São Paulo Federal Institute of Education, Science and Technology

About: São Paulo Federal Institute of Education, Science and Technology is a education organization based out in São Paulo, Brazil. It is known for research contribution in the topics: Context (language use) & Computer science. The organization has 1707 authors who have published 2374 publications receiving 11333 citations.

Fishers and groupers ( Epinephelus marginatus and E. morio) in the coast of Brazil: integrating information for conservation

Abstract: Groupers are a vulnerable but economically important group of fish, especially for small-scale fisheries. We investigated catches and local ecological knowledge (LEK) of diet, habitat, and past fishing experiences. Landings, prices, interviews, and restaurants demand for two species, Epinephelus marginatus (dusky grouper) and Epinephelus morio (red grouper), were registered. We visited 74 markets and 79 sites on the coast of Brazil in 2017–2018, and we interviewed 71 fishers: Bahia (NE), Rio de Janeiro and Sao Paulo (SE), and Santa Catarina (S). The landings sampled of dusky grouper (2016–2017) in Rio de Janeiro were: n = 222, size 38–109 cm, weight 1–24 kg, average 3.84 kg; in Sao Paulo, Sao Sebastiao were: n = 47, size 39–106 cm, weight 2–8 kg, average of 2.77 kg; and at Santos: n = 80, 26–120 cm, weight 0.36–15 kg, average 2.72 kg. Red grouper was observed in markets in the northeastern Brazil. We did not observe Epinephelus marginatus from Bahia northward; a maximum size of 200 cm was reported south of the Bahia, besides Rio de Janeiro and Sao Paulo coasts, 20 years ago (or longer) by 12 fishers. Local knowledge of fishers was important for grouper data of habitat and diet; the reproduction period was identified by fishers as September to March. Groupers can be considered as a cultural and ecological keystone species. We suggest protective measures: 1) fishing zoning, 2) islands (MPAs) with the surveillance of fishers, 3) late Spring and early Summer as key periods for management (grouper reproduction), 4) studies on grouper larvae, 5) mapping of fishing spots, 6) studies on local knowledge. Collaboration with small-scale fishers and local knowledge could contribute to low-conflict management measures. In that regard, integrative models of management from Latin America, by using local knowledge and citizen science, could produce successful grouper management for Brazilian data-poor fisheries, a contrasting reality to the Mediterranean areas. Finally, the distribution of E. marginatus in Brazil leave us with questions: a) Have dusky groupers disappeared from Bahia because of a decline in the population? b) Was it uncommon in Northeast Brazil? c) Did changes in water temperatures forced a movement southward?

Primary Dendrite ARM Spacing Effects upon Mechanical Properties of an AL–3Wt%CU–1Wt%LI Alloy

Abstract: The imposition of a wide range of operational conditions in foundry and castings processes generates, as a direct consequence, a diversity of solidification structures. It is well known that mechanical properties depend on solidification structures. The literature presents relationships between yield strength and grain size, such as the Hall-Petch’s equation, or ultimate tensile strength and dendrite arm spacing. In this work, an Al–3wt%Cu–1wt%Li alloy was solidified under upward unsteady state heat flow conditions. Heat was directionally extracted only through a water-cooled bottom made of steel (SAE 1020). The aim of the present study is to obtain correlations between the as-cast microstructure, solidification thermal variables and mechanical properties of an Al–3wt%Cu–1wt%Li alloy casting. The results include tip growth rate (V L ), cooling rate (\( \dot{T} \)), primary dendrite arm spacing (λ 1), ultimate tensile strength (σ UTS) and yield strength (σ y) as a function of solidification conditions imposed by the metal/mold system. It is found that the primary dendrite arm spacing decreases with the increase in tip growth rate and cooling rate. In both cases (σUTS and σy = 0.2 %e), the finer dendritic arrangement presents superior mechanical properties.

Connoisseurship Consumption Community and Its Dynamics

Abstract: Purpose – What is the dynamics of the connoisseurship consumption community? What are the forces that drive this serious leisure consumption community? Design/methodology/approach – Adopting a naturalistic inquiry approach, we immersed ourselves in the field, visiting and observing consumers and professionals in independent coffee shops in North America: Toronto, Montreal, Seattle, and New York from August 2013 to July 2014. Findings – The research describes the connoisseurship consumption community and explains its forces, which are education, emulation and tensions between the members of the community. Originality/value – Our findings explain the amateur consumer’s behavior and the relationship of these amateurs with professionals and with the public during their consumption practices. We help to advance the study of heterogeneous consumption communities by revealing the tensions between the members of the community and the production of subcultural and social capital. Our research contributes to the consumer culture field by increasing knowledge of this social consumption phenomenon.

Hand Resting Tremor Assessment of Healthy and Patients With Parkinson's Disease: An Exploratory Machine Learning Study.

Abstract: The aim of this study is comparing the accuracies of machine learning algorithms to classify data concerning healthy subjects and patients with Parkinson's Disease (PD), toward different time window lengths and a number of features. Thirty-two healthy subjects and eighteen patients with PD took part on this study. The study obtained inertial recordings by using an accelerometer and a gyroscope assessing both hands of the subjects during hand resting state. We extracted time and temporal frequency domain features to feed seven machine learning algorithms: k-nearest-neighbors (kNN); logistic regression; support vector classifier (SVC); linear discriminant analysis; random forest; decision tree; and gaussian Naive Bayes. The accuracy of the classifiers was compared using different numbers of extracted features (i.e., 272, 190, 136, 82, and 27) from different time window lengths (i.e., 1, 5, 10, and 15 s). The inertial recordings were characterized by oscillatory waveforms that, especially in patients with PD, peaked in a frequency range between 3 and 8 Hz. Outcomes showed that the most important features were the mean frequency, linear prediction coefficients, power ratio, power density skew, and kurtosis. We observed that accuracies calculated in the testing phase were higher than in the training phase. Comparing the testing accuracies, we found significant interactions among time window length and the type of classifier (p < 0.05). The study found significant effects on estimated accuracies, according to their type of algorithm, time window length, and their interaction. kNN presented the highest accuracy, while SVC showed the worst results. kNN feeding by features extracted from 1 and 5 s were the combination with more frequently highest accuracies. Classification using few features led to similar decision of the algorithms. Moreover, performance increased significantly according to the number of features used, reaching a plateau around 136. Finally, the results of this study suggested that kNN was the best algorithm to classify hand resting tremor in patients with PD.