An efficient classifier to diagnose of schizophrenia based on the EEG signals

In this paper, electroencephalogram (EEG) signals of 13 schizophrenic patients and 18 age-matched control participants are analyzed with the objective of classifying the two groups. For each case, multi-channels (22 electrodes) scalp EEG is recorded. Several features including autoregressive (AR) model parameters, band power and fractal dimension are extracted from the recorded signals. Leave-one (participant)-out cross validation is used to have an accurate estimation for the separability of the two groups. Boosted version of Direct Linear Discriminant Analysis (BDLDA) is selected as an efficient classifier which applied on the extracted features. To have comparison, classifiers such as standard LDA, Adaboost, support vector machine (SVM), and fuzzy SVM (FSVM) are applied on the features. Results show that the BDLDA is more discriminative than others such that their classification rates are reported 87.51%, 85.36% and 85.41% for the BDLDA, LDA, Adaboost, respectively. Results of SVM and FSVM classifiers were lower than 50% accuracy because they are more sensitive to outlier instances. In order to determine robustness of the suggested classifier, noises with different amplitudes are added to the test feature vectors and robustness of the BDLDA was higher than the other compared classifiers.     

Associative interactions between chitosan and soy protein fractions: Effects of pH,mixing ratio,heat treatment and ionic strength

The objective of this paper is to explore the complexation between the soy protein fractions (glycinin and β-conglycinin) and chitosan (CS) and to investigate the influence of pH, mixing ratio, heat treatment and ionic strength. Phase behavior and microstructure showed that soluble complex and coacervate were obtained in glycinin/CS and β-conglycinin/CS mixtures at specific pHs, following a nucleation and growth mechanism. Moreover, the coacervates showed higher thermal stability than protein alone. Specially, the glycinin/CS mixture displayed a gel-like network structure at pH 5.5 and 6.0, and this structure kept the mixture soluble at a long pH region. The turbidity versus ζ-potential pattern showed that, independent of protein, the self aggregation of soy protein fractions and the coacervation of glycinin/CS and β-conglycinin/CS mixtures were all obtained at charge neutralization pH, indicating that the ζ-potential is the most critical parameter to understand the stability of soy protein/chitosan mixture. This predictive parameter was less affected by mixing ratio and heating but was significantly affected by ionic strength because mixing ratio and heating only changed the equilibrium between repulsive and attractive forces in colloid system while sodium chloride destroyed the predictability of colloidal stability via shielding charged reactive sites on both biopolymers to disrupt electrostatic interactions.     

Highly efficient metal-free phosphorus-doped platelet ordered mesoporous carbon for electrocatalytic oxygen reduction

Platinum-free electrocatalysts especially, various heteroatom-doped carbon nanostructures have attracted particular attraction as plausible solution for commercializing fuel cell technology. In this direction, novel phosphorus-doped platelet ordered mesoporous carbon (P-pOMC) is developed for the first time as metal-free electrocatalyst for alkaline oxygen reduction reaction. The P-pOMC is synthesized by nanocasting method using platelet ordered mesoporous silica as template. Various characterizations reveal that the P-pOMC materials have covalently bound P atoms with carbon framework for facilitation of oxygen reduction reaction (ORR) and also have very high surface area with uniform distribution of short mesoporous channels for unhindered mass transfer. Combination of P doping and excellent surface properties empowers the newly-developed P-pOMC catalyst to show high ORR activity nearly equal to that of state of the art Pt catalyst along with superior long-term stability and excellent methanol tolerance.     

Comparison of simplex and duplex real-time PCR for the quantification of GMO in maize and soybean

This paper focuses on the determination of the GMO content of maize and soybean samples using real-time PCR, comparing simplex and duplex PCR. The total DNA content of samples was determined by amplifying part of a maize gene encoding a lipid transfer protein, or part of a soybean lectin gene. The transgenic DNA was quantified by amplifying part of the CaMV 35S promoter. The importance of preparation and conservation of standards as well as the relevance of DNA extraction protocol on the variability of results are discussed. For the determination of low GMO content, limitation in the number of copies of the target gene to be amplified is considered. For samples with a theoretical GMO content of 1%, corresponding to the legal threshold for labelling, the value determined by duplex real-time PCR ranged from 0.85% to 1.20%. Both real-time simplex and duplex PCRs allowed identification of GMO free samples without ambiguity.     

Current major degradation methods for aflatoxins: A review

BackgroundAflatoxins are strong cancerogenic compounds predominantly produced by certain strains of the Aspergillus genus. Due to their extreme stability in different conditions, it is very difficult to remove them completely in human diet and animal feeds. In this way aflatoxins are triggering numerous healthy problems (such as liver cancer) and thus becoming a huge burden to the hygiene system and food industry worldwide.Scope and approachTherefore, seeking for an effective technique to degrade aflatoxins to a threshold level has been a “hot-topic” among researchers. Traditional methods to detoxify aflatoxins include physical and chemical treatments, such as an extrusion cooking process and ammoniation, respectively. Meanwhile a bio-degradation by microorganisms gains its popularity due to its friendliness to both environment and body health. Natural phytochemicals (plant extracts) which have great capability to remove aflatoxins without causing any damage on human and animals come out as an improvement.Key findings and conclusionHowever, a fully and systematically discussion of the methods of detoxification for aflatoxins is still not available. Therefore, in the present review we briefly enumerate several traditional strategies, update newly methods, particularly the potential use of natural phytochemicals, and discuss some mechanisms during the detoxification period, summarizing merits and demerits of these methods. We suggest that this important information and our humble opinions could help researchers to understand the degradation of methods for aflatoxins.     

Adaptive robust motion control of SISO nonlinear systems with implementation on linear motors

For the purpose of controlling an X–Y table driven by linear motors with a high precision, an adaptive robust motion tracking control method is first introduced. The controller is developed based upon a class of SISO nonlinear systems whose nonlinear part can be linearly parameterized. The advantage of such a controller is that parametric uncertainties and unknown disturbances can be dealt with, which is essential for a high precision of the control of linear-motor-driven X–Y table. With the prior knowledge of the bounds of the system parameters, a discontinuous projection is utilized in the adaptive law to ensure the boundedness of the parameters estimates. The algorithm is then implemented on a real X–Y table driven by the linear motors. In the modeling of such a system, fiction effects are also considered, which is useful for the derivation of the adaptive law. Experiments on the X–Y table are carried out and the results show excellent tracking performance of the system.     

The visual homing problem: An example of robotics/biology cross fertilization

In this paper, we describe how a mobile robot under simple visual control can retrieve a particular goal location in an open environment. Our model neither needs a precise map nor to learn all the possible positions in the environment. The system is a neural architecture inspired by neurobiological analysis of how visual patterns named landmarks are recognized. The robot merges these visual informations and their azimuth to build a plastic representation of its location. This representation is used to learn the best movement to reach the goal. A simple and fast on-line learning of a few places located near the goal allows this goal to be reached from anywhere in its neighborhood. The system uses only a very rough representation of the robot environment and presents very high generalization capabilities. We describe an efficient implementation of autonomous and motivated navigation tested on our robot in real indoor environments. We show the limitations of the model and its possible extensions.     

Properties of amidated pectins. I. Preparation and characterization of amidated pectins and amidated pectic acids

The preparation of high molecular weight pectic acids with varying degrees of amidation (15–61%) is described. The samples are characterized by analytical parameters, viscosity and behaviour on gel permeation and ion-exchange chromatography columns. Results show that the monomer composition is not changed and that aggregation may occur in aqueous solution of highly amidated pectic acids.