An Approach to Invariant-based Program Refactoring

Refactoring tools include checking of an object-oriented program for the fulfillment of preconditions, for ensuring correctness. However, program invariants â semantic information about classes and fields assumed valid during program execution â are not considered by this precondition checking. As a result, applicability of automated refactorings is constrained in these cases, as refactorings that would be applicable considering the invariants get rejected, usually requiring manual changes. In this paper, we describe initial work on the use of program invariants (declared as code annotations) to increase applicability of automated refactoring. We propose an approach that uses primitive program transformations that employ the invariant to make the program syntactically amenable to the desired refactoring, before applying the refactoring itself

Relating Voluntary Turnover with Job Characteristics, Satisfaction and Work Exhaustion - An Initial Study with Brazilian Developers

High rates of turnover among software developers remain, involving additional costs of hiring and training. Voluntary turnover may be due to workplace issues or personal career decisions, but it might as well relate to Job Characteristics, or even Job Satisfaction and Work Exhaustion. This paper reports on an initial study which quantitatively measured those constructs among 78 software developers working in Brazil who left their jobs voluntarily. For this, we adapted well-known survey instruments, namely the JDS from Hackman and Oldham's Job Characteristics Model, and Maslach et al.'s Burnout Measurement. In average, developers demonstrated low to moderate autonomy (3.75, on a 1-7 scale) and satisfaction (4.08), in addition to moderate exhaustion (4.2) before leaving their jobs, while experiencing high task significance (5.15). Also, testers reported significantly lower job satisfaction than programmers. These results allow us to raise interesting hypotheses to be addressed by future studies.Comment: 4 pages, no figures, 3 tables. Final version for ICSE CHASE 201

Object-oriented Programming Laws for Annotated Java Programs

Object-oriented programming laws have been proposed in the context of languages that are not combined with a behavioral interface specification language (BISL). The strong dependence between source-code and interface specifications may cause a number of difficulties when transforming programs. In this paper we introduce a set of programming laws for object-oriented languages like Java combined with the Java Modeling Language (JML). The set of laws deals with object-oriented features taking into account their specifications. Some laws deal only with features of the specification language. These laws constitute a set of small transformations for the development of more elaborate ones like refactorings

Coalescing disparate data sources for the geospatial prediction of mosquito abundance, using Brazil as a motivating case study

One of the barriers to performing geospatial surveillance of mosquito occupancy or infestation anywhere in the world is the paucity of primary entomologic survey data geolocated at a residential property level and matched to important risk factor information (e.g., anthropogenic, environmental, and climate) that enables the spatial risk prediction of mosquito occupancy or infestation. Such data are invaluable pieces of information for academics, policy makers, and public health program managers operating in low-resource settings in Africa, Latin America, and Southeast Asia, where mosquitoes are typically endemic. The reality is that such data remain elusive in these low-resource settings and, where available, high-quality data that include both individual and spatial characteristics to inform the geospatial description and risk patterning of infestation remain rare. There are many online sources of open-source spatial data that are reliable and can be used to address such data paucity in this context. Therefore, the aims of this article are threefold: (1) to highlight where these reliable open-source data can be acquired and how they can be used as risk factors for making spatial predictions for mosquito occupancy in general; (2) to use Brazil as a case study to demonstrate how these datasets can be combined to predict the presence of arboviruses through the use of ecological niche modeling using the maximum entropy algorithm; and (3) to discuss the benefits of using bespoke applications beyond these open-source online data sources, demonstrating for how they can be the new “gold-standard” approach for gathering primary entomologic survey data. The scope of this article was mainly limited to a Brazilian context because it builds on an existing partnership with academics and stakeholders from environmental surveillance agencies in the states of Pernambuco and Paraiba. The analysis presented in this article was also limited to a specific mosquito species, i.e., Aedes aegypti, due to its endemic status in Brazil

An Evaluation of the OpenWeatherMap API versus INMET Using Weather Data from Two Brazilian Cities: Recife and Campina Grande

Certain weather conditions are inadvertently related to increased population of various mosquitoes. In order to predict the burden of mosquito populations in the Global South, it is imperative to integrate weather-related risk factors into such predictive models. There are a lot of online open-source weather platforms that provide historical, current and future weather forecasts which can be utilised for general predictions, and these electronic sources serve as an alternate option for weather data when physical weather stations are inaccessible (or inactive). Before using data from such online source, it is important to assess the accuracy against some baseline measure. In this paper, we therefore evaluated the accuracy and suitability of weather forecasts of two parameters namely temperature and humidity from the OpenWeatherMap API (an online weather platform) and compared them with actual measurements collected from the Brazilian weather stations (INMET). The evaluation was focused on two Brazilian cites, namely, Recife and Campina Grande. The intention is to prepare an early warning model which will harness data from OpenWeatherMap API for mosquito prediction

Evaluation of the pharmacological activity of Pfaffia paniculata (Martius) Kuntze

O presente trabalho teve como objetivo investigar o efeito anti-inflamatório, antimicrobiano, antiprotozoário e possível ação sobre o sistema nervoso central (SNC) em ratos tratados com extrato hidroalcoólico de Pfaffia paniculata. Verificou-se atividade anti-inflamatória tanto in vivo, na dose de 100 mg/kg, como in vitro nas concentrações de 50 e 100 μg/mL. Porém, verificou-se efeito pró-inflamatório na dose de 200 mg/kg, pelo ensaio de pleurisia e de 200 μg/mL, pela quimiotaxia in vitro. Sugere-se potencial ação antimicrobiana frente a Staphylococcus aureus, nas concentrações de 250 e 500 mg/mL, com forma- ção de halo de inibição de 11 e 21 mm, respectivamente. Observou-se que o extrato de P. paniculata nas concentrações de 1, 10 e 50 μg/mL potencializou o crescimento de trofozoítos de Trichomonas vaginalis. Quanto aos ensaios sobre o SNC, verificou-se diminuição da ansiedade e aumento da atividade locomotora em animais tratados com doses de 125 e 250 mg/kg.Colegio de Farmacéuticos de la Provincia de Buenos Aire

Temporal and Spatiotemporal Arboviruses Forecasting by Machine Learning: A Systematic Review

Arboviruses are a group of diseases that are transmitted by an arthropod vector. Since they are part of the Neglected Tropical Diseases that pose several public health challenges for countries around the world. The arboviruses' dynamics are governed by a combination of climatic, environmental, and human mobility factors. Arboviruses prediction models can be a support tool for decision-making by public health agents. In this study, we propose a systematic literature review to identify arboviruses prediction models, as well as models for their transmitter vector dynamics. To carry out this review, we searched reputable scientific bases such as IEE Xplore, PubMed, Science Direct, Springer Link, and Scopus. We search for studies published between the years 2015 and 2020, using a search string. A total of 429 articles were returned, however, after filtering by exclusion and inclusion criteria, 139 were included. Through this systematic review, it was possible to identify the challenges present in the construction of arboviruses prediction models, as well as the existing gap in the construction of spatiotemporal models

The psychological science accelerator’s COVID-19 rapid-response dataset

In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data