In cardiac muscle, Ca2+ is released from the sarcoplasmic reticulum (SR) in units called Ca2+ sparks. Ca2+ spark characteristics have been studied almost entirely at room temperature. This study compares characteristics of spontaneous sparks detected with fluo 3 in resting mouse ventricular myocytes at 22 and 37 degrees C. The incidence and frequency of Ca2+ sparks decreased dramatically at 37 ...

Through theoretical analysis of the statistics of stochastic calcium (Ca) release (i.e., the amplitude, duration and inter-event interval of simulated Ca puffs and sparks), we show that a Langevin description of the collective gating of Ca channels may be a good approximation to the corresponding Markov chain model when the number of Ca channels per Ca release unit (CaRU) is in the physiologica...

We consider the numerical solution of systems of index 2 implicit differential-algebraic equations (DAEs) by a class of super partitioned additive Runge-Kutta (SPARK) methods. The families of Lobatto IIIA-B-C-C-D methods are included. We show super-convergence of optimal order 2s−2 for the s-stage Lobatto families provided the constraints are treated in a particular way which strongly relies on...

Parallel algorithms, such as the ant colony algorithm, take a long time when solving large-scale problems. In this paper, the MAX-MIN Ant System algorithm (MMAS) is parallelized to solve Traveling Salesman Problem (TSP) based on a Spark cloud computing platform. We combine MMAS with Spark MapReduce to execute the path building and the pheromone operation in a distributed computer cluster. To im...

While sequential pattern mining (SPM) is an import application in uncertain databases, it is challenging in efficiency and scalability. In this paper, we develop a dynamic programming (DP) approach to mine probabilistic frequent sequential patterns in distributed computing platform Spark. Directly applying the DP method to Spark is impractical because its memory-consuming characteristic may cau...

Primal and dual block coordinate descent methods are iterative methods for solving regularized and unregularized optimization problems. Distributed-memory parallel implementations of these methods have become popular in analyzing large machine learning datasets. However, existing implementations communicate at every iteration which, on modern data center and supercomputing architectures, often ...

Machine learning practitioners are increasingly interested in applying their algorithms to Big Data. Unfortunately, current high-level languages for data analytics in the cloud (e.g., [2, 15, 16, 5]) do not fully cover this domain. One key missing ingredient is means to express iteration over the data (e.g., [19]). Zaharia et al., were the first to answer this call from a systems perspective wi...

Transcriptional assays, such as yeast two-hybrid and TANGO, that convert transient protein-protein interactions (PPIs) into stable expression of transgenes are powerful tools for PPI discovery, screens, and analysis of cell populations. However, such assays often have high background and lose information about PPI dynamics. We have developed SPARK (Specific Protein Association tool giving trans...

Powder mixed electrical discharge machining (PM-EDM) is a technological advancement in (EDM) processes where fine powder added to dielectric improve the rate and surface quality. In this paper, of Nimonic-90 was carried out using fabricated PM-EDM, setup by adding silicon kerosene oil. The influence four input process parameters viz. concentration (PC), current (IP), spark on duration (SON), of...