Look Left, Look Right, Look Left Again: An Application of Fractal Symbolic Analysis to Linear Algebra Code Restructuring

Fractal symbolic analysis is a symbolic analysis technique for verifying the legality of program transformations. It is strictly more powerful than dependence analysis; for example, it can be used to verify the legality of blocking LU factorization with pivoting, a task for which dependence analysis is inadequate. In this paper, we show how fractal symbolic analysis can be used to convert between left- and right-looking versions of three kernels of central importance in computational science: triangular solve, Cholesky factorization, and LU factorization with pivoting.     

Numerical Solution of Fractional Advection-Dispersion Equation

Numerical schemes and stability criteria are developed for solution of the one-dimensional fractional advection-dispersion equation (FRADE) derived by revising Fick’s first law. Employing 74 sets of dye test data measured on natural streams, it is found that the fractional order F of the partial differential operator acting on the dispersion term varies around the most frequently occurring value of F = 1.65 in the range of 1.4 to 2.0. Two series expansions are proposed for approximation of the limit definitions of fractional derivatives. On this ground, two three-term finite-difference schemes?“1.3 Backward Scheme” having the first-order accuracy and “F.3 Central Scheme” possessing the F-th order accuracy?are presented for fractional order derivatives. The F.3 scheme is found to perform better than does the 1.3 scheme in terms of error and stability analyses and is thus recommended for numerical solution of FRADE. The fractional dispersion model characterized by the FRADE and the F.3 scheme can accurately simulate the long-tailed dispersion processes in natural rivers.     

Nanoindentation measurement of core–skin interphase viscoelastic properties in a sandwich glass composite

Mechanics of Time-Dependent Materials - Debonding at the core–skin interphase region is one of the primary failure modes in core sandwich composites under shear loads. As a result, the...     

Design and development of bioinspired calcium phosphate nanoparticles of MTX: pharmacodynamic and pharmacokinetic evaluation

The aim of this investigation is the management of rheumatoid arthritis (RA) by developing methotrexate-loaded calcium phosphate nanoparticles (MTX-CAP-NP) and to evaluate pharmacokinetic and pharmacodynamic behavior in adjuvant induced arthritis model. The nanoparticles were synthesized by wet precipitation method and optimized by Box-Behnken experimental design. MTX-CAP-NPs were characterized by TEM, FTIR, DSC and XRD studies. The particle size, zeta potential and entrapment efficiency of the optimized nanoparticles were found to be 204.90?±?64?nm, ?11.58?±?4.80?mV, and 88.33?±?3.74%, respectively. TEM, FTIR, DSC and XRD studies revealed that the developed nanoparticles were nearly spherical in shape and the crystalline structure of CAP-NP was not changed after MTX loading. The pharmacokinetic studies revealed that MTX-CAP-NP enhanced bioavailability of MTX by 2.6-fold when compared to marketed formulation (FOLITRAX-10). Under pharmacodynamic evaluation, arthritic assessment, radiography and histopathology studies revealed that CAP has ability to regenerate cartilage and bone therefore, together with MTX, MTX-CAP-NPs have shown significant reduction in disease progression. The overall work demonstrated that the developed nanodelivery system was well tolerated and more effective than the marketed formulation.     

On a stochastic sensor selection algorithm with applications in sensor scheduling and sensor coverage

In this note we consider the following problem. Suppose a set of sensors is jointly trying to estimate a process. One sensor takes a measurement at every time step and the measurements are then exchanged among all the sensors. What is the sensor schedule that results in the minimum error covariance? We describe a stochastic sensor selection strategy that is easy to implement and is computationally tractable. The problem described above comes up in many domains out of which we discuss two. In the sensor selection problem, there are multiple sensors that cannot operate simultaneously (e.g., sonars in the same frequency band). Thus measurements need to be scheduled. In the sensor coverage problem, a geographical area needs to be covered by mobile sensors each with limited range. Thus from every position, the sensors obtain a different view-point of the area and the sensors need to optimize their trajectories. The algorithm is applied to these problems and illustrated through simple examples.     

Achieving Optimal Inter-Node Communication in Graph Partitioning Using Random Selection and Breadth-First Search

Processing large graph datasets represents an increasingly important area in computing research and applications. The size of many graph datasets has increased well beyond the processing capacity of a single computing node, thereby necessitating distributed approaches. As these datasets are processed over a distributed system of nodes, this leads to an inter-node communication cost problem that negatively affects system performance. Previously proposed algorithms implemented breadth-first search (BFS) for graph searching and focused on the execution, parallel performance and not the communication. In this paper a new methodology is proposed that combines BFS with random selection in order to partition large graph datasets and effectively minimize inter-node communication. The new method is discussed and applied to the single-source shortest path and PageRank algorithms using three graphs that are representative of real-world scenarios. Experimental results show that graph inter-node communication for canonical graphs representative of real-world data is improved up to 42 % in case of Powerlaw graph, up to 27 % in case of Random near K-regular graph (with low degree), and up to 7 % in case of Random near K-regular graph (with high degree).     

Trypsin-like Inhibitor Domain (TIL)-Harboring Protein Is Essential for Aedes aegypti Reproduction

Cysteine-rich trypsin inhibitor-like domain (TIL)-harboring proteins are broadly distributed in nature but remain understudied in vector mosquitoes. Here we have explored the biology of a TIL domain-containing protein of the arbovirus vector Aedes aegypti, cysteine-rich venom protein 379 (CRVP379). CRVP379 was previously shown to be essential for dengue virus infection in Ae. aegypti mosquitoes. Gene expression analysis showed CRVP379 to be highly expressed in pupal stages, male testes, and female ovaries. CRVP379 expression is also increased in the ovaries at 48 h post-blood feeding. We used CRISPR-Cas9 genome editing to generate two mutant lines of CRVP379 with mutations inside or outside the TIL domain. Female mosquitoes from both mutant lines showed severe defects in their reproductive capability; mutant females also showed differences in their follicular cell morphology. However, the CRVP379 line with a mutation outside the TIL domain did not affect male reproductive performance, suggesting that some CRVP379 residues may have sexually dimorphic functions. In contrast to previous reports, we did not observe a noticeable difference in dengue virus infection between the wild-type and any of the mutant lines. The importance of CRVP379 in Ae. aegypti reproductive biology makes it an interesting candidate for the development of Ae. aegypti population control methods.     

Power Spectral Density Analysis of Pressure Fluctuation in Pneumatic Conveying of Powders

In order to reveal the unsteady features of gas–solid flow, the pressure fluctuations were measured at different locations along the length of the pipeline while conveying powders through the pipeline. Power spectral density (PSD) functions were obtained for the analysis of the pressure fluctuation. Two types of powders (fly ash and alumina) were used in this analysis. The PSD analysis was conducted by taking into account different aspects such as flow conditions (dilute or dense), location of transmitter (top and bottom transmitters), location of transmitter along the length of the pipeline (three different locations), material property (fly ash or alumina), etc. Analysis of signals from top and bottom transmitters shows that it is not possible to identify the flow mode at upper and lower portions of pipeline. The magnitude of power is found to be higher for alumina as compared to fly ash. PSD parametric analysis reveals that frequency bandwidth and average power decreases exponentially with increase in solid loading ratio.