Data-based robust multiobjective optimization of interconnected processes: energy efficiency case study in papermaking.

Reducing energy consumption is a major challenge for "energy-intensive" industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of "optimized" operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method.

BarraCUDA - a fast short read sequence aligner using graphics processing units.

BACKGROUND: With the maturation of next-generation DNA sequencing (NGS) technologies, the throughput of DNA sequencing reads has soared to over 600 gigabases from a single instrument run. General purpose computing on graphics processing units (GPGPU), extracts the computing power from hundreds of parallel stream processors within graphics processing cores and provides a cost-effective and energy efficient alternative to traditional high-performance computing (HPC) clusters. In this article, we describe the implementation of BarraCUDA, a GPGPU sequence alignment software that is based on BWA, to accelerate the alignment of sequencing reads generated by these instruments to a reference DNA sequence. FINDINGS: Using the NVIDIA Compute Unified Device Architecture (CUDA) software development environment, we ported the most computational-intensive alignment component of BWA to GPU to take advantage of the massive parallelism. As a result, BarraCUDA offers a magnitude of performance boost in alignment throughput when compared to a CPU core while delivering the same level of alignment fidelity. The software is also capable of supporting multiple CUDA devices in parallel to further accelerate the alignment throughput. CONCLUSIONS: BarraCUDA is designed to take advantage of the parallelism of GPU to accelerate the alignment of millions of sequencing reads generated by NGS instruments. By doing this, we could, at least in part streamline the current bioinformatics pipeline such that the wider scientific community could benefit from the sequencing technology.BarraCUDA is currently available from http://seqbarracuda.sf.net.

Data-based robust multiobjective optimization of interconnected processes: Energy efficiency case study in papermaking

Reducing energy consumption is a major challenge for energy-intensive industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of optimized operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method. © 2006 IEEE.

mRNA 很可能携带三维遗传信息

The forming mechanism of the three - dimensional structures of proteins，i.e.the mechanism of protein folding，is a basic problem in molecular biology which is still unsolved unitl now. In which a core problem is whether there is the three – dimensional genetic information that decide the three - dimensional structures of proteins. However, the research on this field has mot yet been reported. Recently，we made a comparative study on the folded structures of more than 70 mature messeneger RNAs (mRNAs) and the three - dimensional structures of the proteins encoded by them，it has been found that there exist marked correspondences between their featured structures in the following aspects: 1.The number of the structural units. An RNA molecule can form a secondary structure(stem and loop structure) by the folding and the base pairing of itself. The elementary structural unit of an RNA secondary structure is hairpin(or compound hair pin).The regular structural unit in the secondary structure of a protein is # alpha # - helix or #beta# - sheet . We have found that the hairpin number in the secondary structure of each mature mRNA is equal or approximately equal to the number of the regular secondary structural unis of the encoded protein. 2 .Turning region. Turn is a main structrual element in the secondary structure of a protein, which decides the backbone orientation of a protein molecule to some extent .Our analysis shows that the nucleotide sequence segments in an mRNA which encode the turns of the corresponding protein are overall situated in the turning regions of the mRNA secondary structure such as haipin，bulge loop or multibaranch loops. 3 .The arrangement of structural elements in space. In order to understand the backbone orientation of an RNA molecule and the arangement of its structural elements in space，we have modeled the three一dimensional structure of the mRNA molecule on SGI workstation based on its secondary structure.The result shows that the spatial arrangement of most of the nucleotide sequence segments encoding the structural elements of a protein is consistent with that of these stretural exements in the protein. For instance，the nucleotide sequences corresponding to each pleated sheet of a # beta # - sheet structure are close to each other in the mRNA secondary stucture and in the three - dimensional structure，although some of the nucleotide segments are far apart from each other in the one - dimensional sequence. For another instance，the two triplet codons of cysteines which form a disulphide bridge geneal1y are very close to each other in the mRNA folded structure. In addition，we also analyzed the locations of the codons proline - coding and the distrbution of the nucleotide sequences #alpha# - helix - coding in the folded structures of mRNAs . Some distribution laws have been found. All of these results suggest that the transfer of the genetic information from mRNA to protein not only is one – dimensional but also is three - dime ns ional. That is，there exists the genetic information that decide the three - dimensional structures of proteins. To a certain extent，we could say that the mRNA folding detemines the protein folding. Based on these results，it would be possible to predict the three - dimensional structures of proteins from the primary，secondary and tertiary structures of the m RNAs at a higher accuracy.And more important is that a new clue has been provided to uncover the“spatial coding" of the genetic information.

The use of spatial impulse responses to characterise flexible forming processes with mobile tools

A novel test method for the characterisation of flexible forming processes is proposed and applied to four flexible forming processes: Incremental Sheet Forming (ISF), conventional spinning, the English wheel and power hammer. The proposed method is developed in analogy with time-domain control engineering, where a system is characterised by its impulse response. The spatial impulse response is used to characterise the change in workpiece deformation created by a process, but has also been applied with a strain spectrogram, as a novel way to characterise a process and the physical effect it has on the workpiece. Physical and numerical trials to study the effects of process and material parameters on spatial impulse response lead to three main conclusions. Incremental sheet forming is particularly sensitive to process parameters. The English wheel and power hammer are strongly similar and largely insensitive to both process and material parameters. Spinning develops in two stages and is sensitive to most process parameters, but insensitive to prior deformation. Finally, the proposed method could be applied to modelling, classification of existing and novel processes, product-process matching and closed-loop control of flexible forming processes. © 2012 Elsevier B.V.

Exploring consensus mRNA secondary (folding) structure units by stochastic sampling and folding simulation

It is extremely difficult to explore mRNA folding structure by biological experiments. In this report, we use stochastic sampling and folding simulation to test the existence of the stable secondary structural units of-mRNA, look for the folding units, and explore the probabilistic stabilization of the units. Using this method, We made simulations for all possible local optimum secondary structures of a single strand mRNA within a certain range, and searched for the common parts of the secondary structures. The consensus secondary structure units (CSSUs) extracted from the above method are mainly hairpins, with a few single strands. These CSSUs suggest that the mRNA folding units could be relatively stable and could perform specific biological function. The significance of these observations for the mRNA folding problem in general is also discussed. (c) 2004 Elsevier B.V. All rights reserved.

Bulk forming of sheet metal

Ever increasing demands on functional integration of high strength light weight products leads to the development of a new class of manufacturing processes. The application of bulk forming processes to sheet or plate semi-finished products, sometimes in combination with conventional sheet forming processes creates new products with the requested properties. The paper defines this new class of sheet-bulk metal forming processes, gives an overview of the existing processes belonging to this class, highlights the tooling aspects as well as the resulting product properties and presents a short summary of the relevant work that has been done towards modeling and simulation. © 2012 CIRP.

Mechanics of capillary forming of aligned carbon nanotube assemblies.

Elastocapillary self-assembly is emerging as a versatile technique to manufacture three-dimensional (3D) microstructures and complex surface textures from arrangements of micro- and nanoscale filaments. Understanding the mechanics of capillary self-assembly is essential to engineering of properties such as shape-directed actuation, anisotropic wetting and adhesion, and mechanical energy transfer and dissipation. We study elastocapillary self-assembly (herein called "capillary forming") of carbon nanotube (CNT) microstructures, combining in situ optical imaging, micromechanical testing, and finite element modeling. By imaging, we identify sequential stages of liquid infiltration, evaporation, and solid shrinkage, whose kinetics relate to the size and shape of the CNT microstructure. We couple these observations with measurements of the orthotropic elastic moduli of CNT forests to understand how the dynamic of shrinkage of the vapor-liquid interface is coupled to the compression of the forest. We compare the kinetics of shrinkage to the rate of evporation from liquid droplets having the same size and geometry. Moreover, we show that the amount of shrinkage during evaporation is governed by the ability of the CNTs to slip against one another, which can be manipulated by the deposition of thin conformal coatings on the CNTs by atomic layer deposition (ALD). This insight is confirmed by finite element modeling of pairs of CNTs as corrugated beams in contact and highlights the coupled role of elasticity and friction in shrinkage and stability of nanoporous solids. Overall, this study shows that nanoscale porosity can be tailored via the filament density and adhesion at contact points, which is important to the development of lightweight multifunctional materials.

Diverse 3D microarchitectures made by capillary forming of carbon nanotubes.

A new technology called capillary forming enables transformation of vertically aligned nanoscale filaments into complex three-dimensional microarchitectures. We demonstrate capillary forming of carbon nanotubes into diverse forms having intricate bends, twists, and multidirectional textures. In addition to their novel geometries, these structures have mechanical stiffness exceeding that of microfabrication polymers, and can be used as masters for replica molding