A semi-analytical solution for multilayer diffusion in a composite medium consisting of a large number of layers

Diffusion in a composite slab consisting of a large number of layers provides an ideal prototype problem for developing and analysing two-scale modelling approaches for heterogeneous media. Numerous analytical techniques have been proposed for solving the transient diffusion equation in a one-dimensional composite slab consisting of an arbitrary number of layers. Most of these approaches, however, require the solution of a complex transcendental equation arising from a matrix determinant for the eigenvalues that is difficult to solve numerically for a large number of layers. To overcome this issue, in this paper, we present a semi-analytical method based on the Laplace transform and an orthogonal eigenfunction expansion. The proposed approach uses eigenvalues local to each layer that can be obtained either explicitly, or by solving simple transcendental equations. The semi-analytical solution is applicable to both perfect and imperfect contact at the interfaces between adjacent layers and either Dirichlet, Neumann or Robin boundary conditions at the ends of the slab. The solution approach is verified for several test cases and is shown to work well for a large number of layers. The work is concluded with an application to macroscopic modelling where the solution of a fine-scale multilayered medium consisting of two hundred layers is compared against an “up-scaled” variant of the same problem involving only ten layers.

MECHANISMS AND EFFECTS OF MITOCHONDRIAL DNA INSTABILITY AND COPY NUMBER MANIPULATION

Defects in mitochondrial DNA (mtDNA) maintenance cause a range of human diseases, including autosomal dominant progressive external ophthalmoplegia (adPEO). This study aimed to clarify the molecular background of adPEO. We discovered that deoxynucleoside triphosphate (dNTP) metabolism plays a crucial in mtDNA maintenance and were thus prompted to search for therapeutic strategies based on the modulation of cellular dNTP pools or mtDNA copy number. Human mtDNA is a 16.6 kb circular molecule present in hundreds to thousands of copies per cell. mtDNA is compacted into nucleoprotein clusters called nucleoids. mtDNA maintenance diseases result from defects in nuclear encoded proteins that maintain the mtDNA. These syndromes typically afflict highly differentiated, post-mitotic tissues such as muscle and nerve, but virtually any organ can be affected. adPEO is a disease where mtDNA molecules with large-scale deletions accumulate in patients tissues, particularly in skeletal muscle. Mutations in five nuclear genes, encoding the proteins ANT1, Twinkle, POLG, POLG2 and OPA1, have previously been shown to cause adPEO. Here, we studied a large North American pedigree with adPEO, and identified a novel heterozygous mutation in the gene RRM2B, which encodes the p53R2 subunit of the enzyme ribonucleotide reductase (RNR). RNR is the rate-limiting enzyme in dNTP biosynthesis, and is required both for nuclear and mitochondrial DNA replication. The mutation results in the expression of a truncated form of p53R2, which is likely to compete with the wild-type allele. A change in enzyme function leads to defective mtDNA replication due to altered dNTP pools. Therefore, RRM2B is a novel adPEO disease gene. The importance of adequate dNTP pools and RNR function for mtDNA maintenance has been established in many organisms. In yeast, induction of RNR has previously been shown to increase mtDNA copy number, and to rescue the phenotype caused by mutations in the yeast mtDNA polymerase. To further study the role of RNR in mammalian mtDNA maintenance, we used mice that broadly overexpress the RNR subunits Rrm1, Rrm2 or p53R2. Active RNR is a heterotetramer consisting of two large subunits (Rrm1) and two small subunits (either Rrm2 or p53R2). We also created bitransgenic mice that overexpress Rrm1 together with either Rrm2 or p53R2. In contrast to the previous findings in yeast, bitransgenic RNR overexpression led to mtDNA depletion in mouse skeletal muscle, without mtDNA deletions or point mutations. The mtDNA depletion was associated with imbalanced dNTP pools. Furthermore, the mRNA expression levels of Rrm1 and p53R2 were found to correlate with mtDNA copy number in two independent mouse models, suggesting nuclear-mitochondrial cross talk with regard to mtDNA copy number. We conclude that tight regulation of RNR is needed to prevent harmful alterations in the dNTP pool balance, which can lead to disordered mtDNA maintenance. Increasing the copy number of wild-type mtDNA has been suggested as a strategy for treating PEO and other mitochondrial diseases. Only two proteins are known to cause a robust increase in mtDNA copy number when overexpressed in mice; the mitochondrial transcription factor A (TFAM), and the mitochondrial replicative helicase Twinkle. We studied the mechanisms by which Twinkle and TFAM elevate mtDNA levels, and showed that Twinkle specifically implements mtDNA synthesis. Furthermore, both Twinkle and TFAM were found to increase mtDNA content per nucleoid. Increased mtDNA content in mouse tissues correlated with an age-related accumulation of mtDNA deletions, depletion of mitochondrial transcripts, and progressive respiratory dysfunction. Simultaneous overexpression of Twinkle and TFAM led to a further increase in the mtDNA content of nucleoids, and aggravated the respiratory deficiency. These results suggested that high mtDNA levels have detrimental long-term effects in mice. These data have to be considered when developing and evaluating treatment strategies for elevating mtDNA copy number.

A cost effective pipelined divider for double precision floating point number

he growth of high-performance application in computer graphics, signal processing and scientific computing is a key driver for high performance, fixed latency; pipelined floating point dividers. Solutions available in the literature use large lookup table for double precision floating point operations.In this paper, we propose a cost effective, fixed latency pipelined divider using modified Taylor-series expansion for double precision floating point operations. We reduce chip area by using a smaller lookup table. We show that the latency of the proposed divider is 49.4 times the latency of a full-adder. The proposed divider reduces chip area by about 81% than the pipelined divider in [9] which is based on modified Taylor-series.

An Estimator Algorithm For Learning Automata With Changing Number Of Actions

In many problems of decision making under uncertainty the system has to acquire knowledge of its environment and learn the optimal decision through its experience. Such problems may also involve the system having to arrive at the globally optimal decision, when at each instant only a subset of the entire set of possible alternatives is available. These problems can be successfully modelled and analysed by learning automata. In this paper an estimator learning algorithm, which maintains estimates of the reward characteristics of the random environment, is presented for an automaton with changing number of actions. A learning automaton using the new scheme is shown to be e-optimal. The simulation results demonstrate the fast convergence properties of the new algorithm. The results of this study can be extended to the design of other types of estimator algorithms with good convergence properties.

Design of crosspoint-irredundant PLAs using minimal number of control inputs

The problem of determining a minimal number of control inputs for converting a programmable logic array (PLA) with undetectable faults to crosspoint-irredundant PLA for testing has been formulated as a nonstandard set covering problem. By representing subsets of sets as cubes, this problem has been reformulated as familiar problems. It is noted that this result has significance because a crosspoint-irredundant PLA can be converted to a completely testable PLA in a straightforward fashion, thus achieving very good fault coverage and easy testability.

Evolution of polyandry by reduction in progeny number variance in structured populations

When there is a variation in the quality of males in a population, multiple mating can lead to an increase in the genetic fitness of a female by reducing the variance of the progeny number. The extent of selective advantage obtainable by this process is investigated for a population subdivided into structured demes. It is seen that for a wide range of model parameters (deme size, distribution of male quality, local resource level), multiple mating leads to a considerable increase in the fitness. Frequency-dependent selection or a stable coexistence between polyandry and monandry can also result when the possible costs involved in multiple mating are taken into account.

On Finding the Natural Number of Topics with Latent Dirichlet Allocation: Some Observations

It is important to identify the ``correct'' number of topics in mechanisms like Latent Dirichlet Allocation(LDA) as they determine the quality of features that are presented as features for classifiers like SVM. In this work we propose a measure to identify the correct number of topics and offer empirical evidence in its favor in terms of classification accuracy and the number of topics that are naturally present in the corpus. We show the merit of the measure by applying it on real-world as well as synthetic data sets(both text and images). In proposing this measure, we view LDA as a matrix factorization mechanism, wherein a given corpus C is split into two matrix factors M-1 and M-2 as given by C-d*w = M1(d*t) x Q(t*w).Where d is the number of documents present in the corpus anti w is the size of the vocabulary. The quality of the split depends on ``t'', the right number of topics chosen. The measure is computed in terms of symmetric KL-Divergence of salient distributions that are derived from these matrix factors. We observe that the divergence values are higher for non-optimal number of topics - this is shown by a `dip' at the right value for `t'.

Design of speaker identification schemes for large number of speakers (A)

Design of speaker identification schemes for a small number of speakers (around 10) with a high degree of accuracy in controlled environment is a practical proposition today. When the number of speakers is large (say 50–100), many of these schemes cannot be directly extended, as both recognition error and computation time increase monotonically with population size. The feature selection problem is also complex for such schemes. Though there were earlier attempts to rank order features based on statistical distance measures, it has been observed only recently that the best two independent measurements are not the same as the combination in two's for pattern classification. We propose here a systematic approach to the problem using the decision tree or hierarchical classifier with the following objectives: (1) Design of optimal policy at each node of the tree given the tree structure i.e., the tree skeleton and the features to be used at each node. (2) Determination of the optimal feature measurement and decision policy given only the tree skeleton. Applicability of optimization procedures such as dynamic programming in the design of such trees is studied. The experimental results deal with the design of a 50 speaker identification scheme based on this approach.

Integration of miRNA and mRNA expression with DNA copy number of Ewing sarcoma cell lines

Ewing sarcoma is an aggressive and poorly differentiated malignancy of bone and soft tissue. It primarily affects children, adolescents, and young adults, with a slight male predominance. It is characterized by a translocation between chromosomes 11 and 22 resulting in the EWSR1-FLI1fusion transcription factor. The aim of this study is to identify putative Ewing sarcoma target genes through an integrative analysis of three microarray data sets. Array comparative genomic hybridization is used to measure changes in DNA copy number, and analyzed to detect common chromosomal aberrations. mRNA and miRNA microarrays are used to measure expression of protein-coding and miRNA genes, and these results integrated with the copy number data. Chromosomal aberrations typically contain also bystanders in addition to the driving tumor suppressor and oncogenes, and integration with expression helps to identify the true targets. Correlation between expression of miRNAs and their predicted target mRNAs is also evaluated to assess the results of post-transcriptional miRNA regulation on mRNA levels. The highest frequencies of copy number gains were identified in chromosome 8, 1q, and X. Losses were most frequent in 9p21.3, which also showed an enrichment of copy number breakpoints relative to the rest of the genome. Copy number losses in 9p21.3 were found have a statistically significant effect on the expression of MTAP, but not on CDKN2A, which is a known tumor-suppressor in the same locus. MTAP was also down-regulated in the Ewing sarcoma cell lines compared to mesenchymal stem cells. Genes exhibiting elevated expression in association with copy number gains and up-regulation compared to the reference samples included DCAF7, ENO2, MTCP1, andSTK40. Differentially expressed miRNAs were detected by comparing Ewing sarcoma cell lines against mesenchymal stem cells. 21 up-regulated and 32 down-regulated miRNAs were identified, includingmiR-145, which has been previously linked to Ewing sarcoma. The EWSR1-FLI1 fusion gene represses miR-145, which in turn targets FLI1 forming a mutually repressive feedback loop. In addition higher expression linked to copy number gains and compared to mesenchymal stem cells, STK40 was also found to be a target of four different miRNAs that were all down-regulated in Ewing sarcoma cell lines compared to the reference samples. SLCO5A1 was identified as the only up-regulated gene within a frequently gained region in chromosome 8. This region was gained in over 90 % of the cell lines, and also with a higher frequency than the neighboring regions. In addition, SLCO5A1 was found to be a target of three miRNAs that were down-regulated compared to the mesenchymal stem cells.