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The purpose of this study is to describe the prevalence of a sedentary lifestyle (<150 min of physical exercise/week) and associated factors of this behavior in Brazil.

An observational study was conducted through an online questionnaire in August–September 2020 (5.5 months after the beginning of the pandemic in the country). Socioeconomic, lifestyle, anthropometric, dietary and perceived stress data were evaluated as possible related factors to a sedentary lifestyle through multiple logistic regression analysis.

A total of 1,347 individuals were evaluated (median of 31 years old, 80.1% women), of whom 76.7% were considered sedentary. Associated factors to a sedentary lifestyle were being overweight; a greater difference between current weight and prepandemic weight; female sex; lower percentage of home-cooked meals; greater increase in the frequency of consumption of alcoholic beverages; higher frequency of consumption of cereals, sausages and sweets during the pandemic; and higher score of perceived stress.

To the best of the authors’ knowledge, no studies have aimed to reveal the associated factors to a sedentary lifestyle during the COVID-19 pandemic in Brazil. Protective factors against a sedentary lifestyle were eating breakfast, being a student, living with parents, a higher frequency of fruit consumption, a higher rate of alcohol consumption and a higher cognitive restriction of food intake during the pandemic. Most of the study participants were sedentary, especially women. A sedentary lifestyle was associated with worse lifestyle/eating habits and stress. Such findings encourage an interdisciplinary approach because habits and lifestyle have numerous interferences.

This study aims to identify comfort food (CF) consumption and its associated factors during the pandemic period. The study also involves an online survey conducted five months after the quarantine started in Brazil.

Data on lifestyle, eating habits and anthropometric data were collected before and during the pandemic, and the differences in these habits were analyzed. Univariate and multivariate logistic regression models were performed to identify predictors of CF consumption by gender.

A total of 1,363 individuals were included in the sample, with a median age of 31 years old, of whom 80.3% were women. Since individuals were free to respond about the food consumed without predetermined categories, it was possible to carry out a faithful assessment of the occurrence of this behavior. At the same time, allowing the subjectivity and symbolism inherent to the concept of CF to be embraced. CF consumption was present for 54%, with “sweets” being the most mentioned group by both genders. The factors associated with CF consumption in women during the pandemic were increased snacking, increased bread, candies and alcoholic beverage intake, increased time spent at work, worsened sleep quality, reduced meals, perceived stress (PS), emotional eating (EE), age and increased frequency of meat intake. In men, the predictors for CF consumption were remote full-time work/study, PS, EE and early waking time. For both genders, CF consumption during the pandemic period was associated with PS and EE.

This study provides an important overview of the possible contributions of the pandemic on behaviors and food choices related to the consumption of CF in Brazilians. This information is valuable to support further studies to investigate and treat the impacts of the pandemic on lifestyle, eating habits and behavior, mental health and other factors in the postpandemic period.

Sarcasm is a linguistic expression that usually carries the opposite meaning of what is being said by words, thus making it difficult for machines to discover the actual meaning. It is mainly distinguished by the inflection with which it is spoken, with an undercurrent of irony, and is largely dependent on context, which makes it a difficult task for computational analysis. Moreover, sarcasm expresses negative sentiments using positive words, allowing it to easily confuse sentiment analysis models. This paper aims to demonstrate the task of sarcasm detection using the approach of machine and deep learning.

For the purpose of sarcasm detection, machine and deep learning models were used on a data set consisting of 1.3 million social media comments, including both sarcastic and non-sarcastic comments. The data set was pre-processed using natural language processing methods, and additional features were extracted and analysed. Several machine learning models, including logistic regression, ridge regression, linear support vector and support vector machines, along with two deep learning models based on bidirectional long short-term memory and one bidirectional encoder representations from transformers (BERT)-based model, were implemented, evaluated and compared.

The performance of machine and deep learning models was compared in the task of sarcasm detection, and possible ways of improvement were discussed. Deep learning models showed more promise, performance-wise, for this type of task. Specifically, a state-of-the-art model in natural language processing, namely, BERT-based model, outperformed other machine and deep learning models.

This study compared the performance of the various machine and deep learning models in the task of sarcasm detection using the data set of 1.3 million comments from social media.

Aim of the present monograph is the economic analysis of the role of MNEs regarding globalisation and digital economy and in parallel there is a reference and examination of some legal aspects concerning MNEs, cyberspace and e‐commerce as the means of expression of the digital economy. The whole effort of the author is focused on the examination of various aspects of MNEs and their impact upon globalisation and vice versa and how and if we are moving towards a global digital economy.

The raised competitiveness among technology companies, especially for being able to work with markets physically distant from their final consumer, makes it important to know the employee’s perception about the built environment since the physical workspaces influence productivity. This paper aims to analyze the attributes and dimensions of the built environment of a development software company that most impact the employee’s satisfaction through their perception. It allows the company to identify the strengths and weaknesses of the built environment, enhancing the employee’s satisfaction, productivity and, consequently, the company revenues.

This research applied a survey by the drop off method and analyzed data through confirmatory factor analysis and multiple linear regression. Therefore, these methods explain how the attributes behave in each theoretical dimension and evaluate the relation between the dependent and independent dimensions.

The theoretical result of this research concerns the employee’s satisfaction with the built environment of a software development company. Overall, employee satisfaction is related to the dimensions of functionality, appearance and personal relationships, not being significant aspects of configuration. On the other hand, the employee’s overall satisfaction with the built environment is related to the functional dimension.

This research limitation is related to the size of the sample, which is a pre-determined and fixed population: all the company’s employees.

Perceived quality applied to a work environment of a software development company.

This study aims to investigate the impact of traditional teaching and active learning methods in lean management (LM) on the development of both soft and hard skills.

Through a longitudinal study, team members from two different organisations (the administrative sector of a public higher education institution and a public teaching hospital), each adopting different teaching methods to support their LM trainings, were systematically examined at four moments during an 18-month period. How teaching methods impacted team members’ development and knowledge was then assessed using multivariate data analysis techniques.

Results indicated that LM trainings can provide significant impacts when a combination of traditional teaching methods and active learning is adopted. Traditional teaching methods can be a good choice for learning hard skills depending on resources’ availability. However, it is recommended to include active learning methods to assist in the comprehension of more complex and abstract LM concepts (soft skills).

Although there exists a large number of publications on the relationship between LM implementation and teaching methods, the number of studies that consider the development of both hard and soft skills is rather limited. This study complements the existing literature on LM by identifying which teaching methods can support the development of hard skills and which the development of soft skills. Such identification facilitates the work of both scholars wishing either to begin or to dig deeper into this sphere and practitioners pursuing the best outcomes from LM.

What is it about academia anyway? We profess to hate it, spend endless amounts of time complaining about it, and yet we in academia will do practically anything to stay. The pay may be low, job security elusive, and in the end, it's not the glamorous work we envisioned it would be. Yet, it still holds fascination and interest for us. This is an article about American academic fiction. By academic fiction, I mean novels whosemain characters are professors, college students, and those individuals associated with academia. These works reveal many truths about the higher education experience not readily available elsewhere. We learn about ourselves and the university community in which we work.