Random copolymers consisting of dithienylcyclopentadienone, thiophene and benzothiadiazole for bulk heterojunction solar cells

Novel random copolymers containing dithienylcyclopentadienone, thiophene and benzothiadiazole were synthesized and photovoltaic properties of these materials were evaluated. Thermal, structural, optical and electrochemical characterization of the synthesized copolymers was carried out. These thermally stable copolymers are solution processable unlike the homopolymer. The absorption spectra indicated that with the incorporation of alkyl chains in the thiophene moiety, the onset of absorption increases and hence band gap decreases (1.47 eV to 1.41 eV). Bulk heterojunction solar cells were fabricated with the blend of copolymer and phenyl-C61-butyric acid methyl ester (PCBM) as the active material and device parameters were extracted. The copolymer consists of alkyl thiophene exhibit higher open circuit voltage than the copolymer consisting of thiophene moiety. (c) 2012 Elsevier B.V. All rights reserved.

Evolution of Microstructure During Solidification of an Aluminium Alloy Under Stirring

In the present work, the evolution of microstructure during solidification of A356 alloy under stirring is performed experimentally in a high temperature concentric viscometer. The stirring during solidification results a semisolid slurry in the annular space between the cylinders. This slurry is removed periodically during processing using a vacuum removal quartz tube and quenched in water for micrograph analysis. From the micrograph analysis, the shape, stacking arrangement and corresponding microstructural evolution of the suspended primary particles in the slurry are studied. The work also predicts the fraction of solid present in the extracted slurry. Finally, the effect of microstructure and the solid-fraction on the slurry viscosity is presented.

HSPIR: a manually annotated heat shock protein information resource

Heat shock protein information resource (HSPIR) is a concerted database of six major heat shock proteins (HSPs), namely, Hsp70, Hsp40, Hsp60, Hsp90, Hsp100 and small HSP. The HSPs are essential for the survival of all living organisms, as they protect the conformations of proteins on exposure to various stress conditions. They are a highly conserved group of proteins involved in diverse physiological functions, including de novo folding, disaggregation and protein trafficking. Moreover, their critical role in the control of disease progression made them a prime target of research. Presently, limited information is available on HSPs in reference to their identification and structural classification across genera. To that extent, HSPIR provides manually curated information on sequence, structure, classification, ontology, domain organization, localization and possible biological functions extracted from UniProt, GenBank, Protein Data Bank and the literature. The database offers interactive search with incorporated tools, which enhances the analysis. HSPIR is a reliable resource for researchers exploring structure, function and evolution of HSPs.

Ex Situ X-ray Diffraction, X-ray Absorption Near Edge Structure, Electron Spin Resonance, and Transmission Electron Microscopy Study of the Hydrothermal Crystallization of Vanadium Oxide Nanotubes: An Insight into the Mechanism of Formation

The nucleation and growth of vanadium oxide nanotubes (VOx-NT) have been followed by a combination of numerous ex situ techniques. long the hydrothermal process. Intermediate solid phases extracted at different reaction times have been characterized by powder X-ray diffraction, scanning and transmission electron microscopy, electron spin resonance, and V-K edge :X-ray absorption near-edge structure spectroscopy. The supernatant vanadate solutions extracted during the hydrothermal treatment have been studied by liquid V-51 NMR and flame. spectroscopy. For short durations of the hydrothermal synthesis, the initial V2O5-surfactant intercalate. is progressively transformed into VOx-NT whose crystallization starts to be detected after a hydrothermal treatment of 24 h. Upon heating from 24 h to 7 days, VOx-NT are obtained in larger amount and with an improved crystallinity. The detection of soluble amines and cyclic metavanadate V4O12](4-) in the supernatant solution along the hydrothermal process suggests that VOx-NT result from a dissolution precipitation mechanism. Metavanadate species V4O12](4-) could behave as molecular precursors in the polymerization reactions leading to VOx-NT.

Caryophyllene-Rich Essential Oil of Didymocarpus tomentosa: Chemical Composition and Cytotoxic Activity

The essential oil from the leaves of Didymocarpus tomentosa was extracted by hydrodistillation and analyzed by GC/FID and GC/MS. Twenty five constituents amounting to 81.6% of the oil were identified. The leaf oil contained 78.7% sesquiterpenes and 2.9% monoterpenes. The leaf essential oil of D. tomentosa is a unique caryophyllene-rich natural source containing beta-caryophyllene, caryophyllene oxide, alpha-humulene and humulene oxide. The cytotoxic activity of the oil was determined by the BSLT using shrimp larva and the MTT assay using HeLa tumor cell line. The oil showed significant cytotoxic activity with LC50 and IC50 values of 12.26 and 11.4 mu g/mL, respectively. This is the first report on the chemical composition and cytotoxic activity of the essential oil of D. tomentosa.

Activation of Lattice Oxygen of TiO2 by Pd2+ Ion: Correlation of Low-Temperature CO and Hydrocarbon Oxidation with Structure of Ti1-xPdxO2-x (x=0.01-0.03)

Lattice oxygen of TiO2 is activated by the substitution of Pd ion in its lattice. Ti1-xPdxO2-x (x = 0.01-0.03) have been synthesized by solution combustion method crystallizing in anatase TiO2 structure. Pd is in +2 oxidation state and Ti is in +4 oxidation state in the catalyst. Pd is more ionic in TiO2 lattice compared to Pd in PdO. Oxygen storage capacity defined by ``amount of oxygen that is used reversibly to oxidize CO'' is as high as 5100 mu mol/g of Ti0.97Pd0.03O1.97. Oxygen is extracted by CO to CO2 in absence of feed oxygen even at room temperature which is more than 20 times compared to pure TiO2. Rate of CO oxidation is 2.75 mu mol g(-1) s(-1) at 60 degrees C over Ti0.97Pd0.03O1.97 and C2H2 gets oxidized to CO2 and H2O at room temperature. Catalyst is not poisoned on long time operation of the reactor. Such high catalytic activity is due to activated lattice oxygen created by the substitution of Pd ion as seen from first-principles density functional theory (DFT) calculations with 96 atom supercells of Ti32O64, Ti31Pd1O63, Ti30Pd2O62, and Ti29Pd3O61. The compounds crystallize in anatase TiO2 structure with Pd2+ ion in nearly square planar geometry and TiO6 octahedra are distorted by the creation of weakly bound oxygens. Structural analysis of Ti31Pd1O63 which is close to 3% Pd ion substituted TiO2 shows that oxygens associated with both Ti and Pd ions in the lattice show bond valence sum of 1.87, a low value characteristic of weak oxygen in the lattice compared to oxygens with valence 2 and above in the same lattice. Exact positions of activated oxygens have been identified in the lattice from DFT calculations.

HUMAN DETECTION USING SPARSE REPRESENTATION

The problem of human detection is challenging, more so, when faced with adverse conditions such as occlusion and background clutter. This paper addresses the problem of human detection by representing an extracted feature of an image using a sparse linear combination of chosen dictionary atoms. The detection along with the scale finding, is done by using the coefficients obtained from sparse representation. This is of particular interest as we address the problem of scale using a scale-embedded dictionary where the conventional methods detect the object by running the detection window at all scales.

A transient detection algorithm for audio using iterative analysis of STFT

We propose an iterative algorithm to detect transient segments in audio signals. Short time Fourier transform(STFT) is used to detect rapid local changes in the audio signal. The algorithm has two steps that iteratively - (a) calculate a function of the STFT and (b) build a transient signal. A dynamic thresholding scheme is used to locate the potential positions of transients in the signal. The iterative procedure ensures that genuine transients are built up while the localised spectral noise are suppressed by using an energy criterion. The extracted transient signal is later compared to a ground truth dataset. The algorithm performed well on two databases. On the EBU-SQAM database of monophonic sounds, the algorithm achieved an F-measure of 90% while on our database of polyphonic audio an F-measure of 91% was achieved. This technique is being used as a preprocessing step for a tempo analysis algorithm and a TSR (Transients + Sines + Residue) decomposition scheme.

Fully complex-valued ELM classifiers for human action recognition

In this paper, we present a fast learning neural network classifier for human action recognition. The proposed classifier is a fully complex-valued neural network with a single hidden layer. The neurons in the hidden layer employ the fully complex-valued hyperbolic secant as an activation function. The parameters of the hidden layer are chosen randomly and the output weights are estimated analytically as a minimum norm least square solution to a set of linear equations. The fast leaning fully complex-valued neural classifier is used for recognizing human actions accurately. Optical flow-based features extracted from the video sequences are utilized to recognize 10 different human actions. The feature vectors are computationally simple first order statistics of the optical flow vectors, obtained from coarse to fine rectangular patches centered around the object. The results indicate the superior performance of the complex-valued neural classifier for action recognition. The superior performance of the complex neural network for action recognition stems from the fact that motion, by nature, consists of two components, one along each of the axes.

Automatic road extraction using high resolution satellite images based on Level Set and Mean Shift methods

Analysis of high resolution satellite images has been an important research topic for urban analysis. One of the important features of urban areas in urban analysis is the automatic road network extraction. Two approaches for road extraction based on Level Set and Mean Shift methods are proposed. From an original image it is difficult and computationally expensive to extract roads due to presences of other road-like features with straight edges. The image is preprocessed to improve the tolerance by reducing the noise (the buildings, parking lots, vegetation regions and other open spaces) and roads are first extracted as elongated regions, nonlinear noise segments are removed using a median filter (based on the fact that road networks constitute large number of small linear structures). Then road extraction is performed using Level Set and Mean Shift method. Finally the accuracy for the road extracted images is evaluated based on quality measures. The 1m resolution IKONOS data has been used for the experiment.

k.p based closed form energy band gap and transport electron effective mass model for 100] and 110] relaxed and strained Silicon nanowire

In this paper, we address a physics based closed form model for the energy band gap (E-g) and the transport electron effective mass in relaxed and strained 100] and 110] oriented rectangular Silicon Nanowire (SiNW). Our proposed analytical model along 100] and 110] directions are based on the k.p formalism of the conduction band energy dispersion relation through an appropriate rotation of the Hamiltonian of the electrons in the bulk crystal along 001] direction followed by the inclusion of a 4 x 4 Luttinger Hamiltonian for the description of the valance band structure. Using this, we demonstrate the variation in Eg and the transport electron effective mass as function of the cross-sectional dimensions in a relaxed 100] and 110] oriented SiNW. The behaviour of these two parameters in 100] oriented SiNW has further been studied with the inclusion of a uniaxial strain along the transport direction and a biaxial strain, which is assumed to be decomposed from a hydrostatic deformation along 001] with the former one. In addition, the energy band gap and the effective mass of a strained 110] oriented SiNW has also been formulated. Using this, we compare our analytical model with that of the extracted data using the nearest neighbour empirical tight binding sp(3)d(5)s* method based simulations and has been found to agree well over a wide range of device dimensions and applied strain. (C) 2012 Elsevier Ltd. All rights reserved.

Sub-band envelope approach to obtain instants of significant excitation in speech

In this paper, we propose a new sub-band approach to estimate the glottal activity. The method is based on the spectral harmonicity and the sub-band temporal properties of voiced speech. We propose a method to represent glottal excitation signal using sub-band temporal envelope. Instants of maximum glottal excitation or Glottal Closure Instants (GCI) are extracted from the estimated glottal excitation pattern and the result is compared with a standard GCI computation method, DYPSA [1]. The performance of the algorithm is also compared for the noisy signal and it is shown that the proposed method is less variant to GCI estimation under noisy conditions compared to DYPSA. The algorithm is evaluated on the CMU-ARCTIC database.

Covariance profiles: a signature representation for object sets

We consider the problem of extracting a signature representation of similar entities employing covariance descriptors. Covariance descriptors can efficiently represent objects and are robust to scale and pose changes. We posit that covariance descriptors corresponding to similar objects share a common geometrical structure which can be extracted through joint diagonalization. We term this diagonalizing matrix as the Covariance Profile (CP). CP can be used to measure the distance of a novel object to an object set through the diagonality measure. We demonstrate how CP can be employed on images as well as for videos, for applications such as face recognition and object-track clustering.

Supercritical carbon dioxide Brayton cycle for concentrated solar power

Supercritical carbon dioxide based Brayton cycle for possible concentrated solar power applications is investigated and compared with trans- and sub-critical operations of the same fluid. Thermal efficiency, specific work output and magnitude of irreversibility generation are used as some of the performance indicators. While the thermal efficiency increases almost linearly with low side pressure in the sub- and trans-critical cycles, it attains a maximum in the supercritical regime at 85 bar after which there are diminishing returns on increasing the low side pressure. It is also found that supercritical cycle is capable of producing power with a thermal efficiency of >30% even at a lower source temperature (820K) and accounting for foreseeable non-idealities albeit with a higher turbine inlet pressure (similar to 300 bar) which is not matched by a conventional sub-critical cycle even with a high source temperature of 978K. The reasons for lower efficiency than in an ideal cycle are extracted from an irreversibility analysis of components, namely, compressor, regenerator, turbine and gas cooler. Low sensitivity to the source temperature and extremely small volumetric flow rates in the supercritical cycle could offset the drawback of high pressures through a compact system.

Sex and physiological state influence the rate of resource acquisition and monopolisation in urban free-ranging dogs, Canis familiaris

In animal populations, the constraints of energy and time can cause intraspecific variation in foraging behaviour. The proximate developmental mediators of such variation are often the mechanisms underlying perception and associative learning. Here, experience-dependent changes in foraging behaviour and their consequences were investigated in an urban population of free-ranging dogs, Canis familiaris by continually challenging them with the task of food extraction from specially crafted packets. Typically, males and pregnant/lactating (PL) females extracted food using the sophisticated `gap widening' technique, whereas non-pregnant/non-lactating (NPNL) females, the relatively underdeveloped `rip opening' technique. In contrast to most males and PL females (and a few NPNL females) that repeatedly used the gap widening technique and improved their performance in food extraction with experience, most NPNL females (and a few males and PL females) non-preferentially used the two extraction techniques and did not improve over successive trials. Furthermore, the ability of dogs to sophisticatedly extract food was positively related to their ability to improve their performance with experience. Collectively, these findings demonstrate that factors such as sex and physiological state can cause differences among individuals in the likelihood of learning new information and hence, in the rate of resource acquisition and monopolization.