Hull-less Barley Varieties: Storage Proteins and Amino Acid Distribution in Relation to Nutritional Quality

Barley (Hordeum vulgare L.) has had an important impact on human nutrition. Hull-less barley is a genetically improved type that has been widely used in recent years. Six Brazilian hull-less barley varieties (IAC-IBON 214-82; IAC 8612-421; IAC 8501-31; IAC 8501-12; IAPAR 39-ACUMAI; IAC 8501-22) were analyzed for storage protein constituents, amino acid contents, and similarity among the hull-less barley varieties. Albumins, globulins, prolamins I and II, and glutelins were extracted and separated by SDS-PAGE. The total protein amino acid contents of the flour were also determined for each variety by TLC and HPLC. Variations in intensity and appearance and disappearance of protein bands were observed among the varieties suggesting genetic variability. However, the amino acid profile did not indicate any major variations in the amino acid concentrations. The high lysine and threonine total concentrations detected in the seeds of the hull-less barley varieties encouraged an investigation into the regulation of amino acid metabolism and storage protein synthesis.     

Transport of chromium(VI) through a Cyanex 921‐supported liquid membrane from HCl solutions

The transport of chromium(VI) through a flat‐sheet supported liquid membrane containing Cyanex 921 as a carrier has been investigated. The permeation of the metal is investigated as a function of various experimental variables: hydrodynamic conditions, concentration of chromium(VI) and HCl in the feed phase, carrier concentration and diluent in the membrane and strippant concentration in the stripping phase. The mass transfer coefficient and the thickness of the aqueous boundary layer were calculated from the experimental data. Furthermore, the selectivity of Cyanex 921‐based flat‐sheet supported liquid membrane towards different metal ions and the behaviour of the system against other carriers are presented. Copyright © 2003 Society of Chemical Industry     

A Study of Ozone Generation by Negative Corona Discharge Through Different Plasma Chemistry Models

The Steady radial distribution of chemical species in a wire‐to‐cylinder ozone generator filled with pure oxygen has been computed by applying four different plasma chemistry models of increasing complexity. The most complete model considers ten species (e, O₂ ⁺, O₂ ^?, O₃ ^?, O^?, O₂, O₂(¹Δ_g), O₂(¹∑_g ⁺), O and O₃) and 79 reactions, including ionization by electron impact, electron attachment and detachment, electron-ion recombination, charge transfer, etc. The chemical model is coupled with the electrical model through Poisson's equation. The spatially averaged ozone density has been computed as a function of the current intensity and compared with the experimental values obtained by UV spectroscopy.     

Mapping of Trellises Associated with General Encoders onto High-Performance VLSI Architectures

A rate 1/n binary generic convolutional encoder is a shift-register circuit where the inputs are information bits and the outputs are blocks of n bits generated as linear combinations on the appropriate shift register contents. The decoding of the outputs of a convolutional encoder can be carried out by the well-known Viterbi algorithm. The communication pattern of the Viterbi Algorithm is given as a graph, called trellis, associated to the state diagram of the corresponding encoder. In this paper we present a methodology that permits the efficient mapping of the Viterbi algorithm onto a column of an arbitrary number of processors. This is done through the representation of the data flow by using mathematical operators which present an inmediate hardware projection. A single operator string has been obtained to represent a generic encoder through the study of the data flow of free-forward encoders and feed-back encoders. The formal model developed is employed for the partitioning of the computations among an arbitrary number of processors in such a way that the data are recirculated opimizing the use of the processors and the communications. As a result, we obtain a highly regular and modular architecture suitable for VLSI implementation.     

Algorithms for processing the group K nearest-neighbor query on distributed frameworks

Distributed and Parallel Databases - Given two datasets of points (called Query and Training), the Group (K) Nearest-Neighbor (GKNN) query retrieves (K) points of the Training with the smallest sum...     

Modelling the effects of human papillomavirus in cervical cells

Worldwide, cervical cancer is the second most common cancer in women, after breast cancer. The prevalence of this malignant disease is estimated at 1.4 million cases worldwide, causing about 290,000 deaths and 500,000 new cases per year, of which 80% correspond to women living in developing countries. In this work we propose a family of ordered models for basal cells of the cervix corresponding to different stages ranging from normal cells to the formation of precancerous lesions. We analyse the first member of the family analytically and for the second member we developed a non-standard numerical method in order to extract some biological information.     

Learning short synfire chains by self-organization

A model of cortical neurons capable of sustaining a low level of spontaneous activity is investigated. Without learning the activity of the network is chaotic. We report on attempts to learn synfire chains in this type of network by introducing a Hebbian learning mechanism and exciting a small set of neurons at random intervals. We discuss the types of instabilities that can arise and prevent the formation of long synfire chains and also discuss various biologically plausible mechanisms which to some extent cure these instabilities.     

Invariant-driven specifications in Maude

This work presents a general mechanism for executing specifications that comply with given invariants, which may be expressed in different formalisms and logics. We exploit Maude’s reflective capabilities and its properties as a general semantic framework to provide a generic strategy that allows us to execute Maude specifications taking into account user-defined invariants. The strategy is parameterized by the invariants and by the logic in which such invariants are expressed. We experiment with different logics, providing examples for propositional logic, (finite future time) linear temporal logic and metric temporal logic.     

An Analysis of Edge Detection by Using the Jensen-Shannon Divergence

This work constitutes a theoretical study of the edge-detection method by means of the Jensen-Shannon divergence, as proposed by the authors. The overall aim is to establish formally the suitability of the procedure of edge detection in digital images, as a step prior to segmentation. In specific, an analysis is made not only of the properties of the divergence used, but also of the method's sensitivity to the spatial variation, as well as the detection-error risk associated with the operating conditions due to the randomness of the spatial configuration of the pixels. Although the paper deals with the procedure based on the Jensen-Shannon divergence, some problems are also related to other methods based on local detection with a sliding window, and part of the study is focused to noisy and textured images.     

Some Statistical-Estimation Methods for Stochastic Finite-State Transducers

Formal translations constitute a suitable framework for dealing with many problems in pattern recognition and computational linguistics. The application of formal transducers to these areas requires a stochastic extension for dealing with noisy, distorted patterns with high variability. In this paper, some estimation criteria are proposed and developed for the parameter estimation of regular syntax-directed translation schemata. These criteria are: maximum likelihood estimation, minimum conditional entropy estimation and conditional maximum likelihood estimation. The last two criteria were proposed in order to deal with situations when training data is sparse. These criteria take into account the possibility of ambiguity in the translations: i.e., there can be different output strings for a single input string. In this case, the final goal of the stochastic framework is to find the highest probability translation of a given input string. These criteria were tested on a translation task which has a high degree of ambiguity.