**Abstract**

The reactor core system consists of many materials, involving multi-physics processes, and can be analyzed and simulated at multi-scales. With the evolution of cluster computer, traditional programs and models could be translated into new program structure and modified in detail, so that more complex problems can be solved. Based on existing theory, programs of sub-channels analysis, two-dimensional (2D) method of characteristic (MOC), fuel temperature approximation, and threedimensional (3D) discrete ordinate method (SN) are developed and analyzed. The different approach is that the reusable software structure of core calculation is established, with more well-defined storage of nuclear data, control layers, and more effective parallel algorithm for computation. The features of parallel algorithm for these programs are listed succinctly in the discussion. Additionally, the corresponding testing on parallel algorithm and computing results are given.

**Keywords:** reactor core, modeling and simulation, nuclear data, software structure, parallelism


**1.1 Data Mining**

Data mining may be thought of as a natural progression of information technology. It can be simply defined as a procedure for searching, gathering, filtering, and analyzing data. It's the method of extracting useful knowledge from vast volumes of data kept in databases, data centers, or other data repositories. Database technology, statistics, artificial intelligence, machine learning, high-performance computing, pattern recognition, neural networks, data visualization, information retrieval, image and signal processing, and spatial data analysis are all techniques used in data mining. Data mining allows for the extraction of interesting knowledge, regularities, or highlevel information from databases, which can then be viewed or browsed from various perspectives.

It deals with the secondary study of massive databases in order to uncover previously unknown relationships that are of interest or benefit to database owners. It can be thought of as computer-assisted exploratory data analysis of massive, complex data sets from a statistical standpoint. Data mining is having a big effect in business, industry, and science right now. It also opens up a lot of possibilities for new methodological advances in science. New issues occur, partly as a result of the sheer scale of the data sets in question, and partly as a result of pattern matching issues.

Decision making, process control, information management, and query processing are only a few of the applications for the newly discovered experience. As a result, data mining is recognized as one of the most exciting modern database technologies in the information industry, as well as one of the most important frontiers in database systems [1, 2]. This chapter will go into the basics of data mining as well as the data extraction techniques. Mastering this technology and its techniques will have significant advantages as well as a competitive edge.


*Edited by Joi L. Moore and Angela D. Benson*

This book, written by authors representing 12 countries and five continents, is a collection of international perspectives on distance learning and distance learning implementations in higher education. The perspectives are presented in the form of practical case studies of distance learning implementations, research studies on teaching and learning in distance learning environments, and conceptual and theoretical frameworks for designing and developing distance learning tools, courses and programs. The book will appeal to distance learning practitioners, researchers, and higher education administrators. To address the different needs and interests of audience members, the book is organized into five sections: Distance Education Management, Distance Education and Teacher Development, Distance Learning Pedagogy, Distance Learning Students, and Distance Learning Educational Tools.

ISBN 978-953-51-0330-1

International Perspectives of Distance Learning in Higher Education

Photo by FactoryTh / iStock


**8. Sengers Syndrome**

The clinical manifestation of Sengers syndrome is hypertrophic cardiomyopathy and congenital cataracts. Other symptoms including skeletal myopathy, exercise intolerance, lactic acidosis and 3-methylglutaconic aciduria, showing strong similarities to Barth syndrome [131] (Figure 5). Sengers syndrome is caused by mutations in the gene encoding for mitochondrial acylglycerol kinase (AGK) [132]. AGK is a mitochondrial lipid kinase strongly expressed in heart, but also in the skeletal muscle, kidney and brain. This protein can phosphorylate monoacylglycerol to lysophosphatidic acid (LPA) and diacylglycerol to phosphatidic acid (PA), a precursor of CL biosynthesis [132]. AGK has an additional independent function in mitochondrial protein import as a constituent of the mitochondrial carrier translocase TIM22 complex [81,133]. This inner membrane-embedded protein translocase imports proteins of the carrier family from the cytosol. Carrier proteins are a large family of proteins which mediate the transport of metabolites across the inner membrane. A defect in the import and assembly of carrier proteins has been found in AGK-deficient mitochondria [81,133]. In particular, decreased levels of mitochondrial ADP/ATP carrier in heart and muscle tissues was the initial finding in patients of Sengers syndrome [134]. The function in protein transport is independent of AGK kinase activity. It can be assumed that loss of both functions contributes to the pathogenesis in Sengers syndrome.