Search results

This study aims to estimate the overall SARS-CoV-2 seroprevalence and evaluate the accuracy of an antibody rapid test compared to a reference serological assay during a COVID-19 outbreak in a prison complex housing over 13,000 prisoners in Brasília.

The authors obtained a randomized, stratified representative sample of each prison unit and conducted a repeated serosurvey among prisoners between June and July 2020, using a lateral-flow immunochromatographic assay (LFIA). Samples were also retested using a chemiluminescence enzyme immunoassay (CLIA) to compare SARS-CoV-2 seroprevalence and 21-days incidence, as well as to estimate the overall infection fatality rate (IFR) and determine the diagnostic accuracy of the LFIA test.

This study identified 485 eligible individuals and enrolled 460 participants. Baseline and 21-days follow-up seroprevalence were estimated at 52.0% (95% CI 44.9–59.0) and 56.7% (95% CI 48.2–65.3) with LFIA; and 80.7% (95% CI 74.1–87.3) and 81.1% (95% CI 74.4–87.8) with CLIA, with an overall IFR of 0.02%. There were 78.2% (95% CI 66.7–89.7) symptomatic individuals among the positive cases. Sensitivity and specificity of LFIA were estimated at 43.4% and 83.3% for IgM; 46.5% and 91.5% for IgG; and 59.1% and 77.3% for combined tests.

The authors found high seroprevalence of anti-SARS-CoV-2 antibodies within the prison complex. The occurrence of asymptomatic infection highlights the importance of periodic mass testing in addition to case-finding of symptomatic individuals; however, the field performance of LFIA tests should be validated. This study recommends that vaccination strategies consider the inclusion of prisoners and prison staff in priority groups.

The purpose of this study is to show the procedure, application and main features of the hybrid numerical-analytical approach known as generalized integral transform technique by using it to study magnetohydrodynamic flow of electrically conductive Newtonian fluids inside flat parallel-plate channels subjected to a uniform and constant external magnetic field.

The mathematical formulation of the analyzed problem is given in terms of a streamfunction, obtained from the Navier–Stokes and energy equations, by considering steady state laminar and incompressible flow and constant physical properties.

Convergence analyses are performed and presented to illustrate the consistency of the integral transformation technique. The results for the velocity and temperature fields are generated and compared with those in the literature as a function of the main governing parameters.

A detailed analysis of the parametric sensibility of the main dimensionless parameters, such as the Reynolds number, Hartmann number, Eckert number, Prandtl number and electrical parameter, for some typical situations is performed.

This study aims to assess the influence of partial and simultaneous substitution of fat and sodium by hydrolyzed collagen and mix of herbs (MH) in chicken hamburgers, on the physical properties and proximal composition.

Five formulations were developed: (1) HCON–without adding collagen and MH; (2) C25M25–adding 25% of collagen and 25% of MH; (3) C25M50–adding 25% of collagen and 50% of MH; (4) C50M25–adding 50% of collagen and 25% of MH and (5) C50M50–adding 50% of collagen and 50% of MH. Chicken hamburgers were analyzed by proximal composition, sodium content, collagen and color analysis. The influence of treatments on texture profile, cooking performance and lipid oxidation of chicken hamburger was also investigated.

There was reduction in lipid and sodium for modified formulations compared with the HCON. There was great influence for some parameters, such as luminosity, cooking performance and texture profile. The formulation C50M50 showed the best cooking performance when compared to the others.

The formulation adding 50% of collagen and 50% of MH showed the highest yield and water retention (WR), with the least reduction in diameter and shrinkage, as well as presenting the best indexes of the texture profile and the lowest oxidation index, being recommended as the best combination of fat and sodium replacement.

Since 2012, the Brazilian Stock Exchange has recommended that listed companies inform them if they have conducted voluntary disclosure. The purpose of this study is to describe the voluntary disclosure by companies listed in the B3 in Brazil and to analyze which characteristics of the board of directors influence this disclosure.

The study involves quantitative research using a sample of 285 companies and 575 reports from 2011 to 2014. A fixed-effects regression model with panel data was used for the analysis.

The results were statistically significant for gender and duality variables, which confirms the theory that the presence of women as members of the board positively influences voluntary disclosure and that chief executive officer and chairman of the board positions have a negative effect. The age and independence of the board variables did not present statistical significance.

As a theoretical contribution, the authors aim to complement sustainability, finance and strategy research by using agency theory and measuring the variable of voluntary disclosure and the board, which is rarely studied in this context.

As social and empirical contributions, a better understanding of this theme in the context of emerging countries, which is the peculiarities of Brazil with little information transparency and well-known corruption scandals, is likely to aid investors. Increased access to company information can help investors better select their investment portfolios and assist in the choice of their board representatives in companies in which they have participation and voting rights.

The fact that Brazil is an emerging country, where the lack of transparency of information and corruption in these environments stand out the importance of studying the subject of voluntary disclosure in this context. All data were collected manually specifically for this research.

Rainfall simulators are used on experimental hydrology, in areas such as, e.g., urban drainage and soil erosion, with important timesaving when compared to real scale hydrological monitoring. The purpose of this paper is to contribute to increase the quality of rainfall simulation, namely, for its use with scaled physical models.

Two pressurized rainfall simulators are considered. M1 uses three HH-W 1/4 FullJet nozzles under an operating pressure of 166.76 kPa and was tested over a 4.00 m length by 2.00 m width V-shaped surface. M2 was prepared to produce artificial rainfall over an area of 10.00 m length by 10.00 m width. The spatial distribution of rainfall produced from a single nozzle was characterized in order to theoretically find the best positioning for nozzles to cover the full 100 m² area with the best possible rainfall uniformity.

Experiments with M1 led to an average rainfall intensity of 76.77-82.25 mm h⁻¹ with a 24.88 per cent variation coefficient and a Christiansen Uniformity Coefficient (CUC) of 78.86 per cent. The best result with M2 was an average rainfall intensity of 75.12-76.83 mm h⁻¹ with a 21.23 per cent variation coefficient and a CUC of 83.05 per cent.

This study contributes to increase the quality of artificial rainfall produced by pressurized rainfall simulators.

M2 is the largest rainfall simulator known by the authors worldwide. Its use on rainfall-runoff studies (e.g. urban areas, erosion, pollutant transport) will allow for a better understanding of complex surface hydrology processes.

The set of services provided by the mobile phone platform, is becoming increasingly complex and requiring more computing power, hence higher energy consumption, and compromising the autonomy of these devices. The purpose of this paper is to identify scenarios where methods could be applied to reduce such consumption and extend the mobile autonomy.

This mobile evolution has given rise to a lot of energy saving research activities, which mainly focus on the hardware side of computational systems. However, it is tempting to suppose that only hardware dissipates power, not software. This paper characterizes several hardware and software scenarios, which could be explored to develop energy‐efficient mobile techniques.

From this analysis, the authors argue that the development of applications that consider energy saving as one of their requirements, can result in a significant final energy saving because solutions will be part of their own software and they do not depend on external resources to obtain a lower consumption.

This paper provides a broad analysis about the different research directions in energy consumption optimization and stresses the important contributions that the software engineering area could offer to this subject.

This work aims to discuss the motivators for the consumption of pre-loved luxury items and verify how these motivators interact, leading consumers to engage in behaviors that blend the characteristics of different motivators: treasure hunting, bargain hunting and individuality seeking.

This is an exploratory dyadic qualitative research conducted using semi-structured in-depth interviews involving luxury brand store managers and loyal clients for pre-loved luxury products in Monaco.

Throughout the analysis, the authors found three types of behavior that incorporate different parts of motivators that have been considered as specific motivators for pre-loved luxury consumption: bargain hunting, an intersection of recreational and economic motivations, treasure hunting, a blend of nostalgic and recreational motivations, and individuality, a mix of need for uniqueness and fashion involvement motivation.

Identifying three types of behavior for the pre-loved luxury consumer helps practitioners craft marketing strategies for their brands and products in the pre-loved luxury market.

The authors propose a theoretical framework that identifies intersections between the motivators for pre-loved luxury consumption, potentially identifying new types of consumer behavior in this market.

To the best of the authors' knowledge, this is the first work to discuss these three types of behavior in the pre-loved luxury market. The authors propose a theoretical framework that identifies intersections between the motivators for pre-loved luxury consumption, potentially identifying new types of consumer behavior in this market.

Lean Six Sigma (LSS) is a continuous improvement methodology used to increase the efficiency and effectiveness of processes. Although there are several articles published, only two have analyzed the literature from a bibliometrics perspective. The purpose of this paper is to analyze the LSS literature by bibliometrics, identifying its state of the art, scientific gaps and research trends.

Articles published up to 2016 in the database Scopus were investigated to identify the most significant articles, authors, journals, institutions and countries based on citation counting as well as the most frequent keywords and subject areas on LSS. Articles published in 2014, 2015 and 2016 were analyzed to point out scientific gaps and to identify eight main research trends on LSS.

The research trends are: “LSS implementation”, “Healthcare”, “LSS tools”, “Human factors”, “Expansion of results”, “SME”, “LSS combined with other methodologies” and “Education”. The research outcomes also point out the most significant articles, authors, journals, institutions and countries in LSS literature.

This research contributes to develop the state of the art of LSS and helps professionals as well as researchers to identify which issues new studies should address.

The performance of the literature is measured based on the number of citations and not on the number of published papers, and the bibliometric analysis covers the highest number of articles so far (319 articles). Besides, the identification of the main research trends on LSS is exclusively based on the most recent studies.

The purpose of this paper is to explain how internal and external sources of knowledge influence the innovation performance (IP) in Italian manufacturing firms and how different these relationships are for low-technology (LT) and high-technology (HT) firms.

The study proposed a model relating external knowledge, internal knowledge and IP that was tested using Bayesian structural equation modeling with a sample of Italian manufacturing firms of Community Innovation Survey 2010. It was run separately for high-tech firms (including HT and medium-HT aggregations of manufacturing industries of NACE Rev. 2) and low-tech firms (including LT and medium-LT aggregations).

The results showed a difference between high-tech and low-tech manufacturing firms in Italy. The investments to leverage internal knowledge sources are important for high-techs and not significant for low-techs. On the other hand, the level of external KS improves significantly the IP of low-techs and has a negative effect for high-techs. The level of absorptive capacity is central to improve the positive effect of the external knowledge on the IP for all firms, but it is still underdeveloped.

The effects of 2008 economic crisis hit the Italian manufacturing industry specifically hard and are still felt. Innovation is a solution for firms’ growth and Italy is considered a below-average innovator country in Europe. The study could identify important gaps in Italian manufacturing firms that hinder their innovative performance improvement.