Linear programming for large-scale Markov decision problems

We consider the problem of controlling a Markov decision process (MDP) with a large state space, so as to minimize average cost. Since it is intractable to compete with the optimal policy for large scale problems, we pursue the more modest goal of competing with a low-dimensional family of policies. We use the dual linear programming formulation of the MDP average cost problem, in which the variable is a stationary distribution over state-action pairs, and we consider a neighborhood of a low-dimensional subset of the set of stationary distributions (defined in terms of state-action features) as the comparison class. We propose a technique based on stochastic convex optimization and give bounds that show that the performance of our algorithm approaches the best achievable by any policy in the comparison class. Most importantly, this result depends on the size of the comparison class, but not on the size of the state space. Preliminary experiments show the effectiveness of the proposed algorithm in a queuing application.

Model Predictive Static Programming: A Computationally Efficient Technique For Suboptimal Control Design

Combining the philosophies of nonlinear model predictive control and approximate dynamic programming, a new suboptimal control design technique is presented in this paper, named as model predictive static programming (MPSP), which is applicable for finite-horizon nonlinear problems with terminal constraints. This technique is computationally efficient, and hence, can possibly be implemented online. The effectiveness of the proposed method is demonstrated by designing an ascent phase guidance scheme for a ballistic missile propelled by solid motors. A comparison study with a conventional gradient method shows that the MPSP solution is quite close to the optimal solution.

Functional correlation of bacterial LuxS with their quaternary associations: interface analysis of the structure networks

Background The genome of a wide variety of prokaryotes contains the luxS gene homologue, which encodes for the protein S-ribosylhomocysteinelyase (LuxS). This protein is responsible for the production of the quorum sensing molecule, AI-2 and has been implicated in a variety of functions such as flagellar motility, metabolic regulation, toxin production and even in pathogenicity. A high structural similarity is present in the LuxS structures determined from a few species. In this study, we have modelled the structures from several other species and have investigated their dimer interfaces. We have attempted to correlate the interface features of LuxS with the phenotypic nature of the organisms. Results The protein structure networks (PSN) are constructed and graph theoretical analysis is performed on the structures obtained from X-ray crystallography and on the modelled ones. The interfaces, which are known to contain the active site, are characterized from the PSNs of these homodimeric proteins. The key features presented by the protein interfaces are investigated for the classification of the proteins in relation to their function. From our analysis, structural interface motifs are identified for each class in our dataset, which showed distinctly different pattern at the interface of LuxS for the probiotics and some extremophiles. Our analysis also reveals potential sites of mutation and geometric patterns at the interface that was not evident from conventional sequence alignment studies. Conclusion The structure network approach employed in this study for the analysis of dimeric interfaces in LuxS has brought out certain structural details at the side-chain interaction level, which were elusive from the conventional structure comparison methods. The results from this study provide a better understanding of the relation between the luxS gene and its functional role in the prokaryotes. This study also makes it possible to explore the potential direction towards the design of inhibitors of LuxS and thus towards a wide range of antimicrobials.

Programming an FPGA to Emulate the Dynamics of DC Machines

This paper presents the programming an FPGA (Field Programmable Gate Array) to emulate the dynamics of DC machines. FPGA allows high speed real time simulation with high precision. The described design includes block diagram representation of DC machine, which contain all arithmetic and logical operations. The real time simulation of the machine in FPGA is controlled by user interfaces they are Keypad interface, LCD display on-line and digital to analog converter. This approach provides emulation of electrical machine by changing the parameters. Separately Exited DC machine implemented and experimental results are presented.

A linear programming approach for estimating the structure of a sparse linear genetic network from transcript profiling data

Background: A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN) from transcript profiling data. Results: The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting) problem and solved finally by formulating a Linear Program (LP). A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM) initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known regulatory associations. In each S. cerevisiae LP-SLGN, the number of nodes with a particular degree follows an approximate power law suggesting that its degree distributions is similar to that observed in real-world networks. Inspection of these LP-SLGNs suggests biological hypotheses amenable to experimental verification. Conclusion: A statistically robust and computationally efficient LP-based method for estimating the topology of a large sparse undirected graph from high-dimensional data yields representations of genetic networks that are biologically plausible and useful abstractions of the structures of real genetic networks. Analysis of the statistical and topological properties of learned LP-SLGNs may have practical value; for example, genes with high random walk betweenness, a measure of the centrality of a node in a graph, are good candidates for intervention studies and hence integrated computational – experimental investigations designed to infer more realistic and sophisticated probabilistic directed graphical model representations of genetic networks. The LP-based solutions of the sparse linear regression problem described here may provide a method for learning the structure of transcription factor networks from transcript profiling and transcription factor binding motif data.

Parallel parsing of programming languages

A new method of specifying the syntax of programming languages, known as hierarchical language specifications (HLS), is proposed. Efficient parallel algorithms for parsing languages generated by HLS are presented. These algorithms run on an exclusive-read exclusive-write parallel random-access machine. They require O(n) processors and O(log2n) time, where n is the length of the string to be parsed. The most important feature of these algorithms is that they do not use a stack.

Volatile components associated with bacterial spoilage of tropical prawns

Analysis of headspace volatiles by gas chromatography/mass spectrometry from king (Penaeus plebejus), banana (P. merguiensis), tiger (P. esculentus/semisulcatus) and greasy (Metapenaeus bennettae) prawns stored in ice or ice slurry, which is effectively an environment of low oxygen tension, indicated the presence of amines at the early stages of storage (less than 8 days) irrespective of the nature of the storage media. Esters were more prevalent in prawns stored on ice (normal oxygen conditions) at the latter stages of storage (more than 8 days) and were only produced by Pseudomonas fragi, whereas sulphides and amines occurred whether the predominant spoilage organism was Ps.fragi or Shewanella putrefaciens. The free amino acid profiles of banana and king prawns were high in arginine (12–14%) and low in cysteine (0.1–0.17%) and methionine (0.1–0.2%). Filter sterilised raw banana prawn broth inoculated with a total of 15 cultures of Ps. fragi and S. putrefaciens and incubated for two weeks at 5°C, showed the presence of 17 major compounds in the headspace volatiles analysed using gas chromatography/mass spectrometry (GC/MS). These were mainly amines, sulphides, ketones and esters. Principal Component Analysis of the results for the comparative levels of the volatiles produced by pure cultures, inoculated into sterile prawn broth, indicated three subgroupings of the organisms; I, Ps. fragi from a particular geographic location; II, S. putrefaciens from another geographic location; and III, a mixture of Ps. fragi and S. putrefaciens from different geographic locations. The sensory impression created by the cultures was strongly related to the chemical profile as determined by GC/MS. Organisms, even within the same subgrouping classified as identical by the usual tests, produced a different range of volatiles in the same uniform substrate.

Purification of a bacterial organophosphate-hydrolysing phosphatase by cibacron 3GA-Sepharose affinity chromatography

A phosphatase catalysing the hydrolysis of organophosphorus pesticides was purified to homogeneity using Cibacron 3GA-Sepharose CL 6B affinity chromatography. The enzyme which is localized in the periplasm of the bacterium Image NC5 was extracted by treating with 0.2M MgCl2, pH 8.4. The enzyme was adsorbed to the Cibacron-Sepharose at pH 7.0 and eluted with Tris-HCl buffer at pH 8.0, with 47 per cent recovery. The enzyme thus obtained was electrophoretically homogeneous. This simple affinity purification procedure enhances the potential for its use in large scale detoxification systems.

Mathematics, programming, and STEM

Learning mathematics is a complex and dynamic process. In this paper, the authors adopt a semiotic framework (Yeh & Nason, 2004) and highlight programming as one of the main aspects of the semiosis or meaning-making for the learning of mathematics. During a 10-week teaching experiment, mathematical meaning-making was enriched when primary students wrote Logo programs to create 3D virtual worlds. The analysis of results found deep learning in mathematics, as well as in technology and engineering areas. This prompted a rethinking about the nature of learning mathematics and a need to employ and examine a more holistic learning approach for the learning in science, technology, engineering, and mathematics (STEM) areas.

Future switching technology: bacterial protein-based programmable all-optical switch for integrated optics applications?

We report on the bacterial protein-based all-optical switches which operate at low laser power, high speed and fulfil most of the requirements to be an ideal all-optical switch without any moving parts involved. This consists of conventional optical waveguides coated with bacteriorhodopsin films at switching locations. The principle of operation of the switch is based on the light-induced refractive index change of bacteriorhodopsin. This approach opens the possibility of realizing proteinbased all-optical switches for communication network, integrated optics and optical computers.

Effects of secondary crops on bacterial growth and nitrogen removal in shrimp farm effluent treatment systems

Secondary crops provide a means of assimilating some effluent nitrogen from eutrophic shrimp farm settlement ponds. However, a more important role may be their stimulation of beneficial bacterial nitrogen removal processes. In this study, bacterial biomass, growth and nitrogen removal capacity were quantified in shrimp farm effluent treatment systems containing vertical artificial substrates and either the banana shrimp Penaeus merguiensis (de Man) or the grey mullet, Mugil cephalus L. Banana shrimp were found to actively graze biofilm on the artificial substrates and significantly reduced bacterial biomass relative to a control (24.5 ± 5.6mgCm−2 and 39.2 ± 8.7mgCm−2, respectively). Bacterial volumetric growth rates, however, were significantly increased in the presence of the shrimp relative to the control 45.2±11.3mgCm−2 per day and 22.0±4.3mgCm−2 per day, respectively). Specific growth rate, or growth rate per cell, of bacteria was therefore appreciably stimulated by the banana shrimp. Nitrate assimilation was found to be significantly higher on grazed substrate biofilm relative to the control (223±54 mgNm−2 per day and 126±36 mg Nm−2 per day, respectively), suggesting that increased bacterial growth rate does relate to enhanced nitrogen uptake. Regulated banana shrimp feeding activity therefore can increase the rate of newbacterial biomass production and also the capacity for bacterial effluent nitrogen assimilation. Mullet had a negligible influence on the biofilm associated with the artificial substrate but reduced sediment bacterial biomass (224 ± 92 mgCm−2) relative to undisturbed sediment (650 ± 254 mgCm−2). Net, or volumetric bacterial growth in the sediment was similar in treatments with and without mullet, suggesting that the growth rate per cell of bacteria in grazed sediments was enhanced. Similar rates of dissolved nitrogen mineralisation werefound in sediments with and without mullet but nitrificationwas reduced. Presence of mullet increased water column suspended solids concentrations, water column bacterial growth and dissolved nutrient uptake. This study has shown that secondary crops, particularly banana shrimp, can play a stimulatory role in the bacterial processing of effluent nitrogen in eutrophic shrimp effluent treatment systems.

Develop added value uses of high anti-bacterial honey

Honey is valued for its medicinal properties. There interest from industry to develop a rapid method to detect the bioactivity of honey and also to develop value added products from high antibacterial honey.

Application of Mathematical Programming to the Plywood Design and Manufacturing Problem

Plywood manufacture includes two fundamental stages. The first is to peel or separate logs into veneer sheets of different thicknesses. The second is to assemble veneer sheets into finished plywood products. At the first stage a decision must be made as to the number of different veneer thicknesses to be peeled and what these thicknesses should be. At the second stage, choices must be made as to how these veneers will be assembled into final products to meet certain constraints while minimizing wood loss. These decisions present a fundamental management dilemma. Costs of peeling, drying, storage, handling, etc. can be reduced by decreasing the number of veneer thicknesses peeled. However, a reduced set of thickness options may make it infeasible to produce the variety of products demanded by the market or increase wood loss by requiring less efficient selection of thicknesses for assembly. In this paper the joint problem of veneer choice and plywood construction is formulated as a nonlinear integer programming problem. A relatively simple optimal solution procedure is developed that exploits special problem structure. This procedure is examined on data from a British Columbia plywood mill. Restricted to the existing set of veneer thicknesses and plywood designs used by that mill, the procedure generated a solution that reduced wood loss by 79 percent, thereby increasing net revenue by 6.86 percent. Additional experiments were performed that examined the consequences of changing the number of veneer thicknesses used. Extensions are discussed that permit the consideration of more than one wood species.