A new linearly constrained minimum variance beamformer for reconstructing EEG sparse sources

Brain source imaging based on EEG aims to reconstruct the neural activities producing the scalp potentials. This includes solving the forward and inverse problems. The aim of the inverse problem is to estimate the activity of the brain sources based on the measured data and leadfield matrix computed in the forward step. Spatial filtering, also known as beamforming, is an inverse method that reconstructs the time course of the source at a particular location by weighting and linearly combining the sensor data. In this paper, we considered a temporal assumption related to the time course of the source, namely sparsity, in the Linearly Constrained Minimum Variance (LCMV) beamformer. This assumption sounds reasonable since not all brain sources are active all the time such as epileptic spikes and also some experimental protocols such as electrical stimulations of a peripheral nerve can be sparse in time. Developing the sparse beamformer is done by incorporating L1-norm regularization of the beamformer output in the relevant cost function while obtaining the filter weights. We called this new beamformer SParse LCMV (SP-LCMV). We compared the performance of the SP-LCMV with that of LCMV for both superficial and deep sources with different amplitudes using synthetic EEG signals. Also, we compared them in localization and reconstruction of sources underlying electric median nerve stimulation. Results show that the proposed sparse beamformer can enhance reconstruction of sparse sources especially in the case of sources with high amplitude spikes.     

Design of a low cross‐talk micro‐coil array for micro‐scale MRI

Design of magnetic resonance micro‐coil arrays with low cross‐talk among the coils can be the main challenge to improve the effectiveness of magnetic resonance micro‐imaging because the electrical cross‐talk which is mainly due to the inductive coupling perturbs the sensitivity profile of the array and causes image artifacts. In this work, a capacitive decoupling network with N(M ? 1) + (N ? 1)(M ? 2) capacitors is proposed to reduce the inductive coupling in an N × M array. A 3 × 3 array of optimized micro‐coils is designed using the finite element simulations and all the needed elements for the array equivalent circuit are extracted in order to evaluate the effectiveness of the proposed decoupling method by assessing the reduction of the coupled signals after employing the capacitive network on the circuit. The achieved results for the designed array show that the high cross‐talk level is reduced by the factor of 2.2–3.4 after employing the capacitive network. By employing this method of decoupling, the adjacent coils in each row and inner columns can be decoupled properly while the minimum decoupling belongs to the outer columns because of the lack of all necessary decoupling capacitances for these columns. The main advantages of the proposed decoupling method are its efficiency and design easiness which facilitates the design of dense arrays with the properly decoupled coils, especially the inner coils which are more coupled due to their neighbors. © 2013 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 23, 353–359, 2013     

Mixing of Oil in Water Through Electrical Resistance Tomography and Response Surface Methodology

The mixing performance of the oil‐in‐water dispersion system was evaluated. Using an electrical resistance tomography system composed of two measuring planes, the effect of parameters such as impeller type, impeller speed, oil type, and oil volume fraction on the mixing performance through axial mixing indices were explored. The oil type and the oil volume fraction were identified as the most influential factors on the mixing index. Castor oil, with the highest viscosity of the tested oils, was found as the most difficult oil to disperse. The Scaba impeller was the most efficient impeller in dispersing oil in water. The interactions between oil type and impeller type as well as between impeller speed and oil type, had the greatest impact on the mixing index.     

Simulation and Estimation of Vapor-Liquid Equilibrium for Asymmetric Binary Systems (CO2-Alcohols) Using Artificial Neural Network

Since it is not always possible to carry out experiments at all desired temperatures and pressures, generally thermodynamic models based on equations of state are used for estimation of vapor-liquid equilibrium. In this work, a method using artificial neural network (ANN) was designed and applied to simulate and estimate the VLE for the binary asymmetric systems containing CO₂ and Alcohols. The vapor-liquid equilibrium data of six systems include (CO₂-methanol), (CO₂-ethanol), (CO₂-1-butanol), (CO₂-2-butanol), (CO₂-1-pentanol) and (CO₂-2-pentanol) were used to developed the ANN for simulation of VLE. The results when using a developed ANN model or other methods such as SRK equations of state with LCVM, PSRK, WS, were compared with experimental data at various temperatures and pressures. Finally, it was observed that there is more qualitative and quantitative conformity between ANN model results and experimental data. Furthermore, the developed ANN model showed more accurate estimation over wide range of experimental conditions.     

An efficient method for nitration of aromatic compounds over solid acid and polymer‐supported sodium nitrite

A variety of aromatic compounds are nitrated under heterogeneous conditions using a polymer‐supported hydrochloric acid, [P₄‐(VP)]HCl, with a polymer‐supported sodium nitrite, [P₄‐VP]NO₂, or sodium nitrite in ethanol at room temperature with high yields. This methodology is useful for nitration of activated aromatic compounds. In this procedure, the work‐up is very easy, and the spent polymeric reagent can be regenerated and reused. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011     

Regioselective and green synthesis of nitro aromatic compounds using polymer‐supported sodium nitrite/KHSO4

Polymer supported reagents have become the subject of considerable and increasing interest as insoluble materials in the organic synthesis. Use of polymeric reagents simplifies routine nitration of aromatic compounds because it eliminates traditional purification. In this article, the use of readily available cross‐linked poly(4‐vinylpyridine) supported sodium nitrite, [P₄‐Me] NO₂, as an efficient polymeric nitrating agent in the presence of KHSO₄ is described. A good range of available aromatic compounds were also subjected to nitration in the presence of [P₄‐Me] NO₂/KHSO₄. This reagent is regioselective and chemoselective nitrating polymeric reagent for activated aromatic rings. In this procedure, the work‐up is easy, and the spent polymeric reagent is easily regenerated and reused. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011