Terrace grading of SiGe for high-quality virtual substrates

Silicon germanium (SiGe) virtual substrates of final germanium composition x = 0.50 have been fabricated using solid-source molecular beam epitaxy with a thickness of 2 µm. A layer structure that helps limit the size of dislocation pileups associated with the modified Frank–Read dislocation multiplication mechanism has been studied. It is shown that this structure can produce lower threading dislocation densities than conventional linearly graded virtual substrates. Cross-sectional transmission electron microscopy shows the superior quality of the dislocation network in the graded regions with a lower rms roughness shown by atomic force microscopy. X-ray diffractometry shows these layers to be highly relaxed. This method of Ge grading suggests that high-quality virtual substrates can be grown considerably thinner than with conventional grading methods

Microbial metabolism of isoprene: a much-neglected climate-active gas

The climate-active gas isoprene is the major volatile produced by a variety of trees and is released into the atmosphere in enormous quantities, on a par with global emissions of methane. While isoprene production in plants and its effect on atmospheric chemistry have received considerable attention, research into the biological isoprene sink has been neglected until recently. Here, we review current knowledge on the sources and sinks of isoprene and outline its environmental effects. Focusing on degradation by microbes, many of which are able to use isoprene as the sole source of carbon and energy, we review recent studies characterizing novel isoprene degraders isolated from soils, marine sediments and in association with plants. We describe the development and use of molecular methods to identify, quantify and genetically characterize isoprene-degrading strains in environmental samples. Finally, this review identifies research imperatives for the further study of the environmental impact, ecology, regulation and biochemistry of this interesting group of microbes

Information flow in a kinetic ising model peaks in the disordered phase

There is growing evidence that for a range of dynamical systems featuring complex interactions between large ensembles of interacting elements, mutual information peaks at order-disorder phase transitions. We conjecture that, by contrast, information flow in such systems will generally peak strictly on the disordered side of a phase transition. This conjecture is verified for a ferromagnetic 2D lattice Ising model with Glauber dynamics and a transfer entropy-based measure of systemwide information flow. Implications of the conjecture are considered, in particular, that for a complex dynamical system in the process of transitioning from disordered to ordered dynamics (a mechanism implicated, for example, in financial market crashes and the onset of some types of epileptic seizures); information dynamics may be able to predict an imminent transition

Energy-based General Sequential Episodic Memory Networks at the Adiabatic Limit

The General Associative Memory Model (GAMM) has a constant state-dependant energy surface that leads the output dynamics to fixed points, retrieving single memories from a collection of memories that can be asynchronously preloaded. We introduce a new class of General Sequential Episodic Memory Models (GSEMM) that, in the adiabatic limit, exhibit temporally changing energy surface, leading to a series of meta-stable states that are sequential episodic memories. The dynamic energy surface is enabled by newly introduced asymmetric synapses with signal propagation delays in the network's hidden layer. We study the theoretical and empirical properties of two memory models from the GSEMM class, differing in their activation functions. LISEM has non-linearities in the feature layer, whereas DSEM has non-linearity in the hidden layer. In principle, DSEM has a storage capacity that grows exponentially with the number of neurons in the network. We introduce a learning rule for the synapses based on the energy minimization principle and show it can learn single memories and their sequential relationships online. This rule is similar to the Hebbian learning algorithm and Spike-Timing Dependent Plasticity (STDP), which describe conditions under which synapses between neurons change strength. Thus, GSEMM combines the static and dynamic properties of episodic memory under a single theoretical framework and bridges neuroscience, machine learning, and artificial intelligence

Fusiform Rust Trends in East Texas: 1969-1987

Five surveys of pine plantations in East Texas over an 18-year period (1969-1987) indicated that fusiform rust (Cronartium quercuum [Berk.] Miyabe ex Shirai f. sp. fusiforme Birdsall and Snow) infection rates have increased to current levels of about 50% on slash pine (Pinus elliottii Engelm.) and are continuing to increase on loblolly pine (Pinus taeda L.) to 10-15% levels. South. J. Appl. For. 12(4):259-26

Regulation of plasmid-encoded isoprene metabolism in Rhodococcus, a representative of an important link in the global isoprene cycle

Emissions of biogenic volatile organic compounds (VOCs) form an important part of the global carbon cycle, comprising a significant proportion of net ecosystem productivity. They impact atmospheric chemistry and contribute directly and indirectly to greenhouse gases. Isoprene, emitted largely from plants, comprises one third of total VOCs, yet in contrast to methane, which is released in similar quantities, we know little of its biodegradation. Here, we report the genome of an isoprene degrading isolate, Rhodococcus sp. AD45, and, using mutagenesis shows that a plasmid-encoded soluble di-iron centre isoprene monooxygenase (IsoMO) is essential for isoprene metabolism. Using RNA sequencing (RNAseq) to analyse cells exposed to isoprene or epoxyisoprene in a substrate-switch time-course experiment, we show that transcripts from 22 contiguous genes, including those encoding IsoMO, were highly upregulated, becoming among the most abundant in the cell and comprising over 25% of the entire transcriptome. Analysis of gene transcription in the wild type and an IsoMO-disrupted mutant strain showed that epoxyisoprene, or a subsequent product of isoprene metabolism, rather than isoprene itself, was the inducing molecule. We provide a foundation of molecular data for future research on the environmental biological consumption of this important, climate-active compound

On the number of minimal completely separating systems and antichains in a Boolean lattice

An (n)completely separating system C ((n)CSS) is a collection of blocks of [n] = {1,..., n} such that for all distinct a, b ∈ [n] there are blocks A, B ∈C with a ∈ A \ B and b ∈ B \ A. An (n)CSS is minimal if it contains the minimum possible number of blocks for a CSS on [n]. The number of non-isomorphic minimal (n)CSSs is determined for 11 ≤ n ≤ 35. This also provides an enumeration of a natural class of antichains