Silica membrane reactors for hydrogen production from water gas shift

This paper presents an analysis of membrane reactor (MR) operation and design for enhanced hydrogen production from the water gas shift (WGS) reaction. It has been established that membrane reactors can enhance an equilibrium limited reaction through product separation. However, the detailed effects of reactor setup, membrane configuration and catalyst volume have yet to be properly analysed for this reaction. This paper investigates new ideas for membrane reactors such as the development of new catalytic films, for improved interaction between the reaction and separation zones. Current membrane reactors utilise a packed bed of catalyst within the membrane tube, utilising a large volume of catalyst to drive reaction. This is still inefficient and provides only limited benefits over conventional WGS reactors. New reactor configurations look to optimise the interactive effects between reaction and separation to provide improved operation. In this paper, thin film catalysts were produced using dip coating and spray coating techniques. This technique produced catalyst coatings with good thickness, though the abrasion strength of the dip coated catalyst was quite low. The catalyst was tested in a packed bed reactor for temperature activity at low temperatures and catalyst activity at varying levels of excess water

The Pineapple EST sequencing and microarray project

We have initiated an EST sequencing project to survey a range of expressed sequences from green fruit, yellow fruit, roots, and root-knot nematode infected root/gall tissues. In total, 5681 edited EST sequences were retrieved. Clone redundancy was high in the fruit libraries, with the combined fruit 1548 clone sequences clustering into just 634 contigs comprising 191 consensus sequences and 443 singletons. Half of all fruit EST clone sequences clustered within approximately 14 and 9% of contigs from green unripe and yellow ripe libraries respectively, indicating that a small subset of genes dominates the majority of the transcriptome. The root and root/gall libraries had lower levels of redundancy than the fruit libraries. Half of the root/gall ESTs clustered within approximately 40% of all contigs, indicating the roots possess a more complex transcriptome. Contig assembly and cluster analysis revealed major differences in the abundant gene sequences expressed between the unripe green and the ripe yellow fruit tissues, or gene sequences expressed between the weeks 1-4 and weeks 5-10 nematode infected gall vascular cylinder libraries.

Retrotransposon expression profiling: Unveiling the hidden SINE transcriptome through Next-Generation Sequencing data analysis

Of the ~1.7 million SINE elements in the human genome, only a tiny number are estimated to be active in transcription by RNA polymerase (Pol) III. Tracing the individual loci from which SINE transcripts originate is complicated by their highly repetitive nature. By exploiting RNA-Seq datasets and unique SINE DNA sequences, we devised a bioinformatic pipeline allowing us to identify Pol III-dependent transcripts of individual SINE elements. When applied to ENCODE transcriptomes of seven human cell lines, this search strategy identified ~1300 Alu loci and ~1100 MIR loci corresponding to detectable transcripts, with ~120 and ~60 respectively Alu and MIR loci expressed in at least three cell lines. In vitro transcription of selected SINEs did not reflect their in vivo expression properties, and required the native 5’-flanking region in addition to internal promoter. We also identified a cluster of expressed AluYa5-derived transcription units, juxtaposed to snaR genes on chromosome 19, formed by a promoter-containing left monomer fused to an Alu-unrelated downstream moiety. Autonomous Pol III transcription was also revealed for SINEs nested within Pol II-transcribed genes raising the possibility of an underlying mechanism for Pol II gene regulation by SINE transcriptional units. Moreover the application of our bioinformatic pipeline to both RNA-seq data of cells subjected to an in vitro pro-oncogenic stimulus and of in vivo matched tumor and non-tumor samples allowed us to detect increased Alu RNA expression as well as the source loci of such deregulation. The ability to investigate SINE transcriptomes at single-locus resolution will facilitate both the identification of novel biologically relevant SINE RNAs and the assessment of SINE expression alteration under pathological conditions.

Neural control of a batch distillation

The purpose of the work reported here was to investigate the application of neural control to a common industrial process. The chosen problem was the control of a batch distillation. In the first phase towards deployment, a complex software simulation of the process was controlled. Initially, the plant was modelled with a neural emulator. The neural emulator was used to train a neural controller using the backpropagation through time algorithm. A high accuracy was achieved with the emulator after a large number of training epochs. The controller converged more rapidly, but its performance varied more widely over its operating range. However, the controlled system was relatively robust to changes in ambient conditions.

Inventory parameter management and focused continuous improvement for repetitive batch manufacturers

What this thesis proposes is a methodology to assist repetitive batch manufacturers in the adoption of certain aspects of the Lean Production principles. The methodology concentrates on the reduction of inventory through the setting of appropriate batch sizes, taking account of the effect of sequence dependent set-ups and the identification and elimination of bottlenecks. It uses a simple Pareto and modified EBQ based analysis technique to allocate items to period order day classes based on a combination of each item's annual usage value and set-up cost. The period order day classes the items are allocated to are determined by the constraints limits in the three measured dimensions, capacity, administration and finance. The methodology overcomes the limitations associated with MRP in the area of sequence dependent set-ups, and provides a simple way of setting planning parameters taking this effect into account by concentrating on the reduction of inventory through the systematic identification and elimination of bottlenecks through set-up reduction processes, so allowing batch sizes to reduce. It aims to help traditional repetitive batch manufacturers in a route to continual improvement by: Highlighting those areas where change would bring the greatest benefits. Modelling the effect of proposed changes. Quantifying the benefits that could be gained through implementing the proposed changes. Simplifying the effort required to perform the modelling process. It concentrates on increasing flexibility through managed inventory reduction through rationally decreasing batch sizes, taking account of sequence dependent set-ups and the identification and elimination of bottlenecks. This was achieved through the development of a software modelling tool, and validated through a case study approach.

A hybrid genetic algorithm for sequencing PCB component placement

A chip shooter machine for electronic components assembly has a movable feeder carrier holding components, a movable X-Y table carrying a printed circuit board (PCB), and a rotary turret having multiple assembly heads. This paper presents a hybrid genetic algorithm to optimize the sequence of component placements for a chip shooter machine. The objective of the problem is to minimize the total traveling distance of the X-Y table or the board. The genetic algorithm developed in the paper hybridizes the nearest neighbor heuristic, and an iterated swap procedure, which is a new improved heuristic. We have compared the performance of the hybrid genetic algorithm with that of the approach proposed by other researchers and have demonstrated our algorithm is superior in terms of the distance traveled by the X-Y table or the board.

A hybrid genetic algorithm for component sequencing and feeder arrangement

This paper presents a hybrid genetic algorithm to optimize the sequence of component placements on a printed circuit board and the arrangement of component types to feeders simultaneously for a pick-and-place machine with multiple stationary feeders, a fixed board table and a movable placement head. The objective of the problem is to minimize the total travelling distance, or the travelling time, of the placement head. The genetic algorithm developed in the paper hybrisizes different search heuristics including the nearest neighbor heuristic, the 2-opt heuristic, and an iterated swap procedure, which is a new improving heuristic. Compared with the results obtained by other researchers, the performance of the hybrid genetic algorithm is superior to others in terms of the distance travelled by the placement head.