Selection of compositions with high glass forming ability in the Ni-Nb-B alloy system

A combination of an extension of the topological instability "λ criterion" and the "average electronegativity" has been recently reported in the literature to predict compositions with high glass-forming ability (GFA). In the present work, both criteria have been applied to select the Ni61.0Nb36.0B3 alloy with a high glass-forming ability. Ingots were prepared by arc-melting and were used to produce ribbons processed by the melt-spinning technique further characterized by differential scanning calorimetry (DSC), X-ray diffraction (XRD) and scanning electron microscopy (SEM). The Ni61.0Nb36.0B3 alloy revealed a complete amorphization and supercooled liquid region ΔTx = 68 K. In addition, wedge-shaped samples were prepared using copper mold casting in order to determine the critical thickness for amorphous formation. Scanning electron microscopy (SEM) revealed that fully amorphous samples could be obtained, reaching up to ~800 µm in thickness.

Optimal Code Set Selection and Security Issues in Spectral Phase-Encoded Time Spreading (SPECTS) OCDMA Systems

In this paper, we perform a thorough analysis of a spectral phase-encoded time spreading optical code division multiple access (SPECTS-OCDMA) system based on Walsh-Hadamard (W-H) codes aiming not only at finding optimal code-set selections but also at assessing its loss of security due to crosstalk. We prove that an inadequate choice of codes can make the crosstalk between active users to become large enough so as to cause the data from the user of interest to be detected by other user. The proposed algorithm for code optimization targets code sets that produce minimum bit error rate (BER) among all codes for a specific number of simultaneous users. This methodology allows us to find optimal code sets for any OCDMA system, regardless the code family used and the number of active users. This procedure is crucial for circumventing the unexpected lack of security due to crosstalk. We also show that a SPECTS-OCDMA system based on W-H 32(64) fundamentally limits the number of simultaneous users to 4(8) with no security violation due to crosstalk. More importantly, we prove that only a small fraction of the available code sets is actually immune to crosstalk with acceptable BER (<10(-9)) i.e., approximately 0.5% for W-H 32 with four simultaneous users, and about 1 x 10(-4)% for W-H 64 with eight simultaneous users.

Occurrence of molds on laminated paperboard for aseptic packaging, selection of the most hydrogen peroxide- and heat-resistant isolates and determination of their thermal death kinetics in sterile distilled water

This study aimed at enumerating molds (heat-labile and heat-resistant) on the surface of paperboard material to be filled with tomato pulps through an aseptic system and at determining the most heat-and hydrogen peroxide-resistant strains. A total of 118 samples of laminated paperboard before filling were collected, being 68 before and 50 after the hydrogen peroxide bath. Seven molds, including heat-resistant strains (Penicillium variotii and Talaromyces flavus) with counts ranging between 0.71 and 1.02 CFU/cm(2) were isolated. P. variotii was more resistant to hydrogen peroxide than T. flavus and was inactivated after heating at 85 degrees C/15 min. When exposed to 35 % hydrogen peroxide at 25 degrees C, T. flavus (F5E2) and N. fischeri (control) were less resistant than P. variotti (F1A1). P. citrinum (F7E2) was shown to be as resistant as P. variotti. The D values (the time to cause one logarithmic cycle reduction in a microbial population at a determined temperature) for spores of P. variotii (F1A1) and N. fischeri (control) with 4 months of age at 85 and 90 degrees C were 3.9 and 4.5 min, respectively. Although the contamination of packages was low, the presence of heat-and chemical-resistant molds may be of concern for package sterility and product stability during shelf-life. To our knowledge, this is the first report that focuses on the isolation of molds, including heat-resistant ones, contaminating paperboard packaging material and on estimating their resistance to the chemical and physical processes used for packaging sterilization.

Emergence of sensory selection mechanisms in Artificial Life simulations

Background The evolutionary advantages of selective attention are unclear. Since the study of selective attention began, it has been suggested that the nervous system only processes the most relevant stimuli because of its limited capacity [1]. An alternative proposal is that action planning requires the inhibition of irrelevant stimuli, which forces the nervous system to limit its processing [2]. An evolutionary approach might provide additional clues to clarify the role of selective attention. Methods We developed Artificial Life simulations wherein animals were repeatedly presented two objects, "left" and "right", each of which could be "food" or "non-food." The animals' neural networks (multilayer perceptrons) had two input nodes, one for each object, and two output nodes to determine if the animal ate each of the objects. The neural networks also had a variable number of hidden nodes, which determined whether or not it had enough capacity to process both stimuli (Table 1). The evolutionary relevance of the left and the right food objects could also vary depending on how much the animal's fitness was increased when ingesting them (Table 1). We compared sensory processing in animals with or without limited capacity, which evolved in simulations in which the objects had the same or different relevances. Table 1. Nine sets of simulations were performed, varying the values of food objects and the number of hidden nodes in the neural networks. The values of left and right food were swapped during the second half of the simulations. Non-food objects were always worth -3. The evolution of neural networks was simulated by a simple genetic algorithm. Fitness was a function of the number of food and non-food objects each animal ate and the chromosomes determined the node biases and synaptic weights. During each simulation, 10 populations of 20 individuals each evolved in parallel for 20,000 generations, then the relevance of food objects was swapped and the simulation was run again for another 20,000 generations. The neural networks were evaluated by their ability to identify the two objects correctly. The detectability (d') for the left and the right objects was calculated using Signal Detection Theory [3]. Results and conclusion When both stimuli were equally relevant, networks with two hidden nodes only processed one stimulus and ignored the other. With four or eight hidden nodes, they could correctly identify both stimuli. When the stimuli had different relevances, the d' for the most relevant stimulus was higher than the d' for the least relevant stimulus, even when the networks had four or eight hidden nodes. We conclude that selection mechanisms arose in our simulations depending not only on the size of the neuron networks but also on the stimuli's relevance for action.

A system for classification of time-series data from industrial non-destructive device

This work proposes a system for classification of industrial steel pieces by means of magnetic nondestructive device. The proposed classification system presents two main stages, online system stage and off-line system stage. In online stage, the system classifies inputs and saves misclassification information in order to perform posterior analyses. In the off-line optimization stage, the topology of a Probabilistic Neural Network is optimized by a Feature Selection algorithm combined with the Probabilistic Neural Network to increase the classification rate. The proposed Feature Selection algorithm searches for the signal spectrogram by combining three basic elements: a Sequential Forward Selection algorithm, a Feature Cluster Grow algorithm with classification rate gradient analysis and a Sequential Backward Selection. Also, a trash-data recycling algorithm is proposed to obtain the optimal feedback samples selected from the misclassified ones.