Planos nutricionais com a utilização de aminoácidos e fitase para frangos de corte mantendo o conceito de proteína ideal nas dietas Nutritional plans with use of amino acids and phytase for broiler chickens maintaining the ideal protein profile in the diets

Objetivou-se neste estudo avaliar o desempenho e as características de carcaça de frangos de corte, recebendo rações com níveis reduzidos de PB, P disponível (Pd) e Ca, suplementadas com fitase e aminoácidos. As fases de crescimento avaliadas foram: fase 1, 1 - 21dias de idade e fase 2, 22 - 42 dias de idade. O delineamento experimental foi inteiramente casualizado, sendo os tratamentos constituídos de cincos planos nutricionais (PN), com seis repetições de 25 aves cada. Os planos nutricionais são: PN1 - ração basal (21,4% PB - fase 1) + ração basal (19,3% PB - fase 2); PN2 - ração a basal (fase 1) + ração com 18% PB (fase 2); PN3 - ração basal (fase 1) + ração com 16% PB (fase 2); PN4 - ração com 19% PB (fase 1) + ração com 16% PB (fase 2); e PN5 = ração com 17 % PB (fase 1) + ração com 16% PB (fase 2). Exceto para a ração basal, reduziu-se o nível de Pd para 0,34 e 0,30% e o de Ca para 0,80 e 0,70% nas fases 1 e 2, respectivamente; nestas rações foram adicionados 500 FTU de fitase/kg de ração. As aves alimentadas com PN2 e PN3 apresentaram desempenho semelhante ao daquelas que receberam PN1, enquanto o das aves que receberam os PN4 e PN5 permaneceu inalterado. Os rendimentos de carcaça e peito não foram influenciados pelos planos nutricionais. As aves que consumiram a ração basal nas duas fases de criação (PN1) apresentaram maior rendimento de coxa+sobre-coxa. Houve aumento da gordura abdominal quando as aves receberam os PN3, 4 e 5. É possível reduzir a PB da ração até 16% na fase 2, suplementada com fitase e aminoácidos, desde que a ração da primeira fase seja formulada com níveis nutricionais recomendados.<br>This study was carried out to evaluate the performance and characteristics of carcass of broiler chickens fed diets with reduced levels of CP, available P (aP) and Ca, supplemented with phytase and amino acids. The growth phases evaluated were: Phase1, 1 - 21 days old, phase 2, 22 - 42 days old. A completely randomized design was used, with the treatments constituted of five nutritional plans (NP), with six replicates of 25 birds each. The nutritional plans were: NP1 - basal ration (21.4% CP - phase 1) + basal ration (19.3% CP - phase 2); NP2 = basal ration (phase 1) + ration with 18% CP (phase 2); NP3 = basal ration (phase 1) + ration with 16% CP (phase 2); NP4 = ration with 19% CP (phase 1) + ration with 16% CP (phase 2) and NP5 = ration with 17% CP (phase 1) + ration with 16% CP (phase 2). Except for basal ration, it was reduced the level of aP for 0.34% and 0.30% in the phases 1 an 2, respectively, and Ca to 0.80 and 0.70% in the phases 1 and 2, respectively , and in theses diets were added 500 FTU of phytase/ kg of ration. The NP4 and NP5 affected the bird performance. The bird fed NP2 and NP3 showed performance similar to those which was fed NP1, while birds that were fed PN4 and PN5 remained unchanged. The carcass and breast yield were not influenced by the nutritional plans. The birds fed basal diets in the two rearing phases (NP1) showed higher yield of thigh + drumstick. There was increase of the abdominal fat when the birds were fed NP3, 4 and 5. In conclusion, is possible to reduce the protein of the ration up to 16% in the phase 2, supplemented with phytase and amino acids, since the ration of the phase 1 be formulated with recommended nutritional levels

A novel method for automated classification of epileptiform activity in the human electroencephalogram-based on independent component analysis.

Diagnosis of several neurological disorders is based on the detection of typical pathological patterns in the electroencephalogram (EEG). This is a time-consuming task requiring significant training and experience. Automatic detection of these EEG patterns would greatly assist in quantitative analysis and interpretation. We present a method, which allows automatic detection of epileptiform events and discrimination of them from eye blinks, and is based on features derived using a novel application of independent component analysis. The algorithm was trained and cross validated using seven EEGs with epileptiform activity. For epileptiform events with compensation for eyeblinks, the sensitivity was 65 +/- 22% at a specificity of 86 +/- 7% (mean +/- SD). With feature extraction by PCA or classification of raw data, specificity reduced to 76 and 74%, respectively, for the same sensitivity. On exactly the same data, the commercially available software Reveal had a maximum sensitivity of 30% and concurrent specificity of 77%. Our algorithm performed well at detecting epileptiform events in this preliminary test and offers a flexible tool that is intended to be generalized to the simultaneous classification of many waveforms in the EEG

Seizure Onset Detection in EEG Signals Based on Entropy from Generalized Gaussian PDF Modeling and Ensemble Bagging Classifier

This paper proposes a new algorithm for epileptic seizure onset detection in EEG signals. The algorithm relies on the measure of the entropy of observed data sequences. Precisely, the data is decomposed into different brain rhythms using wavelet multi-scale transformation. The resulting coefficients are represented using their generalized Gaussian distribution. The proposed algorithm estimates the parameters of the distribution and the associated entropy. Next, an ensemble bagging classifier is used to performs the seizure onset detection using the entropy of each brain rhythm, by discriminating between seizure and non-seizure. Preliminary experiments with 105 epileptic events suggest that the proposed methodology is a powerful tool for detecting seizures in epileptic signals in terms of classification accuracy, sensitivity and specificity