Apache Spark is an open-source cluster computing framework. It has emerged as the next generation big data processing engine, overtaking Hadoop MapReduce which helped ignite the big data revolution. Spark maintains MapReduce’s linear scalability and fault tolerance, but extends it in a few important ways: it is much faster (100 times faster for certain applications), much easier to program in d...

Upon activation, mammalian eggs release billions of zinc ions in an exocytotic event termed the "zinc spark." The zinc spark is dependent on and occurs coordinately with intracellular calcium transients, which are tightly associated with embryonic development. Thus, we hypothesized that the zinc spark represents an early extracellular physicochemical marker of the developmental potential of the...

Simulations of forced ignition of non-premixed laminar counterflow flames are used to study the effect of strain rate on ignition success. A one dimensional calculation is performed, using detailed methane chemical kinetics and treating the spark as an instantaneous heat release in an inert mixing layer. Ignition success depends on the mixture composition at the spark location, resulting in lea...

AIMS The cardiac ryanodine receptor (RyR) Ca(2+) release channel homotetramer harbours approximately 21 potentially redox-sensitive cysteine residues on each subunit and may act as a sensor for reactive oxygen species (ROS), linking ROS homeostasis to the regulation of Ca(2+) signalling. In cardiac myocytes, arrayed RyRs or Ca(2+) release units are packed in the close proximity of mitochondria,...

Guidelines for the development of software in safety-critical systems usually restrict programming languages, removing features that are unsafe and/or hard to thoroughly test and certify. There are also recommendations and demands in newer guidelines for the use of formal methods, as a way to achieve high assurance software. SPARK is a strict subset of Ada that was designed to have unambiguous ...

The normal specifications of motor gasolines as well as their combustion characteristics in internal combustion engines are reviewed in this paper. The effective factors influencing the fuel performance, such as the molecular structure of the fuel constituents, the operating conditions and the atmospheric pressure and temperature are also discussed. A relationship between the optimum octane num...

Many machine learning models, such as logistic regression (LR) and support vector machine (SVM), can be formulated as composite optimization problems. Recently, many distributed stochastic optimization (DSO) methods have been proposed to solve the large-scale composite optimization problems, which have shown better performance than traditional batch methods. However, most of these DSO methods m...

Big Data Optimization is the term used to refer to optimization problems which have to manage very large amounts of data. In this paper, we focus on the parallelization of metaheuristics with the Apache Spark cluster computing system for solving multi-objective Big Data Optimization problems. Our purpose is to study the influence of accessing data stored in the Hadoop File System (HDFS) in each...

Batched stream processing systems achieve higher throughput than traditional stream processing systems while providing low latency guarantee. Recently, batched stream processing systems tend to be deployed in cloud due to their requirement of elasticity and cost efficiency. However, the performance of batched stream processing systems are hardly guaranteed in cloud because static resource provi...

Frequent subgraph mining (FSM) plays an important role in graph mining, attracting a great deal of attention in many areas, such as bioinformatics, web data mining and social networks. In this paper, we propose SSIGRAM (Spark based Single Graph Mining), a Spark based parallel frequent subgraph mining algorithm in a single large graph. Aiming to approach the two computational challenges of FSM, ...