An intra-industry trade model in a vertical differentiation framework

We developed a partial equilibrium model in which intra-industry trade arises as a result of utility maximization of consumers and profit maximization of firms. The driving force for intra-industry trade is non-homothetic preferences of consumers. We utilized a vertical differentiation framework, in which consumers have the same tastes for quality but different income levels determining their non-homogeneous choices. All firms in all countries have access to the same production technology, and there are no differences in factor endowments. Intra-industry trade arises as a result of each firm specializing on a certain segment of the market in all countries. We solved the model numerically for a two-country two-firm setup. In this setup, firms choose their product quality level and their price by maximizing their profits in a two-stage optimization problem. They also decide whether to export to the foreign market or to concentrate only on the domestic market in a standard two-by-two game. With introduction of non-zero transportation costs, trade volumes in both directions decrease. Transportation costs are shared between consumers and firms according to the marginal demand in the domestic versus in the foreign country. This model supports Krugman’s home market effect: In case of non-zero transportation costs, firms want to locate their production site in the country where there is higher marginal demand for their product.     

Adsorptive removal of phenol from aqueous solutions on activated carbon prepared from tobacco residues: equilibrium, kinetics and thermodynamics

This study consists of producing high surface area activated carbon from tobacco residues by chemical activation and its behavior of phenol removal from aqueous solutions. K(2)CO(3) and KOH were used as chemical activation agents and three impregnation ratios (50, 75 and 100 wt.%) were applied on biomass. Maximum BET surface areas of activated carbons were obtained from impregnation with 75 wt.% of K(2)CO(3) and 75 wt.% of KOH as 1635 and 1474 m(2)/g, respectively. Optimum adsorption conditions were determined as a function of pH, adsorbent dosage, initial phenol concentration, contact time and temperature of solution for phenol removal. To describe the equilibrium isotherms the experimental data were analyzed by the Langmuir, Freundlich, Dubinin-Radushkevich (D-R) and Temkin isotherm models. Pseudo-first order, pseudo-second order and intraparticle diffusion kinetic models were used to find out the kinetic parameters and mechanism of adsorption process. The thermodynamic parameters such as ΔG°, ΔH° and ΔS° were calculated for predicting the nature of adsorption. According to the experimental results, activated carbon prepared from tobacco residue seems to be an effective, low-cost and alternative adsorbent precursor for the removal of phenol from aqueous solutions.     

Current density measurements in direct methanol fuel cells

The current density in the fuel cell is the direct consequence of reactions taking place over the active surface area. Thus, measurement of its distribution will lead to identification of the location and nature of reactions and will give opportunity to improve the overall efficiency of fuel cells. Within this study, the current density distribution in a direct methanol fuel cell was analyzed by segmenting the current collector into nine sections. Besides, the effect of the different operating parameters such as molarity, flow rate and reactant gas on the current density distribution was analyzed.     

Rheological properties of reduced-fat and low-fat ice cream containing whey protein isolate and inulin

Instrumental analyses were used to evaluate the rheological properties of regular (10%), reduced-fat (6%) and low-fat (3%) ice cream mixes and frozen ice creams stored at −18 °C. The reduced-fat and low-fat ice creams were prepared using 4% whey protein isolate (WPI) or 4% inulin as the fat replacement ingredient. The composition, colour, apparent viscosity, consistency coefficient, flow behaviour index, hardness and melting characteristics were measured. No effect of WPI or inulin was obtained on the colour values. Compared with regular ice cream, WPI changed rheological properties, resulting in significantly higher apparent viscosities, consistency indices and greater deviations from Newtonian flow. In addition, both hardness and melting resistance significantly increased by using WPI in reduced-fat and low-fat ice creams. Inulin also increased the hardness in comparison to regular ice cream, but the products made with inulin melted significantly faster than the other samples.     

Aloe vera-based antibacterial porous sponges for wound dressing applications

Journal of Porous Materials - The antibacterial sponges with high macroporosity, high interconnectivity and high biocompatibility is a significant concern for wound healing applications. In this...     

Alcoholism detection based on Hu moment invariants of event-related potentials

Diagnostic efforts to identify alcoholism are frequently subjective; however, recent technological advances have allowed the automated assessment of objective signals. To improve the performance of the automated classification of patients with alcohol dependence (AD) and controls, we analyzed features of event-related potentials (ERPs) in 72 subjects with AD and 42 controls while the subjects underwent three different visual oddball tasks. In addition to such commonly used morphological features (MFs) as time-domain amplitude and latency components as well as discrete wavelet transform coefficient entropies (WEs), we analyzed Hu moment invariants (HMIs) in this study. Smaller P3 and P2 amplitudes, longer latencies, lower WE values, and lower HMI values were observed for AD subjects relative to those observed for controls. We used a Naïve Bayes algorithm to compare classification accuracies among MFs, WEs, HMIs, combinations of MFs/WEs, and combinations of all three characteristics. We found that HMIs improved the classification accuracy by 17%. Our findings demonstrated that a combined feature analysis of ERPs obtained during a visual oddball task can be a useful and discriminative tool for diagnostic purposes in alcoholism and that HMIs show promise for improving the objective diagnosis of alcoholism and similar diseases.     

Combining functional near-infrared spectroscopy and EEG measurements for the diagnosis of attention-deficit hyperactivity disorder

Neural Computing and Applications - Recently multimodal neuroimaging which combines signals from different brain modalities has started to be considered as a potential to improve the accuracy of...     

Extracting Low-Frequency Spatio-Temporal Patterns in Ambient Power System Data Using Blind Source Separation

Wide-area techniques provide a powerful tool to extract spatio-temporal patterns from high-dimensional datasets and can be used for event detection and visualization, data fusion, stability assessment, and coherency analysis. In this paper, a novel blind source separation-based approach for extracting low-frequency spatio-temporal patterns from measured ambient power system data is proposed and a spatio-temporal visualization index is also suggested. This methodology combines a nonlinear hierarchical neural network with a Blind Source Separation (BSS) technique. The neural network allows reducing noise and removing the nonlinear relations among data (preserve dynamic features of interest), while the BSS technique permits extracting spatial and temporal patterns. In addition, the proposed approach takes advantage of the latest techniques in nonlinear estimation of non-stationary time series. Finally, application examples of the proposed framework on real test cases recorded from an actual power system by Phasor Measurement Units (PMUs) are presented. The obtained results show that the temporal patterns can be used for extracting and identifying the low-frequency oscillation modes and the spatial patterns can be used for identifying modes with the most contribution in original data. Compared to other BSS approaches, the proposed method has shown to be better for the analysis of real ambient data.