Learning domain-specific sentiment lexicons for predicting product sales

Generic sentiment lexicons have been widely used for sentiment analysis these days. However, manually constructing sentiment lexicons is very time-consuming and it may not be feasible for certain application domains where annotation expertise is not available. One contribution of this paper is the development of a statistical learning based computational method for the automatic construction of domain-specific sentiment lexicons to enhance cross-domain sentiment analysis. Our initial experiments show that the proposed methodology can automatically generate domain-specific sentiment lexicons which contribute to improve the effectiveness of opinion retrieval at the document level. Another contribution of our work is that we show the feasibility of applying the sentiment metric derived based on the automatically constructed sentiment lexicons to predict product sales of certain product categories. Our research contributes to the development of more effective sentiment analysis system to extract business intelligence from numerous opinionated expressions posted to the Web

Hybrid genetic algorithm for elimination of severe stress concentration in railhead ends

This paper presents a computational method for eliminating severe stress concentration at the unsupported railhead ends in rail joints through innovative shape optimization of the contact zone, which is complex due to near field nonlinear contact. With a view to minimizing the computational efforts, hybrid genetic algorithm method coupled with parametric finite element has been developed and compared with the traditional genetic algorithm (GA). The shape of railhead top surface where the wheel contacts nonlinearly was optimized using the hybridized GA method. Comparative study of the optimal result and the search efficiency between the traditional and hybrid GA methods has shown that the hybridized GA provides the optimal shape in fewer computational cycles without losing accuracy. The method will be beneficial to solving complex engineering problems involving contact nonlinearity.

Buffer scheme with battery energy storage capability for enhancement of network transient stability and load ride-through

This paper examines a buffer scheme to mitigate the negative impacts of power-conditioned loads on network voltage and transient stabilities. The scheme is based on the use of battery energy-storage systems in the buffers. The storage systems ensure that protected loads downstream of the buffers can ride through upstream voltage sags and swells. Also, by controlling the buffers to operate in either constant impedance or constant power modes, power is absorbed or injected by the storage systems. The scheme thereby regulates the rotor-angle deviations of generators and enhances network transient stability. A computational method is described in which the capacity of the storage systems is determined to achieve simultaneously the above dual objectives of load ride-through and stability enhancement. The efficacy of the resulting scheme is demonstrated through numerical examples.

Case Studies in Bayesian Statistical Modelling and Analysis

Provides an accessible foundation to Bayesian analysis using real world models This book aims to present an introduction to Bayesian modelling and computation, by considering real case studies drawn from diverse fields spanning ecology, health, genetics and finance. Each chapter comprises a description of the problem, the corresponding model, the computational method, results and inferences as well as the issues that arise in the implementation of these approaches. Case Studies in Bayesian Statistical Modelling and Analysis: •Illustrates how to do Bayesian analysis in a clear and concise manner using real-world problems. •Each chapter focuses on a real-world problem and describes the way in which the problem may be analysed using Bayesian methods. •Features approaches that can be used in a wide area of application, such as, health, the environment, genetics, information science, medicine, biology, industry and remote sensing. Case Studies in Bayesian Statistical Modelling and Analysis is aimed at statisticians, researchers and practitioners who have some expertise in statistical modelling and analysis, and some understanding of the basics of Bayesian statistics, but little experience in its application. Graduate students of statistics and biostatistics will also find this book beneficial.

Allostery in tRNA Synthetases Elucidated from MD Simulations and Protein Structure Networks

tRNA synthetases (aaRS) are enzymes crucial in the translation of genetic code. The enzyme accylates the acceptor stem of tRNA by the congnate amino acid bound at the active site, when the anti-codon is recognized by the anti-codon site of aaRS. In a typical aaRS, the distance between the anti-codon region and the amino accylation site is approximately 70 Å. We have investigated this allosteric phenomenon at molecular level by MD simulations followed by the analysis of protein structure networks (PSN) of non-covalent interactions. Specifically, we have generated conformational ensembles by performing MD simulations on different liganded states of methionyl tRNA synthetase (MetRS) from Escherichia coli and tryptophenyl tRNA synthetase (TrpRS) from Human. The correlated residues during the MD simulations are identified by cross correlation maps. We have identified the amino acids connecting the correlated residues by the shortest path between the two selected members of the PSN. The frequencies of paths have been evaluated from the MD snapshots[1]. The conformational populations in different liganded states of the protein have been beautifully captured in terms of network parameters such as hubs, cliques and communities[2]. These parameters have been associated with the rigidity and plasticity of the protein conformations and can be associated with free energy landscape. A comparison of allosteric communication in MetRS and TrpRS [3] elucidated in this study highlights diverse means adopted by different enzymes to perform a similar function. The computational method described for these two enzymes can be applied to the investigation of allostery in other systems.

Development of a transient gradient enhanced non local continuum damage mechanics model for masonry

Due to the advent of varied types of masonry systems a comprehensive failure mechanism of masonry essential for the understanding of its behaviour is impossible to be determined from experimental testing. As masonry is predominantly used in wall structures a biaxial stress state dominates its failure mechanism. Biaxial testing will therefore be necessary for each type of masonry, which is expensive and time consuming. A computational method would be advantageous; however masonry is complex to model which requires advanced computational modelling methods. This thesis has formulated a damage mechanics inspired modelling method and has shown that the method effectively determines the failure mechanisms and deformation characteristics of masonry under biaxial states of loading.

Dynamic nature of proteins - interpretation of residual dipolar couplings

Protein conformations and dynamics can be studied by nuclear magnetic resonance spectroscopy using dilute liquid crystalline samples. This work clarifies the interpretation of residual dipolar coupling data yielded by the experiments. It was discovered that unfolded proteins without any additional structure beyond that of a mere polypeptide chain exhibit residual dipolar couplings. Also, it was found that molecular dynamics induce fluctuations in the molecular alignment and doing so affect residual dipolar couplings. The finding clarified the origins of low order parameter values observed earlier. The work required the development of new analytical and computational methods for the prediction of intrinsic residual dipolar coupling profiles for unfolded proteins. The presented characteristic chain model is able to reproduce the general trend of experimental residual dipolar couplings for denatured proteins. The details of experimental residual dipolar coupling profiles are beyond the analytical model, but improvements are proposed to achieve greater accuracy. A computational method for rapid prediction of unfolded protein residual dipolar couplings was also developed. Protein dynamics were shown to modulate the effective molecular alignment in a dilute liquid crystalline medium. The effects were investigated from experimental and molecular dynamics generated conformational ensembles of folded proteins. It was noted that dynamics induced alignment is significant especially for the interpretation of molecular dynamics in small, globular proteins. A method of correction was presented. Residual dipolar couplings offer an attractive possibility for the direct observation of protein conformational preferences and dynamics. The presented models and methods of analysis provide significant advances in the interpretation of residual dipolar coupling data from proteins.

Quantum Chemical Studies on Tropospheric Nucleation Mechanisms Involving Sulfuric Acid

Nucleation is the first step of the process by which gas molecules in the atmosphere condense to form liquid or solid particles. Despite the importance of atmospheric new-particle formation for both climate and health-related issues, little information exists on its precise molecular-level mechanisms. In this thesis, potential nucleation mechanisms involving sulfuric acid together with either water and ammonia or reactive biogenic molecules are studied using quantum chemical methods. Quantum chemistry calculations are based on the numerical solution of Schrödinger's equation for a system of atoms and electrons subject to various sets of approximations, the precise details of which give rise to a large number of model chemistries. A comparison of several different model chemistries indicates that the computational method must be chosen with care if accurate results for sulfuric acid - water - ammonia clusters are desired. Specifically, binding energies are incorrectly predicted by some popular density functionals, and vibrational anharmonicity must be accounted for if quantitatively reliable formation free energies are desired. The calculations reported in this thesis show that a combination of different high-level energy corrections and advanced thermochemical analysis can quantitatively replicate experimental results concerning the hydration of sulfuric acid. The role of ammonia in sulfuric acid - water nucleation was revealed by a series of calculations on molecular clusters of increasing size with respect to all three co-ordinates; sulfuric acid, water and ammonia. As indicated by experimental measurements, ammonia significantly assists the growth of clusters in the sulfuric acid - co-ordinate. The calculations presented in this thesis predict that in atmospheric conditions, this effect becomes important as the number of acid molecules increases from two to three. On the other hand, small molecular clusters are unlikely to contain more than one ammonia molecule per sulfuric acid. This implies that the average NH3:H2SO4 mole ratio of small molecular clusters in atmospheric conditions is likely to be between 1:3 and 1:1. Calculations on charged clusters confirm the experimental result that the HSO4- ion is much more strongly hydrated than neutral sulfuric acid. Preliminary calculations on HSO4- NH3 clusters indicate that ammonia is likely to play at most a minor role in ion-induced nucleation in the sulfuric acid - water system. Calculations of thermodynamic and kinetic parameters for the reaction of stabilized Criegee Intermediates with sulfuric acid demonstrate that quantum chemistry is a powerful tool for investigating chemically complicated nucleation mechanisms. The calculations indicate that if the biogenic Criegee Intermediates have sufficiently long lifetimes in atmospheric conditions, the studied reaction may be an important source of nucleation precursors.

Carbon dioxide and methane exchange between a boreal pristine lake and the atmosphere

Lakes serve as sites for terrestrially fixed carbon to be remineralized and transferred back to the atmosphere. Their role in regional carbon cycling is especially important in the Boreal Zone, where lakes can cover up to 20% of the land area. Boreal lakes are often characterized by the presence of a brown water colour, which implies high levels of dissolved organic carbon from the surrounding terrestrial ecosystem, but the load of inorganic carbon from the catchment is largely unknown. Organic carbon is transformed to methane (CH4) and carbon dioxide (CO2) in biological processes that result in lake water gas concentrations that increase above atmospheric equilibrium, thus making boreal lakes as sources of these important greenhouse gases. However, flux estimates are often based on sporadic sampling and modelling and actual flux measurements are scarce. Thus, the detailed temporal flux dynamics of greenhouse gases are still largely unknown. ----- One aim here was to reveal the natural dynamics of CH4 and CO2 concentrations and fluxes in a small boreal lake. The other aim was to test the applicability of a measuring technique for CO2 flux, i.e. the eddy covariance (EC) technique, and a computational method for estimation of primary production and community respiration, both commonly used in terrestrial research, in this lake. Continuous surface water CO2 concentration measurements, also needed in free-water applications to estimate primary production and community respiration, were used over two open water periods in a study of CO2 concentration dynamics. Traditional methods were also used to measure gas concentration and fluxes. The study lake, Valkea-Kotinen, is a small, humic, headwater lake within an old-growth forest catchment with no local anthropogenic disturbance and thus possible changes in gas dynamics reflect the natural variability in lake ecosystems. CH4 accumulated under the ice and in the hypolimnion during summer stratification. The surface water CH4 concentration was always above atmospheric equilibrium and thus the lake was a continuous source of CH4 to the atmosphere. However, the annual CH4 fluxes were small, i.e. 0.11 mol m-2 yr-1, and the timing of fluxes differed from that of other published estimates. The highest fluxes are usually measured in spring after ice melt but in Lake Valkea-Kotinen CH4 was effectively oxidised in spring and highest effluxes occurred in autumn after summer stratification period. CO2 also accumulated under the ice and the hypolimnetic CO2 concentration increased steadily during stratification period. The surface water CO2 concentration was highest in spring and in autumn, whereas during the stable stratification it was sometimes under atmospheric equilibrium. It showed diel, daily and seasonal variation; the diel cycle was clearly driven by light and thus reflected the metabolism of the lacustrine ecosystem. However, the diel cycle was sometimes blurred by injection of hypolimnetic water rich in CO2 and the surface water CO2 concentration was thus controlled by stratification dynamics. The highest CO2 fluxes were measured in spring, autumn and during those hypolimnetic injections causing bursts of CO2 comparable with the spring and autumn fluxes. The annual fluxes averaged 77 (±11 SD) g C m-2 yr-1. In estimating the importance of the lake in recycling terrestrial carbon, the flux was normalized to the catchment area and this normalized flux was compared with net ecosystem production estimates of -50 to 200 g C m-2 yr-1 from unmanaged forests in corresponding temperature and precipitation regimes in the literature. Within this range the flux of Lake Valkea-Kotinen yielded from the increase in source of the surrounding forest by 20% to decrease in sink by 5%. The free water approach gave primary production and community respiration estimates of 5- and 16-fold, respectively, compared with traditional bottle incubations during a 5-day testing period in autumn. The results are in parallel with findings in the literature. Both methods adopted from the terrestrial community also proved useful in lake studies. A large percentage of the EC data was rejected, due to the unfulfilled prerequisites of the method. However, the amount of data accepted remained large compared with what would be feasible with traditional methods. Use of the EC method revealed underestimation of the widely used gas exchange model and suggests simultaneous measurements of actual turbulence at the water surface with comparison of the different gas flux methods to revise the parameterization of the gas transfer velocity used in the models.

Functional linkages can reveal protein complexes for structure determination

The study of molecular machines, and protein complexes in general, is a growth area of biology. Is there a computational method for inferring which combinations of proteins in an organism are likely to form a crystallizable complex? We use the Protein Data Bank (PDB) to assess the usefulness of inferred functional protein linkages for this task. We find that of 242 nonredundant prokaryotic protein complexes (complexes excluding structural variants of the same protein) from organisms that are shared between the current PDB and the Prolinks functional linkage database, 44% (107/242) contain proteins that are linked at high-confidence by one or more methods of computed functional linkages. This suggests that computing functional linkages will be useful in defining protein complexes for structural studies. We offer a database of such inferred linkages corresponding to likely protein complexes for some 629,952 pairs of proteins in 154 prokaryotes and archea.

Cascaded walks in protein sequence space: use of artificial sequences in remote homology detection between natural proteins

Over the past two decades, many ingenious efforts have been made in protein remote homology detection. Because homologous proteins often diversify extensively in sequence, it is challenging to demonstrate such relatedness through entirely sequence-driven searches. Here, we describe a computational method for the generation of `protein-like' sequences that serves to bridge gaps in protein sequence space. Sequence profile information, as embodied in a position-specific scoring matrix of multiply aligned sequences of bona fide family members, serves as the starting point in this algorithm. The observed amino acid propensity and the selection of a random number dictate the selection of a residue for each position in the sequence. In a systematic manner, and by applying a `roulette-wheel' selection approach at each position, we generate parent family-like sequences and thus facilitate an enlargement of sequence space around the family. When generated for a large number of families, we demonstrate that they expand the utility of natural intermediately related sequences in linking distant proteins. In 91% of the assessed examples, inclusion of designed sequences improved fold coverage by 5-10% over searches made in their absence. Furthermore, with several examples from proteins adopting folds such as TIM, globin, lipocalin and others, we demonstrate that the success of including designed sequences in a database positively sensitized methods such as PSI-BLAST and Cascade PSI-BLAST and is a promising opportunity for enormously improved remote homology recognition using sequence information alone.

A Model for the Temperature Distribution in Resin Impregnated Paper Bushings

Resin impregnated paper (RIP) is a relatively new insulation system recommended for the use in transformer bushings. In the recent past, RIP has acquired prominence as insulation in bushings, over conventional oil impregnated paper (OIP), in view of its overwhelming advantages the more important among them being low dielectric loss and possibility for positioning the bushing at any desired angle over the transformer. In addition, the fact that such systems do not pose problems of fire hazard is counted as a very important consideration. The disadvantage of RIP compared to OIP, however, is its much higher cost and involved manufacturing process. The temperature rise in RIP bushings under normal operating conditions is seen to be a difficult parameter to control in view of the limited options for effective cooling. It is therefore essential to take serious note of this aspect, to arrest rapid deterioration of bushing. The degradation of dry-type insulation such as RIP is often due to thermal stress. The long time performance thereof, depends strongly, on the maximum operating temperature. With this in view, the Authors have developed a theoretical model and computational method to study the temperature distribution in the body of insulation. The Authors consider that the basis for the model as being the temperature and electric stress aided AC conductivity. The ensuing heat balance (continuity) equations in 2-D cylindrical geometry are treated as a Dirichelet-Neumann boundary value problem.

Role of Vertex Index in Substructure Identification and Activity Prediction: A Study on Antitubercular Activity of a Series of Acid Alkyl Ester Derivatives

Tuberculosis (TB) is a life threatening disease caused due to infection from Mycobacterium tuberculosis (Mtb). That most of the TB strains have become resistant to various existing drugs, development of effective novel drug candidates to combat this disease is a need of the day. In spite of intensive research world-wide, the success rate of discovering a new anti-TB drug is very poor. Therefore, novel drug discovery methods have to be tried. We have used a rule based computational method that utilizes a vertex index, named `distance exponent index (D-x)' (taken x = -4 here) for predicting anti-TB activity of a series of acid alkyl ester derivatives. The method is meant to identify activity related substructures from a series a compounds and predict activity of a compound on that basis. The high degree of successful prediction in the present study suggests that the said method may be useful in discovering effective anti-TB compound. It is also apparent that substructural approaches may be leveraged for wide purposes in computer-aided drug design.

Porous lithium rich Li1.2Mn0.54Ni0.22Fe0.04O2 prepared by microemulsion route as a high capacity and high rate capability positive electrode material

A porous layered composite of Li2MnO3 and LiMn0.35Ni0.55Fe0.1O2 (composition:Li1.2Mn0.54Ni0.22Fe0.04O2) is prepared by inverse microemulsion method and studied as a positive electrode material. The precursor is heated at several temperatures between 500 and 900 degrees C. The X-ray diffraction, scanning electron microscopy, and transmission electron microscopy studies suggested that well crystalline submicronsized particles are obtained. The product samples possess mesoporosity with broadly distributed pores around 10 similar to 50 nm diameter. Pore volume and surface area decrease by increasing the temperature of preparation. However, the electrochemical activity of the composite samples increases with an increase in temperature. The discharge capacity values of the samples prepared at 900 degrees C are about 186 mAh g(-1) at a specific current of 25 mA g(-1) with an excellent cycling stability. The composite sample also possesses high rate capability. The high rate capability is attributed to the porous nature of the material. (C) 2014 Elsevier Ltd. All rights reserved.

Photo-induced optical bleaching in Ge12Sb25S63 amorphous chalcogenide thin films: effect of 532 nm laser illumination

The photo-induced effects of Ge12Sb25S63 films illuminated with 532 nm laser light are investigated from transmission spectra measured by FTIR spectroscopy. The material exhibits photo-bleaching (PB) when exposed to band gap light for a prolonged time in a vacuum. The PB is ascribed to structural changes inside the film as well as surface photooxidation. The amorphous nature of thin films was detected by x-ray diffraction. The chemical composition of the deposited thin films was examined by energy dispersive x-ray analysis (EDAX). The refractive indices of the films were obtained from the transmission spectra based on an inverse synthesis method and the optical band gaps were derived from optical absorption spectra using the Tauc plot. The dispersion of the refractive index is discussed in terms of the single-oscillator Wemple-DiDomenico model. It was found that the mechanism of the optical absorption follows the rule of the allowed non-direct transition. Raman and x-ray photoelectron spectra (XPS) were measured and decomposed into several peaks that correspond to the different structural units which support the optical changes.