983 resultados para -monoidal categories


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In the absence of interlogs, building docking models is a time intensive task, involving generation of a large pool of docking decoys followed by refinement and screening to identify near native docking solutions. This limits the researcher interested in building docking methods with the choice of benchmarking only a limited number of protein complexes. We have created a repository called dockYard (http://pallab.serc.iisc.ernet.in/dockYard), that allows modelers interested in protein-protein interaction to access large volume of information on protein dimers and their interlogs, and also download decoys for their work if they are interested in building modeling methods. dockYard currently offers four categories of docking decoys derived from: Bound (native dimer co-crystallized), Unbound (individual subunits are crystallized, as well as the target dimer), Variants (match the previous two categories in at least one subunit with 100% sequence identity), and Interlogs (match the previous categories in at least one subunit with >= 90% or >= 50% sequence identity). The web service offers options for full or selective download based on search parameters. Our portal also serves as a repository to modelers who may want to share their decoy sets with the community.

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There is a need to understand the carbon (C) sequestration potential of the forestry option and its financial implications for each country.In India the C emissions from deforestation are estimated to be nearly offset by C sequestration in forests under succession and tree plantations. India has nearly succeeded in stabilizing the area under forests and has adequate forest conservation strategies. Biomass demands for softwood, hardwood and firewood are estimated to double or treble by the year 2020. A set of forestry options were developed to meet the projected biomass needs, and keeping in mind the features of land categories available, three scenarios were developed: potential; demand-driven; and programme-driven scenarios. Adoption of the demand-driven scenario, targeted at meeting the projected biomass needs, is estimated to sequester 78 Mt of C annually after accounting for all emissions resulting from clearfelling and end use of biomass. The demand-driven scenario is estimated to offset 50% of national C emission at 1990 level. The cost per t of C sequestered for forestry options is lower than the energy options considered. The annual investment required for implementing the demand-driven scenario is estimated to be US$ 2.1 billion for six years and is shown to be feasible. Among forestry options, the ranking based on investment cost per t of C sequestered from least cost to highest cost is; natural regeneration-agro-forestry-enhanced natural regeneration (< US$ 2.5/t C)-timber-community-softwood forestry (US$ 3.3 to 7.3 per t of C).

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We report here the role of remote sensing (RS) and geographical information system (GIS) in the identification of geomorphic records and understanding of the local controls on the retreat of glaciers of the Baspa Valley, Himachal Pradesh, India. The geomorphic records mapped are accumulation zone, exposed ablation zone, moraine-covered ablation zone, snout, deglaciated valley, lateral moraine, medial moraine, terminal moraine and hanging glacier. Details of these features and stages of deglaciation have been extracted from RS data and mapped in a GIS environment. Glacial geomorphic data have been generated for 22 glaciers of the Baspa Valley. The retreat of glaciers has been estimated using the glacial maxima observed on satellite images. On the basis of percentage of retreat and the critical analysis of glacial geomorphic data for 22 glaciers of the Baspa Valley, they are classified into seven categories of very low to very very high retreat. From the analysis of the above 22 glaciers, it has been found that other than global warming, the retreat of glaciers of the Baspa Valley is inversely proportional to the size of the accumulation zone and the ratio of the moraine covered ablation/exposed ablation zone.

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Biodiversity surveys were conducted in 13, 10x50 m(2) plots located between 1400 to 3100 in abode mean sea level in a range of habitats in temperate mixed Oak and Coniferous forests through sub-alpine to the alpine grasslands in Chamoli district of Uttaranchal state in the Indian Garhwal Himalaya. Cross-taxon congruence in biodiversity (alpha-diversity and beta-diversity) across macrolichens, mosses, liverworts, woody plants (shrubs and trees) and ants was investigated, so as to examine the extent to which these group, of organisms can function as Surrogates for each other. Although woody plants provided a major substrate for macrolichens and mosses, there was no species-specific association between them. Woody plant species richness was highly positively correlated with mosses (r(2) = 0.63, P < 0.001) but the relationship, as not particularly very strong with lichens and liverworts. While there was a significant correlation in the species turnover (&beta;-diversity) of macrolichens with mosses (r(2) = 0.21 P < 0.005). the relationship was relatively poor with the woody plants. On the other hand. negative correlations emerged in the species richness of ants with those of macrolichens, mosses and woody plants (r(2) = -0.44 P < 0.05). but most of the complementarity (turnover) relationships among them were positive, Since diversity between taxonomic hierarchies within the group was consistently significantly positively correlated in all these taxa, the higher taxonomic categories Such as genus and family may be employed as surrogates for rapid assessment and monitoring of species diversity, Although no single group other than macrolichens has emerged as a good indicator of changes in species richness in all other groups, some concordant relationships between them conform to the hypothesis that species assemblages of certain taxonomic groups could still be used as surrogates for efficient monitoring of species diversity in other groups whose distribution may further predict the importance of conserving overall biodiversity in landscapes such as the Garhwal Himalaya. (C) 2002 Elsevier Science Ltd. All rights reserved.

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Background: Temporal analysis of gene expression data has been limited to identifying genes whose expression varies with time and/or correlation between genes that have similar temporal profiles. Often, the methods do not consider the underlying network constraints that connect the genes. It is becoming increasingly evident that interactions change substantially with time. Thus far, there is no systematic method to relate the temporal changes in gene expression to the dynamics of interactions between them. Information on interaction dynamics would open up possibilities for discovering new mechanisms of regulation by providing valuable insight into identifying time-sensitive interactions as well as permit studies on the effect of a genetic perturbation. Results: We present NETGEM, a tractable model rooted in Markov dynamics, for analyzing the dynamics of the interactions between proteins based on the dynamics of the expression changes of the genes that encode them. The model treats the interaction strengths as random variables which are modulated by suitable priors. This approach is necessitated by the extremely small sample size of the datasets, relative to the number of interactions. The model is amenable to a linear time algorithm for efficient inference. Using temporal gene expression data, NETGEM was successful in identifying (i) temporal interactions and determining their strength, (ii) functional categories of the actively interacting partners and (iii) dynamics of interactions in perturbed networks. Conclusions: NETGEM represents an optimal trade-off between model complexity and data requirement. It was able to deduce actively interacting genes and functional categories from temporal gene expression data. It permits inference by incorporating the information available in perturbed networks. Given that the inputs to NETGEM are only the network and the temporal variation of the nodes, this algorithm promises to have widespread applications, beyond biological systems. The source code for NETGEM is available from https://github.com/vjethava/NETGEM

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Uttara Kannada is the only district in Karnataka, which has a forested area of about 80% and falls in the region of the Western Ghats. It is considered to be a very resourceful in terms of abundant natural resources and constitutes an important district in Karnataka. The forest resources of the district are under pressure as a large portion of the forested area has been converted to non-forestry activities since independence owing to the increased demands from human and animal population resulting in degradation of the forest ecosystem. This has led to poor productivity and regenerative capacity which is evident in the form of barren hill tops, etc in Coastal taluks of Uttara Kannada, entailing regular monitoring of the forest resources very essential. The classification of forest is a prerequisite for managing forest resources. Geographical Information System (GIS), allows the spatial and temporal analysis of the features of interest, and helps in solving the problem of deforestation and associated environmental and ecological problems. Spatial and temporal tools such as GIS and remotely sensed data helps the planners and decision makers in evolving the sustainable strategies for management and conservation of natural resources. Uttara Kannada district was classified on the basis of the land-use using supervised hard classifiers. The land use categories identified were urban area, water bodies, agricultural land, forest cover, and waste land. Further classification was carried out on the basis of forest type. The types of forest categorised were semi-evergreen, evergreen, moist deciduous, dry deciduous, plantations and scrub, thorny and non-forested area. The identified classes were correlated with the ground data collected during field visits. The observed results were compared with the historic data and the changes in the forest cover were analysed. From the assessment made it was clear that there has been a considerable degree of forest loss in certain areas of the district. It was also observed that plantations and social forests have increased drastically over the last fifteen years, and natural forests have declined.

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Uttara Kannada is the only district in Karnataka, which has a forested area of about 80% and falls in the region of the Western Ghats. It is considered to be a very resourceful in terms of abundant natural resources and constitutes an important district in Karnataka. The forest resources of the district are under pressure as a large portion of the forested area has been converted to non-forestry activities since independence owing to the increased demands from human and animal population resulting in degradation of the forest ecosystem. This has led to poor productivity and regenerative capacity which is evident in the form of barren hill tops, etc in Coastal taluks of Uttara Kannada, entailing regular monitoring of the forest resources very essential. The classification of forest is a prerequisite for managing forest resources. Geographical Information System (GIS), allows the spatial and temporal analysis of the features of interest, and helps in solving the problem of deforestation and associated environmental and ecological problems. Spatial and temporal tools such as GIS and remotely sensed data helps the planners and decision makers in evolving the sustainable strategies for management and conservation of natural resources. Uttara Kannada district was classified on the basis of the land-use using supervised hard classifiers. The land use categories identified were urban area, water bodies, agricultural land, forest cover, and waste land. Further classification was carried out on the basis of forest type. The types of forest categorised were semi-evergreen, evergreen, moist deciduous, dry deciduous, plantations and scrub, thorny and non-forested area. The identified classes were correlated with the ground data collected during field visits. The observed results were compared with the historic data and the changes in the forest cover were analysed. From the assessment made it was clear that there has been a considerable degree of forest loss in certain areas of the district. It was also observed that plantations and social forests have increased drastically over the last fifteen years,and natural forests have declined.

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Advertisements(Ads) are the main revenue earner for Television (TV) broadcasters. As TV reaches a large audience, it acts as the best media for advertisements of products and services. With the emergence of digital TV, it is important for the broadcasters to provide an intelligent service according to the various dimensions like program features, ad features, viewers interest and sponsors preference. We present an automatic ad recommendation algorithm that selects a set of ads by considering these dimensions and semantically match them with programs. Features of the ad video are captured interms of annotations and they are grouped into number of predefined semantic categories by using a categorization technique. Fuzzy categorical data clustering technique is applied on categorized data for selecting better suited ads for a particular program. Since the same ad can be recommended for more than one program depending upon multiple parameters, fuzzy clustering acts as the best suited method for ad recommendation. The relative fuzzy score called degree of membership calculated for each ad indicates the membership of a particular ad to different program clusters. Subjective evaluation of the algorithm is done by 10 different people and rated with a high success score.

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Among the many different objectives of large scale structural genomics projects are expanding the protein fold space, enhancing understanding of a model or disease-related organism, and providing foundations for structure-based drug discovery. Systematic analysis of protein structures of Mycobacterium tuberculosis has been ongoing towards meeting some of these objectives. Indian participation in these efforts has been enthusiastic and substantial. The proteins of M. tuberculosis chosen for structural analysis by the Indian groups span almost all the functional categories. The structures determined by the Indian groups have led to significant improvement in the biochemical knowledge on these proteins and consequently have started providing useful insights into the biology of M. tuberculosis. Moreover, these structures form starting points for inhibitor design studies, early results of which are encouraging. The progress made by Indian structural biologists in determining structures of M. tuberculosis proteins is highlighted in this review. (C) 2011 Elsevier Ltd. All rights reserved.

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A technique is proposed for classifying respiratory volume waveforms(RVW) into normal and abnormal categories of respiratory pathways. The proposed method transforms the temporal sequence into frequency domain by using an orthogonal transform, namely discrete cosine transform (DCT) and the transformed signal is pole-zero modelled. A Bayes classifier using model pole angles as the feature vector performed satisfactorily when a limited number of RVWs recorded under deep and rapid (DR) manoeuvre are classified.

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The use of Fourier shape descriptors for morphological studies of vectorcardio-grams (VCGs) is p resented . The FDs can effectively be used as features for classf-fication of VCGs of different clinical categories . In addition , they provide cli-nically significant qualitative shape information for use by the Cardiologist. The initial result sofanalysisof nwrmal and abnormal VCGs areencouraging.

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The data obtained in the earlier parts of this series for the donor and acceptor end parameters of N-H. O and O-H. O hydrogen bonds have been utilised to obtain a qualitative working criterion to classify the hydrogen bonds into three categories: very good (VG), moderately good (MG) and weak (W). The general distribution curves for all the four parameters are found to be nearly of the Gaussian type. Assuming that the VG hydrogen bonds lie between 0 and la, MG hydrogen bonds between 1s and 2s, W hydrogen bonds beyond 2s (where s is the standard deviation), suitable cut-off limits for classifying the hydrogen bonds in the three categories have been derived. These limits are used to get VG and MG ranges for the four parameters 1 and (at the donor end) and and (at the acceptor end). The qualitative strength of a hydrogen bond is decided by the cumulative application of the criteria to all the four parameters. The criterion has been further applied to some practical examples in conformational studies such as -helix and can be used for obtaining suitable location of hydrogen atoms to form good hydrogen bonds. An empirical approach to the energy of hydrogen bonds in the three categories has also been presented.

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This study presents the future seismic hazard map of Coimbatore city, India, by considering rupture phenomenon. Seismotectonic map for Coimbatore has been generated using past earthquakes and seismic sources within 300 km radius around the city. The region experienced a largest earthquake of moment magnitude 6.3 in 1900. Available earthquakes are divided into two categories: one includes events having moment magnitude of 5.0 and above, i.e., damaging earthquakes in the region and the other includes the remaining, i.e., minor earthquakes. Subsurface rupture character of the region has been established by considering the damaging earthquakes and total length of seismic source. Magnitudes of each source are estimated by assuming the subsurface rupture length in terms of percentage of total length of sources and matched with reported earthquake. Estimated magnitudes match well with the reported earthquakes for a RLD of 5.2% of the total length of source. Zone of influence circles is also marked in the seismotectonic map by considering subsurface rupture length of fault associated with these earthquakes. As earthquakes relive strain energy that builds up on faults, it is assumed that all the earthquakes close to damaging earthquake have released the entire strain energy and it would take some time for the rebuilding of strain energy to cause a similar earthquake in the same location/fault. Area free from influence circles has potential for future earthquake, if there is seismogenic source and minor earthquake in the last 20 years. Based on this rupture phenomenon, eight probable locations have been identified and these locations might have the potential for the future earthquakes. Characteristic earthquake moment magnitude (M-w) of 6.4 is estimated for the seismic study area considering seismic sources close to probable zones and 15% increased regional rupture character. The city is divided into several grid points at spacing of 0.01 degrees and the peak ground acceleration (PGA) due to each probable earthquake is calculated at every grid point in city by using the regional attenuation model. The maximum of all these eight PGAs is taken for each grid point and the final PGA map is arrived. This map is compared to the PGA map developed based on the conventional deterministic seismic hazard analysis (DSHA) approach. The probable future rupture earthquakes gave less PGA than that of DSHA approach. The occurrence of any earthquake may be expected in near future in these eight zones, as these eight places have been experiencing minor earthquakes and are located in well-defined seismogenic sources.

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We present reduced dimensionality (RD) 3D HN(CA)NH for efficient sequential assignment in proteins. The experiment correlates the N-15 and H-1 chemical shift of a residue ('i') with those of its immediate N-terminal (i - 1) and C-terminal (i + 1) neighbors and provides four-dimensional chemical shift correlations rapidly with high resolution. An assignment strategy is presented which combines the correlations observed in this experiment with amino acid type information obtained from 3D CBCA(CO)NH. By classifying the 20 amino acid types into seven distinct categories based on C-13(beta) chemical shifts, it is observed that a stretch of five sequentially connected residues is sufficient to map uniquely on to the polypeptide for sequence specific resonance assignments. This method is exemplified by application to three different systems: maltose binding protein (42 kDa), intrinsically disordered domain of insulin-like growth factor binding protein-2 and Ubiquitin. Fast data acquisition is demonstrated using longitudinal H-1 relaxation optimization. Overall, 3D HN(CA)NH is a powerful tool for high throughput resonance assignment, in particular for unfolded or intrinsically disordered polypeptides.

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The December 2011 release of a draft United States Food and Drug Administration (FDA) guidance concerning regulatory classification of pharmaceutical cocrystals of active pharmaceutical ingredients (APIs) addressed two matters of topical interest to the crystal engineering and pharmaceutical science communities: (1) a proposed definition of cocrystals; (2) a proposed classification of pharmaceutical cocrystals as dissociable ``API-excipient'' molecular complexes. The Indo U.S. Bilateral Meeting sponsored by the Indo-U.S. Science and Technology Forum titled The Evolving Role of Solid State Chemistry in Pharmaceutical Science was held in Manesar near Delhi, India, from February 2-4, 2012. A session of the meeting was devoted to discussion of the FDA guidance draft. The debate generated strong consensus on the need to define cocrystals more broadly and to classify them like salts. It was also concluded that the diversity of API crystal forms makes it difficult to classify solid forms into three categories that are mutually exclusive. This perspective summarizes the discussion in the Indo-U.S. Bilateral Meeting and includes contributions from researchers who were not participants in the meeting.