Photocatalytic properties of KBiO(3) and LiBiO(3) with tunnel structures

In the present study, KBiO(3) is synthesized by a standard oxidation technique while LiBiO(3) is prepared by hydrothermal method. The synthesized catalysts are characterized by X-ray diffraction (XRD), Scanning Electron Microscopy (SEM), BET surface area analysis and Diffuse Reflectance Spectroscopy (DRS). The XRD patterns suggest that KBiO(3) crystallizes in the cubic structure while LiBiO(3) crystallizes in orthorhombic structure and both of these adopt the tunnel structure. The SEM images reveal micron size polyhedral shaped KBiO(3) particles and rod-like or prismatic shape particles for LiBiO(3). The band gap is calculated from the diffuse reflectance spectrum and is found to be 2.1 eV and 1.8 eV for KBiO(3) and LiBiO(3), respectively. The band gap and the crystal structure data suggest that these materials can be used as photocatalysts. The photocatalytic activity of KBiO(3) and LiBiO(3) are evaluated for the degradation of anionic and cationic dyes, respectively, under UV and solar radiations.

Health Monitoring Of Composite Structures Based On Acoustic Wave Sensing Using Fiber Optic Sensors

Structural Health Monitoring has gained wide acceptance in the recent past as a means to monitor a structure and provide an early warning of an unsafe condition using real-time data. Utilization of structurally integrated, distributed sensors to monitor the health of a structure through accurate interpretation of sensor signals and real-time data processing can greatly reduce the inspection burden. The rapid improvement of the Fiber Optic Sensor technology for strain, vibration, ultrasonic and acoustic emission measurements in recent times makes it feasible alternative to the traditional strain gauges, PVDF and conventional Piezoelectric sensors used for Non Destructive Evaluation (NDE) and Structural Health Monitoring (SHM). Optical fiber-based sensors offer advantages over conventional strain gauges, and PZT devices in terms of size, ease of embedment, immunity from electromagnetic interference (EMI) and potential for multiplexing a number of sensors. The objective of this paper is to demonstrate the acoustic wave sensing using Extrinsic Fabry-Perot Interferometric (EFPI) sensor on a GFRP composite laminates. For this purpose experiments have been carried out initially for strain measurement with Fiber Optic Sensors on GFRP laminates with intentionally introduced holes of different sizes as defects. The results obtained from these experiments are presented in this paper. Numerical modeling has been carried out to obtain the relationship between the defect size and strain.

Testing concordance in species boundaries using acoustic, morphological, and molecular data in the field cricket genus Itaropsis (Orthoptera: Grylloidea, Gryllidae: Gryllinae)

In most taxa, species boundaries are inferred based on differences in morphology or DNA sequences revealed by taxonomic or phylogenetic analyses. In crickets, acoustic mating signals or calling songs have species-specific structures and provide a third data set to infer species boundaries. We examined the concordance in species boundaries obtained using acoustic, morphological, and molecular data sets in the field cricket genus Itaropsis. This genus is currently described by only one valid species, Itaropsis tenella, with a broad distribution in western peninsular India and Sri Lanka. Calling songs of males sampled from four sites in peninsular India exhibited significant differences in a number of call features, suggesting the existence of multiple species. Cluster analysis of the acoustic data, molecular phylogenetic analyses, and phylogenetic analyses combining all data sets suggested the existence of three clades. Whatever the differences in calling signals, no full congruence was obtained between all the data sets, even though the resultant lineages were largely concordant with the acoustic clusters. The genus Itaropsis could thus be represented by three morphologically cryptic incipient species in peninsular India; their distributions are congruent with usual patterns of endemism in the Western Ghats, India. Song evolution is analysed through the divergence in syllable period, syllable and call duration, and dominant frequency.

A review of recent developments in parametric based acoustic emission techniques applied to concrete structures

This article presents a review of recent developments in parametric based acoustic emission (AE) techniques applied to concrete structures. It recapitulates the significant milestones achieved by previous researchers including various methods and models developed in AE testing of concrete structures. The aim is to provide an overview of the specific features of parametric based AE techniques of concrete structures carried out over the years. Emphasis is given to traditional parameter-based AE techniques applied to concrete structures. A significant amount of research on AE techniques applied to concrete structures has already been published and considerable attention has been given to those publications. Some recent studies such as AE energy analysis and b-value analysis used to assess damage of concrete bridge beams have also been discussed. The formation of fracture process zone and the AE energy released during the fracture process in concrete beam specimens have been summarised. A large body of experimental data on AE characteristics of concrete has accumulated over the last three decades. This review of parametric based AE techniques applied to concrete structures may be helpful to the concerned researchers and engineers to better understand the failure mechanism of concrete and evolve more useful methods and approaches for diagnostic inspection of structural elements and failure prediction/prevention of concrete structures.

Network properties of protein-decoy structures

Convergence of the vast sequence space of proteins into a highly restricted fold/conformational space suggests a simple yet unique underlying mechanism of protein folding that has been the subject of much debate in the last several decades. One of the major challenges related to the understanding of protein folding or in silico protein structure prediction is the discrimination of non-native structures/decoys from the native structure. Applications of knowledge-based potentials to attain this goal have been extensively reported in the literature. Also, scoring functions based on accessible surface area and amino acid neighbourhood considerations were used in discriminating the decoys from native structures. In this article, we have explored the potential of protein structure network (PSN) parameters to validate the native proteins against a large number of decoy structures generated by diverse methods. We are guided by two principles: (a) the PSNs capture the local properties from a global perspective and (b) inclusion of non-covalent interactions, at all-atom level, including the side-chain atoms, in the network construction accommodates the sequence dependent features. Several network parameters such as the size of the largest cluster, community size, clustering coefficient are evaluated and scored on the basis of the rank of the native structures and the Z-scores. The network analysis of decoy structures highlights the importance of the global properties contributing to the uniqueness of native structures. The analysis also exhibits that the network parameters can be used as metrics to identify the native structures and filter out non-native structures/decoys in a large number of data-sets; thus also has a potential to be used in the protein `structure prediction' problem.

Two Novel Heterometallic Chains Featuring Mn-II and Na-I Ions in Trigonal-Prismatic Geometries Alternately Linked to Octahedral Mn-IV Ions: Synthesis, Structures, and Magnetic Behavior

Two new one-dimensional heterometallic complexes, Mn3Na(L)(4)(CH3CO2)(MeOH)(2)]-(ClO4)(2)center dot 3H(2)O (1), Mn3Na(L)(4)(CH3CH2CO2)-(MeOH)(2)](ClO4)(2)center dot 2MeOH center dot H2O (2) LH2 = 2-methyl-2-(2-pyridyl)propane-1,3-diol], have been synthesized and characterized by X-ray crystallography. Both complexes feature Mn-II and Na-I ions in trigonal-prismatic geometries that are linked to octahedral Mn-IV ions by alkoxy bridges. Variable-temperature direct- and alternating-current magnetic susceptibility data indicated a spin ground state of S = 11/2 for both complexes. Density functional theory calculations performed on 1 supported this conclusion.

Small-Angle Neutron-Scattering Studies of Mixed Micellar Structures Made of Dimeric Surfactants Having Imidazolium and Ammonium Headgroups

Planar imidazolium cation based gemini surfactants 16-Im-n-Im-16], 2Br(-) (where n = 2, 3, 4, 5, 6, 8, 10, and 12), exhibit different morphologies and internal packing arrangements by adopting different supramolecular assemblies in aqueous media depending on their number of spacer methylene units (CH2)(n). Detailed measurements of the small-angle neutron-scattering (SANS) cross sections from different imidazolium-based surfactant micelles in aqueous media (D2O) are reported. The SANS data, containing the information of aggregation behavior of such surfactants in the molecular level, have been analyzed on the basis of the Hayter and Penfold model for the macro ion solution to compute the interparticle structure factor S(Q) taking into account the screened Coulomb interactions between the dimeric surfactant micelles. The characteristic changes in the SANS spectra of the dimeric surfactant with n = 4 due to variation of temperature have also been investigated. These data are then compared with the SANS characterization data of the corresponding gemini micelles containing tetrahedral ammonium ion based polar headgroups. The critical micellar concentration of each surfactant micelle (cmc) has been determined using pyrene as an extrinsic fluorescence probe. The variation of cmc as a function of spacer chain length has been explained in terms of conformational variation and progressive looping of the spacer into the micellar interior upon increasing the n values. Small-angle neutron-scattering (SANS) cross sections from different mixed micelles composed of surfactants with ammonium headgroups, 16-A(0), 16-Am-n-Am-16], 2Br(-) (where n = 4), 16-I-0, and 16-Im-n-Im-16], 2Br(-) (where n = 4), in aqueous media (D2O) have also been analyzed. The aggregate composition matches with that predicted from the ideal mixing model.

A study of vertical cloud structure of the Indian summer monsoon using CloudSat data

Precise specification of the vertical distribution of cloud optical properties is important to reduce the uncertainty in quantifying the radiative impacts of clouds. The new global observations of vertical profiles of clouds from the CloudSat mission provide opportunities to describe cloud structures and to improve parameterization of clouds in the weather and climate prediction models. In this study, four years (2007-2010) of observations of vertical structure of clouds from the CloudSat cloud profiling radar have been used to document the mean vertical structure of clouds associated with the Indian summer monsoon (ISM) and its intra-seasonal variability. Active and break monsoon spells associated with the intra-seasonal variability of ISM have been identified by an objective criterion. For the present analysis, we considered CloudSat derived column integrated cloud liquid and ice water, and vertically profiles of cloud liquid and ice water content. Over the South Asian monsoon region, deep convective clouds with large vertical extent (up to 14 km) and large values of cloud water and ice content are observed over the north Bay of Bengal. Deep clouds with large ice water content are also observed over north Arabian Sea and adjoining northwest India, along the west coast of India and the south equatorial Indian Ocean. The active monsoon spells are characterized by enhanced deep convection over the Bay of Bengal, west coast of India and northeast Arabian Sea and suppressed convection over the equatorial Indian Ocean. Over the Bay of Bengal, cloud liquid water content and ice water content is enhanced by similar to 90 and similar to 200 % respectively during the active spells. An interesting feature associated with the active spell is the vertical tilting structure of positive CLWC and CIWC anomalies over the Arabian Sea and the Bay of Bengal, which suggests a pre-conditioning process for the northward propagation of the boreal summer intra-seasonal variability. It is also observed that during the break spells, clouds are not completely suppressed over central India. Instead, clouds with smaller vertical extent (3-5 km) are observed due to the presence of a heat low type of circulation. The present results will be useful for validating the vertical structure of clouds in weather and climate prediction models.

Crop stage classification of hyperspectral data using unsupervised techniques

The presence of a large number of spectral bands in the hyperspectral images increases the capability to distinguish between various physical structures. However, they suffer from the high dimensionality of the data. Hence, the processing of hyperspectral images is applied in two stages: dimensionality reduction and unsupervised classification techniques. The high dimensionality of the data has been reduced with the help of Principal Component Analysis (PCA). The selected dimensions are classified using Niche Hierarchical Artificial Immune System (NHAIS). The NHAIS combines the splitting method to search for the optimal cluster centers using niching procedure and the merging method is used to group the data points based on majority voting. Results are presented for two hyperspectral images namely EO-1 Hyperion image and Indian pines image. A performance comparison of this proposed hierarchical clustering algorithm with the earlier three unsupervised algorithms is presented. From the results obtained, we deduce that the NHAIS is efficient.

Scalar field visualization via extraction of symmetric structures

Identifying symmetry in scalar fields is a recent area of research in scientific visualization and computer graphics communities. Symmetry detection techniques based on abstract representations of the scalar field use only limited geometric information in their analysis. Hence they may not be suited for applications that study the geometric properties of the regions in the domain. On the other hand, methods that accumulate local evidence of symmetry through a voting procedure have been successfully used for detecting geometric symmetry in shapes. We extend such a technique to scalar fields and use it to detect geometrically symmetric regions in synthetic as well as real-world datasets. Identifying symmetry in the scalar field can significantly improve visualization and interactive exploration of the data. We demonstrate different applications of the symmetry detection method to scientific visualization: query-based exploration of scalar fields, linked selection in symmetric regions for interactive visualization, and classification of geometrically symmetric regions and its application to anomaly detection.

Network properties of decoys and CASP predicted models: a comparison with native protein structures

Protein structure space is believed to consist of a finite set of discrete folds, unlike the protein sequence space which is astronomically large, indicating that proteins from the available sequence space are likely to adopt one of the many folds already observed. In spite of extensive sequence-structure correlation data, protein structure prediction still remains an open question with researchers having tried different approaches (experimental as well as computational). One of the challenges of protein structure prediction is to identify the native protein structures from a milieu of decoys/models. In this work, a rigorous investigation of Protein Structure Networks (PSNs) has been performed to detect native structures from decoys/ models. Ninety four parameters obtained from network studies have been optimally combined with Support Vector Machines (SVM) to derive a general metric to distinguish decoys/models from the native protein structures with an accuracy of 94.11%. Recently, for the first time in the literature we had shown that PSN has the capability to distinguish native proteins from decoys. A major difference between the present work and the previous study is to explore the transition profiles at different strengths of non-covalent interactions and SVM has indeed identified this as an important parameter. Additionally, the SVM trained algorithm is also applied to the recent CASP10 predicted models. The novelty of the network approach is that it is based on general network properties of native protein structures and that a given model can be assessed independent of any reference structure. Thus, the approach presented in this paper can be valuable in validating the predicted structures. A web-server has been developed for this purpose and is freely available at http://vishgraph.mbu.iisc.ernet.in/GraProStr/PSN-QA.html.

Crystal structures of SCP2-thiolases of Trypanosomatidae, human pathogens causing widespread tropical diseases: the importance for catalysis of the cysteine of the unique HDCF loop

Thiolases are essential CoA-dependent enzymes in lipid metabolism. In the present study we report the crystal structures of trypanosomal and leishmanial SCP2 (sterol carrier protein, type-2)-thiolases. Trypanosomatidae cause various widespread devastating (sub)-tropical diseases, for which adequate treatment is lacking. The structures reveal the unique geometry of the active site of this poorly characterized subfamily of thiolases. The key catalytic residues of the classical thiolases are two cysteine residues, functioning as a nucleophile and an acid/base respectively. The latter cysteine residue is part of a CxG motif. Interestingly, this cysteine residue is not conserved in SCP2-thiolases. The structural comparisons now show that in SCP2-thiolases the catalytic acid/base is provided by the cysteine residue of the HDCF motif, which is unique for this thiolase subfamily. This HDCF cysteine residue is spatially equivalent to the CxG cysteine residue of classical thiolases. The HDCF cysteine residue is activated for acid/base catalysis by two main chain NH-atoms, instead of two water molecules, as present in the CxG active site. The structural results have been complemented with enzyme activity data, confirming the importance of the HDCF cysteine residue for catalysis. The data obtained suggest that these trypanosomatid SCP2-thiolases are biosynthetic thiolases. These findings provide promise for drug discovery as biosynthetic thiolases catalyse the first step of the sterol biosynthesis pathway that is essential in several of these parasites.

Understanding Self-Segregation of Immiscible Peripheral Segments in Pseudodendritic Hyperbranched Polydithioacetals: Formation of Improved Janus Structures

Peripherally heterofunctionalized hyperbranched polymers (HBPs) undergo immiscibility-driven self-segregation of the outer segments to form Janus molecular entities (Macromolecules 2012, 45, 2348). In HBPs prepared via AB2 type self-condensation, single-step peripheral heterofunctionalization would lead to random distribution of the two types of terminal units, namely, homofunctionalized (homo-T) and heterofunctionalized (hetero-T) termini. Here, we examine the role of such hetero-T units on the self-segregation of heterofunctionalized pseudodendritic hyperbranched polydithioacetals. Three different heterofunctionalized HB dithioacetals bearing roughly 50 mol % each of docsyl (C-22) and MPEG-350 chains at the periphery were prepared: one of them carried a statistical distribution of homo-T and hetero-T units, and the other carried only two types of homo-T (-TR1R1 and -TR2R2) termini, whereas the third carried largely hetero-T (-TR1R2) termini. Careful examination of DSC and SAXS data reveals that the self-segregation is most effective in HBPs devoid of hetero-T units; interestingly, however, it also showed that randomly heterofunctionalized HBPs self-segregated nearly as effectively.

Assessment of land surface temperature and heat fluxes over Delhi using remote sensing data

Surface energy processes has an essential role in urban weather, climate and hydrosphere cycles, as well in urban heat redistribution. The research was undertaken to analyze the potential of Landsat and MODIS data in retrieving biophysical parameters in estimating land surface temperature & heat fluxes diurnally in summer and winter seasons of years 2000 and 2010 and understanding its effect on anthropogenic heat disturbance over Delhi and surrounding region. Results show that during years 2000-2010, settlement and industrial area increased from 5.66 to 11.74% and 4.92 to 11.87% respectively which in turn has direct effect on land surface temperature (LST) and heat fluxes including anthropogenic heat flux. Based on the energy balance model for land surface, a method to estimate the increase in anthropogenic heat flux (Has) has been proposed. The settlement and industrial areas has higher amounts of energy consumed and has high values of Has in all seasons. The comparison of satellite derived LST with that of field measured values show that Landsat estimated values are in close agreement within error of 2 degrees C than MODIS with an error of 3 degrees C. It was observed that, during 2000 and 2010, the average change in surface temperature using Landsat over settlement & industrial areas of both seasons is 1.4 degrees C & for MODIS data is 3.7 degrees C. The seasonal average change in anthropogenic heat flux (Has) estimated using Landsat & MODIS is up by around 38 W/m(2) and 62 W/m(2) respectively while higher change is observed over settlement and concrete structures. The study reveals that the dynamic range of Has values has increased in the 10 year period due to the strong anthropogenic influence over the area. The study showed that anthropogenic heat flux is an indicator of the strength of urban heat island effect, and can be used to quantify the magnitude of the urban heat island effect. (C) 2013 Elsevier Ltd. All rights reserved.

Identification of local variations within secondary structures of proteins

Secondary-structure elements (SSEs) play an important role in the folding of proteins. Identification of SSEs in proteins is a common problem in structural biology. A new method, ASSP (Assignment of Secondary Structure in Proteins), using only the path traversed by the C atoms has been developed. The algorithm is based on the premise that the protein structure can be divided into continuous or uniform stretches, which can be defined in terms of helical parameters, and depending on their values the stretches can be classified into different SSEs, namely -helices, 3(10)-helices, -helices, extended -strands and polyproline II (PPII) and other left-handed helices. The methodology was validated using an unbiased clustering of these parameters for a protein data set consisting of 1008 protein chains, which suggested that there are seven well defined clusters associated with different SSEs. Apart from -helices and extended -strands, 3(10)-helices and -helices were also found to occur in substantial numbers. ASSP was able to discriminate non--helical segments from flanking -helices, which were often identified as part of -helices by other algorithms. ASSP can also lead to the identification of novel SSEs. It is believed that ASSP could provide a better understanding of the finer nuances of protein secondary structure and could make an important contribution to the better understanding of comparatively less frequently occurring structural motifs. At the same time, it can contribute to the identification of novel SSEs. A standalone version of the program for the Linux as well as the Windows operating systems is freely downloadable and a web-server version is also available at .