A Faster and More Space-Efficient Algorithm for Inferring Arc-Annotations of RNA Sequences through Alignment

The nested arc-annotation of a sequence is an important model used to represent structural information for RNA and protein sequences. Given two sequences S₁ and S₂ and a nested arc-annotation P₁ for S₁, this paper considers the problem of inferring the nested arc-annotation P₂ for S₂ such that (S₁, P₁) and (S₂, P₂) have the largest common substructure. The problem has a direct application in predicting the secondary structure of an RNA sequence given a closely related sequence with known secondary structure. The currently most efficient algorithm for this problem requires O(nm³) time and O(nm²) space where n is the length of the sequence with known arc-annotation and m is the length of the sequence whose arc-annotation is to be inferred. By using sparsification on a new recursive dynamic programming algorithm and applying a Hirschberg-like traceback technique with compression, we obtain an improved algorithm that runs in min{O(nm² + n²m),O(nm² log n), O(nm³)} time and min{O(m² + mn), O(m² log n + n)} space.     

6G and the UN SDGs: Where is the Connection?

Wireless Personal Communications - Sustainability has entered all aspects of life, calling for an active approach from the wireless and mobile communications community to help in solving...     

Interaction of carbon with vacancy and self-interstitial atom clusters in α-iron studied using metallic-covalent interatomic potential

The presence of even small amount of carbon interstitial impurity affects properties of Fe and Fe-based ferritic alloys. From earlier experiments it follows that carbon exhibits considerably strong interaction with lattice defects and therefore influences their mobility, hence affecting the evolution of the microstructure under irradiation. This work is dedicated to understanding the interaction of carbon-vacancy complexes with glissile dislocation loops, which form in Fe, Fe-based alloys and ferritic steels under irradiation. We apply large scale atomistic simulations coupled with the so-called ‘metallic-covalent bonding’ interatomic model for the Fe-C system, known to be the most consistent interatomic model available today. With these techniques we have studied (i) the stability of vacancy-carbon clusters; (ii) the interaction of octahedral carbon with ½〈1 1 1〉 loops; (iii) possibility of the dynamic drag of carbon by ½〈1 1 1〉 loops and (iv) the interaction of ½〈1 1 1〉 loops with the most stable vacancy-carbon clusters expected to occur under irradiation. Finally, we have shown that carbon-vacancy complexes act as strong traps for ½〈1 1 1〉 loops.     

Modelling temperature-dependent heat production over decades in High Arctic coal waste rock piles

Subsurface heat production from oxidation of pyrite is an important process that may increase subsurface temperatures within coal waste rock piles and increase the release of acid mine drainage, AMD. Waste rock piles in the Arctic are especially vulnerable to changes in subsurface temperatures as the release of AMD normally is limited by permafrost. Here we show that temperatures within a 20 year old heat-producing waste rock pile in Svalbard (78°N) can be modelled by the one-dimensional heat and water flow model (CoupModel) with a new temperature-dependent heat-production module that includes both biological and chemical oxidation processes and heat source depletion over time. Inputs to the model are meteorological measurements, physical properties of the waste rock material and measured subsurface heat-production rates. Measured mean annual subsurface temperatures within the waste rock pile are up to 10 °C higher than the mean annual air temperature of −5.8 °C. Subsurface temperatures are currently decreasing with 0.5 °C per year due to decreasing heat production, which can be modelled using an exponential decay function corresponding to a half-life period of pyrite oxidation of 7 years. Simulations further suggest that subsurface temperatures two years after construction of the pile may have been up to 34.0 °C higher than in 2009 and that the release of AMD may have been more than 20 times higher. Sensitivity simulations show that maximum temperatures in the pile would have been up to 30.5-32.5 °C lower and that the pile would have been frozen 12-27 years earlier if the pile had been initially saturated with water, constructed with a thickness half of the original or a combination of both. Simulation show that the pile thickness and waste rock pyrite content are important factors controlling the internal build up of heat leading to potential self-incineration. However, site specific measurements of temperature-dependent heat production as well as simulation results show that the heat produced from pyrite oxidation alone cannot cause such a temperature increase and that processes such as heat production from coal oxidation may be equally important.     

Effects of TiO2 particles size and heat treatment on friction coefficient and corrosion performance of electroless Ni-P/TiO2 composite coatings

The effects of the titanium dioxide (TiO₂) particles size on the friction coefficient and corrosion performance of the Ni-P/TiO₂ composite coatings before and after heat treatment at 400°C for 1h have been investigated. Pin-on-disc analysis results have revealed that the highest and the lowest friction coefficients belonged, respectively, to the simple Ni-P coating and the Ni-P/TiO₂ composite coating containing TiO₂ particles of the average size of 0.1 μm (μ ～ 0.62 against 0.52). Eventually, a relative reduction in the corrosion resistance and the friction coefficient (as low as μ ～ 0.38) have been observed after heat treatment of Ni-P and Ni-P/TiO₂ composite coatings.     

Review of Spark Discharge Generators for Production of Nanoparticle Aerosols

In the growing field of nanotechnology there is an increasing need to develop production methods for nanoparticles, especially methods that provide control and reproducibility. The spark discharge generator (SDG) is a versatile device for the production of nanoparticle aerosols. It can produce aerosol nanoparticles in the entire nanometer range (1–100 nm), and beyond. Depending on requirements, and the system used, these nanoparticles can be completely contamination free and composed of one or more materials. This provides a unique opportunity to create new materials on the nanoscale. Already in use in semiconductor, materials, health and environmental research, the SDG shows promise for yet more applications. If needed, particle production by the SDG could be scaled up using parallel generators facilitating continuous high-volume production of aerosol nanoparticles. Still, there is a surprisingly low knowledge of fundamental processes in the SDG. In this article we present a thorough review of the most common and relevant SDGs and the theory of their operation. Some possible improvements are also discussed.

Copyright 2012 American Association for Aerosol Research     

C?C Hydrolases for Biocatalysis

Although C C bond hydrolases are distributed widely in Nature, they has as yet have received only limited attention in the area of biocatalysis compared to their counterpart the C‐heteroatom hydrolases, such as lipases and proteases. However, the substrate range of C C hydrolases, and their non‐dependence on cofactors, suggest that these enzymes may have considerable potential for applications in synthesis. In addition, hydrolases such as the β‐diketone hydrolase from Rhodococcus (OCH) are known, that catalyse the formation of interesting chiral intermediates. Further enzymes, such as kynureninase and a meta‐cleavage product hydrolase (MhpC), are able to catalyse carbon‐carbon bond formation, suggesting wider applications in biocatalysis than previously envisaged. In this review, the distribution, catalytic characteristics and applications of C C hydrolases are described, with a view to assessing their potentialfor use in biocatalytic processes in the future.     

Crystallization of sheared polymer melts: poly(ethylene oxide) fractions

Summary Crystallization under controlled shear conditions has been optically monitored for a series of sharp molecular weight fractions of poly(ethylene oxide). The minimum shear rate (MSR) necessary to produce oriented crystalline morphologies exhibited a strong molecular weight (M) dependence: MSR=K/M^1.47. The time necessary for erasure of orientation effects after crystal melting was also determined and found to be proportional to M^1.42.