Site characterization model using least-square support vector machine and relevance vector machine based on corrected SPT data (N-c)

Statistical learning algorithms provide a viable framework for geotechnical engineering modeling. This paper describes two statistical learning algorithms applied for site characterization modeling based on standard penetration test (SPT) data. More than 2700 field SPT values (N) have been collected from 766 boreholes spread over an area of 220 sqkm area in Bangalore. To get N corrected value (N,), N values have been corrected (Ne) for different parameters such as overburden stress, size of borehole, type of sampler, length of connecting rod, etc. In three-dimensional site characterization model, the function N-c=N-c (X, Y, Z), where X, Y and Z are the coordinates of a point corresponding to N, value, is to be approximated in which N, value at any half-space point in Bangalore can be determined. The first algorithm uses least-square support vector machine (LSSVM), which is related to aridge regression type of support vector machine. The second algorithm uses relevance vector machine (RVM), which combines the strengths of kernel-based methods and Bayesian theory to establish the relationships between a set of input vectors and a desired output. The paper also presents the comparative study between the developed LSSVM and RVM model for site characterization. Copyright (C) 2009 John Wiley & Sons,Ltd.

A neural network based CBIR system using STI features and relevance feedback

Multimedia mining primarily involves, information analysis and retrieval based on implicit knowledge. The ever increasing digital image databases on the Internet has created a need for using multimedia mining on these databases for effective and efficient retrieval of images. Contents of an image can be expressed in different features such as Shape, Texture and Intensity-distribution(STI). Content Based Image Retrieval(CBIR) is an efficient retrieval of relevant images from large databases based on features extracted from the image. Most of the existing systems either concentrate on a single representation of all features or linear combination of these features. The paper proposes a CBIR System named STIRF (Shape, Texture, Intensity-distribution with Relevance Feedback) that uses a neural network for nonlinear combination of the heterogenous STI features. Further the system is self-adaptable to different applications and users based upon relevance feedback. Prior to retrieval of relevant images, each feature is first clustered independent of the other in its own space and this helps in matching of similar images. Testing the system on a database of images with varied contents and intensive backgrounds showed good results with most relevant images being retrieved for a image query. The system showed better and more robust performance compared to existing CBIR systems

New evidences on Tau-DNA interactions and relevance to neurodegeneration

Tau is mainly distributed in cytoplasm and also found to be localized in the nucleus. There is limited data on DNA binding potential of Tau.We provide novel evidence on nicking of DNA by Tau. Tau nicks the supercoiled DNA leading to open circular and linear forms. The metal ion magnesium (a co-factor for endonuclease) enhanced the Tau DNA nicking ability, while an endonuclease specific inhibitor,aurinetricarboxylic acid (ATA) inhibited the Tau DNA nicking ability Further, we also evidenced that Tau induces B-C-A mixed conformational transition in DNA and also changes DNA stability. Tau-scDNA complex is more sensitive to DNAse I digestion indicating stability changes in DNA caused by Tau. These findings indicate that Tau alters DNA helicity and integrity and also nicks the DNA. The relevance of these novel intriguing findings regarding the role Tau in neuronal dysfunction is discussed. (C) 2010 Elsevier Ltd. All rights reserved.

Extent of Structural Asymmetry in Homodimeric Proteins: Prevalence and Relevance

Most homodimeric proteins have symmetric structure. Although symmetry is known to confer structural and functional advantage, asymmetric organization is also observed. Using a non-redundant dataset of 223 high-resolution crystal structures of biologically relevant homodimers, we address questions on the prevalence and significance of asymmetry. We used two measures to quantify global and interface asymmetry, and assess the correlation of several molecular and structural parameters with asymmetry. We have identified rare cases (11/223) of biologically relevant homodimers with pronounced global asymmetry. Asymmetry serves as a means to bring about 2:1 binding between the homodimer and another molecule; it also enables cellular signalling arising from asymmetric macromolecular ligands such as DNA. Analysis of these cases reveals two possible mechanisms by which possible infinite array formation is prevented. In case of homodimers associating via non-topologically equivalent surfaces in their tertiary structures, ligand-dependent mechanisms are used. For stable dimers binding via large surfaces, ligand-dependent structural change regulates polymerisation/depolymerisation; for unstable dimers binding via smaller surfaces that are not evolutionarily well conserved, dimerisation occurs only in the presence of the ligand. In case of homodimers associating via interaction surfaces with parts of the surfaces topologically equivalent in the tertiary structures, steric hindrance serves as the preventive mechanism of infinite array. We also find that homodimers exhibiting grossly symmetric organization rarely exhibit either perfect local symmetry or high local asymmetry. Binding of small ligands at the interface does not cause any significant variation in interface asymmetry. However, identification of biologically relevant interface asymmetry in grossly symmetric homodimers is confounded by the presence of similar small magnitude changes caused due to artefacts of crystallisation. Our study provides new insights regarding accommodation of asymmetry in homodimers.

Estimation of Probabilistic Bounds on Phase CPI and Relevance in WCET Analysis

Estimating program worst case execution time(WCET) accurately and efficiently is a challenging task. Several programs exhibit phase behavior wherein cycles per instruction (CPI) varies in phases during execution. Recent work has suggested the use of phases in such programs to estimate WCET with minimal instrumentation. However the suggested model uses a function of mean CPI that has no probabilistic guarantees. We propose to use Chebyshev's inequality that can be applied to any arbitrary distribution of CPI samples, to probabilistically bound CPI of a phase. Applying Chebyshev's inequality to phases that exhibit high CPI variation leads to pessimistic upper bounds. We propose a mechanism that refines such phases into sub-phases based on program counter(PC) signatures collected using profiling and also allows the user to control variance of CPI within a sub-phase. We describe a WCET analyzer built on these lines and evaluate it with standard WCET and embedded benchmark suites on two different architectures for three chosen probabilities, p={0.9, 0.95 and 0.99}. For p= 0.99, refinement based on PC signatures alone, reduces average pessimism of WCET estimate by 36%(77%) on Arch1 (Arch2). Compared to Chronos, an open source static WCET analyzer, the average improvement in estimates obtained by refinement is 5%(125%) on Arch1 (Arch2). On limiting variance of CPI within a sub-phase to {50%, 10%, 5% and 1%} of its original value, average accuracy of WCET estimate improves further to {9%, 11%, 12% and 13%} respectively, on Arch1. On Arch2, average accuracy of WCET improves to 159% when CPI variance is limited to 50% of its original value and improvement is marginal beyond that point.

SPSA Based Feature Relevance Estimation For Video Retrieval

With the availability of a huge amount of video data on various sources, efficient video retrieval tools are increasingly in demand. Video being a multi-modal data, the perceptions of ``relevance'' between the user provided query video (in case of Query-By-Example type of video search) and retrieved video clips are subjective in nature. We present an efficient video retrieval method that takes user's feedback on the relevance of retrieved videos and iteratively reformulates the input query feature vectors (QFV) for improved video retrieval. The QFV reformulation is done by a simple, but powerful feature weight optimization method based on Simultaneous Perturbation Stochastic Approximation (SPSA) technique. A video retrieval system with video indexing, searching and relevance feedback (RF) phases is built for demonstrating the performance of the proposed method. The query and database videos are indexed using the conventional video features like color, texture, etc. However, we use the comprehensive and novel methods of feature representations, and a spatio-temporal distance measure to retrieve the top M videos that are similar to the query. In feedback phase, the user activated iterative on the previously retrieved videos is used to reformulate the QFV weights (measure of importance) that reflect the user's preference, automatically. It is our observation that a few iterations of such feedback are generally sufficient for retrieving the desired video clips. The novel application of SPSA based RF for user-oriented feature weights optimization makes the proposed method to be distinct from the existing ones. The experimental results show that the proposed RF based video retrieval exhibit good performance.

Varied Immune Response to FVIII: Presence of Proteolytic Antibodies Directed to Factor VIII in Different Human Pathologies

The versatility of antibodies is demonstrated by the various functions that they mediate such as neutralization, agglutination, fixation of the complement and its activation, and activation of effector cells. In addition to this plethora of functions, antibodies are capable of expressing enzymatic activity. Antibodies with catalytic function are a result of the productive interplay between the highly evolved machinery of the immune system and the chemical framework used to induce them (antigens). Catalytic antibodies are immunoglobulins with an ability to catalyze the reactions involving the antigen for which they are specific. Catalytic immunoglobulins of the IgM and IgG isotypes have been detected in the serum of healthy donors. In addition, catalytic immunoglobulins of the IgA isotype have been detected in the milk of healthy mothers. Conversely, antigen-specific hydrolytic antibodies have been reported in a number of inflammatory, autoimmune, and neoplastic disorders. The pathophysiological occurrence and relevance of catalytic antibodies remains a debated issue. Through the description of the hydrolysis of coagulation factor VIII as model target antigen, we propose that catalytic antibodies directed to the coagulation factor VIII may play a beneficial or a deleterious role depending on the immuno-inflammatory condition under which they occur.

Applicability of Statistical Learning Algorithms for Spatial Variability of Rock Depth

Two algorithms are outlined, each of which has interesting features for modeling of spatial variability of rock depth. In this paper, reduced level of rock at Bangalore, India, is arrived from the 652 boreholes data in the area covering 220 sqa <.km. Support vector machine (SVM) and relevance vector machine (RVM) have been utilized to predict the reduced level of rock in the subsurface of Bangalore and to study the spatial variability of the rock depth. The support vector machine (SVM) that is firmly based on the theory of statistical learning theory uses regression technique by introducing epsilon-insensitive loss function has been adopted. RVM is a probabilistic model similar to the widespread SVM, but where the training takes place in a Bayesian framework. Prediction results show the ability of learning machine to build accurate models for spatial variability of rock depth with strong predictive capabilities. The paper also highlights the capability ofRVM over the SVM model.

Studies on multi-metal ion tolerance of Thiobacillus ferrooxidans

The influence of different concentrations of base metal ions, such as CU2+, Zn2+ and Fe3+, when present either alone or in different possible binary and ternary combinations in a 9K medium, on the fel rous ion oxidation ability of Thiobacillus ferrooxidans was studied. Levels and degree of toxicity of these ions have been quantified in terms of toxicity index (TI). Copper and zinc tolerant strains of the bacteria were developed through serial subculturing and their activity tested in the presence of the above metal ions in comparison with the behavior of wild unadapted cells under similar conditions. Copper tolerant strains (25 g/L Cu2+) were found to be more efficient in the bioleaching of both copper and zinc concentrates than wild unadapted strains, while zinc tolerant strains (40 g/L Zn2+) exhibited better leaching efficiency only in the bioleaching of sphalerite concentrates. The significance and relevance of multi-metal ion tolerance in Thiobacillus ferrooxidans has been highlighted with respect to bioleaching of sulphide mineral concentrates. (C) 1997 Published by Elsevier Science Ltd.

Microbial aspects of acid generation and bioremediation with relevance to indian mining

The role of Acidithiobacillus group of bacteria in acid generation and heavy metal dissolution was studied with relevance to some Indian mines. Microorganisms implicated in acid generation such as Acidithiobacillus Acidithicibacillus thiooxidans and Leptospirillum ferrooxidans were isolated from abandoned mines, waste rocks and tailing dumps. Arsenite oxidizing Thiomonas and Bacillus group of bacteria were isolated and their ability to oxidize As (111) to As (V) established. Mine isolated Sulfate reducing bacteria were used to remove dissolved copper, zinc, iron and arsenic from solutions.

The generalized anomeric effect in the 1,3-thiazolidines: Evidence forboth sulphur and nitrogen as electron donors. Crystal structures of various N-acylthiazolidines including mercury(II) complexes. Possible relevance to penicillin action

Evidence for the generalized anomeric effect (GAE) in the N-acyl-1,3-thiazolidines, an important structural motif in the penicillins, was sought in the crystal structures of N-(4-nitrobenzoyl)-1,3-thiazolidine and its (2:1) complex with mercuric chloride, N-acetyl-2-phenyl-1,3-thiazolidine, and the (2:1) complex of N-benzoyl-1,3-thiazolidine with mercuric bromide. An inverse relationship was generally observed between the. C-2-N and C-2-S bond lengths of the thiazolidine ring, supporting the existence of the GAE. (Maximal bond length changes were similar to 0.04 angstrom for C-2-N-3, S-1-C-2, and similar to 0.08 angstrom for N-3-C-6.) Comparison with N-acylpyrrolidines and tetrahydrothiophenes indicates that both the nitrogen-to-sulphur and sulphur-to-nitrogen GAE's operate simultaneously in the 1,3-thiazolidines, the former being dominant. (This is analogous to the normal and exo-anomeric effects in pyranoses, and also leads to an interesting application of Baldwin's rules.) The nitrogen-to-sulphur GAE is generally enhanced in the mercury(II) complexes (presumably via coordination at the sulphur); a 'competition' between the GAE and the amide resonance of the N-acyl moiety is apparent. There is evidence for a 'push-pull' charge transfer between the thiazolidine moieties in the mercury(II) complexes, and for a 'back-donation' of charge from the bromine atoms to the thiazolidine moieties in the HgBr2 complex. (The sulphur atom appears to be sp(2) hybridised in the mercury(II) complexes, possibly for stereoelectronic reasons.) These results are apparently relevant to the mode of action of the penicillins. (c) 2006 Elsevier B.V. All rights reserved.

Positional dependence of material flow in friction stir welding: analysis of joint line remnant and its relevance to dissimilar metal welding

Understanding material flow in friction stir welding is important for production of sound dissimilar metal welding that control the intermixing of two alloys being welded and consequent formation of new constituents which influences the weld properties. In the present experimental investigation material flow patterns are visualised using dissimilar and similar aluminium alloys using a simple innovative ,experiment. The experimental results reveal that only a portion of material transported from the leading edge undergoes chaotic flow and the remaining is deposited systematically in the trailing edge of the weld. Using this information it is shown that the formation of a friction stir welding defect, joint line remnant, does not occur only when the weld interface is on the advancing side. The material flow visualisation study has been utilised to analyse the mechanism of weld formation and its usefulness in improving fatigue properties and for dissimilar metal welds.

An XPS study on oxidation states of Pt and its alloys with Co and Cr and its relevance to electroreduction of oxygen

Cathodic reduction of oxygen in fuel cells is known to be enhanced on platinum alloys in relation to the platinum metal. The higher performance of the platinum alloys is as a result of the improved oxygen-reduction kinetics on the alloys but there is hardly any increase in the electrode platinum-surface-areas for the platinum alloys as compared to the platinum metal, and thus the higher performance is solely due to the enhanced electrocatalytic activity of the alloys as compared to the platinum metal. The present X-ray photoelectron spectroscopic (XPS) study on carbon-supported Pt, Pt–Co and Pt–Co–Cr electrocatalysts suggests the presence of a relatively lower Pt-oxide content on the alloys. The X-ray powder diffraction patterns for these electrocatalysts show that while the carbon-supported platinum electrocatalyst has a face-centered cubic (fcc) phase, carbon-supported Pt–Co and Pt–Co–Cr electrocatalysts exhibit a face-centered tetragonal (fct) phase. But, Pt electrocatalyst has a lower particle-size and, hence, a higher dispersion. Previous studies have shown higher activities on the Pt-alloys than on Pt, and have attributed it to changes in the electronic and structural characteristics of Pt. These changes can be correlated with the lower oxidation-state of Pt sites, as found in this study.