produced information on non-surgical masks. NHS recommends the use of certified non-surgical masks. MH diverged from WHO guidelines and advised cloth masks. NHS has adopted the preventive approach and the use of celebrities to stress the importance of following its guidelines. MH adopted an institutional approach to encourage adherence to the instructions. Both profiles offered incomplete content on the production, use, disposal, and maintenance of masks.The paper aims to present a graph based recommender system for managing the Covid-19 crisis by considering patient and medical staff data. Working with limited number of medical staff, require optimization when creating the appropriate medical staff to assist patient. Patient medical files usually contain more information about the patient diseases and symptoms. In this paper the recommender system at first analyses the patient medical files to find and decide which profile of medical staff could assist efficiency this patient in a crisis situation. Second the recommender system by taking into account the availability of the medical staff will try to propose others doctors with the same profile and the nearest competencies.The global COVID-19 pandemic and the need for organisations to provide digital support for work-from-anywhere has put collaboration software into the centre of attention for IT managers. In this paper we examine (self-managed) workspaces in (integrated) Enterprise Collaboration Systems (ECS) that provide the environment for asynchronous communication and exchange of information. Our aim is to better understand how employees use the ECS to support their work. Based on a structured literature review and an in-depth case study of an ECS user company we developed a generic typology of workspaces containing three main categories (community, team and non-work-related) and 5 different types of workspaces. The types are characterised by their purpose, characteristics and possible metrics for their identification. The findings contribute to our understanding of collaborative user activity in enterprise collaboration environments and provide the basis for Social Collaboration Analytics.The global pandemic triggered by the new COVID-19 led to severe limitations in daily life, both private and professional. Almost all companies have been affected in one way or another. The COVID-19 crisis imposed new challenges for enterprises. As a result, many companies have been forced to rethink how to align many of their processes and practices with the new COVID-19 context, and fulfill their mission while maintaining a safe and secure management business operating environment for both employees and customers. This paper aims to bring empirical evidence, through a questionnaire survey, of the positive influence of using Lean Management tools and Industry 4.0 technologies on five organizational dimensions (strategy, leadership, culture, operations and products, and technology). Data from 98 Algerian and French companies of different sizes and representing various activity sectors was collected. Respondents were asked to answer 5 organizational dimensions (strategy, leadership, culture, operations and products, and technology) in the context COVID-19 crisis.