Hybrid signal processing and machine intelligence techniques for detection,quantification and classification of power quality disturbances

This paper presents an advanced signal processing technique known as S-transform (ST) to detect and quantify various power quality (PQ) disturbances. ST is also utilized to extract some useful features of the disturbance signal. The excellent time–frequency resolution characteristic of the ST makes it an attractive candidate for analysis of power system disturbance signals. The number of features required in the proposed approach is less than that of the wavelet transform (WT) for identification of PQ disturbances. The features extracted by using ST are used to train a support vector machine (SVM) classifier for automatic classification of the PQ disturbances. Since the proposed methodology can reduce the features of disturbance signal to a great extent without losing its original property, it efficiently utilizes the memory space and computation time of the processor. Eleven types of PQ disturbances are considered for the classification purpose. The simulation results show that the combination of ST and SVM can effectively detect and classify different PQ disturbances.     

MHD combined free and forced convection flow through two parallel porous walls

Summary The flow of a viscous conducting fluid between two parallel plates of infinite length (one of which is at rest and the other moving parallel to itself with a linear axial temperature variation) under the influence of a uniform transverse magnetic field is considered. It is assumed that the fluid is injected into the channel through the lower wall and sucked from the channel through the upper wall with the same velocityv ₀. The velocity and temperature distributions, the coefficient of skin friction and the rate of heat transfer coefficient are evaluated. The effects of magnetic parameterM, the suction Reynolds numberR, the Grashoff numberG and Binkmann numberB on the above mentioned physical quantities are investigated.With 21 Figures     

PEO／V2O5纳米复合薄膜的变色特性研究

为改善V2O5薄膜的电致变色性能，采用溶胶-凝胶法将具有高离子电导率并具有水溶性的聚环氧乙烷（PEO）直接嵌入V2O5层间，制备了PEO／V2O5纳米复合薄膜。采用标准三电极法从0．5mol／L LiClO4的PC电解质溶液向PEO／V2O5纳米复合薄膜注入锂离子，测量了纳米复合薄膜在注入不同数量锂离子时的可见光透射光谱以及对应的颜色变化，并运用循环伏安法测试其电化学性能。实验结果表明，PEO／V2O5纳米复合薄膜的循环伏安图出现了2对氧化还原峰，并且具有稳定的循环可逆性。随着应用电压的不同，薄膜呈现黄色、绿色和蓝色的多色可逆变化。PEO／V2O5纳米复合薄膜的电化学稳定性和机械性能都优于V2O5干凝胶薄膜，可以作为电致变色材料得到应用。X射线光电子能谱（XPS）成分分析表明PEO／V2O5纳米复合薄膜的电致变色效应与V、O的化合价和化学环境密切相关。     

Non‐linear finite element modal approach for the large amplitude free vibration of symmetric and unsymmetric composite plates

A theoretical analysis is presented for the large amplitude vibration of symmetric and unsymmetric composite plates using the non‐linear finite element modal reduction method. The problem is first reduced to a set of Duffing‐type modal equations using the finite element modal reduction method. The main advantage of the proposed approach is that no updating of the non‐linear stiffness matrices is needed. Without loss of generality, accurate frequency ratios for the fundamental mode and the higher modes of a composite plate at various values of maximum deflection are then determined by using the Runge–Kutta numerical integration scheme. The procedure for obtaining proper initial conditions for the periodic plate motions is very time consuming. Thus, an alternative scheme (the harmonic balance method) is adopted and assessed, as it was employed to formulate the large amplitude free vibration of beams in a previous study, and the results agreed well with the elliptic solution. The numerical results that are obtained with the harmonic balance method agree reasonably well with those obtained with the Runge–Kutta method. The contribution of each linear mode to the maximum deflection of a plate can also be obtained. The frequency ratios for isotropic and composite plates at various maximum deflections are presented, and convergence of frequencies with the number of finite elements, number of linear modes, and number of harmonic terms is also studied. Copyright © 2005 John Wiley & Sons, Ltd.     

Characteristics of soil-cement blocks using highly sandy soils

Soil-cement blocks also known as compressed earth blocks or stabilised mud blocks are used for load bearing masonry. The paper focuses on the study of various characteristics of soil-cement blocks using highly sandy soils through an experimental investigation. Characteristics of soilcement blocks having three different cement contents (6%, 8% and 12%) have been examined. Paper reports results of influence of cement content on compressive strength, tensile strength, the initial rate of absorption (IRA), water absorption, rate of water absorption, surface porosity and pore size, stress-strain relationships and elastic properties of soil-cement blocks. The results indicate that there is 2.5 times increase in strength for doubling of cement content from 6%. IRA decreases drastically with the increase in cement content of the block. Saturated water content of the blocks is not sensitive to cement content, whereas rate of moisture absorption greatly depends on the cement content. Pore size decreases with increase in cement content of block, whereas surface porosity is independent of the cement content. Soil-cement block modulus varies between 2000 and 6000MPa. Elastic modulus increases by 2.5 times when the cement content is increased from 6 to 8%, whereas the increase in modulus is marginal when cement content goes from 8 to 12%.     

Neural networks for estimating the tool path length in concurrent engineering applications

This paper deals with the development of a neural computing system that can predict the cutting tool path length for milling an arbitrary pocket defined within the domain of a product design, in a computer numerically controlled (CNC) setting. Existing computer aided design and manufacturing systems (CAD/CAM) consume significant amounts of time in terms of data entry pertaining to the geometries and subsequent modifications to them. In the concurrent engineering environment, where even the designer needs information from the CAD/CAM systems, such time-consuming processes can be expensive. To alleviate this problem, a neural network system can be used to estimate machining time by predicting cost-dependent variables such as tool path length for the pocket milling operation. Pockets are characterized and classified into various groups. A randomized design is described so that the training samples that have been chosen represent the domain evenly. An appropriate network was built and trained with the sample pocket geometries. The analysis of the performance of the system in terms of tool path length prediction for new pocket geometries is presented.     

Variable Expression of GABAA Receptor Subunit Gamma 2 Mutation in a Nuclear Family Displaying Developmental and Encephalopathic Phenotype

Mutations in GABA_A receptor subunit genes (GABRs) are a major etiology for developmental and epileptic encephalopathies (DEEs). This article reports a case of a genetic abnormality in GABRG2 and updates the pathophysiology and treatment development for mutations in DEEs based on recent advances. Mutations in GABRs, especially in GABRA1, GABRB2, GABRB3, and GABRG2, impair GABAergic signaling and are frequently associated with DEEs such as Dravet syndrome and Lennox–Gastaut syndrome, as GABAergic signaling is critical for early brain development. We here present a novel association of a microdeletion of GABRG2 with a diagnosed DEE phenotype. We characterized the clinical phenotype and underlying mechanisms, including molecular genetics, EEGs, and MRI. We then compiled an update of molecular mechanisms of GABR mutations, especially the mutations in GABRB3 and GABRG2 attributed to DEEs. Genetic therapy is also discussed as a new avenue for treatment of DEEs through employing antisense oligonucleotide techniques. There is an urgent need to define treatment targets and explore new treatment paradigms for the DEEs, as early deployment could alleviate long-term disabilities and improve quality of life for patients. This study highlights biomolecular targets for future therapeutic interventions, including via both pharmacological and genetic approaches.     

Reduced VDAC1, Maintained Mitochondrial Dynamics and Enhanced Mitochondrial Biogenesis in a Transgenic Tau Mouse Model of Alzheimer’s Disease

Alzheimer’s disease (AD) is one of the most common forms of neurodegeneration, defined by reduced cognitive function, which is caused by the gradual death of neurons in the brain. Recent studies have shown an age-dependent rise in the levels of voltage-dependent anion channel 1 (VDAC1) in AD. In addition, we discovered an aberrant interaction between VDAC1 and P-TAU in the brains of AD patients, which led to abnormalities in the structural and functional integrity of the mitochondria. The purpose of our study is to understand the protective effects of reduced VDAC1 against impaired mitochondrial dynamics and defective mitochondrial biogenesis in transgenic TAU mice. Recently, we crossed heterozygote VDAC1 knockout (VDAC1^+/−) mice with transgenic TAU mice to obtain double-mutant VDAC1^+/−/TAU mice. Our goal was to evaluate whether a partial decrease in VDAC1 lessens the amount of mitochondrial toxicity in transgenic Tau (P301L) mice. We found that mitochondrial fission proteins were significantly reduced, and mitochondrial fusion and biogenesis proteins were increased in double-mutant mice compared to TAU mice. On the basis of these discoveries, the current work may have significance for the development of reduced-VDAC1-based treatments for individuals suffering from AD as well as other tauopathies.