A method for the preferential isolation of actinomycetes from soils

A successful plate-method for the preferential isolation of actinomycetes from soils is described. The principles underlying it are: (1) the inhibition of growth of non-sporulating bacteria by pre-incubation at a high temperature (110 C) for 10 min, and (2) limiting the spreading growth of sporeforming bacteria and fungi by the use of dried plates. The majority of the 191 species isolated by this method from 82 soil samples were shown to be pectinolytic.

A Framework for Classification of Prokaryotic Protein Kinases

Background:Overwhelming majority of the Serine/Threonine protein kinases identified by gleaning archaeal and eubacterial genomes could not be classified into any of the well known Hanks and Hunter subfamilies of protein kinases. This is owing to the development of Hanks and Hunter classification scheme based on eukaryotic protein kinases which are highly divergent from their prokaryotic homologues. A large dataset of prokaryotic Serine/Threonine protein kinases recognized from genomes of prokaryotes have been used to develop a classification framework for prokaryotic Ser/Thr protein kinases. Methodology/Principal Findings: We have used traditional sequence alignment and phylogenetic approaches and clustered the prokaryotic kinases which represent 72 subfamilies with at least 4 members in each. Such a clustering enables classification of prokaryotic Ser/Thr kinases and it can be used as a framework to classify newly identified prokaryotic Ser/Thr kinases. After series of searches in a comprehensive sequence database we recognized that 38 subfamilies of prokaryotic protein kinases are associated to a specific taxonomic level. For example 4, 6 and 3 subfamilies have been identified that are currently specific to phylum proteobacteria, cyanobacteria and actinobacteria respectively. Similarly subfamilies which are specific to an order, sub-order, class, family and genus have also been identified. In addition to these, we also identify organism-diverse subfamilies. Members of these clusters are from organisms of different taxonomic levels, such as archaea, bacteria, eukaryotes and viruses.Conclusion/Significance: Interestingly, occurrence of several taxonomic level specific subfamilies of prokaryotic kinases contrasts with classification of eukaryotic protein kinases in which most of the popular subfamilies of eukaryotic protein kinases occur diversely in several eukaryotes. Many prokaryotic Ser/Thr kinases exhibit a wide variety of modular organization which indicates a degree of complexity and protein-protein interactions in the signaling pathways in these microbes.

Comparison of Multiclass SVM Classification Methods to Use in a Supportive System for Distance Relay Coordination

This paper aims at evaluating the methods of multiclass support vector machines (SVMs) for effective use in distance relay coordination. Also, it describes a strategy of supportive systems to aid the conventional protection philosophy in combating situations where protection systems have maloperated and/or information is missing and provide selective and secure coordinations. SVMs have considerable potential as zone classifiers of distance relay coordination. This typically requires a multiclass SVM classifier to effectively analyze/build the underlying concept between reach of different zones and the apparent impedance trajectory during fault. Several methods have been proposed for multiclass classification where typically several binary SVM classifiers are combined together. Some authors have extended binary SVM classification to one-step single optimization operation considering all classes at once. In this paper, one-step multiclass classification, one-against-all, and one-against-one multiclass methods are compared for their performance with respect to accuracy, number of iterations, number of support vectors, training, and testing time. The performance analysis of these three methods is presented on three data sets belonging to training and testing patterns of three supportive systems for a region and part of a network, which is an equivalent 526-bus system of the practical Indian Western grid.

Classification of magnetic resonance brain images using wavelets as input to support vector machine and neural network

In this paper. we propose a novel method using wavelets as input to neural network self-organizing maps and support vector machine for classification of magnetic resonance (MR) images of the human brain. The proposed method classifies MR brain images as either normal or abnormal. We have tested the proposed approach using a dataset of 52 MR brain images. Good classification percentage of more than 94% was achieved using the neural network self-organizing maps (SOM) and 98% front support vector machine. We observed that the classification rate is high for a Support vector machine classifier compared to self-organizing map-based approach.

Liquid Limit Of Kaolinitic Soils

This paper elucidates the relative importance of soil structure and various compositional factors in influencing the liquid limit of natural kaolinitic soils. Earlier studies dealt with purified systems and anticipated that the liquid limit of the soils would increase with percentage clay size fraction and surface area, and that soils with a greater degree of paricle flocculation would possess a higher liquid limit than soils with a more parallel particle arrangement. The results revealed that the inter-particle attraction and repulsion forces have a prominent role in determining the liquid limit of kaolinitic soils. These forces determine the particle arrangement (clay fabric) which in turn regulates the liquid limit values. The influence of clay fabric was ascertained from the relationships of liquid limit with shrinkage limit and sediment volume (in water) values. It was anticipated that kaolinitic soils with a greater degree of particle flocculatin and a higher liquid limit would shrink less and occupy a higher sedimentation volume. As expected an increase in liquid limit was accompanied by an increase in shrinkage limit and sediment volume in water.

Classification of Protein Kinases on the Basis of Both Kinase and Non-Kinase Regions

Background: Protein phosphorylation is a generic way to regulate signal transduction pathways in all kingdoms of life. In many organisms, it is achieved by the large family of Ser/Thr/Tyr protein kinases which are traditionally classified into groups and subfamilies on the basis of the amino acid sequence of their catalytic domains. Many protein kinases are multidomain in nature but the diversity of the accessory domains and their organization are usually not taken into account while classifying kinases into groups or subfamilies. Methodology: Here, we present an approach which considers amino acid sequences of complete gene products, in order to suggest refinements in sets of pre-classified sequences. The strategy is based on alignment-free similarity scores and iterative Area Under the Curve (AUC) computation. Similarity scores are computed by detecting common patterns between two sequences and scoring them using a substitution matrix, with a consistent normalization scheme. This allows us to handle full-length sequences, and implicitly takes into account domain diversity and domain shuffling. We quantitatively validate our approach on a subset of 212 human protein kinases. We then employ it on the complete repertoire of human protein kinases and suggest few qualitative refinements in the subfamily assignment stored in the KinG database, which is based on catalytic domains only. Based on our new measure, we delineate 37 cases of potential hybrid kinases: sequences for which classical classification based entirely on catalytic domains is inconsistent with the full-length similarity scores computed here, which implicitly consider multi-domain nature and regions outside the catalytic kinase domain. We also provide some examples of hybrid kinases of the protozoan parasite Entamoeba histolytica. Conclusions: The implicit consideration of multi-domain architectures is a valuable inclusion to complement other classification schemes. The proposed algorithm may also be employed to classify other families of enzymes with multidomain architecture.

Semi-Supervised Classification Using Sparse Gaussian Process Regression

Gaussian Processes (GPs) are promising Bayesian methods for classification and regression problems. They have also been used for semi-supervised learning tasks. In this paper, we propose a new algorithm for solving semi-supervised binary classification problem using sparse GP regression (GPR) models. It is closely related to semi-supervised learning based on support vector regression (SVR) and maximum margin clustering. The proposed algorithm is simple and easy to implement. It gives a sparse solution directly unlike the SVR based algorithm. Also, the hyperparameters are estimated easily without resorting to expensive cross-validation technique. Use of sparse GPR model helps in making the proposed algorithm scalable. Preliminary results on synthetic and real-world data sets demonstrate the efficacy of the new algorithm.

Analysis of Compressibility of Sensitive Soils

Sensitive soils, in general, are prone to mechanical disturbances while sampling, handling, and testing. This necessitates the prediction of true field behavior. The compressibility response of such soils is typical of having three zones, mechanistically explained as nonparticulate, transitional, and particulate. Such zoning has enabled the development of a simple method to predict the field compressibility response of the sample. The field compression curve with sigmact act as the most probable yield stress is considered to reflect 0% disturbance. By a comparison of experimentally determined sigmac and sigmact, it is possible to estimate the degree of sample disturbance. When the value of sigmac is closer to sigmact, the sampling disturbance approaches zero. As the value of sigmac reduces, the degree of sampling disturbance increases. The possibility of using this degree of sample disturbance from compressibility data to obtain other true properties from laboratory results of the sampled specimens has been examined.

Cement stabilised rammed earth. Part A: compaction characteristics and physical properties of compacted cement stabilised soils

Rammed earth is used for load bearing walls of buildings and there is growing interest in this low carbon building material. This paper is focused on understanding the compaction characteristics and physical properties of compacted cement stabilised soil mixtures and cement stabilised rammed earth (CSRE). This experimental study addresses (a) influence of soil composition, cement content, time lag on compaction characteristics of stabilised soils and CSRE and (b) effect of moulding water content and density on compressive strength and water absorption of compacted cement stabilised soil mixes. Salient conclusions of the study are (a) compaction characteristics of soils are not affected by the addition of cement, (b) there is 50% fall in strength of CSRE for 10 h time lag, (c) compressive strength of compacted cement stabilised soil increases with increase in density irrespective of moulding moisture content and cement content, and (d) compressive strength increases with the increase in moulding water content and compaction of CSRE on the wet side of OMC is beneficial in terms of strength.

Generalized State Parameter for Partly Saturated Soils

Studies on compressibility and shear strength aspects are the concern of many investigators concerned with partly saturated soils. In soil engineering connected with partly saturated soils, there are no approaches connecting soil states and stress conditions. The present investigation is essentially a step in this direction. A generalized state parameter, identified with regard to material states is shown to be related to the compressibility and shear strength. The involved parameters are simple and normally determined in routine investigations. The advantage of this approach is that changes in soil states due to external stress conditions and the associated changes in strength can be examined particularly when different types of soils are involved.