Computational framework to integrate the effect of antigen recognition on disease epidemiology outcome: multi-scale approach

Human Leukocyte Antigen (HLA) plays an important role, in presenting foreign pathogens to our immune system, there by eliciting early immune responses. HLA genes are highly polymorphic, giving rise to diverse antigen presentation capability. An important factor contributing to enormous variations in individual responses to diseases is differences in their HLA profiles. The heterogeneity in allele specific disease responses decides the overall disease epidemiological outcome. Here we propose an agent based computational framework, capable of incorporating allele specific information, to analyze disease epidemiology. This framework assumes a SIR model to estimate average disease transmission and recovery rate. Using epitope prediction tool, it performs sequence based epitope detection for a given the pathogenic genome and derives an allele specific disease susceptibility index depending on the epitope detection efficiency. The allele specific disease transmission rate, that follows, is then fed to the agent based epidemiology model, to analyze the disease outcome. The methodology presented here has a potential use in understanding how a disease spreads and effective measures to control the disease.

PolyGLoT: A Polyhedral Loop Transformation Framework for a Graphical Dataflow Language

Polyhedral techniques for program transformation are now used in several proprietary and open source compilers. However, most of the research on polyhedral compilation has focused on imperative languages such as C, where the computation is specified in terms of statements with zero or more nested loops and other control structures around them. Graphical dataflow languages, where there is no notion of statements or a schedule specifying their relative execution order, have so far not been studied using a powerful transformation or optimization approach. The execution semantics and referential transparency of dataflow languages impose a different set of challenges. In this paper, we attempt to bridge this gap by presenting techniques that can be used to extract polyhedral representation from dataflow programs and to synthesize them from their equivalent polyhedral representation. We then describe PolyGLoT, a framework for automatic transformation of dataflow programs which we built using our techniques and other popular research tools such as Clan and Pluto. For the purpose of experimental evaluation, we used our tools to compile LabVIEW, one of the most widely used dataflow programming languages. Results show that dataflow programs transformed using our framework are able to outperform those compiled otherwise by up to a factor of seventeen, with a mean speed-up of 2.30x while running on an 8-core Intel system.

An iterative framework for sparse signal reconstruction algorithms

It has been shown that iterative re-weighted strategies will often improve the performance of many sparse reconstruction algorithms. However, these strategies are algorithm dependent and cannot be easily extended for an arbitrary sparse reconstruction algorithm. In this paper, we propose a general iterative framework and a novel algorithm which iteratively enhance the performance of any given arbitrary sparse reconstruction algorithm. We theoretically analyze the proposed method using restricted isometry property and derive sufficient conditions for convergence and performance improvement. We also evaluate the performance of the proposed method using numerical experiments with both synthetic and real-world data. (C) 2014 Elsevier B.V. All rights reserved.

Compiler/Runtime Framework for Dynamic Dataflow Parallelization of Tiled Programs

Task-parallel languages are increasingly popular. Many of them provide expressive mechanisms for intertask synchronization. For example, OpenMP 4.0 will integrate data-driven execution semantics derived from the StarSs research language. Compared to the more restrictive data-parallel and fork-join concurrency models, the advanced features being introduced into task-parallelmodels in turn enable improved scalability through load balancing, memory latency hiding, mitigation of the pressure on memory bandwidth, and, as a side effect, reduced power consumption. In this article, we develop a systematic approach to compile loop nests into concurrent, dynamically constructed graphs of dependent tasks. We propose a simple and effective heuristic that selects the most profitable parallelization idiom for every dependence type and communication pattern. This heuristic enables the extraction of interband parallelism (cross-barrier parallelism) in a number of numerical computations that range from linear algebra to structured grids and image processing. The proposed static analysis and code generation alleviates the burden of a full-blown dependence resolver to track the readiness of tasks at runtime. We evaluate our approach and algorithms in the PPCG compiler, targeting OpenStream, a representative dataflow task-parallel language with explicit intertask dependences and a lightweight runtime. Experimental results demonstrate the effectiveness of the approach.

Functionality preservation with enhanced mechanical integrity in the nanocomposites of the metal-organic framework, ZIF-8, with BN nanosheets

Metal-organic frameworks (MOFs) and boron nitride both possess novel properties, the former associated with microporosity and the latter with good mechanical properties. We have synthesized composites of the imidazolate based MOF, ZIF-8, and few-layer BN in order to see whether we can incorporate the properties of both these materials in the composites. The composites so prepared between BN nanosheets and ZIF-8 have compositions ZIF-1BN, ZIF-2BN, ZIF-3BN and similar to ZIF-4BN. The composites have been characterized by PXRD, TGA, XPS, electron microscopy, IR, Raman and solid state NMR spectroscopy. The composites possess good surface areas, the actual value decreasing only slightly with the increase in the BN content. The CO2 uptake remains nearly the same in the composites as in the parent ZIF-8. More importantly, the addition of BN markedly improves the mechanical properties of ZIF-8, a feature that is much desired in MOFs. Observation of microporous features along with improved mechanical properties in a MOF is indeed noteworthy. Such manipulation of properties can be profitably exploited in practical applications.

A Matroidal Framework for Network-Error Correcting Codes

Matroidal networks were introduced by Dougherty et al. and have been well studied in the recent past. It was shown that a network has a scalar linear network coding solution if and only if it is matroidal associated with a representable matroid. A particularly interesting feature of this development is the ability to construct (scalar and vector) linearly solvable networks using certain classes of matroids. Furthermore, it was shown through the connection between network coding and matroid theory that linear network coding is not always sufficient for general network coding scenarios. The current work attempts to establish a connection between matroid theory and network-error correcting and detecting codes. In a similar vein to the theory connecting matroids and network coding, we abstract the essential aspects of linear network-error detecting codes to arrive at the definition of a matroidal error detecting network (and similarly, a matroidal error correcting network abstracting from network-error correcting codes). An acyclic network (with arbitrary sink demands) is then shown to possess a scalar linear error detecting (correcting) network code if and only if it is a matroidal error detecting (correcting) network associated with a representable matroid. Therefore, constructing such network-error correcting and detecting codes implies the construction of certain representable matroids that satisfy some special conditions, and vice versa. We then present algorithms that enable the construction of matroidal error detecting and correcting networks with a specified capability of network-error correction. Using these construction algorithms, a large class of hitherto unknown scalar linearly solvable networks with multisource, multicast, and multiple-unicast network-error correcting codes is made available for theoretical use and practical implementation, with parameters, such as number of information symbols, number of sinks, number of coding nodes, error correcting capability, and so on, being arbitrary but for computing power (for the execution of the algorithms). The complexity of the construction of these networks is shown to be comparable with the complexity of existing algorithms that design multicast scalar linear network-error correcting codes. Finally, we also show that linear network coding is not sufficient for the general network-error correction (detection) problem with arbitrary demands. In particular, for the same number of network errors, we show a network for which there is a nonlinear network-error detecting code satisfying the demands at the sinks, whereas there are no linear network-error detecting codes that do the same.

An interdisciplinary framework to evaluate bioshield plantations: Insights from peninsular India

Bioshields or coastal vegetation structures are currently amongst the most important coastal habitat modification activities in south-east Asia, particularly after the December 2004 tsunami. Coastal plantations have been promoted at a large scale as protection against severe natural disasters despite considerable debate over their efficacy as protection measures. In this paper, we provide an interdisciplinary framework for evaluating and monitoring coastal plantations. We then use this framework in a case study in peninsular India. We conducted a socio-ecological questionnaire-based survey on government and non-government organizations directly involved in coastal plantation efforts in three 2004 Indian Ocean tsunami affected states in mainland India. We found that though coastal protection was stated to be the primary cause, socio-economic factors like providing rural employment were strong drivers of plantation activities. Local communities were engaged primarily as daily wage labour for plantation. rather than in the planning or monitoring phases. Application of ecological criteria has been undermined during the establishment and maintenance of plantations and there was a general lack of awareness about conservation laws relating to coastal forests. While ample flow of international aid has fuelled the plantation of exotics in the study area particularly after the Indian Ocean tsunami in 2004, the long term ecological consequences need further evaluation and rigorous monitoring in the future. (C) 2014 Elsevier Masson SAS. All rights reserved.

Analytical approach to quantile estimation in regional frequency analysis based on fuzzy framework

Regional frequency analysis is widely used for estimating quantiles of hydrological extreme events at sparsely gauged/ungauged target sites in river basins. It involves identification of a region (group of watersheds) resembling watershed of the target site, and use of information pooled from the region to estimate quantile for the target site. In the analysis, watershed of the target site is assumed to completely resemble watersheds in the identified region in terms of mechanism underlying generation of extreme event. In reality, it is rare to find watersheds that completely resemble each other. Fuzzy clustering approach can account for partial resemblance of watersheds and yield region(s) for the target site. Formation of regions and quantile estimation requires discerning information from fuzzy-membership matrix obtained based on the approach. Practitioners often defuzzify the matrix to form disjoint clusters (regions) and use them as the basis for quantile estimation. The defuzzification approach (DFA) results in loss of information discerned on partial resemblance of watersheds. The lost information cannot be utilized in quantile estimation, owing to which the estimates could have significant error. To avert the loss of information, a threshold strategy (TS) was considered in some prior studies. In this study, it is analytically shown that the strategy results in under-prediction of quantiles. To address this, a mathematical approach is proposed in this study and its effectiveness in estimating flood quantiles relative to DFA and TS is demonstrated through Monte-Carlo simulation experiments and case study on Mid-Atlantic water resources region, USA. (C) 2015 Elsevier B.V. All rights reserved.

A thermodynamic framework for the evolution of damage in concrete under fatigue

A closed-form expression for the dual of dissipation potential is derived within the framework of irreversible thermodynamics using the principles of dimensional analysis and self-similarity. Through this potential, a damage evolution law is proposed for concrete under fatigue loading using the concepts of damage mechanics in conjunction with fracture mechanics. The proposed law is used to compute damage in a volume element when a member is subjected to fatigue loading. The evolution of damage from microcracking to macrocracking of the entire member is captured through a series of volume elements failing one after the other. The number of loading cycles to failure of the member is obtained as the summation of number of cycles to failure for each individual volume element. A parametric study is conducted to determine the effect of the size of the volume element on the model's prediction of fatigue life. A global damage index is also defined, and the residual moment carrying capacity of damaged beams is evaluated. Through a deterministic sensitivity analysis, it is found that the load range and maximum aggregate size are the most influencing parameters on the fatigue life of a plain concrete beam.

A Disulfide Stabilized beta-Sandwich Defines the Structure of a New Cysteine Framework M-Superfamily Conotoxin

The structure of a new cysteine framework (-C-CC-C-C-C) ``M''-superfamily conotoxin, Mo3964, shows it to have a beta-sandwich structure that is stabilized by inter-sheet cross disulfide bonds. Mo3964 decreases outward K+ currents in rat dorsal root ganglion neurons and increases the reversal potential of the Na(V)1.2 channels. The structure of Mo3964 (PDB ID: 2MW7) is constructed from the disulfide connectivity pattern, i.e., 1-3, 2-5, and 4-6, that is hitherto undescribed for the ``M''-superfamily conotoxins. The tertiary structural fold has not been described for any of the known conus peptides. NOE (549), dihedral angle (84), and hydrogen bond (28) restraints, obtained by measurement of (h3)J(NC') scalar couplings, were used as input for structure calculation. The ensemble of structures showed a backbone root mean square deviation of 0.68 +/- 0.18 angstrom, with 87% and 13% of the backbone dihedral (phi, psi) angles lying in the most favored and additional allowed regions of the Ramachandran map. The conotoxin Mo3964 represents a new bioactive peptide fold that is stabilized by disulfide bonds and adds to the existing repertoire of scaffolds that can be used to design stable bioactive peptide molecules.

QoS Aware Trust Metric based Framework for Wireless Sensor Networks

Wireless Sensor Networks have gained popularity due to their real time applications and low-cost nature. These networks provide solutions to scenarios that are critical, complicated and sensitive like military fields, habitat monitoring, and disaster management. The nodes in wireless sensor networks are highly resource constrained. Routing protocols are designed to make efficient utilization of the available resources in communicating a message from source to destination. In addition to the resource management, the trustworthiness of neighboring nodes or forwarding nodes and the energy level of the nodes to keep the network alive for longer duration is to be considered. This paper proposes a QoS Aware Trust Metric based Framework for Wireless Sensor Networks. The proposed framework safeguards a wireless sensor network from intruders by considering the trustworthiness of the forwarder node at every stage of multi-hop routing. Increases network lifetime by considering the energy level of the node, prevents the adversary from tracing the route from source to destination by providing path variation. The framework is built on NS2 Simulator. Experimental results show that the framework provides energy balance through establishment of trustworthy paths from the source to the destination. (C) 2015 The Authors. Published by Elsevier B.V.

General framework for acoustic emission during plastic deformation

Despite the long history, so far there is no general theoretical framework for calculating the acoustic emission spectrum accompanying any plastic deformation. We set up a discrete wave equation with plastic strain rate as a source term and include the Rayleigh-dissipation function to represent dissipation accompanying acoustic emission. We devise a method of bridging the widely separated time scales of plastic deformation and elastic degrees of freedom. While this equation is applicable to any type of plastic deformation, it should be supplemented by evolution equations for the dislocation microstructure for calculating the plastic strain rate. The efficacy of the framework is illustrated by considering three distinct cases of plastic deformation. The first one is the acoustic emission during a typical continuous yield exhibiting a smooth stress-strain curve. We first construct an appropriate set of evolution equations for two types of dislocation densities and then show that the shape of the model stress-strain curve and accompanying acoustic emission spectrum match very well with experimental results. The second and the third are the more complex cases of the Portevin-Le Chatelier bands and the Luders band. These two cases are dealt with in the context of the Ananthakrishna model since the model predicts the three types of the Portevin-Le Chatelier bands and also Luders-like bands. Our results show that for the type-C bands where the serration amplitude is large, the acoustic emission spectrum consists of well-separated bursts of acoustic emission. At higher strain rates of hopping type-B bands, the burst-type acoustic emission spectrum tends to overlap, forming a nearly continuous background with some sharp acoustic emission bursts. The latter can be identified with the nucleation of new bands. The acoustic emission spectrum associated with the continuously propagating type-A band is continuous. These predictions are consistent with experimental results. More importantly, our study shows that the low-amplitude continuous acoustic emission spectrum seen in both the type-B and type-A band regimes is directly correlated to small-amplitude serrations induced by propagating bands. The acoustic emission spectrum of the Luders-like band matches with recent experiments as well. In all of these cases, acoustic emission signals are burstlike, reflecting the intermittent character of dislocation-mediated plastic flow.

A FRAMEWORK FOR THE ERROR ANALYSIS OF DISCONTINUOUS FINITE ELEMENT METHODS FOR ELLIPTIC OPTIMAL CONTROL PROBLEMS AND APPLICATIONS TO C-0 IP METHODS

In this article, an abstract framework for the error analysis of discontinuous Galerkin methods for control constrained optimal control problems is developed. The analysis establishes the best approximation result from a priori analysis point of view and delivers a reliable and efficient a posteriori error estimator. The results are applicable to a variety of problems just under the minimal regularity possessed by the well-posedness of the problem. Subsequently, the applications of C-0 interior penalty methods for a boundary control problem as well as a distributed control problem governed by the biharmonic equation subject to simply supported boundary conditions are discussed through the abstract analysis. Numerical experiments illustrate the theoretical findings.

Order-disorder phase transition and multiferroic behaviour in a metal organic framework compound (CH3)(2)NH2Co(HCOO)(3)

We have investigated the multiferroic and glassy behaviour of metal-organic framework (MOF) material (CH3)(2)NH2Co(CHOO)(3). The compound has perovskite-like architecture in which the metal-formate forms a framework. The organic cation (CH3)(2)NH2+ occupies the cavities in the formate framework in the framework via N-H center dot center dot center dot O hydrogen bonds. At room temperature, the organic cation is disordered and occupies three crystallographically equivalent positions. Upon cooling, the organic cation is ordered which leads to a structural phase transition at 155 K. The structural phase transition is associated with a para-ferroelectric phase transition and is revealed by dielectric and pyroelectric measurements. Further, a PE hysteresis loop below 155 K confirms the ferroelectric behaviour of the material. Analysis of dielectric data reveal large frequency dispersion in the values of dielectric constant and tan delta which signifies the presence of glassy dielectric behaviour. The material displays a antiferromagnetic ordering below 15 K which is attributed to the super-exchange interaction between Co2+ ions mediated via formate linkers. Interestingly, another magnetic transition is also found around 11 K. The peak of the transition shifts to lower temperature with increasing frequency, suggesting glassy magnetism in the sample. (C) 2016 AIP Publishing LLC.

Framework for morphometric classification of cells in imaging flow cytometry

Imaging flow cytometry is an emerging technology that combines the statistical power of flow cytometry with spatial and quantitative morphology of digital microscopy. It allows high-throughput imaging of cells with good spatial resolution, while they are in flow. This paper proposes a general framework for the processing/classification of cells imaged using imaging flow cytometer. Each cell is localized by finding an accurate cell contour. Then, features reflecting cell size, circularity and complexity are extracted for the classification using SVM. Unlike the conventional iterative, semi-automatic segmentation algorithms such as active contour, we propose a noniterative, fully automatic graph-based cell localization. In order to evaluate the performance of the proposed framework, we have successfully classified unstained label-free leukaemia cell-lines MOLT, K562 and HL60 from video streams captured using custom fabricated cost-effective microfluidics-based imaging flow cytometer. The proposed system is a significant development in the direction of building a cost-effective cell analysis platform that would facilitate affordable mass screening camps looking cellular morphology for disease diagnosis. Lay description In this article, we propose a novel framework for processing the raw data generated using microfluidics based imaging flow cytometers. Microfluidics microscopy or microfluidics based imaging flow cytometry (mIFC) is a recent microscopy paradigm, that combines the statistical power of flow cytometry with spatial and quantitative morphology of digital microscopy, which allows us imaging cells while they are in flow. In comparison to the conventional slide-based imaging systems, mIFC is a nascent technology enabling high throughput imaging of cells and is yet to take the form of a clinical diagnostic tool. The proposed framework process the raw data generated by the mIFC systems. The framework incorporates several steps: beginning from pre-processing of the raw video frames to enhance the contents of the cell, localising the cell by a novel, fully automatic, non-iterative graph based algorithm, extraction of different quantitative morphological parameters and subsequent classification of cells. In order to evaluate the performance of the proposed framework, we have successfully classified unstained label-free leukaemia cell-lines MOLT, K562 and HL60 from video streams captured using cost-effective microfluidics based imaging flow cytometer. The cell lines of HL60, K562 and MOLT were obtained from ATCC (American Type Culture Collection) and are separately cultured in the lab. Thus, each culture contains cells from its own category alone and thereby provides the ground truth. Each cell is localised by finding a closed cell contour by defining a directed, weighted graph from the Canny edge images of the cell such that the closed contour lies along the shortest weighted path surrounding the centroid of the cell from a starting point on a good curve segment to an immediate endpoint. Once the cell is localised, morphological features reflecting size, shape and complexity of the cells are extracted and used to develop a support vector machine based classification system. We could classify the cell-lines with good accuracy and the results were quite consistent across different cross validation experiments. We hope that imaging flow cytometers equipped with the proposed framework for image processing would enable cost-effective, automated and reliable disease screening in over-loaded facilities, which cannot afford to hire skilled personnel in large numbers. Such platforms would potentially facilitate screening camps in low income group countries; thereby transforming the current health care paradigms by enabling rapid, automated diagnosis for diseases like cancer.