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da Silva Vilela M.,Federal Institute of Maranhao | de Andrade Ferreira M.,Federal University of Pernambuco | de Azevedo M.,Federal University of Pernambuco | Modesto E.C.,Federal University of Pernambuco | And 2 more authors.
Applied Animal Behaviour Science | Year: 2010

The aim of this study was to assess the effects of feeding strategy and processing of the spineless cactus on the ingestive behavior of lactating Holstein cows. Eight cows with a mean live weight of 453 ± 75.8 kg, production of 14 kg of milk per day and 20 weeks of lactation at the beginning of the experiment were distributed into two 4 × 4 Latin squares based on lactation order (primiparous and multiparous). The treatments were distributed in a factorial arrangement, with two forms of cactus processing knife-chopped (KC) and fodder machine (FM) and two different feeding strategies separate concentrate (SC) and total mixed ration (TMR). We visually assessed and recorded behavioral variables at 10-min intervals over 48 consecutive hours. The environment was monitored every hour from 6:00 to 18:00 h using dry-bulb and wet-bulb temperatures. There were no significant differences (P > 0.05) in the behavioral variables between the visual observations at 24 and 48 h. Ingestion time (276 min/day, P = 0.01) and idle time (612 min/day, P = 0.005) were less when the cactus was processed using the FM than when the cactus was KC, but rumination time (522 min/day, P = 0.005 and 32.4 min/kg dry matter, P = 0.02) and mastication time (798 min/day, P = 0.03) were greater. Less time was spent on ingestion (282 min/day, P = 0.05) and rumination (480 min/day, P = 0.001) when the cactus was supplied as a SC, than when the cactus was supplied as a TMR, but idle time was greater (672 min/day, P = 0.02) with this diet. Cactus processing in a fodder machine is recommended in order to maximize the DM intake and avoid alterations in milk composition. The TMR feeding strategy is recommended in order to reduce selectivity on the part of the cows, which results in an imbalance between the diet offered and that consumed. © 2010 Elsevier B.V. All rights reserved. Source

Cardenas Gomez A.O.,Federal University of Uberlandia | Hoffmann A.R.K.,Federal Institute of Maranhao | Bandarra Filho E.P.,Federal University of Uberlandia
International Journal of Heat and Mass Transfer | Year: 2015

This article presents an experimental evaluation of the thermal-hydraulic performance of carbon nanotube (CNT) nanoparticles dispersed in distilled water in single-phase flow in a horizontal tube. An experimental bench was constructed to evaluate the convective heat transfer coefficient during flow in the transition and turbulent regimes and determine the pressure drop in the flow. The tests were performed while maintaining constant input temperatures in the section of 10, 15, and 20°C, where the heat flux varied between 10 and 18 kW/m2 and the mass flow rate varied between 20 and 100 g/s. The nanofluids with the multi-walled carbon nanotubes (MWCNTs) in water were tested at volume concentrations that varied between 0.12% and 0.24% with distinct aspect ratios, length by diameter, of 100, 600, and 2400. The experimental heat transfer results were evaluated as a function of mass velocity, G, and Reynolds number, where differences in the behavior were observed. Regarding the pressure drop, the nanofluids exhibited pressure drops between 5% and 8.7% greater than that of the base fluid. Finally, a parameter was proposed to evaluate the obtained results, which relates the increase in heat transfer as a function of pumping power. © 2015 Elsevier Ltd.All rights reserved. Source

Feitosa R.M.,Federal University of Maranhao | Labidi S.,Federal University of Maranhao | Dos Santos A.L.S.,Federal Institute of Maranhao
2014 14th International Conference on Hybrid Intelligent Systems, HIS 2014 | Year: 2014

The research aims to create an application that uses techniques from Machine Learning to extract and collate data geolocated - collected a Social Network, aiming to promote the Social Recommendation users. Existing research in the field of social recommendation deficiencies remain regarding the effectiveness of the filtered data. This paper presents a study and implementation using Text Mining techniques as a proposal for resolution of problems found in social recommendation and more effective results. © 2014 IEEE. Source

Costa T.S.,Federal Institute of Maranhao | de Oliveira A.C.M.,Federal University of Maranhao
Soft Computing | Year: 2015

Clustering Search (*CS) has been proposed as a generic way of combining search metaheuristics with clustering to detect promising search areas before applying local search procedures. The clustering process may keep representative solutions associated with different search subspaces. In this paper, new approaches are proposed, based on *CS, as an Artificial Bee Colony-based one, which detects promising food sources alike *CS approaches. The other new *CS approach is based on Differential Evolution (DE) algorithm. The DE is just a CS component (the evolutionary algorithm), different from ABC-based approach, called Artificial Bee Clustering Search (ABCS). ABCS tries to find promising solutions using some concepts from CS. The proposed hybrid algorithms, performing a Hooke and Jeeves-based local, are compared to another hybrid approaches, exploring an elitist criteria to apply local search. The experiments show that the proposed ABCS and Differential Evolutionary Clustering Search (DECS) are competitive for the majority continuous optimization functions benckmarks selected in this paper. © 2014, Springer-Verlag Berlin Heidelberg. Source

Da Silva M.F.,Federal Institute of Bahia | De Area Leao Pereira E.J.,Federal Institute of Maranhao | De Castro A.P.N.,Computational Modeling Program SENAI CIMATEC | Garcia Vivas Miranda J.,Federal University of Bahia | Zebende G.F.,Computational Modeling Program SENAI CIMATEC
Physica A: Statistical Mechanics and its Applications | Year: 2015

The objective of this paper is to demonstrate the influence of the blue-chips companies in the stock market. In this, we apply the detrended cross-correlation coefficient ρDCCA at the São Paulo stock market (Ibovespa, Brazil). Initially we found that there is a positive cross-correlation between these companies and the index. Afterwards, we show that the cross-correlation coefficient value depends on the time scale and the specific company (blue-chips). Thus, this type of analysis lets to infer what is the most adherent company with Ibovespa. Also, in this paper we analyze, in the point of view of ρDCCA, the 2008 financial crisis (before/after). Altogether, the results show that there is more cross-correlation between Ibovespa index the blue-chips after the 2008 crisis. © 2015 Elsevier B.V. All rights reserved. Source

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