34 resultados para correlation coefficient

em Indian Institute of Science - Bangalore - Índia


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The significant correlation coefficient between the terrestial heat flow and thermal conductivity computed from the continental heat flow data by Horai and Nur [1]2) may be explained as a natural consequence of terrestrial heat flow through a random medium. The theory predicts a value of 0.40 for the correlation coefficient. A simple statistical test shows that the majority of the computed coefficients belong to the statistical population whose mean is equal to the theoretical correlation coefficient. There are, however, a few observations of unsually high correlation coefficient which cannot be explained by the above hypothesis.

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Conformational changes in proteins are extremely important for their biochemical functions. Correlation between inherent conformational variations in a protein and conformational differences in its homologues of known structure is still unclear. In this study, we have used a structural alphabet called Protein Blocks (PBs). PBs are used to perform abstraction of protein 3-D structures into a 1-D strings of 16 alphabets (a-p) based on dihedral angles of overlapping pentapeptides. We have analyzed the variations in local conformations in terms of PBs represented in the ensembles of 801 protein structures determined using NMR spectroscopy. In the analysis of concatenated data over all the residues in all the NMR ensembles, we observe that the overall nature of inherent local structural variations in NMR ensembles is similar to the nature of local structural differences in homologous proteins with a high correlation coefficient of .94. High correlation at the alignment positions corresponding to helical and beta-sheet regions is only expected. However, the correlation coefficient by considering only the loop regions is also quite high (.91). Surprisingly, segregated position-wise analysis shows that this high correlation does not hold true to loop regions at the structurally equivalent positions in NMR ensembles and their homologues of known structure. This suggests that the general nature of local structural changes is unique; however most of the local structural variations in loop regions of NMR ensembles do not correlate to their local structural differences at structurally equivalent positions in homologues.

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In this work, we address the recovery of block sparse vectors with intra-block correlation, i.e., the recovery of vectors in which the correlated nonzero entries are constrained to lie in a few clusters, from noisy underdetermined linear measurements. Among Bayesian sparse recovery techniques, the cluster Sparse Bayesian Learning (SBL) is an efficient tool for block-sparse vector recovery, with intra-block correlation. However, this technique uses a heuristic method to estimate the intra-block correlation. In this paper, we propose the Nested SBL (NSBL) algorithm, which we derive using a novel Bayesian formulation that facilitates the use of the monotonically convergent nested Expectation Maximization (EM) and a Kalman filtering based learning framework. Unlike the cluster-SBL algorithm, this formulation leads to closed-form EMupdates for estimating the correlation coefficient. We demonstrate the efficacy of the proposed NSBL algorithm using Monte Carlo simulations.

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We believe the Babcock-Leighton process of poloidal field generation to be the main source of irregularity in the solar cycle. The random nature of this process may make the poloidal field in one hemisphere stronger than that in the other hemisphere at the end of a cycle. We expect this to induce an asymmetry in the next sunspot cycle. We look for evidence of this in the observational data and then model it theoretically with our dynamo code. Since actual polar field measurements exist only from the 1970s, we use the polar faculae number data recorded by Sheeley (1991, 2008) as a proxy of the polar field and estimate the hemispheric asymmetry of the polar field in different solar minima during the major part of the twentieth century. This asymmetry is found to have a reasonable correlation with the asymmetry of the next cycle. We then run our dynamo code by feeding information about this asymmetry at the successive minima and compare the results with observational data. We find that the theoretically computed asymmetries of different cycles compare favorably with the observational data, with the correlation coefficient being 0.73. Due to the coupling between the two hemispheres, any hemispheric asymmetry tends to get attenuated with time. The hemispheric asymmetry of a cycle either from observational data or from theoretical calculations statistically tends to be less than the asymmetry in the polar field (as inferred from the faculae data) in the preceding minimum. This reduction factor turns out to be 0.43 and 0.51 respectively in observational data and theoretical simulations.

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Cast aluminium alloy-mica particle composites were made by dispersing mica particles in a vortex produced by stirring the liquid Al-4 wt% Cu-1.5 wt% Mg alloy and then casting the melt containing the suspended particles into permanent moulds. Spiral fluidity and casting fluidity of the alloy containing mica particles in suspension were determined. Both the spiral fluidity and the casting fluidity of the base alloy were found to decrease with an increase in volume or weight percent of mica particles (of a given size), and with a decrease in particle size (for a given amount of particles). The fluidities of Al-4 wt% Cu-1.5 wt% Mg alloys containing suspended mica particles were found to correlate very well with the surface area of suspended mica particles. The regression equation for spiral fluidity Y (cm) as a function of surface area of mica particles per gram of spiral X (cm2 g–1) at 700° C was found to be Y=42.62–0.42X with a correlation coefficient of 0.9634. The regression equations for casting fluidity Yprime (cm) as a functiono of surface area of mica particles per gram of fluidity test piece Xprime (cm2 g–1) at 710 and 670° C were found to be Yprime=19.71–0.17Xprime and Yprime=13.52–0.105Xprime with correlation coefficients of 0.9194 and 0.9612 respectively. The percentage decrease in casting fluidity of composite melts containing up to 2.5 wt% mica with a drop in temperature is quite similar to the corresponding decrease in the casting fluidity of base alloy melts (without mica). The change in fluidity due to mica dispersions has been discussed in terms of changes in viscosity of the composite melts. However, the fluidities of these composite alloys containing up to 2.5 wt% mica are adequate for making a variety of simple castings including bearings for which these alloys have been developed.

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his paper describes an improved microtiter solid-phase enzyme immunoassay for the determination of total and allergen-specific human IgE. This assay technique is unique in its use of the avidin-biotin interaction to increase sensitivity. The avidin-biotin microtiter enzyme-linked immunosorbant assay (AB-microELISA) was performed in polyvinyl chloride microtiter plates using biotinylated anti-IgE and horseradish peroxidase (HRP)-avidin conjugate. This AB-microELISA technique enabled the quantitation of human serum IgE in the range of 0.1–5 ng/ml (10–500 pg/test) in less than 3 h. Total serum IgE, whether measured by the AB-microELISA or the paper radioimmunosorbant test (PRIST) was similar (correlation coefficient, r = 0.92). Further, the presence or absence of positive skin tests to 7 specific allergens determined in serum donors generally agreed with the presence or absence of allergen-specific IgE in their sera as measured by the AB-microELISA. The quantity of short ragweed allergen-specific IgE as determined by the AB-microELISA agreed with values obtained by the radioimmunosorbant test (RAST) (correlation coefficient, r = 0.89). No significant interference by ragweed-specific IgG (blocking antibody) was observed in the quantitation of allergen-specific IgE. The AB-microELISA is not only rapid and inexpensive, but also more sensitive than other published ELISA procedures and comparable to solid-phase radioimmunoassays in the quantitation of total and allergen-specific IgE.

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This study explores the utility of polarimetric measurements for discriminating between hydrometeor types with the emphasis on (a) hail detection and discrimination of its size, (b) measurement of heavy precipitation, (c) identification and quantification of mixed-phase hydrometeors, and (d) discrimination of ice forms. In particular, we examine the specific differential phase, the backscatter differential phase, the correlation coefficient between vertically and horizontally polarized waves, and the differential reflectivity, collected from a storm at close range. Three range–height cross sections are analyzed together with complementary data from a prototype WSR-88D radar. The case is interesting because it demonstrates the complementary nature of these polarimetric measurands. Self-consistency among them allows qualitative and some quantitative discrimination between hydrometeors.

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Four polarimetric measurands were collected in the stratiform region of a mesoscale convective system. The four are the reflectivity factor, the differential reflectivity, the correlation coefficient between orthogonal copolar echoes, and the differential propagation constant. Most striking is a signature of large aggregates (about 10 mm in size) seen in the differential phase through the melting layer. Another significant feature is an abrupt notch in the correlation coefficient that occurs towards the bottom of the bright band. Aircraft observations and a one-dimensional cloud model are used to explain some polarimetric measurements and to infer the presence of aggregates, graupel, and supercooled cloud water in the stratiform region. These unique observations and model data provide inferences concerning the presence of graupel and the growth of large aggregates in the melting layer.

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The EEG time series has been subjected to various formalisms of analysis to extract meaningful information regarding the underlying neural events. In this paper the linear prediction (LP) method has been used for analysis and presentation of spectral array data for the better visualisation of background EEG activity. It has also been used for signal generation, efficient data storage and transmission of EEG. The LP method is compared with the standard Fourier method of compressed spectral array (CSA) of the multichannel EEG data. The autocorrelation autoregressive (AR) technique is used for obtaining the LP coefficients with a model order of 15. While the Fourier method reduces the data only by half, the LP method just requires the storage of signal variance and LP coefficients. The signal generated using white Gaussian noise as the input to the LP filter has a high correlation coefficient of 0.97 with that of original signal, thus making LP as a useful tool for storage and transmission of EEG. The biological significance of Fourier method and the LP method in respect to the microstructure of neuronal events in the generation of EEG is discussed.

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Simple and rapid HPLC, GC, and TLC procedures have been developed for detection and determination of nimesulide, a non-pharmacopeial drug, in preformulation and dosage form. Use of these techniques has enabled separation of impurities and the precursor in the bulk material and in formulations. Isocratic reversed-phase HPLC was performed on a C-18 column with methanol-water-acetic acid, 67:32:1 (v/v), as mobile phase and UV detection at 230 nm. Calibration curves were linear over the concentration range 100-1000 mug mL(-1) with a good correlation coefficient (0.9993) and a coefficient of variation of 1.5%. Gas chromatography was performed on an OV-17 packed column with temperature programming and flame-ionization detection. The lower limit of determination by HPLC and GC was 4 ppm. Thin-layer chromatography of nimesulide was performed on silica gel G with toluene-ethyl acetate, 8:2, as mobile phase. Stability testing of the drug was performed under different temperature, humidity, and UV-radiation conditions.

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Depth measures the extent of atom/residue burial within a protein. It correlates with properties such as protein stability, hydrogen exchange rate, protein-protein interaction hot spots, post-translational modification sites and sequence variability. Our server, DEPTH, accurately computes depth and solvent-accessible surface area (SASA) values. We show that depth can be used to predict small molecule ligand binding cavities in proteins. Often, some of the residues lining a ligand binding cavity are both deep and solvent exposed. Using the depth-SASA pair values for a residue, its likelihood to form part of a small molecule binding cavity is estimated. The parameters of the method were calibrated over a training set of 900 high-resolution X-ray crystal structures of single-domain proteins bound to small molecules (molecular weight < 1.5 KDa). The prediction accuracy of DEPTH is comparable to that of other geometry-based prediction methods including LIGSITE, SURFNET and Pocket-Finder (all with Matthew's correlation coefficient of similar to 0.4) over a testing set of 225 single and multi-chain protein structures. Users have the option of tuning several parameters to detect cavities of different sizes, for example, geometrically flat binding sites. The input to the server is a protein 3D structure in PDB format. The users have the option of tuning the values of four parameters associated with the computation of residue depth and the prediction of binding cavities. The computed depths, SASA and binding cavity predictions are displayed in 2D plots and mapped onto 3D representations of the protein structure using Jmol. Links are provided to download the outputs. Our server is useful for all structural analysis based on residue depth and SASA, such as guiding site-directed mutagenesis experiments and small molecule docking exercises, in the context of protein functional annotation and drug discovery.

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For over a century, the term break has been used for spells in which the rainfall over the Indian monsoon zone is interrupted. The phenomenon of 'break monsoon' is of great interest because long intense breaks are often associated with poor monsoon seasons. Such breaks have distinct circulation characteristics (heat trough type circulation) and have a large impact on rainfed agriculture. Although interruption of the monsoon rainfall is considered to be the most important feature of the break monsoon, traditionally breaks have been identified on the basis of the surface pressure and wind patterns over the Indian region. We have defined breaks (and active spells) on the basis of rainfall over the monsoon zone. The rainfall criteria are chosen so as to ensure a large overlap with the traditional breaks documented by Ramamurthy (1969) and De et al (1998). We have identified these rainbreaks for 1901-89. We have also identified active spells on the basis of rainfall over the Indian monsoon zone. We have shown that the all-India summer monsoon rainfall is significantly negatively correlated with the number of rainbreak days (correlation coefficient -0.56) and significantly positively correlated with the number of active days (correlation coefficient 0.47). Thus the interannual variation of the all-India summer monsoon rainfall is shown to be related to the number of days of rainbreaks and active spells identified here. There have been several studies of breaks (and also active spells in several cases) identified on the basis of different criteria over regions differing in spatial scales (e.g., Webster et al 1998; Krishnan et al 2000; Goswami and Mohan 2000; and Annamalai and Slingo 2001). We find that there is considerable overlap between the rainbreaks we have identified and breaks based on the traditional definition. There is some overlap with the breaks identified by Krishnan et al (2000) but little overlap with breaks identified by Webster et al (1998). Further, there are three or four active-break cycles in a season according to Webster et al (1998) which implies a time scale of about 40 days for which Goswami and Mohan (2000), and Annamalai and Slingo'(2001) have studied breaks and active minus break fluctuations. On the other hand, neither the traditional breaks (Ramamurthy 1969; and De et al 1998) nor the rainbreaks occur every year. This suggests that the 'breaks' in these studies axe weak spells of the intraseasonal variation of the monsoon, which occur every year. We have derived the OLR and circulation patterns associated with rainbreaks and active spells and compared them with the patterns associated with breaks/active minus break spells from these studies. Inspite of differences in the patterns over the Indian region, there is one feature which is seen in the OLR anomaly patterns of breaks identified on the basis of different criteria as well as the rainbreaks identified in this paper viz., a quadrapole over the Asia-west Pacific region arising from anomalies opposite (same) in sign to those over the Indian region occurring over the equatorial Indian Ocean and northern tropical (equatorial) parts of the west Pacific. Thus it appears that this quadrapole is a basic feature of weak spells of the intraseasonal,variation over the Asia-west Pacific region. Since the rainbreaks are intense weak spells, this basic feature is also seen in the composite patterns of these breaks. We find that rainbreaks (active spells) are also associated with negative (positive) anomalies over a part of the cast Pacific suggesting that the convection over the Indian region is linked to that over the east Pacific not only on the interannual scale (as evinced by the link between the Indian summer monsoon rainfall and ENSO) but on the intraseasonal scale as well.

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Land-use changes influence local biodiversity directly, and also cumulatively, contribute to regional and global changes in natural systems and quality of life. Consequent to these, direct impacts on the natural resources that support the health and integrity of living beings are evident in recent times. The Western Ghats being one of the global biodiversity hotspots, is reeling under a tremendous pressure from human induced changes in terms of developmental projects like hydel or thermal power plants, big dams, mining activities, unplanned agricultural practices,monoculture plantations, illegal timber logging, etc. This has led to the once contiguous forest habitats to be fragmented in patches, which in turn has led to the shrinkage of original habitat for the wildlife, change in the hydrological regime of the catchment, decreased inflow in streams,human-animal conflicts, etc. Under such circumstances, a proper management practice is called for requiring suitable biological indicators to show the impact of these changes, set priority regions and in developing models for conservation planning. Amphibians are regarded as one of the best biological indicators due to their sensitivity to even the slightest changes in the environment and hence they could be used as surrogates in conservation and management practices. They are the predominating vertebrates with a high degree of endemism (78%) in Western Ghats. The present study is an attempt to bring in the impacts of various land-uses on anuran distribution in three river basins. Sampling was carried out for amphibians during all seasons of 2003-2006 in basins of Sharavathi, Aghanashini and Bedthi. There are as many as 46 species in the region, one of which is new to science and nearly 59% of them are endemic to the Western Ghats. They belong to nine families, Dicroglossidae being represented by 14 species,followed by Rhacophoridae (9 species) and Ranidae (5 species). Species richness is high in Sharavathi river basin, with 36 species, followed by Bedthi 33 and Aghanashini 27. The impact of land-use changes, was investigated in the upper catchment of Sharavathi river basin. Species diversity indices, relative abundance values, percentage endemics gave clear indication of differences in each sub-catchment. Karl Pearson’s correlation coefficient (r) was calculated between species richness, endemics, environmental descriptors, land-use classes and fragmentation metrics. Principal component analysis was performed to depict the influence of these variables. Results show that sub-catchments with lesser percentage of forest, low canopy cover, higher amount of agricultural area, low rainfall have low species richness, less endemic species and abundant non-endemic species, whereas endemism, species richness and abundance of endemic species are more in the sub-catchments with high tree density, endemic trees, canopy cover, rainfall and lower amount of agriculture fields. This analysis aided in prioritising regions in the Sharavathi river basin for further conservation measures.

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This paper elucidates the methodology of applying artificial neural network model (ANNM) to predict the percent swell of calcitic soil in sulphuric acid solutions, a complex phenomenon involving many parameters. Swell data required for modelling is experimentally obtained using conventional oedometer tests under nominal surcharge. The phases in ANN include optimal design of architecture, operation and training of architecture. The designed optimal neural model (3-5-1) is a fully connected three layer feed forward network with symmetric sigmoid activation function and trained by the back propagation algorithm to minimize a quadratic error criterion.The used model requires parameters such as duration of interaction, calcite mineral content and acid concentration for prediction of swell. The observed strong correlation coefficient (R2 = 0.9979) between the values determined by the experiment and predicted using the developed model demonstrates that the network can provide answers to complex problems in geotechnical engineering.