Ensemble Approach for Detection of Depression Using EEG Features

Depression is a public health issue that severely affects one’s well being and can cause negative social and economic effects to society. To raise awareness of these problems, this research aims at determining whether the long-lasting effects of depression can be determined from electroencephalographic (EEG) signals. The article contains an accuracy comparison for SVM, LDA, NB, kNN, and D3 binary classifiers, which were trained using linear (relative band power, alpha power variability, spectral asymmetry index) and nonlinear (Higuchi fractal dimension, Lempel–Ziv complexity, detrended fluctuation analysis) EEG features. The age- and gender-matched dataset consisted of 10 healthy subjects and 10 subjects diagnosed with depression at some point in their lifetime. Most of the proposed feature selection and classifier combinations achieved accuracy in the range of 80% to 95%, and all the models were evaluated using a 10-fold cross-validation. The results showed that the motioned EEG features used in classifying ongoing depression also work for classifying the long-lasting effects of depression.     

Solid-phase extraction of Pb2+ ion from environmental samples onto L-AC-Ag-NP by flame atomic absorption spectrometry (FAAS)

The development of a solid-phase extraction (SPE) procedure for the pre-concentration of trace amounts of Pb²⁺ ion on 2-furan-2-yl-1-furan-2-ylmethyl-1H-benzoimidazole loaded on activated carbon modified with silver nanoparticles (L-AC-Ag-NP) was presented. The metal ion retained on the sorbent was quantitatively determined via complexation with the ligand. The complexed metal ion was efficiently eluted using 10 mL of 4 mol L^?1 sulphuric acid in 10 w/v% acetone. The influences of the analytical parameters, including pH, amounts of the ligand and the solid phase, eluent conditions and sample volume, on the recoveries of the metal ion were optimised. Using the optimised parameters, the linear response of the SPE method for Pb²⁺ ion were in the ranges of 0.2–160 µg L^?1, and the detection limit for Pb²⁺ ion was 0.034 µg L^?1. The proposed method exhibits a pre-concentration factor (PF) of 80 and an enhancement factor of 30 for Pb²⁺ ion. The presented results demonstrate the successful application of the proposed method for the determination of Pb²⁺ ion in some real samples with high recoveries (>93%) and reasonable relative standard deviation (RSD < 2%).     

Ultra-trace determination of arsenic species in environmental waters,food and biological samples using a modified aluminum oxide nanoparticle sorbent and AAS detection after multivariate optimization

We describe a simple and efficient method for solid phase extraction and speciation of trace quantities of arsenic. It is based on the use of functionalized aluminum oxide nanoparticles and does not require any oxidation or reduction steps. The experimental parameters affecting extraction and quantitation were optimized using fractional factorial design methods. Adsorbed arsenic was eluted from the sorbent with 1 M hydrochloric acid and determined by graphite furnace atomic absorption spectrometry. Preconcentration factors up to 750 were achieved depending on the sample volume. Studies on potential interferences by various anions and cations showed the method to be highly selective. Under optimum conditions, the calibration plots are linear in the 5.0 to 280 ng L⁻¹ and 8.0 to 260 ng L⁻¹ concentration ranges for As(III) and total arsenic, respectively. The detection limits (calculated for S/N ratios of 3) are 1.81 and 1.97 ng L⁻¹ for As(III) and total arsenic, respectively. The method was successfully applied to the determination and speciation of arsenic in (spiked) environmental, food and biological samples and gave good recoveries. The method was validated using a certified geological reference material.

Novel functionalized Al₂O₃ nanoparticles were synthesized and used for speciation and determination of arsenic in different samples. The experimental variables were optimized using fractional factorial design that can save time and operational costs.

     

Preparation of ethylene/α-olefins copolymers using (2-RInd)2ZrCl2/MCM-41 (R:Ph,H) catalyst,microstructural study

(2-RInd)₂ZrCl₂ (R:Ph,H) catalyst was supported on MCM-41 and ethylene copolymerization behavior as well as microstructure of copolymers were studied. A steady rate–time profile behavior was observed for homo and copolymerization of ethylene using supported catalysts. It was noticed that increasing the comonomer content can result in lower physical properties. The obtained results indicated that (2-PhInd)₂ZrCl₂/MCM-41 had higher ability of comonomer incorporation than the non-substituted supported catalysts. The CCC, CCE, and ECC (C: comonomer, E: ethylene) triad sequence distribution in backbone of copolymers were negligible, that means no evidence could be detected for comonomer blocks. The polymer characterization revealed that utilizing 1-octene instead of 1-hexene as the comonomer leads to more heterogeneous distribution of chemical composition. The heterogeneity of the chemical composition distribution and the physical properties were influenced by the type of comonomer and catalyst. (2-PhInd)₂ZrCl₂/MCM-41 produced copolymers containing narrower distribution of lamellae (0.3–1 nm) than the copolymer produce using Ind₂ZrCl₂/MCM-41 (0.3–1.6 nm).     

Determination of fatty acids by high-performance liquid chromatography and fluorescence detection using precolumn derivatization with 9-fluorenylmethyl chloroformate

A new high-performance liquid chromatographic method is described for the determination of fatty acids in seed oils. The method was based on precolumn derivatization with 9-fluorenylmethyl chloroformate as a labeling agent and fluorescence detection. Fatty acids were extracted from the samples and subjected to derivatization with the reagent at 60°C for 10?min. The chromatographic separation of 14 fatty acids (C10–C22) was achieved on a combined loading compression octadecyl sulfate (CLC-ODS) column with a run time of 30?min. Three-step gradient elution of a mobile phase consisted of acetonitrile and water was used, and the signal was monitored at excitation and emission wavelengths of 265 and 315?nm, respectively. The method indicated favorable sensitivity and reproducibility for fatty acids’ derivatives. The detection limits, at a signal-to-noise ratio of 3, were 0.01–0.05?µg/ml and relative standard deviations (RSDs) were less than 0.27%. Excellent linear responses were observed with coefficients of 0.9995. This method was applied to quantify fatty acids in white, brown, and black sesame seeds’ oil.     

Turbulent forced convection heat transfer of non-Newtonian nanofluids

Forced convection heat transfer of non-Newtonian nanofluids in a circular tube with constant wall temperature under turbulent flow conditions was investigated experimentally. Three types of nanofluids were prepared by dispersing homogeneously γ-Al₂O₃, TiO₂ and CuO nanoparticles into the base fluid. An aqueous solution of carboxymethyl cellulose (CMC) was used as the base fluid. Nanofluids as well as the base fluid show shear-thinning (pseudoplastic) rheological behavior. Results indicate that the convective heat transfer coefficient of nanofluids is higher than that of the base fluid. The enhancement of the convective heat transfer coefficient increases with an increase in the Peclet number and the nanoparticle concentration. The increase in the convective heat transfer coefficient of nanofluids is greater than the increase that would be observed considering strictly the increase in the effective thermal conductivity of nanofluids. Experimental data were compared to heat transfer coefficients predicted using available correlations for purely viscous non-Newtonian fluids. Results show poor agreement between experimental and predicted values. New correlation was proposed to predict successfully Nusselt numbers of non-Newtonian nanofluids as a function of Reynolds and Prandtl numbers.     

Investigation of the effect of the added mass fluctuation and lateral vibration absorbers on the vertical nonlinear vibrations of the offshore wind turbine

Nonlinear Dynamics - In this article, the effects of the changes in the mass of the floating wind turbine (as a multi-body system) on its nonlinear vertical vibrations are investigated. The...     

Pool boiling heat transfer performance of Newtonian nanofluids

Experimental measurements were carried out on the boiling heat transfer characteristics of γ-Al₂O₃/water and SnO₂/water Newtonian nanofluids. Nanofluids are liquid suspensions containing nanoparticles with sizes smaller than 100 nm. In this research, suspensions with different concentrations of γ-Al₂O₃ and SnO₂ nanoparticles in water were studied under nucleate pool boiling heat transfer conditions. Results show that nanofluids possess noticeably higher boiling heat transfer coefficients than the base fluid. The boiling heat transfer coefficients depend on the type and concentration of nanoparticles.     

Effects of the van der Waals force,squeeze-film damping,and contact bounce on the dynamics of electrostatic microcantilevers before and after pull-in

The operational range of microcantilever beams under electrostatic force can be extended beyond pull-in in the presence of an intermediate dielectric layer. In this paper, a systematic method for deriving dynamic equation of microcantilevers under electrostatic force is presented. This model covers the behavior of the microcantilevers before and after the pull-in including the effects of van der Waals force, squeeze-film damping, and contact bounce. First, a polynomial approximate shape function with a time-dependent variable for each configuration is defined. Using Hamilton’s principle, dynamic equations of microcantilever in all configurations have been derived. Comparison between modeling results and previous experimental data that have been used for validation of the model shows a good agreement.