Seismic progressive-failure analysis of tall steel structures under beam-removal scenarios

Investigating progressive collapse of tall structures under beam removal scenarios after earthquake is a complex subject because the earthquake damage acts as an initial condition for the subsequent scenario. An investigation is performed here on a 10 story steel moment resisting structure designed to meet the life safety level of performance when different beam removal scenarios after earthquake are considered. To this end, the structure is first subjected to the design earthquake simulated by Tabas earthquake acceleration. The beam removal scenarios are then considered at different locations assuming that both ends connections of the beam to columns are simultaneously detached from the columns; thus the removed beam falls on the underneath floor with an impact. This imposes considerable loads to the structure leading to a progressive collapse in all the scenarios considered. The results also show that the upper stories are much more vulnerable under such scenarios than the lower stories. Hence, more attention shall be paid to the beam-to-column connections of the upper stories during the process of design and construction.     

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.     

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.     

Dynamics of a neuron exposed to integer- and fractional-order discontinuous external magnetic flux

We propose a modified Fitzhugh-Nagumo neuron (MFNN) model. Based on this model, an integer-order MFNN system (case A) and a fractional-order MFNN system (case B) were investigated. In the presence of electromagnetic induction and radiation, memductance and induction can show a variety of distributions. Fractional-order magnetic flux can then be considered. Indeed, a fractional-order setting can be acceptable for non-uniform diffusion. In the case of an MFNN system with integer-order discontinuous magnetic flux, the system has chaotic and non-chaotic attractors. Dynamical analysis of the system shows the birth and death of period doubling, which is a sign of antimonotonicity. Such a behavior has not been studied previously in the dynamics of neurons. In an MFNN system with fractional-order discontinuous magnetic flux, different attractors such as chaotic and periodic attractors can be observed. However, there is no sign of antimonotonicity.

     

Low-voltage and low-power Ku-band CMOS LNA using capacitive feedback

Analog Integrated Circuits and Signal Processing - An ultra-wideband (12–18 GHz) low-noise amplifier (LNA) using a 65 nm CMOS technology is proposed, in which a...     

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     

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