Analog Module Placement Design Using Genetic Algorithm

This paper presents a novel genetic algorithm for analog module placement based on a generalization of the two-dimensional bin packing problem. The genetic encoding and operators assure that all problem constraints are always satisfied. Thus the potential problems of adding penalty terms to the cost function are eliminated so that the search configuration space is drastically decreased. The dedicated cost function is based on the special requirements of analog integrated circuits. A fractional factorial experiment was conducted using an orthogonal array to study the algorithm parameters. A meta-GA was applied to determine the optimal parameter values. The algorithm was tested with several local benchmark circuits. The experimental results show that the algorithm has better performance than the simulated annealing approach with satisfactory results comparable to manual placement. This study demonstrates the effectiveness of the genetic algorithm in the analog module placement problem. The algorithm has b     

Forecast Combinations in a DSGE‐VAR Lab

We explore the benefits of forecast combinations based on forecast‐encompassing tests compared to simple averages and to Bates–Granger combinations. We also consider a new combination algorithm that fuses test‐based and Bates–Granger weighting. For a realistic simulation design, we generate multivariate time series samples from a macroeconomic DSGE‐VAR (dynamic stochastic general equilibrium–vector autoregressive) model. Results generally support Bates–Granger over uniform weighting, whereas benefits of test‐based weights depend on the sample size and on the prediction horizon. In a corresponding application to real‐world data, simple averaging performs best. Uniform averages may be the weighting scheme that is most robust to empirically observed irregularities. Copyright © 2016 John Wiley & Sons, Ltd.     

Molecular diversity and ecology of microbial plankton

The history of microbial evolution in the oceans is probably as old as the history of life itself. In contrast to terrestrial ecosystems, microorganisms are the main form of biomass in the oceans, and form some of the largest populations on the planet. Theory predicts that selection should act more efficiently in large populations. But whether microbial plankton populations harbour organisms that are models of adaptive sophistication remains to be seen. Genome sequence data are piling up, but most of the key microbial plankton clades have no cultivated representatives, and information about their ecological activities is sparse.     

Revised rates for the stellar triple-alpha process from measurement of 12C nuclear resonances

In the centres of stars where the temperature is high enough, three alpha-particles (helium nuclei) are able to combine to form 12C because of a resonant reaction leading to a nuclear excited state. (Stars with masses greater than approximately 0.5 times that of the Sun will at some point in their lives have a central temperature high enough for this reaction to proceed.) Although the reaction rate is of critical significance for determining elemental abundances in the Universe, and for determining the size of the iron core of a star just before it goes supernova, it has hitherto been insufficiently determined. Here we report a measurement of the inverse process, where a 12C nucleus decays to three alpha-particles. We find a dominant resonance at an energy of approximately 11 MeV, but do not confirm the presence of a resonance at 9.1 MeV (ref. 3). We show that interference between two resonances has important effects on our measured spectrum. Using these data, we calculate the triple-alpha rate for temperatures from 10(7) K to 10(10) K and find significant deviations from the standard rates. Our rate below approximately 5 x 10(7) K is higher than the previous standard, implying that the critical amounts of carbon that catalysed hydrogen burning in the first stars are produced twice as fast as previously believed. At temperatures above 10(9) K, our rate is much less, which modifies predicted nucleosynthesis in supernovae.     

Mutations in SIL1 cause Marinesco-Sjögren syndrome, a cerebellar ataxia with cataract and myopathy

SIL1 (also called BAP) acts as a nucleotide exchange factor for the Hsp70 chaperone BiP (also called GRP78), which is a key regulator of the main functions of the endoplasmic reticulum. We found nine distinct mutations that would disrupt the SIL1 protein in individuals with Marinesco-Sj?gren syndrome, an autosomal recessive cerebellar ataxia complicated by cataracts, developmental delay and myopathy. Identification of SIL1 mutations implicates Marinesco-Sj?gren syndrome as a disease of endoplasmic reticulum dysfunction and suggests a role for this organelle in multisystem disorders.