Micro-shock wave assisted bacterial transformation

A gene is a unit of heredity in a living organism. It normally resides on a stretch of DNA that codes for a type of protein or for an RNA chain that has a function in the organism. All living things depend on genes, as they specify all proteins and functional RNA chains. Genes hold the information to build and maintain an organism’s cells and pass genetic traits to offspring. The gene has to be transferred to bacteria or eukaryotic cells for basic and applied molecular biology studies. Bacteria can uptake exogenous genetic material by three ways: conjugation, transduction and transformation. Genetic material is naturally transferred to bacteria in case of conjugation and transferred through bacteriophage in transduction. Transformation is the acquisition of exogenous genetic material through cell wall. The ability of bacteria of being transformed is called competency and those bacteria which have competency are competent cells. Divalent Calcium ions can make the bacteria competent and a heat shock can cause the bacteria to uptake DNA. But the heat shock method cannot be used for all the bacteria. In electroporation, a brief electric shock with an electric field of 10-20kV/cmmakes pores in the cell wall, facilitates the DNA to enter into the bacteria. Microprecipitates, microinjection, liposomes, and biological vectors are also used to transfer polar molecules like DNA into host cells.

A method for measurement of planar liquid volume fraction in dense sprays

A methodology for measurement of planar liquid volume fraction in dense sprays using a combination of Planar Laser-Induced Fluorescence (PLIF) and Particle/Droplet Imaging Analysis (PDIA) is presented in this work. The PLIF images are corrected for loss of signal intensity due to laser sheet scattering, absorption and auto-absorption. The key aspect of this work pertains to simultaneously solving the equations involving the corrected PLIF signal and liquid volume fraction. From this, a quantitative estimate of the planar liquid volume fraction is obtained. The corrected PLIF signal and the corrected planar Mie scattering can be also used together to obtain the Sauter Mean Diameter (SMD) distribution by using data from the PDIA technique at a particular location for calibration. This methodology is applied to non-evaporating sprays of diesel and a more viscous pure plant oil at an injection pressure of 1000 bar and a gas pressure of 30 bar in a high pressure chamber. These two fuels are selected since their viscosity values are very different with a consequently very different spray structure. The spatial distribution of liquid volume fraction and SMD is obtained for two fuels. The proposed method is validated by comparing liquid volume fraction obtained by the current method with data from PDIA technique. (C) 2012 Elsevier Inc. All rights reserved.

Influence of strain localization on reliability based design of bridge abutments using pseudo-dynamic method

The paper focuses on reliability based design of bridge abutments when subjected to earthquake loading. Planar failure surface has been used in conjunction with pseudo-dynamic approach to compute the seismic active earth pressures on the bridge abutment. The proposed pseudo dynamic method, considers the effects of strain localization in the backfill soil and associated post-peak reduction in the shear resistance from peak to residual values along a previously formed failure plane, phase difference in shear waves and soil amplification along with the horizontal seismic accelerations. Four modes of stability viz. sliding, overturning, eccentricity and bearing capacity of the foundation soil are considered for the reliability analysis. The influence of various design parameters on the seismic reliability indices against four modes of failure is presented, following the suggestions of Japan Road Association, Caltrans Bridge Design Specifications and U.S Department of the Army.

A Finite Element Method Based Approach for Evaluating the Sensitivity of Faraday-Type Electromagnetic Flow Meter for Liquid Sodium Flow

Faraday-type electromagnetic flow meters are employed for measuring the flow rate of liquid sodium in fast breeder reactors. The calibration of such flow meters, owing to the required elaborative arrangements is rather difficult. On the other hand, theoretical approach requires solution of two coupled electromagnetic partial differential equation with profile of the flow and applied magnetic field as the inputs. This is also quite involved due to the 3D nature of the problem. Alternatively, Galerkin finite element method based numerical solution is suggested in the literature as an attractive option for the required calibration. Based on the same, a computer code in Matlab platform has been developed in this work with both 20 and 27 node brick elements. The boundary conditions are correctly defined and several intermediate validation exercises are carried out. Finally it is shown that the sensitivities predicted by the code for flow meters of four different dimensions agrees well with the results given by analytical expression, thereby providing strong validation. Sensitivity for higher flow rates, for which analytical approach does not exist, is shown to decrease with increase in flow velocity.

A LSQR-type method provides a computationally efficient automated optimal choice of regularization parameter in diffuse optical tomography

Purpose: Developing a computationally efficient automated method for the optimal choice of regularization parameter in diffuse optical tomography. Methods: The least-squares QR (LSQR)-type method that uses Lanczos bidiagonalization is known to be computationally efficient in performing the reconstruction procedure in diffuse optical tomography. The same is effectively deployed via an optimization procedure that uses the simplex method to find the optimal regularization parameter. The proposed LSQR-type method is compared with the traditional methods such as L-curve, generalized cross-validation (GCV), and recently proposed minimal residual method (MRM)-based choice of regularization parameter using numerical and experimental phantom data. Results: The results indicate that the proposed LSQR-type and MRM-based methods performance in terms of reconstructed image quality is similar and superior compared to L-curve and GCV-based methods. The proposed method computational complexity is at least five times lower compared to MRM-based method, making it an optimal technique. Conclusions: The LSQR-type method was able to overcome the inherent limitation of computationally expensive nature of MRM-based automated way finding the optimal regularization parameter in diffuse optical tomographic imaging, making this method more suitable to be deployed in real-time. (C) 2013 American Association of Physicists in Medicine. http://dx.doi.org/10.1118/1.4792459]

Method for Seismic Microzonation with Geotechnical Aspects

This study presents an overview of seismic microzonation and existing methodologies with a newly proposed methodology covering all aspects. Earlier seismic microzonation methods focused on parameters that affect the structure or foundation related problems. But seismic microzonation has generally been recognized as an important component of urban planning and disaster management. So seismic microzonation should evaluate all possible hazards due to earthquake and represent the same by spatial distribution. This paper presents a new methodology for seismic microzonation which has been generated based on location of study area and possible associated hazards. This new method consists of seven important steps with defined output for each step and these steps are linked with each other. Addressing one step and respective result may not be seismic microzonation, which is practiced widely. This paper also presents importance of geotechnical aspects in seismic microzonation and how geotechnical aspects affect the final map. For the case study, seismic hazard values at rock level are estimated considering the seismotectonic parameters of the region using deterministic and probabilistic seismic hazard analysis. Surface level hazard values are estimated considering site specific study and local site effects based on site classification/characterization. The liquefaction hazard is estimated using standard penetration test data. These hazard parameters are integrated in Geographical Information System (GIS) using Analytic Hierarchy Process (AHP) and used to estimate hazard index. Hazard index is arrived by following a multi-criteria evaluation technique - AHP, in which each theme and features have been assigned weights and then ranked respectively according to a consensus opinion about their relative significance to the seismic hazard. The hazard values are integrated through spatial union to obtain the deterministic microzonation map and probabilistic microzonation map for a specific return period. Seismological parameters are widely used for microzonation rather than geotechnical parameters. But studies show that the hazard index values are based on site specific geotechnical parameters.

Sequential alternating proximal method for scalable sparse structural SVMs

Structural Support Vector Machines (SSVMs) have recently gained wide prominence in classifying structured and complex objects like parse-trees, image segments and Part-of-Speech (POS) tags. Typical learning algorithms used in training SSVMs result in model parameters which are vectors residing in a large-dimensional feature space. Such a high-dimensional model parameter vector contains many non-zero components which often lead to slow prediction and storage issues. Hence there is a need for sparse parameter vectors which contain a very small number of non-zero components. L1-regularizer and elastic net regularizer have been traditionally used to get sparse model parameters. Though L1-regularized structural SVMs have been studied in the past, the use of elastic net regularizer for structural SVMs has not been explored yet. In this work, we formulate the elastic net SSVM and propose a sequential alternating proximal algorithm to solve the dual formulation. We compare the proposed method with existing methods for L1-regularized Structural SVMs. Experiments on large-scale benchmark datasets show that the proposed dual elastic net SSVM trained using the sequential alternating proximal algorithm scales well and results in highly sparse model parameters while achieving a comparable generalization performance. Hence the proposed sequential alternating proximal algorithm is a competitive method to achieve sparse model parameters and a comparable generalization performance when elastic net regularized Structural SVMs are used on very large datasets.

Growth and characterization of micro and nanostructures of lead telluride (PbTe) by thermal evaporation method

Lead telluride micro and nanostructures have been grown on silicon and glass substrates by a simple thermal evaporation of PbTe in high vacuum of 3 x 10(-5) mbar. Growth was carried out for two different distances between the evaporation source and the substrates. Synthesized products consist of nanorods and micro towers for 2.4 cm and 3.4 cm of distance between the evaporation source and the substrates respectively. X-ray diffraction and transmission electron microscopy studies confirmed crystalline nature of the nanorods and micro towers. Nanorods were grown by vapor solid mechanism. Each micro tower consists of nano platelets and is capped with spherical catalyst particle at their end, suggesting that the growth proceeds via vapor-liquid-solid (VLS) mechanism. EDS spectrum recorded on the tip of the micro tower has shown the presence of Pb and Te confirming the self catalytic VLS growth of the micro towers. These results open up novel synthesis methods for PbTe nano and microstructures for various applications.

Synthesis, microstructure and thermal expansion studies on Ca0 center dot 5+x/2Sr0 center dot 5+x/2Zr4P6-2x Si-2x O-24 system prepared by co-precipitation method

We report on the synthesis, microstructure and thermal expansion studies on Ca0 center dot 5 + x/2Sr0 center dot 5 + x/2Zr4P6 -aEuro parts per thousand 2x Si-2x O-24 (x = 0 center dot 00 to 1 center dot 00) system which belongs to NZP family of low thermal expansion ceramics. The ceramics synthesized by co-precipitation method at lower calcination and the sintering temperatures were in pure NZP phase up to x = 0 center dot 37. For x a parts per thousand yen 0 center dot 5, in addition to NZP phase, ZrSiO4 and Ca2P2O7 form as secondary phases after sintering. The bulk thermal expansion behaviour of the members of this system was studied from 30 to 850 A degrees C. The thermal expansion coefficient increases from a negative value to a positive value with the silicon substitution in place of phosphorous and a near zero thermal expansion was observed at x = 0 center dot 75. The amount of hysteresis between heating and cooling curves increases progressively from x = 0 center dot 00 to 0 center dot 37 and then decreases for x > 0 center dot 37. The results were analysed on the basis of formation of the silicon based glassy phase and increase in thermal expansion anisotropy with silicon substitution.

Stiff string approximations in Rayleigh-Ritz method for rotating beams

The governing differential equation of the rotating beam reduces to that of a stiff string when the centrifugal force is assumed as constant. The solution of the static homogeneous part of this equation is enhanced with a polynomial term and used in the Rayleighs method. Numerical experiments show better agreement with converged finite element solutions compared to polynomials. Using this as an estimate for the first mode shape, higher mode shape approximations are obtained using Gram-Schmidt orthogonalization. Estimates for the first five natural frequencies of uniform and tapered beams are obtained accurately using a very low order Rayleigh-Ritz approximation.

Surfactant free, non-aqueous method, for the deposition of ZnO nanoparticle thin films on Si(100) substrate with tunable ultraviolet (UV) emission

We report, strong ultraviolet (UV) emission from ZnO nanoparticle thin film obtained by a green synthesis, where the film is formed by the microwave irradiation of the alcohol solution of the precursor. The deposition is carried out in non-aqueous medium without the use of any surfactant, and the film formation is quick (5 min). The film is uniform comprising of mono-disperse nanoparticles having a narrow size distribution (15-22 nm), and that cover over an entire area (625 mm(2)) of the substrate. The growth rate is comparatively high (30-70 nm/min). It is possible to tune the morphology of the films and the UV emission by varying the process parameters. The growth mechanism is discussed precisely and schematic of the growth process is provided.

A multichannel sampling method for 2-D finite-rate-of-innovation signals

We address the problem of sampling and reconstruction of two-dimensional (2-D) finite-rate-of-innovation (FRI) signals. We propose a three-channel sampling method for efficiently solving the problem. We consider the sampling of a stream of 2-D Dirac impulses and a sum of 2-D unit-step functions. We propose a 2-D causal exponential function as the sampling kernel. By causality in 2-D, we mean that the function has its support restricted to the first quadrant. The advantage of using a multichannel sampling method with causal exponential sampling kernel is that standard annihilating filter or root-finding algorithms are not required. Further, the proposed method has inexpensive hardware implementation and is numerically stable as the number of Dirac impulses increases.

Gene expression programming-fuzzy logic method for crop type classification

Crop type classification using remote sensing data plays a vital role in planning cultivation activities and for optimal usage of the available fertile land. Thus a reliable and precise classification of agricultural crops can help improve agricultural productivity. Hence in this paper a gene expression programming based fuzzy logic approach for multiclass crop classification using Multispectral satellite image is proposed. The purpose of this work is to utilize the optimization capabilities of GEP for tuning the fuzzy membership functions. The capabilities of GEP as a classifier is also studied. The proposed method is compared to Bayesian and Maximum likelihood classifier in terms of performance evaluation. From the results we can conclude that the proposed method is effective for classification.