Site characterization model using least-square support vector machine and relevance vector machine based on corrected SPT data (N-c)

Statistical learning algorithms provide a viable framework for geotechnical engineering modeling. This paper describes two statistical learning algorithms applied for site characterization modeling based on standard penetration test (SPT) data. More than 2700 field SPT values (N) have been collected from 766 boreholes spread over an area of 220 sqkm area in Bangalore. To get N corrected value (N,), N values have been corrected (Ne) for different parameters such as overburden stress, size of borehole, type of sampler, length of connecting rod, etc. In three-dimensional site characterization model, the function N-c=N-c (X, Y, Z), where X, Y and Z are the coordinates of a point corresponding to N, value, is to be approximated in which N, value at any half-space point in Bangalore can be determined. The first algorithm uses least-square support vector machine (LSSVM), which is related to aridge regression type of support vector machine. The second algorithm uses relevance vector machine (RVM), which combines the strengths of kernel-based methods and Bayesian theory to establish the relationships between a set of input vectors and a desired output. The paper also presents the comparative study between the developed LSSVM and RVM model for site characterization. Copyright (C) 2009 John Wiley & Sons,Ltd.

Main chain and segmental dynamics of semi interpenetrating based on polyisoprene and poly(methyl methacrylate)

Main chain and segmental dynamics of polyisoprene (PI) and poly(methyl methacrylate)(PMMA) chains in semi IPNs were systematically studied over a wide range of temperatures (above and below T-g of both polymers) as a function of composition, crosslink density, and molecular weight. The immiscible polymers retained most of its characteristic molecular motion; however, the semi IPN synthesis resulted in dramatic changes in the motional behavior of both polymers due to the molecular level interpenetration between two polymer chains. ESR spin probe method was found to be sensitive to the concentration changes of PMMA in semi IPNs. Low temperature spectra showed the characteristics of rigid limit spectra, and in the range of 293-373 K.complex spectra were obtained with the slow component mostly arisingout of the PMMA rich regions and fast component from the PI phase. We found that the rigid PMMA chains closely interpenetrated into thehighly mobile PI network imparts motional restriction in nearby PI chains, and the highly mobile PI chains induce some degree of flexibility in highly rigid PMMA chains. Molecular level interchain mixing was found to be more efficient at a PMMA concentration of 35 wt.%. Moreover, the strong interphase formed in the above mentionedsemi IPN contributed to the large slow component in the ESR spectra at higher temperature. The shape of the spectra along with the data obtained from the simulations of spectra was correlated to the morphology of the semi IPNs. The correlation time measurement detected the motional region associated with the glass transition of PI and PMMA, and these regions were found to follow the same pattern of shifts in a-relaxation of PI and PMMA observed in DMA analysis. Activation energies associated with the T-g regions were also calculated. T-50G was found to correlate with the T-g of PMMA, and the volume of polymer segments undergoing glass transitional motion was calculated to be 1.7 nm(3).C-13 T-1 rho measurements of PMMA carbons indicate that the molecular level interactions were strong in semi IPN irrespective of the immiscible nature of polymers. The motional characteristics of H atoms attached to carbon atoms in both polymers were analyzed using 2D WISE NMR. Main relaxations of both components shifted inward, and both SEM and TEM analysis showed the development of a nanometer sized morphology in the case of highly crosslinked semi IPN. (C) 2010 Elsevier Ltd. All rights reserved.

Ambient temperature, zinc ion-conducting, binary molten electrolyte based on acetamide and zinc perchlorate: Application in rechargeable zinc batteries

Binary room temperature molten electrolytes based on acetamide and zinc perchlorate have been prepared and characterized. The electrolytes are found to be highly zinc ion-conducting with very favorable physicochemical and electrochemical characteristics. Raman and infrared spectroscopic studies reveal the presence of large free-ion concentration in the molten liquid. This is corroborated by the high conductivity observed under ambient conditions. Rechargeable zinc batteries assembled using gamma-MnO2 as the cathode and Zn as the anode with the molten electrolyte show high discharge capacities over several cycles, indicating excellent reversibility. This unique class of acetamide-based, room temperature molten liquids may become viable and green alternative electrolytes for rechargeable zinc-based secondary batteries. (C) 2009 Elsevier Inc. All rights reserved.

A novel approach for large-scale polypeptide folding based on elastic networks using continuous optimization

We present a new computationally efficient method for large-scale polypeptide folding using coarse-grained elastic networks and gradient-based continuous optimization techniques. The folding is governed by minimization of energy based on Miyazawa–Jernigan contact potentials. Using this method we are able to substantially reduce the computation time on ordinary desktop computers for simulation of polypeptide folding starting from a fully unfolded state. We compare our results with available native state structures from Protein Data Bank (PDB) for a few de-novo proteins and two natural proteins, Ubiquitin and Lysozyme. Based on our simulations we are able to draw the energy landscape for a small de-novo protein, Chignolin. We also use two well known protein structure prediction software, MODELLER and GROMACS to compare our results. In the end, we show how a modification of normal elastic network model can lead to higher accuracy and lower time required for simulation.

Dual-Drug Delivery System Based on In Situ Gel-Forming Nanosuspension of Forskolin to Enhance Antiglaucoma Efficacy

The present study was designed to improve the bioavailability of forskolin by the influence of precorneal residence time and dissolution characteristics. Nanosizing is an advanced approach to overcome the issue of poor aqueous solubility of active pharmaceutical ingredients. Forskolin nanocrystals have been successfully manufactured and stabilized by poloxamer 407. These nanocrystals have been characterized in terms of particle size by scanning electron microscopy and dynamic light scattering. By formulating Noveon AA-1 polycarbophil/poloxamer 407 platforms, at specific concentrations, it was possible to obtain a pH and thermoreversible gel with a pH(gel)/T-gel close to eye pH/temperature. The addition of forskolin nanocrystals did not alter the gelation properties of Noveon AA-1 polycarbophil/poloxamer 407 and nanocrystal properties of forskolin. The formulation was stable over a period of 6 months at room temperature. In vitro release experiments indicated that the optimized platform was able to prolong and control forskolin release for more than 5 h. The in vivo studies on dexamethasone-induced glaucomatous rabbits indicated that the intraocular pressure lowering efficacy for nanosuspension/hydrogel systems was 31% and lasted for 12 h, which is significantly better than the effect of traditional eye suspension (18%, 4-6 h). Hence, our investigations successfully prove that the pH and thermoreversible polymeric in situ gel-forming nanosuspension with ability of controlled drug release exhibits a greater potential for glaucoma therapy.

Probabilistic evaluation of seismic soil liquefaction potential based on SPT data

The performance-based liquefaction potential analysis was carried out in the present study to estimate the liquefaction return period for Bangalore, India, through a probabilistic approach. In this approach, the entire range of peak ground acceleration (PGA) and earthquake magnitudes was used in the evaluation of liquefaction return period. The seismic hazard analysis for the study area was done using probabilistic approach to evaluate the peak horizontal acceleration at bed rock level. Based on the results of the multichannel analysis of surface wave, it was found that the study area belonged to site class D. The PGA values for the study area were evaluated for site class D by considering the local site effects. The soil resistance for the study area was characterized using the standard penetration test (SPT) values obtained from 450 boreholes. These SPT data along with the PGA values obtained from the probabilistic seismic hazard analysis were used to evaluate the liquefaction return period for the study area. The contour plot showing the spatial variation of factor of safety against liquefaction and the corrected SPT values required for preventing liquefaction for a return period of 475 years at depths of 3 and 6 m are presented in this paper. The entire process of liquefaction potential evaluation, starting from collection of earthquake data, identifying the seismic sources, evaluation of seismic hazard and the assessment of liquefaction return period were carried out, and the entire analysis was done based on the probabilistic approach.

Angel Investing in Finland: An Analysis Based on Agency Theory and the Incomplete Contracting Theory

Wealthy individuals - business angels who invest a share of their net worth in entrepreneurial ventures - form an essential part of an informal venture capital market that can secure funding for entrepreneurial ventures. In Finland, business angels represent an untapped pool of capital that can contribute to fostering entrepreneurial development. In addition, business angels can bridge knowledge gaps in new business ventures by means of making their human capital available. This study has two objectives. The first is to gain an understanding of the characteristics and investment behaviour of Finnish business angels. The strongest focus here is on the due diligence procedures and their involvement post investment. The second objective is to assess whether agency theory and the incomplete contacting theory are useful theoretical lenses in the arena of business angels. To achieve the second objective, this study investigates i) how risk is mitigated in the investment process, ii) how uncertainty influences the comprehensiveness of due diligence as well as iii) how control is allocated post investment. Research hypotheses are derived from assumptions underlying agency theory and the incomplete contacting theory. The data for this study comprise interviews with 53 business angels. In terms of sample size this is the largest on Finnish business angels. The research hypotheses in this study are tested using regression analysis. This study suggests that the Finnish informal venture capital market appears to be comprised of a limited number of business angels whose style of investing much resembles their formal counterparts’. Much focus is placed on managing risks prior to making the investment by strong selectiveness and by a relatively comprehensive due diligence. The involvement is rarely on a day-to-day basis and many business angels seem to see board membership as a more suitable alternative than involvement in the operations of an entrepreneurial venture. The uncertainty involved does not seem to drive an increase in due diligence. On the contrary, it would appear that due diligence is more rigorous in safer later stage investments and when the business angels have considerable previous experience as investors. Finnish business angels’ involvement post investment is best explained by their degree of ownership in the entrepreneurial venture. It seems that when investors feel they are sufficiently rewarded, in terms of an adequate equity stake, they are willing to involve themselves actively in their investments. The lack of support for a relationship between increased uncertainty and the comprehensiveness of due diligence may partly be explained by an increasing trend towards portfolio diversification. This is triggered by a taxation system that favours investments through investment companies rather than direct investments. Many business angels appear to have substituted a specialization strategy that builds on reducing uncertainty for a diversification strategy that builds on reducing firm specific (idiosyncratic) risk by holding shares in ventures whose returns are not expected to exhibit a strong positive correlation.

From cages to wedges and clefts : Design of some novel hosts based on Image , Image , Image -triquinane framework

Annulation of aromatic rings on the folded Image ,Image ,Image -triquinane backbone has led to the design of potential host systems Image and Image whose crystal structures have been determined.

Syntheses based on cyclohexadienes. Part 2. Convenient synthesis of 6-alkylsalicylates, 6-alkyl 2,4-dihydroxybenzoate, and 2,5-dialkylresorcinols

A one pot synthesis of 6-alkylsalicylates and 6-alkyl-2,4- dihydroxybenzoates is described. Cycloaddition of 1-methoxycyclohexa-1,4- or 1,3-dienes with alkylpropiolic esters results in the regio-specific formation of 2-alkyl-6-methoxybenzoates. Thus, methyl 2-methoxy-6-methyl benzoate, methyl 2,4-dimethoxy-6-methylbenzoate, methyl 2,5-dimethoxy-6-methylbenzoate, methyl 2-methoxy-4,6-dimethylbenzoate, and ethyl 2-butyl-4,6-dimethoxybenzoate, have been prepared. By making use of this method, the synthesis of two dihydroisocoumarins namely (±)-mellein (12) and (±)-6-methoxy- mellein (14) is described. Employing a similar strategy, a novel route to 2,5-dialkylresorcinols has been developed. Stemphol (24b) and the antibiotic DB2073 (24d) have been synthesized.

Rotation sensitivity of Lau fringes: an analysis based on coherence theory

An analysis based on coherence theory is presented, which explains the experimentally observed rotation sensitivity of the contrast of Lau fringes obtained under spatially incoherent illumination.

Estimation of signals in colored non gaussian noise based on Gaussian Mixture models

Non-Gaussianity of signals/noise often results in significant performance degradation for systems, which are designed using the Gaussian assumption. So non-Gaussian signals/noise require a different modelling and processing approach. In this paper, we discuss a new Bayesian estimation technique for non-Gaussian signals corrupted by colored non Gaussian noise. The method is based on using zero mean finite Gaussian Mixture Models (GMMs) for signal and noise. The estimation is done using an adaptive non-causal nonlinear filtering technique. The method involves deriving an estimator in terms of the GMM parameters, which are in turn estimated using the EM algorithm. The proposed filter is of finite length and offers computational feasibility. The simulations show that the proposed method gives a significant improvement compared to the linear filter for a wide variety of noise conditions, including impulsive noise. We also claim that the estimation of signal using the correlation with past and future samples leads to reduced mean squared error as compared to signal estimation based on past samples only.

Optimal reactive power dispatch based on voltage stability criteria in a large power system with AC/DC and FACTs devices

An algorithm for optimal allocation of reactive power in AC/DC system using FACTs devices, with an objective of improving the voltage profile and also voltage stability of the system has been presented. The technique attempts to utilize fully the reactive power sources in the system to improve the voltage stability and profile as well as meeting the reactive power requirements at the AC-DC terminals to facilitate the smooth operation of DC links. The method involves successive solution of steady-state power flows and optimization of reactive power control variables with Unified Power Flow Controller (UPFC) using linear programming technique. The proposed method has been tested on a real life equivalent 96-bus AC and a two terminal DC system under normal and contingency conditions.

Optimal resource partitioning in conflicts based on Lanchester (n, 1) attrition model

This paper develops a model for military conflicts where the defending forces have to determine an optimal partitioning of available resources to counter attacks from an adversary from n different fronts. The problem of optimally partitioning the defending forces against the attacking forces is addressed. The Lanchester square law model is used to develop the dynamical equations governing the variation in force strength. Two different allocation schemes-Time-ZeroAllocation (TZA) and Continuous Constant Allocation (CCA) are considered and the optimal solutions for both are obtained analytically. These results generalize other results available in the literature. Numerical examples are given to support the analytical results.