Experiences running NASTRAN on the Microvax 2 computer

The MicroVAX operates NASTRAN so well that the only detectable difference in its operation compared to an 11/780 VAX is in the execution time. On the modest installation described here, the engineer has all of the tools he needs to do an excellent job of analysis. System configuration decisions, system sizing, preparation of the system disk, definition of user quotas, installation, monitoring of system errors, and operation policies are discussed

A multidisciplinary survey of modeling techniques for biochemical networks

All processes of life are dominated by networks of interacting biochemical components. The purpose of modeling these networks is manifold. From a theoretical point of view it allows the exploration of network structures and dynamics, to find emergent properties or to explain the organization and evolution of networks. From a practical point of view, in silico experiments can be performed that would be very expensive or impossible to achieve in the laboratory, such as hypothesis-testing with regard to knockout experiments or overexpression, or checking the validity of a proposed molecular mechanism. The literature on modeling biochemical networks is growing rapidly and the motivations behind different modeling techniques are sometimes quite distant from each other. To clarify the current context, we present a systematic overview of the different philosophies to model biochemical networks. We put particular emphasis on three main domains which have been playing a major role in the past, namely: mathematics with ordinary and partial differential equations, statistics with stochastic simulation algorithms, Bayesian networks and Markov chains, and the field of computer science with process calculi, term rewriting systems and state based systems. For each school, we evaluate advantages and disadvantages such as the granularity of representation, scalability, accessibility or availability of analysis tools. Following this, we describe how one can combine some of those techniques and thus take advantages of several techniques through the use of bridging tools. Finally, we propose a next step for modeling biochemical networks by using artificial chemistries and evolutionary computation. This work was funded by ESIGNET (Evolving Cell Signaling Networks in Silico), an European Integrated Project in the EU FP6 NEST Initiative (contract no. 12789)

Threshold Analysis of Non-Binary Spatially-Coupled LDPC Codes with Windowed Decoding

In this paper we study the iterative decoding threshold performance of non-binary spatially-coupled low-density parity-check (NB-SC-LDPC) code ensembles for both the binary erasure channel (BEC) and the binary-input additive white Gaussian noise channel (BIAWGNC), with particular emphasis on windowed decoding (WD). We consider both (2,4)-regular and (3,6)-regular NB-SC-LDPC code ensembles constructed using protographs and compute their thresholds using protograph versions of NB density evolution and NB extrinsic information transfer analysis. For these code ensembles, we show that WD of NB-SC-LDPC codes, which provides a significant decrease in latency and complexity compared to decoding across the entire parity-check matrix, results in a negligible decrease in the near-capacity performance for a sufficiently large window size W on both the BEC and the BIAWGNC. Also, we show that NB-SC-LDPC code ensembles exhibit gains in the WD threshold compared to the corresponding block code ensembles decoded across the entire parity-check matrix, and that the gains increase as the finite field size q increases. Moreover, from the viewpoint of decoding complexity, we see that (3,6)-regular NB-SC-LDPC codes are particularly attractive due to the fact that they achieve near-capacity thresholds even for small q and W.Comment: 6 pages, 8 figures; submitted to 2014 IEEE International Symposium on Information Theor

The Hydro-Mechanical Properties of Fracture Intersections: Pressure-Dependant Permeability and Effective Stress Law

Fluid flow through the brittle crust is primarily controlled by the capability of fracture networks to provide pathways for fluid transport. The dominant permeability orientation within fractured rock masses has been consistently correlated with the development of fracture intersections; an observation also made at the meso-regional scale. Despite the importance attributed to fracture intersections in promoting fluid flow, the magnitude of their enhancement of fractured rock permeability has not yet been quantified. Here, we characterize the hydro-mechanical properties of intersections in samples of Seljadalur Basalt by generating two orthogonal, tensile fractures produced by two separate loadings using a Brazilian test apparatus, and measuring their permeability as a function of hydrostatic pressure. We observe that intersecting fractures are significantly more permeable and less compliant than two independent macro-fractures. We formulate a model for fracture intersection permeability as a function of pressure by adding the contributions of two independent fractures plus a tube-like cavity with an effective elastic compressibility determined by its geometry. Permeability measurements during cyclic loading allowed determination of the effective stress coefficient (α in pe = pc − αpp) for fracture and intersection permeability. We observe a trend of lower αintersection values with respect to αfracture, which suggests that the channels controlling fluid flow have a higher aspect ratio (are more tubular) for the intersections relative to independent fractures. Our results suggest that fracture intersections play a critical role in maintaining permeability at depth, which has significant implications for the quantification and upscaling of fracture permeability toward reservoir-scale simulations

Virulence Attributes and Hyphal Growth of C. neoformans Are Quantitative Traits and the MATα Allele Enhances Filamentation

Cryptococcus neoformans is a fungal human pathogen with a bipolar mating system. It undergoes a dimorphic transition from a unicellular yeast to hyphal filamentous growth during mating and monokaryotic fruiting. The traditional sexual cycle that leads to the production of infectious basidiospores involves cells of both α and a mating type. Monokaryotic fruiting is a modified form of sexual reproduction that involves cells of the same mating type, most commonly α, which is the predominant mating type in both the environment and clinical isolates. However, some a isolates can also undergo monokaryotic fruiting. To determine whether mating type and other genetic loci contribute to the differences in fruiting observed between α and a cells, we applied quantitative trait loci (QTL) mapping to an inbred population of F(2) progeny. We discovered that variation in hyphal length produced during fruiting is a quantitative trait resulting from the combined effects of multiple genetic loci, including the mating type (MAT) locus. Importantly, the α allele of the MAT locus enhanced hyphal growth compared with the a allele. Other virulence traits, including melanization and growth at 39 °C, also are quantitative traits that share a common QTL with hyphal growth. The Mac1 transcription factor, encoded in this common QTL, regulates copper homeostasis. MAC1 allelic differences contribute to phenotypic variation, and mac1Δ mutants exhibit defects in filamentation, melanin production, and high temperature growth. Further characterization of these QTL regions will reveal additional quantitative trait genes controlling biological processes central to fungal development and pathogenicity