Scalable Massively Parallel Artificial Neural Networks

There is renewed interest in computational intelligence, due to advances in algorithms, neuroscience, and computer hardware. In addition there is enormous interest in autonomous vehicles (air, ground, and sea) and robotics, which need significant onboard intelligence. Work in this area could not only lead to better understanding of the human brain but also very useful engineering applications. The functioning of the human brain is not well understood, but enormous progress has been made in understanding it and, in particular, the neocortex. There are many reasons to develop models of the brain. Artificial Neural Networks (ANN), one type of model, can be very effective for pattern recognition, function approximation, scientific classification, control, and the analysis of time series data. ANNs often use the back-propagation algorithm for training, and can require large training times especially for large networks, but there are many other types of ANNs. Once the network is trained for a particular problem, however, it can produce results in a very short time. Parallelization of ANNs could drastically reduce the training time. An object-oriented, massively-parallel ANN (Artificial Neural Network) software package SPANN (Scalable Parallel Artificial Neural Network) has been developed and is described here. MPI was use

The chromosome 9p21.3 coronary heart disease risk allele is associated with altered gene expression in normal heart and vascular tissues

10.1371/journal.pone.0039574PLoS ONE76e3957

Galvanomagnetic properties of CdTe below and above the melting point

Temperature dependence of conductivity � and Hall coefficient RH is measured by DC and AC methods at temperatures between 600-1180°C. Two experimental approaches are used. Galvanomagnetic measurements at defined temperature and Cd or Te pressure are performed in solid samples in the whole field of stability of solid in the pressure-temperature (P-T) diagram. Galvanomagnetic measurements define temperature both in solid and in liquid phase. The typical semiconducting character of � and 1/|eRH|, when both parameters increase with temperature, is observed also in the liquid. The negative sign of RH is observed above 600°C within the whole region of stability of solid, both at Cd and at Te saturation, and RH < 0 both in solid and liquid. 1/|eRH| reaches 5 � 1019 cm-3 at 1180°C and the corresponding Hall mobility is 20 cm2/Vs. Three slopes characterize the temperature dependence of a 0.7 eV in the solid CdTe below the melting point 1092°C and 4.6 eV in the liquid phase at 1092°C < T < 1160°C. Above 1160°C, conductivity increases moderately with the slope 0.8 eV. The experimental data for solid CdTe are evaluated by a theoretical model, including electrons from both the central minimum (�-point) and four satellite minima (L-point) of the Brillouin zone. The ab initio results fit our experimental data after small modifications very well