An enzymic approach to the study of sewage and sludges

The purpose of the work described here has been (a) to obtain some evidence on catalase (an oxidative enzyme) and protease, urease and phosphatase (hydrolytic enzymes) in sewage, activated sludge and septic tank sludge, and (b) to use this evidence, as a new approach, to find out the relationship between the main groups of the micro-organisms (bacteria and protozoa) and their relative influence on the purification process. To make a rapid assessment of the enzyme activities in these systems in the course of three weeks, as an experimental measure, rat tissues were added, which might serve as an additional or a ‘shock’ load of organic matter to follow broadly the development of bacteria and protozoa and the changes in the enzyme activities in the different systems. A control system with sewage alone was also run. The results showed that the initial decomposition of the fresh organic matter added to sewage and sludges was almost entirely due to bacterial activity and the later oxidative changes and removal of the suspended solids, including the bacteria, were largely due to the protozoa, such as Epistylis articulata. Analysis of the enzyme activities in the different materials showed, among other things, that the activated sludge, with its mized bacteria, protozoa and other organisms, as a whole, contained about twenty times more protease activity than an equivalent amount of the protozoan E. articulata, and that this protozoan contained five times more catalase activity than the activated sludge. The significance of these observations is discussed.

Learning with a mutualistic teacher

The concept of a “mutualistic teacher” is introduced for unsupervised learning of the mean vectors of the components of a mixture of multivariate normal densities, when the number of classes is also unknown. The unsupervised learning problem is formulated here as a multi-stage quasi-supervised problem incorporating a cluster approach. The mutualistic teacher creates a quasi-supervised environment at each stage by picking out “mutual pairs” of samples and assigning identical (but unknown) labels to the individuals of each mutual pair. The number of classes, if not specified, can be determined at an intermediate stage. The risk in assigning identical labels to the individuals of mutual pairs is estimated. Results of some simulation studies are presented.

Image reconstruction from incomplete projections data: A multiresolution modeling approach

Computerized tomography is an imaging technique which produces cross sectional map of an object from its line integrals. Image reconstruction algorithms require collection of line integrals covering the whole measurement range. However, in many practical situations part of projection data is inaccurately measured or not measured at all. In such incomplete projection data situations, conventional image reconstruction algorithms like the convolution back projection algorithm (CBP) and the Fourier reconstruction algorithm, assuming the projection data to be complete, produce degraded images. In this paper, a multiresolution multiscale modeling using the wavelet transform coefficients of projections is proposed for projection completion. The missing coefficients are then predicted based on these models at each scale followed by inverse wavelet transform to obtain the estimated projection data.

A chemical approach to understand fragilities of glass-forming liquids

Fragility is viewed as a measure of the loss of rigidity of a glass structure above its glass transition temperature. It is attributed to the weakness of directional bonding and to the presence of a high density of low-energy configurational states. An a priori fragility function of electronegativities and bond distances is proposed which quite remarkably reproduces the entire range of reported fragilities and demonstrates that the fragility of a melt is indeed encrypted in the chemistry of the parent material. It has also been shown that the use of fragility-modified activation barriers in the Arrhenius function account for the whole gamut of viscosity behavior of liquids. It is shown that fragility can be a universal scaling parameter to collapse all viscosity curves on to a master plot.

A multi-level multi-scale approach to study essential genes in Mycobacterium tuberculosis

Background: The set of indispensable genes that are required by an organism to grow and sustain life are termed as essential genes. There is a strong interest in identification of the set of essential genes, particularly in pathogens, not only for a better understanding of the pathogen biology, but also for identifying drug targets and the minimal gene set for the organism. Essentiality is inherently a systems property and requires consideration of the system as a whole for their identification. The available experimental approaches capture some aspects but each method comes with its own limitations. Moreover, they do not explain the basis for essentiality in most cases. A powerful prediction method to recognize this gene pool including rationalization of the known essential genes in a given organism would be very useful. Here we describe a multi-level multi-scale approach to identify the essential gene pool in a deadly pathogen, Mycobacterium tuberculosis. Results: The multi-level workflow analyses the bacterial cell by studying (a) genome-wide gene expression profiles to identify the set of genes which show consistent and significant levels of expression in multiple samples of the same condition, (b) indispensability for growth by using gene expression integrated flux balance analysis of a genome-scale metabolic model, (c) importance for maintaining the integrity and flow in a protein-protein interaction network and (d) evolutionary conservation in a set of genomes of the same ecological niche. In the gene pool identified, the functional basis for essentiality has been addressed by studying residue level conservation and the sub-structure at the ligand binding pockets, from which essential amino acid residues in that pocket have also been identified. 283 genes were identified as essential genes with high-confidence. An agreement of about 73.5% is observed with that obtained from the experimental transposon mutagenesis technique. A large proportion of the identified genes belong to the class of intermediary metabolism and respiration. Conclusions: The multi-scale, multi-level approach described can be generally applied to other pathogens as well. The essential gene pool identified form a basis for designing experiments to probe their finer functional roles and also serve as a ready shortlist for identifying drug targets.

Reliability-based load and resistance factor design approach for external seismic stability of reinforced soil walls

Load and resistance factor design (LRFD) approach for the design of reinforced soil walls is presented to produce designs with consistent and uniform levels of risk for the whole range of design applications. The evaluation of load and resistance factors for the reinforced soil walls based on reliability theory is presented. A first order reliability method (FORM) is used to determine appropriate ranges for the values of the load and resistance factors. Using pseudo-static limit equilibrium method, analysis is conducted to evaluate the external stability of reinforced soil walls subjected to earthquake loading. The potential failure mechanisms considered in the analysis are sliding failure, eccentricity failure of resultant force (or overturning failure) and bearing capacity failure. The proposed procedure includes the variability associated with reinforced backfill, retained backfill, foundation soil, horizontal seismic acceleration and surcharge load acting on the wall. Partial factors needed to maintain the stability against three modes of failure by targeting component reliability index of 3.0 are obtained for various values of coefficients of variation (COV) of friction angle of backfill and foundation soil, distributed dead load surcharge, cohesion of the foundation soil and horizontal seismic acceleration. A comparative study between LRFD and allowable stress design (ASD) is also presented with a design example. (C) 2014 Elsevier Ltd. All rights reserved.

Avoiding acidic region streaking in two-dimensional gel electrophoresis: Case study with two bacterial whole cell protein extracts

Acidic region streaking (ARS) is one of the lacunae in two-dimensional gel electrophoresis (2DE) of bacterial proteome. This streaking is primarily caused by nucleic acid (NuA) contamination and poses major problem in the downstream processes like image analysis and protein identification. Although cleanup and nuclease digestion are practiced as remedial options, these strategies may incur loss in protein recovery and perform incomplete removal of NuA. As a result, ARS has remained a common observation across publications, including the recent ones. In this work, we demonstrate how ultrasound wave can be used to shear NuA in plain ice-cooled water, facilitating the elimination of ARS in the 2DE gels without the need for any additional sample cleanup tasks. In combination with a suitable buffer recipe, IEF program and frequent paper-wick changing approach, we are able to reproducibly demonstrate the production of clean 2DE gels with improved protein recovery and negligible or no ARS. We illustrate our procedure using whole cell protein extracts from two diverse organisms, Escherichia coli and Mycobacterium smegmatis. Our designed protocols are straightforward and expected to provide good 2DE gels without ARS, with comparable times and significantly lower cost.

Estimation of `drainable' storage - A geomorphological approach

Storage of water within a river basin is often estimated by analyzing recession flow curves as it cannot be `instantly' estimated with the aid of available technologies. In this study we explicitly deal with the issue of estimation of `drainable' storage, which is equal to the area under the `complete' recession flow curve (i.e. a discharge vs. time curve where discharge continuously decreases till it approaches zero). But a major challenge in this regard is that recession curves are rarely `complete' due to short inter-storm time intervals. Therefore, it is essential to analyze and model recession flows meaningfully. We adopt the wellknown Brutsaert and Nieber analytical method that expresses time derivative of discharge (dQ/dt) as a power law function of Q : -dQ/dt = kQ(alpha). However, the problem with dQ/dt-Q analysis is that it is not suitable for late recession flows. Traditional studies often compute alpha considering early recession flows and assume that its value is constant for the whole recession event. But this approach gives unrealistic results when alpha >= 2, a common case. We address this issue here by using the recently proposed geomorphological recession flow model (GRFM) that exploits the dynamics of active drainage networks. According to the model, alpha is close to 2 for early recession flows and 0 for late recession flows. We then derive a simple expression for drainable storage in terms the power law coefficient k, obtained by considering early recession flows only, and basin area. Using 121 complete recession curves from 27 USGS basins we show that predicted drainable storage matches well with observed drainable storage, indicating that the model can also reliably estimate drainable storage for `incomplete' recession events to address many challenges related to water resources. (C) 2014 Elsevier Ltd. All rights reserved.