Optimal Blood Glucose Regulation using Single Network Adaptive Critics

Diabetes is a serious disease during which the body's production and use of insulin is impaired, causing glucose concentration level toincrease in the bloodstream. Regulating blood glucose levels as close to normal as possible, leads to a substantial decrease in long term complications of diabetes. In this paper, an intelligent neural network on-line optimal feedback treatment strategy based on nonlinear optimal control theory is presented for the disease using subcutaneous treatment strategy. A simple mathematical model of the nonlinear dynamics of glucose and insulin interaction in the blood system is considered based on the Bergman's minimal model. A glucose infusion term representing the effect of glucose intake resulting from a meal is introduced into the model equations. The efficiency of the proposed controllers is shown taking random parameters and random initial conditions in presence of physical disturbances like food intake. A comparison study with linear quadratic regulator theory brings Out the advantages of the nonlinear control synthesis approach. Simulation results show that unlike linear optimal control, the proposed on-line continuous infusion strategy never leads to severe hypoglycemia problems.

Optimal blood glucose regulation of diabetic patients using single network adaptive critics

Diabetes is a long-term disease during which the body's production and use of insulin are impaired, causing glucose concentration level to increase in the bloodstream. Regulating blood glucose levels as close to normal as possible leads to a substantial decrease in long-term complications of diabetes. In this paper, an intelligent online feedback-treatment strategy is presented for the control of blood glucose levels in diabetic patients using single network adaptive critic (SNAC) neural networks (which is based on nonlinear optimal control theory). A recently developed mathematical model of the nonlinear dynamics of glucose and insulin interaction in the blood system has been revised and considered for synthesizing the neural network for feedback control. The idea is to replicate the function of pancreatic insulin, i.e. to have a fairly continuous measurement of blood glucose and a situation-dependent insulin injection to the body using an external device. Detailed studies are carried out to analyze the effectiveness of this adaptive critic-based feedback medication strategy. A comparison study with linear quadratic regulator (LQR) theory shows that the proposed nonlinear approach offers some important advantages such as quicker response, avoidance of hypoglycemia problems, etc. Robustness of the proposed approach is also demonstrated from a large number of simulations considering random initial conditions and parametric uncertainties. Copyright (C) 2009 John Wiley & Sons, Ltd.

Design of a manual press for the production of compacted stabilized soil blocks

In this paper, we discuss the design of a manually operated soil compaction machine that is being used to manufacture stabilized soil blocks (SSB). A case study of manufacturing more than three million blocks in a housing project using manually operated machines is illustrated. The paper is focussed on the design, development, and evaluation of a manually operated soil compaction machine for the production of SSB. It also details the machine design philosophy, compaction characteristics of soils, employment generation potential of small-scale stabilized soil block productions systems, and embodied energy. Static compaction of partially saturated soils was performed to generate force-displacement curves in a confined compaction process were generated. Based on the soil compaction data engineering design aspects of a toggle press are illustrated. The results of time and motion study on block production operations using manual machines are discussed. Critical path network diagrams were used for small-scale SSB production systems. Such production systems generate employment at a very low capital cost.

A new load distribution strategy for linear network with communication delays

In this paper, we propose a new load distribution strategy called `send-and-receive' for scheduling divisible loads, in a linear network of processors with communication delay. This strategy is designed to optimally utilize the network resources and thereby minimizes the processing time of entire processing load. A closed-form expression for optimal size of load fractions and processing time are derived when the processing load originates at processor located in boundary and interior of the network. A condition on processor and link speed is also derived to ensure that the processors are continuously engaged in load distributions. This paper also presents a parallel implementation of `digital watermarking problem' on a personal computer-based Pentium Linear Network (PLN) topology. Experiments are carried out to study the performance of the proposed strategy and results are compared with other strategies found in literature.

A Network Model of Static Foam Drainage

On the basis of a more realistic tetrakaidecahedral structure of foam bubbles, a network model of static foam drainage has been developed. The model considers the foam to be made up of films and Plateau borders. The films drain into the adjacent Plateau borders, which in turn form a network through which the liquid moves from the foam to the liquid pool. From the structure, a unit flow cell was found, which constitutes the foam when stacked together both horizontally and vertically. Symmetry in the unit flow cell indicates that the flow analysis of a part of it can be employed to obtain the drainage for the whole foam. Material balance equations have been written for each segment of this subsection, ensuring connectivity, and solved with the appropriate boundary and initial conditions. The calculated rates of drainage, when compared with the available experimental results, indicate that the model predicts the experimental results well.

An Efficient Load Distribution Strategy for a Distributed Linear Network of Processors with Communication Delays

In this paper, we present an improved load distribution strategy, for arbitrarily divisible processing loads, to minimize the processing time in a distributed linear network of communicating processors by an efficient utilization of their front-ends. Closed-form solutions are derived, with the processing load originating at the boundary and at the interior of the network, under some important conditions on the arrangement of processors and links in the network. Asymptotic analysis is carried out to explore the ultimate performance limits of such networks. Two important theorems are stated regarding the optimal load sequence and the optimal load origination point. Comparative study of this new strategy with an earlier strategy is also presented.

Fault-tolerant characteristics and topological properties of a hierarchical network of hypercubes

We analyse the fault-tolerant parameters and topological properties of a hierarchical network of hypercubes. We take a close look at the Extended Hypercube (EH) and the Hyperweave (HW) architectures and also compare them with other popular architectures. These two architectures have low diameter and constant degree of connectivity making it possible to expand these networks without affecting the existing configuration. A scheme for incrementally expanding this network is also presented. We also look at the performance of the ASCEND/DESCEND class of algorithms on these architectures.

A comparative social network analysis of wasp colonies and classrooms: Linking network structure to functioning

A major question in current network science is how to understand the relationship between structure and functioning of real networks. Here we present a comparative network analysis of 48 wasp and 36 human social networks. We have compared the centralisation and small world character of these interaction networks and have studied how these properties change over time. We compared the interaction networks of (1) two congeneric wasp species (Ropalidia marginata and Ropalidia cyathiformis), (2) the queen-right (with the queen) and queen-less (without the queen) networks of wasps, (3) the four network types obtained by combining (1) and (2) above, and (4) wasp networks with the social networks of children in 36 classrooms. We have found perfect (100%) centralisation in a queen-less wasp colony and nearly perfect centralisation in several other queen-less wasp colonies. Note that the perfectly centralised interaction network is quite unique in the literature of real-world networks. Differences between the interaction networks of the two wasp species are smaller than differences between the networks describing their different colony conditions. Also, the differences between different colony conditions are larger than the differences between wasp and children networks. For example, the structure of queen-right R. marginata colonies is more similar to children social networks than to that of their queen-less colonies. We conclude that network architecture depends more on the functioning of the particular community than on taxonomic differences (either between two wasp species or between wasps and humans).

N-acetyl cysteine enhances imatinib-induced apoptosis of Bcr-Abl(+) cells by endothelial nitric oxide synthase-mediated production of nitric oxide

Imatinib, a small-molecule inhibitor of the Bcr-Abl kinase, is a successful drug for treating chronic myeloid leukemia (CML). Bcr-Abl kinase stimulates the production of H2O2, which in turn activates Abl kinase. We therefore evaluated whether N-acetyl cysteine (NAC), a ROS scavenger improves imatinib efficacy. Effects of imatinib and NAC either alone or in combination were assessed on Bcr-Abl(+) cells to measure apoptosis. Role of nitric oxide (NO) in NAC-induced enhanced cytotoxicity was assessed using pharmacological inhibitors and siRNAs of nitric oxide synthase isoforms. We report that imatinib-induced apoptosis of imatinib-resistant and imatinib-sensitive Bcr-Abl(+) CML cell lines and primary cells from CML patients is significantly enhanced by co-treatment with NAC compared to imatinib treatment alone. In contrast, another ROS scavenger glutathione reversed imatinib-mediated killing. NAC-mediated enhanced killing correlated with cleavage of caspases, PARP and up-regulation and down regulation of pro- and anti-apoptotic family of proteins, respectively. Co-treatment with NAC leads to enhanced production of nitric oxide (NO) by endothelial nitric oxide synthase (eNOS). Involvement of eNOS dependent NO in NAC-mediated enhancement of imatinib-induced cell death was confirmed by nitric oxide synthase (NOS) specific pharmacological inhibitors and siRNAs. Indeed, NO donor sodium nitroprusside (SNP) also enhanced imatinib-mediated apoptosis of Bcr-Abl(+) cells. NAC enhances imatinib-induced apoptosis of Bcr-Abl(+) cells by endothelial nitric oxide synthase-mediated production of nitric oxide.

Immunization of male rabbits with sheep luteal receptor to LH results in production of antibodies exhibiting hormone-agonistic and -antagonistic activities

Antibodies to LH/chorionic gonadotrophin receptor (LH/CG-R; molecular weight 67 000), isolated in a homogenous state (established by SDS-PAGE and ligand blotting) from sheep luteal membrane using human CG (hCG)-Sepharose affinity chromatography, were raised in three adult male rabbits (R-I, R-II and R-III). Each of the rabbits received 20-30 mu g oi the purified receptor in Freund's complete adjuvant at a time. Primary immunization was followed by booster injection at intervals. Production of receptor antibodies was monitored by (1) determining the dilution of the serum (IgG fraction) that could specifically bind 50% of I-125-LH/CG-R added and (2) analysing sera for any chance in testosterone levels. Following primary immunization and the first booster, all three rabbits exhibited a 2.5- to 6.0-fold increase in serum testosterone over basal levels and this effect was spread over a period of time (similar to 40 days) coinciding with the rise and fall of receptor antibodies. The maximal antibody titre (ED(50)) produced at this time ranged from 1:350 to 1:100 to below detectable limits for R-I, R-II and R-III respectively. Subsequent immunizations followed by the second booster resulted in a substantial increase in antibody titre (ED(50) of 1:5000) in R-I, but this was not accompanied by any change in serum testosterone over preimmune levels, suggesting that with the progress of immunization the character of the antibody produced had also changed. Two pools of antisera from R-I collected 10 days following the booster (at day 70 (bleed I) and day 290 (bleed II)) were used in further experiments. IgG isolated from bleed I but not from bleed II antiserum showed a dose-dependent stimulation of testosterone production by mouse Leydig cells in vitro, thus confirming the in vivo hormone-mimicking activity antibodies generated during the early immunization phase. The IgG fractions from both bleeds were, however, capable of inhibiting (1) I-125-hCG binding to crude sheep luteal membrane (EC(50) of 1:70 and 1:350 for bleed I and II antisera respectively) and (2) ovine LH-stimulated testosterone production by mouse Leydig cells in vitro, indicating the presence oi antagonistic antibodies irrespective of the period of time during which the rabbits were immunized. The: fact that bleed I-stimulated testosterone production could be inhibited in a dose-dependent manner by the addition of IgG from bleed II to the mouse Leydig cell in vitro assay system showed that the agonistic activity is intrinsic to the bleed I antibody. The receptor antibody (bleed II) was also capable of blocking LH action in vivo, as rabbits passively (for 24 h with LH/CG-R antiserum) as well as actively (for 130 days) immunized against LH/CG-R failed to respond to a bolus injection of LH (50 mu g). At no time, however, was the serum testosterone reduced below the basal level. This study clearly shows that, unlike with LH antibody, attempts to achieve an LH deficiency effect in vivo by resorting to immunization with hole LH receptor is difficult, as receptor antibodies exhibit both hormone-mimicking (agonistic) as well as hormone-blocking (antagonistic) activities.

Defect production due to quenching through a multicritical point

We study the generation of defects when a quantum spin system is quenched through a multicritical point by changing a parameter of the Hamiltonian as t/tau, where tau is the characteristic timescale of quenching. We argue that when a quantum system is quenched across a multicritical point, the density of defects (n) in the final state is not necessarily given by the Kibble-Zurek scaling form n similar to 1/tau(d nu)/((z nu+1)), where d is the spatial dimension, and. and z are respectively the correlation length and dynamical exponent associated with the quantum critical point. We propose a generalized scaling form of the defect density given by n similar to 1/(tau d/(2z2)), where the exponent z(2) determines the behavior of the off-diagonal term of the 2 x 2 Landau-Zener matrix at the multicritical point. This scaling is valid not only at a multicritical point but also at an ordinary critical point.

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.

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.

Latency, Power and Performance Trade-offs in Network-on-Chips by Link Microarchitecture Exploration

This paper presents a power, latency and throughput trade-off study on NoCs by varying microarchitectural (e.g. pipelining) and circuit level (e.g. frequency and voltage) parameters. We change pipelining depth, operating frequency and supply voltage for 3 example NoCs - 16 node 2D Torus, Tree network and Reduced 2D Torus. We use an in-house NoC exploration framework capable of topology generation and comparison using parameterized models of Routers and links developed in SystemC. The framework utilizes interconnect power and delay models from a low-level modelling tool called Intacte[1]1. We find that increased pipelining can actually reduce latency. We also find that there exists an optimal degree of pipelining which is the most energy efficient in terms of minimizing energy-delay product.

On-Chip Clock Network Skew Measurement using Sub-Sampling

We present a technique for an all-digital on-chip delay measurement system to measure the skews in a clock distribution network. It uses the principle of sub-sampling. Measurements from a prototype fabricated in a 65 nm industrial process, indicate the ability to measure delays with a resolution of 0.5ps and a DNL of 1.2 ps.