Hirsch's index: a case study conducted at the Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo

An analysis of scientific bibliographic productivity using the Hirsch h-index, information from the Institute of Scientific Information database and the Curriculum Lattes (CNPq, Brazil) was performed at the Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo (FFCLRP-USP) that has four departments in natural, biological and social sciences. Bibliometric evaluations of undergraduate programs showed a better performance of the departments of Chemistry (P < 0.001) and Biology (P < 0.001) when compared to the departments of Physics and Mathematics and Psychology and Education. We also analyzed the scientific output of the six graduate programs of FFCLRP: Psychology, Psychobiology, Chemistry, Physics Applied to Medicine and Biology, Comparative Biology, and Entomology. The graduate program in Psychology presented a lower h-index (P < 0.001) and had fewer papers indexed by the ISI web of science (P < 0.001) when compared to the other graduate programs. The poorer performance of the Psychology program may be associated with the limited coverage by the Thompson Institute of Scientific Information database.

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.

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.

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.

Continuidade ou ruptura? Uma análise de alguns aspectos da filosofia social de John Stuart Mill, Alfred Marshall e John Maynard Keynes

O artigo argumenta que é possível se falar em uma 'tradição' no campo de filosofia social e econômica unindo as obras de J.S. Mill e Alfred Marshall e J.M. Keynes. Essa 'tradição' pode ser caracterizada pelas seguintes concepções: (a) pela rejeição moral aos valores aquisitivos do capitalismo; (b) pela visão de que o sistema capitalista seria incapaz de resolver de forma espontânea as questões das desigualdades de renda e riqueza e da pobreza; (c) pela ideia de que, por uma questão de garantia de liberdade e da diversidade, além de por questões de eficiência econômica, dever-se-ia deixar a iniciativa individual agir livremente nas esferas em que é capaz de engendrar bons resultados, mas que o Estado deveria intervir, quando essa falha, atuando em benefício da coletividade; (d) pela crença de que seria possível melhorar significativamente esse sistema por meio de mudanças pontuais e graduais.

Rodolfo Mondolfo e o início da filosofia grega

O presente artigo pretende chamar a atenção para o papel representado por Rodolfo Mondolfo, com sua teoria da dependência da primeira filosofia grega em relação a uma reflexão anterior sobre o homem e a vida social, na "viragem" que reinseriu na história o início da filosofia.