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1.
Rev. bras. med. esporte ; 27(spe2): 83-86, Apr.-June 2021. tab, graf
Article in English | LILACS | ID: biblio-1280091

ABSTRACT

ABSTRACT Athletes' psychological control ability directly affects competitions. Therefore, it is necessary to supervise the athletes' game psychology. Athletes' game state supervision model is constructed through the facial information extraction algorithm. The homography matrix and the calculation method are introduced. Then, two methods are introduced to solve the rotation matrix from the homography matrix. After the rotation matrix is solved, the method of obtaining the facial rotation angle from the rotation matrix is introduced. The two methods are compared in the simulation data, and the advantages and disadvantages of each algorithm are analyzed to determine the method used in this paper. The experimental results show that the model prediction accuracy reaches 70%, which can effectively supervise the psychological state of athletes. This research study is of great significance to improve the performance of athletes in competitions and improve the application of back propagation (BP) neural network algorithm.


RESUMO A capacidade de controle psicológico de atletas afeta diretamente as competições. Portanto, é muito necessário supervisionar a psicologia de jogo desses indivíduos. O modelo de supervisão do estado de jogo dos atletas é construído através do algoritmo de extração de informações faciais. A matriz de homografia e o método de cálculo são introduzido. Em seguida, são introduzidos dois métodos para resolver a matriz de rotação a partir da matriz de homografia. Após a resolução da matriz de rotação, introduz-se o método de obtenção do ângulo de rotação facial a partir dessa matriz. Os dois métodos são comparados nos dados da simulação, e as vantagens e desvantagens de cada algoritmo são analisadas para determinar o método utilizado neste estudo. Os resultados experimentais mostram que a precisão da previsão do modelo atinge 70%, sendo possível efetivamente supervisionar o estado psicológico dos atletas. O presente estudo é de grande importância para melhorar o desempenho dos atletas em competições e melhorar a aplicação do algoritmo de rede neural backpropagation (BP).


RESUMEN La capacidad de control psicológico de atletas afecta directamente las competencias. Por lo tanto, es muy necesario supervisar la psicología de juego de esos individuos. El modelo de supervisión del estado de juego de los atletas es construido por medio del algoritmo de extracción de informaciones faciales. La matriz de homografía y el método de cálculo son introducidos. Enseguida, son introducidos dos métodos para resolver la matriz de rotación a partir de la matriz de homografía. Después de la resolución de la matriz de rotación, se introduce el método de obtención del ángulo de rotación facial a partir de esa matriz. Los dos métodos son comparados en los datos de la simulación, y las ventajas y desventajas de cada algoritmo son analizadas para determinar el método utilizado en este estudio. Los resultados experimentales muestran que la precisión de la previsión del modelo alcanza 70%, siendo posible efectivamente supervisar el estado psicológico de los atletas. El presente estudio es de gran importancia para mejorar el desempeño de los atletas en competencias y mejorar la aplicación del algoritmo de red neuronal backpropagation (BP).


Subject(s)
Humans , Neural Networks, Computer , Athletic Performance/psychology , Athletes/psychology , Algorithms
2.
Indian J Biochem Biophys ; 2013 Jun; 50(3): 196-201
Article in English | IMSEAR | ID: sea-147302

ABSTRACT

A 15 kDa ribonuclease (RNase) was purified from dried fruiting bodies of the wild edible mushroom Armillaria luteo-virens. The simple 4-step purification protocol involved ion-exchange chromatography on DEAE-cellulose, affinity chromatography on Affi-gel blue gel, ion-exchange chromatography on SP-Sepharose and a final gel filtration by FPLC on Superdex-75. The RNase was unadsorbed on Affi-gel blue gel, but adsorbed on DEAE-cellulose and SP-Sepharose. The N-terminal amino acid sequence of purified RNase was AGVQYKLTILLV, which showed low sequence homology to those of previously reported RNases. The optimal pH and temperature of the enzyme were very close to 4.0 and 70°C, respectively. The enzyme showed considerably high ribonucleolytic activity and broad specificity towards polyhomoribonucleotides, with a specificity of poly(U)>poly(C)>poly (G)>poly(A). The ribonucleolytic activities towards poly(U), poly(C), poly(G) and poly(A) were 279.5, 184.1, 69.9 and 52.3 U/mg, respectively.


Subject(s)
Agaricales/enzymology , Animals , Enzyme Activation , Enzyme Stability , Fungal Proteins/chemistry , Fungal Proteins/isolation & purification , Ribonucleases/chemistry , Ribonucleases/isolation & purification , Substrate Specificity
3.
Indian J Biochem Biophys ; 2012 Feb; 49(1): 49-54
Article in English | IMSEAR | ID: sea-140218

ABSTRACT

A novel phytase with a molecular mass of 14 kDa was isolated from fresh fruiting bodies of the common edible mushroom Volvariella volvacea (Straw mushroom). The isolation procedure involved successive chromatography on DEAE-cellulose, CM-cellulose, Affi-gel blue gel, Q-Sepharose and Superdex-75. The enzyme was a monomeric protein and was unadsorbed on DEAE-cellulose, CM-cellulose and Affi-gel blue gel, but was adsorbed on Q-Sepharose. The enzyme was purified 51.6-fold from the crude extract with 25.9% yield. Its N-terminal amino acid sequence GEDNEHDTQA exhibited low homology to the other reported phytases. The optimal pH and temperature of the purified enzyme was 5 and 45oC, respectively. The enzyme was quite stable over the pH range of 3.0 to 9.0 with less than 30% change in its activity, suggesting that it can be used in a very wide pH range. The enzyme exhibited broad substrate selectivity towards various phosphorylated compounds, but lacked antifungal activity against tested plant pathogens.


Subject(s)
6-Phytase/chemistry , 6-Phytase/isolation & purification , Adaptation, Physiological , Chromatography, DEAE-Cellulose/methods , Enzyme Stability , Hydrogen-Ion Concentration , Molecular Weight , Sepharose/chemistry , Sequence Alignment/methods , Substrate Specificity , Temperature , Triazines/chemistry , Volvariella/enzymology
4.
Braz. j. microbiol ; 42(1): 96-104, Jan.-Mar. 2011. ilus, tab
Article in English | LILACS | ID: lil-571380

ABSTRACT

Representative strains of Serratia marcescens from an edible cactus plant and silkworms were characterized and a comparison based on their cellular fatty acid composition, 16S rRNA and groE gene sequence analysis as well as silkworm virulence and chitosan susceptibility was carried out. Results from this study indicate that there are no significant differences between the phenotypic and molecular characterization, virulence and chitosan susceptibility of the S. marcescens strains from the cactus plant and silkworms. Silkworms inoculated with S. marcescens from either plant or silkworm resulted in nearly 100 percent mortality. Chitosan solution exhibited strong antibacterial activity against S. marcescens. This activity increased with the increase of chitosan concentration and incubation time regardless of the strain source. Also, the results indicate that the plant associated S. marcescens maybe plays a possible role in the contamination of humans and animals, in particular silkworms, while chitosan showed a potential to control the contamination caused by S. marcescens.


Subject(s)
Anti-Bacterial Agents/analysis , Anti-Bacterial Agents/isolation & purification , Base Sequence , Bombyx/genetics , Enzyme Reactivators , Genetic Predisposition to Disease , Chitosan/analysis , Chitosan/isolation & purification , Serratia marcescens/genetics , Serratia marcescens/isolation & purification , Enzyme Activation , Methods , Methods , Virulence
5.
J Genet ; 2006 Apr; 85(1): 45-51
Article in English | IMSEAR | ID: sea-114503

ABSTRACT

The heritability, the number of segregating genes and the type of gene interaction of nine agronomic traits were analysed based on F2 populations of synthetic oilseed Brassica napus produced from interspecific hybridization of B. campestris and B. oleracea through ovary culture. The nine traits-plant height, stem width, number of branches, length of main raceme, number of pods per plant, number of seeds per pod, length of pod, seed weight per plant and 1000-seed weight-had heritabilities of 0.927, 0.215, 0.172, 0.381, 0.360, 0.972, 0.952, 0.516 and 0.987 respectively, while the mean numbers of controlling genes for these characters were 7.4, 10.4, 9.9, 12.9, 11.5, 21.7, 20.5, 19.8 and 6.4 respectively. According to estimated coefficients of skewness and kurtosis of the traits tested, no significant gene interaction was found for plant height, stem width, number of branches, length of main raceme, number of seeds per pod and 1000-seed weight. Seed yield per plant is an important target for oilseed production. In partial correlation analysis, number of pods per plant, number of seeds per pod and 1000-seed weight were positively correlated with seed yield per plant. On the other hand, length of pod was negatively correlated (r = -0.69) with seed yield per plant. Other agronomic characters had no significant correlation to seed yield per plant. In this experiment, the linear regressions of seed yield per plant and other agronomic traits were also analysed. The linear regression equation was y = 0.074x8 + 1.819x9 + 6.72x12- 60.78 (R2= 0.993), where x8, x9 and x12 represent number of pods per plant, number of seeds per pod and 1000-seed weight respectively. The experiment also showed that erucic acid and oil contents of seeds from F2 plants were lower than those of their maternal parents. However, glucosinolate content was higher than that of the maternal plants. As for protein content, similar results were found in the F2 plants and their maternal parents. It was shown that the four quality traits, i.e. erucic acid, glucosinolate, oil content, and protein content, had heritability values of 0.614, 0.405, 0.153 and 0.680 respectively.


Subject(s)
Analysis of Variance , Hybridization, Genetic , Linear Models , Seeds/genetics
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