Plant height reduction in populations of triticale (X triticosecale Wittmack) by induced mutations and artificial crosses

Induced mutations by gamma radiation (0, 5, 10, 20 and 40 kR doses) and reciprocal crosses were tested as mechanisms of enhancing genetic variability for plant height in two triticale cultivars, BR4 and EMBRAPA18. The reciprocal crosses and all doses of radiation showed similar increase in genetic amplitude for this trait, being suitable for increasing variability in breeding programs. Genotypes showed different responses as the gamma ray doses were increased, expressing shorter plant height. The decision of using induced mutations or artificial crosses depends on the resources available and the selection method to be used

Milk protein polymorphisms in Brazilian Zebu cattle

Five bovine milk protein polymorphisms were studied in Zebuine cattle raised in Brazil, through horizontal electrophoresis on starch gel containing urea and 2-mercaptoethanol, using basic and acidic buffer systems. Allelic frequencies for a-La, b-Lg, aS1-Cn, b-Cn and k-Cn loci were estimated in six Gyr herds (N = 283), six Guzerat herds (N = 205), one Nelore herd (N = 17) and one Sindi herd (N = 22), all from São Paulo or Minas Gerais State, Brazil. Genotypic frequencies observed for each locus and breed studied are in accordance with the assumption of genetic equilibrium, demonstrating absence of high inbreeding levels for the breeds tested. The FST value found indicated significant genetic differentiation among breeds; however, the Gyr and Guzerat herds showed significantly different gene frequencies. Genetic distance estimates among zebuine breeds studied and the Holstein breed, taken as a reference for a taurine breed, showed strong differences between these two racial groups

Differential in vitro pathogenicity of predatory fungi of the genus Monacrosporium for phytonematodes, free-living nematodes and parasitic nematodes of cattle

In vitro tests were carried out on the pathogenicity of nine isolates of the predatory fungi of the genus Monacrosporium (5 M. sinense isolates, 3 M. appendiculatum and 1 M. thaumasium isolate) for a phytonematode (second stage juveniles from Meloidogyne incognita, race 3), a free-living nematode (Panagrellus spp), and two gastrointestinal parasitic nematodes of cattle (infective larvae of Cooperia punctata and Haemonchus placei). A suspension containing 2,000 nematodes from each species was added to Petri dishes containing fungi and grown on 2% water-agar medium at 25oC in the dark for up to 7 days. The dishes were examined every other day for 7 days and predation-free nematodes were counted. The results showed that the free-living nematodes, Panagrellus spp, were the most susceptible (P<0.05), followed by the phytonematode M. incognita, while the controls were ³98.5% viable. However, a variable susceptibility of the nematodes to different fungi was observed. This indicates that the use of predatory fungi for the environmental control of nematodes will be limited by the multiplicity of nematodes in the environment and their differential susceptibility to fungal isolates of the same genus.

Automated grading of left ventricular segmental wall motion by an artificial neural network using color kinesis images

The present study describes an auxiliary tool in the diagnosis of left ventricular (LV) segmental wall motion (WM) abnormalities based on color-coded echocardiographic WM images. An artificial neural network (ANN) was developed and validated for grading LV segmental WM using data from color kinesis (CK) images, a technique developed to display the timing and magnitude of global and regional WM in real time. We evaluated 21 normal subjects and 20 patients with LVWM abnormalities revealed by two-dimensional echocardiography. CK images were obtained in two sets of viewing planes. A method was developed to analyze CK images, providing quantitation of fractional area change in each of the 16 LV segments. Two experienced observers analyzed LVWM from two-dimensional images and scored them as: 1) normal, 2) mild hypokinesia, 3) moderate hypokinesia, 4) severe hypokinesia, 5) akinesia, and 6) dyskinesia. Based on expert analysis of 10 normal subjects and 10 patients, we trained a multilayer perceptron ANN using a back-propagation algorithm to provide automated grading of LVWM, and this ANN was then tested in the remaining subjects. Excellent concordance between expert and ANN analysis was shown by ROC curve analysis, with measured area under the curve of 0.975. An excellent correlation was also obtained for global LV segmental WM index by expert and ANN analysis (R² = 0.99). In conclusion, ANN showed high accuracy for automated semi-quantitative grading of WM based on CK images. This technique can be an important aid, improving diagnostic accuracy and reducing inter-observer variability in scoring segmental LVWM.

Recombinant E2 glycoprotein of bovine viral diarrhea virus induces a solid humoral neutralizing immune response but fails to confer total protection in cattle

Two recombinant baculoviruses were produced in order to obtain a bovine viral diarrhea virus (BVDV) immunogen: AcNPV/E2 expressing E2 glycoprotein, and AcNPV/E0E1E2 expressing the polyprotein region coding for the three structural proteins of BVDV (E0, E1, and E2). Mice were immunized with Sf9 cells infected with the recombinant baculoviruses in a water in oil formulation and the production of neutralizing antibodies was evaluated. Since E2 elicited higher neutralizing antibody titers than E0-E1-E2 polyprotein, it was selected to immunize cattle. Calves received two doses of recombinant E2 vaccine and were challenged with homologous BVDV 37 days later. The recombinant immunogen induced neutralizing titers which showed a mean value of 1.5 ± 0.27 on the day of challenge and reached a top value of 3.36 ± 0.36, 47 days later (84 days post-vaccination). On the other hand, sera from animals which received mock-infected Sf9 cells did not show neutralizing activity until 25 days post-challenge (62 days post-vaccination), suggesting that these antibodies were produced as a consequence of BVDV challenge. Even when no total protection was observed in cattle, in vitro viral neutralization assays revealed that the recombinant immunogen was able to induce neutralizing antibody synthesis against the homologous strain as well as against heterologous strains in a very efficient way.

Synergistic control of forearm based on accelerometer data and artificial neural networks

In the present study, we modeled a reaching task as a two-link mechanism. The upper arm and forearm motion trajectories during vertical arm movements were estimated from the measured angular accelerations with dual-axis accelerometers. A data set of reaching synergies from able-bodied individuals was used to train a radial basis function artificial neural network with upper arm/forearm tangential angular accelerations. The trained radial basis function artificial neural network for the specific movements predicted forearm motion from new upper arm trajectories with high correlation (mean, 0.9149-0.941). For all other movements, prediction was low (range, 0.0316-0.8302). Results suggest that the proposed algorithm is successful in generalization over similar motions and subjects. Such networks may be used as a high-level controller that could predict forearm kinematics from voluntary movements of the upper arm. This methodology is suitable for restoring the upper limb functions of individuals with motor disabilities of the forearm, but not of the upper arm. The developed control paradigm is applicable to upper-limb orthotic systems employing functional electrical stimulation. The proposed approach is of great significance particularly for humans with spinal cord injuries in a free-living environment. The implication of a measurement system with dual-axis accelerometers, developed for this study, is further seen in the evaluation of movement during the course of rehabilitation. For this purpose, training-related changes in synergies apparent from movement kinematics during rehabilitation would characterize the extent and the course of recovery. As such, a simple system using this methodology is of particular importance for stroke patients. The results underlie the important issue of upper-limb coordination.

Effect of lipoarabinomannan from Mycobacterium avium subsp avium in Freund’s incomplete adjuvant on the immune response of cattle

The aim of the present study was to determine whether lipoarabinomannan (LAM), in combination with Freund’s incomplete adjuvant (FIA), was able to improve cell-mediated and antibody-mediated immune responses against ovalbumin (OVA) in cattle. Twenty-three calves were assigned to four treatment groups, which were subcutaneously immunized with either OVA plus FIA, OVA plus FIA and LAM from Mycobacterium avium subsp avium, FIA plus LAM, or FIA alone. Lymphoproliferation, IFN-γ production and cell subpopulations on peripheral blood mononuclear cells before and 15 days after treatment were evaluated. Delayed hypersensitivity was evaluated on day 57. Specific humoral immune response was measured by ELISA. Inoculation with LAM induced higher levels of lymphoproliferation and IFN-γ production in response to ConA and OVA (P < 0.05). Specific antibody titers were similar in both OVA-immunized groups. Interestingly, our results showed that the use of LAM in vaccine preparations improved specific cell immune response evaluated by lymphoproliferation and IFN-γ production by at least 50 and 25%, respectively, in cattle without interfering with tuberculosis and paratuberculosis diagnosis.

Artificial neural network models for predicting 1-year mortality in elderly patients with intertrochanteric fractures in China

The mortality rate of older patients with intertrochanteric fractures has been increasing with the aging of populations in China. The purpose of this study was: 1) to develop an artificial neural network (ANN) using clinical information to predict the 1-year mortality of elderly patients with intertrochanteric fractures, and 2) to compare the ANN's predictive ability with that of logistic regression models. The ANN model was tested against actual outcomes of an intertrochanteric femoral fracture database in China. The ANN model was generated with eight clinical inputs and a single output. ANN's performance was compared with a logistic regression model created with the same inputs in terms of accuracy, sensitivity, specificity, and discriminability. The study population was composed of 2150 patients (679 males and 1471 females): 1432 in the training group and 718 new patients in the testing group. The ANN model that had eight neurons in the hidden layer had the highest accuracies among the four ANN models: 92.46 and 85.79% in both training and testing datasets, respectively. The areas under the receiver operating characteristic curves of the automatically selected ANN model for both datasets were 0.901 (95%CI=0.814-0.988) and 0.869 (95%CI=0.748-0.990), higher than the 0.745 (95%CI=0.612-0.879) and 0.728 (95%CI=0.595-0.862) of the logistic regression model. The ANN model can be used for predicting 1-year mortality in elderly patients with intertrochanteric fractures. It outperformed a logistic regression on multiple performance measures when given the same variables.

HYBRID ARTIFICIAL NEURAL NETWORK APPLIEDTO MODELING SCFE OF BASIL AND ROSEMARY OILS

This work presents the results of a Hybrid Neural Network (HNN) technique as applied to modeling SCFE curves obtained from two Brazilian vegetable matrices. A series Hybrid Neural Network was employed to estimate the parameters of the phenomenological model. A small set of SCFE data of each vegetable was used to generate an extended data set, sufficient to train the network. Afterwards, other sets of experimental data, not used in the network training, were used to validate the present approach. The series HNN correlates well the experimental data and it is shown that the predictions accomplished with this technique may be promising for SCFE purposes.

Previsão de estabilidade de óleos vegetais através da rede de inteligência artificial

Redes Neurais Artificiais são técnicas computacionais que se utilizam de um modelo matemático capaz de adquirir conhecimentos pela experiência; esse comportamento inteligente da rede provém das interações entre unidades de processamento, denominadas de neurônios artificiais. O objetivo deste trabalho foi criar uma rede neural capaz de prever a estabilidade de óleos vegetais, a partir de dados de suas composições químicas, visando um modelo para a previsão da shelf-life de óleos vegetais, tendo como parâmetros apenas dados de suas composições químicas. Os primeiros passos do processo de desenvolvimento da rede consistiram na coleta de dados relativos ao problema e sua separação em um conjunto de treinamento e outro de testes. Estes conjuntos apresentaram como variáveis dados de composição química, que incluíram os valores totais em ácidos graxos, fenóis, tocoferóis e a composição individual em ácidos graxos. O passo seguinte foi a execução do treinamento, onde o padrão de entrada apresentado à rede como parâmetro de estabilidade foi o índice de peróxido, determinado experimentalmente por um período de 16 dias de armazenagem na ausência de luz, a 65ºC. Após o treinamento foi testada a capacidade de previsão adquirida pela rede, em função do parâmetro de estabilidade adotado, mas com um novo grupo de óleos. Seguindo o teste, foi determinada a correlação linear entre os valores de estabilidade previstos pela rede e aqueles determinados experimentalmente. Com os resultados obtidos, pode-se confirmar a viabilidade de previsão da estabilidade de óleos vegetais pela rede neural, a partir de dados de sua composição química, utilizando como parâmetro de estabilidade o índice de peróxido.

An artificial neural network model for prediction of quality characteristics of apples during convective dehydration

In this study, the effects of hot-air drying conditions on color, water holding capacity, and total phenolic content of dried apple were investigated using artificial neural network as an intelligent modeling system. After that, a genetic algorithm was used to optimize the drying conditions. Apples were dried at different temperatures (40, 60, and 80 °C) and at three air flow-rates (0.5, 1, and 1.5 m/s). Applying the leave-one-out cross validation methodology, simulated and experimental data were in good agreement presenting an error < 2.4 %. Quality index optimal values were found at 62.9 °C and 1.0 m/s using genetic algorithm.

Artificial neural networks (ANN): prediction of sensory measurements from instrumental data

The objective of this study was to predict by means of Artificial Neural Network (ANN), multilayer perceptrons, the texture attributes of light cheesecurds perceived by trained judges based on instrumental texture measurements. Inputs to the network were the instrumental texture measurements of light cheesecurd (imitative and fundamental parameters). Output variables were the sensory attributes consistency and spreadability. Nine light cheesecurd formulations composed of different combinations of fat and water were evaluated. The measurements obtained by the instrumental and sensory analyses of these formulations constituted the data set used for training and validation of the network. Network training was performed using a back-propagation algorithm. The network architecture selected was composed of 8-3-9-2 neurons in its layers, which quickly and accurately predicted the sensory texture attributes studied, showing a high correlation between the predicted and experimental values for the validation data set and excellent generalization ability, with a validation RMSE of 0.0506.

Survival of Shiga toxin-producing Escherichia coli O157:H7 in Minas frescal cheese

Shiga toxin-producing Escherichia coli (STEC) O157:H7 strains (isolated by cattle’s faeces and a reference strain, EDL933), were inoculated into pasteurized milk (102 and 103 cells.mL–1) to prepare the Minas frescal cheese. As control was used uninfected milk. Physicochemical and microbiological analyses were performed to milk and elaborated cheese. The O157:H7 strains were quantified in the stages of cheese processing and during 0, 2, 4, 5, 7, 10 and 15 storage days at 8 °C onto Sorbitol MacConkey Agar supplemented with potassium tellurite and cefixime (CT-SMAC). O157:H7 was not present in the pasteurised milk prior to the artificial inoculation. At the end of the processing the cheese had 10 to 100 times more STEC O157:H7 than the initial inoculum. During the storage, the Minas frescal cheese exhibited the largest population increase on the 4th and 5th day when inoculated with 102 and 103 cells.mL–1, respectively. Additionally, viable cells were found up to the 10th and 15th day, according to the amount of initial inoculum. This number of cells is able to cause infection in humans, and therefore, Minas frescal cheese, even when stored under refrigeration, is a potential vehicle of disease caused by STEC O157:H7.

Inteligência artificial e teoria de resolução de problemas

Este artigo é uma tentativa de delinear as principais características da pesquisa numa nova área de estudos a chamada Inteligência Artificial (AI). Os itens 1 e 2 constituem um rápido histórico da AI e seus pressupostos básicos. O item 3 trata da teoria de resolução de problemas, desenvolvida por A. Newell e H. Simon. O item 4 procura mostrar a relevância da AI para a Filosofia, em especial para a filosofia da Mente e para a Teoria do Conhecimento.

Robots, intencionalidade e inteligência artificial

O artigo aborda problemas filosóficos relativos à natureza da intencionalidade e da representação mental. A primeira parte apresenta um breve histórico dos problemas, percorrendo rapidamente alguns episódios da filosofia clássica e da filosofia contemporânea. A segunda parte examina o Chinese Room Argument (Argumento do Quarto do Chinês) formulado por J. Searle. A terceira parte desenvolve alguns argumentos visando mostrar a inadequação do modelo funcionalista de mente na construção de robots. A conclusão (quarta parte) aponta algumas alternativas ao modelo funcionalista tradicional, como, por exemplo, o conexionismo.