Immunomodulation using agonists and antagonists: potential clinical applications

Introduction: Extensive studies have gone into understanding the differential role of the innate and adaptive arms of the immune system in the context of various diseases. Receptor-ligand interactions are responsible for mediating cross-talk between the innate and adaptive arms of the immune system, so as to effectively counter the pathogenic challenge. While TLRs remain the best studied innate immune receptor, many other receptor families are now coming to the fore for their role in various pathologies. Research has focused on the discovery of novel agonists and antagonists for these receptors as potential therapeutics. Areas covered: In this review, we present an overview of the recent advances in the discovery of drugs targeting important receptors such as G-protein coupled receptors, TRAIL-R, IL-1 beta receptor, PPARs, etc. All these receptors play a critical role in the modulation of the immune response. We focus on the recent paradigms applied for the generation of specific and effective therapeutics for these receptors and their status in clinical trials. Expert opinion: Non-specific activation by antagonist/agonist is a difficult problem to dodge. This demands innovation in ligand designing with the use of strategies such as allosterism and dual-specific ligands. Rigorous preclinical and clinical studies are required in transforming a compound to a therapeutic.

Fast Robust Pattern Classification Algorithms for Real Time Neuro-Motor Prosthetic Applications

In this paper, we give a brief review of pattern classification algorithms based on discriminant analysis. We then apply these algorithms to classify movement direction based on multivariate local field potentials recorded from a microelectrode array in the primary motor cortex of a monkey performing a reaching task. We obtain prediction accuracies between 55% and 90% using different methods which are significantly above the chance level of 12.5%.

A novel free floating accelerometer force balance system for shock tunnel applications

In order to overcome the interference of the model mounting system with the external aerodynamics of the body during shock tunnel testing, a new free floating internally mountable balance system that ensures unrestrained model motion during testing has been designed, fabricated and tested. Minimal friction ball bearings are used for ensuring the free floating condition of the model during tunnel testing. The drag force acting on a blunt leading edge flat plate at hypersonic Mach number has been measured using the new balance system. Finite element model (FEM) and CFD are exhaustively used in the design as well as for calibrating the new balance system. The experimentally measured drag force on the blunt leading edge flat plate at stagnation enthalpy of 0.7 and 1.2 MJ/kg and nominal Mach number of 5.75 matches well with FEM results. The concept can also be extended for measuring all the three fundamental aerodynamic forces in short duration test facilities like free piston driven shock tunnels.

Reinforcement learning applications in dynamic pricing of retail markets

In this paper, we investigate the use of reinforcement learning (RL) techniques to the problem of determining dynamic prices in an electronic retail market. As representative models, we consider a single seller market and a two seller market, and formulate the dynamic pricing problem in a setting that easily generalizes to markets with more than two sellers. We first formulate the single seller dynamic pricing problem in the RL framework and solve the problem using the Q-learning algorithm through simulation. Next we model the two seller dynamic pricing problem as a Markovian game and formulate the problem in the RL framework. We solve this problem using actor-critic algorithms through simulation. We believe our approach to solving these problems is a promising way of setting dynamic prices in multi-agent environments. We illustrate the methodology with two illustrative examples of typical retail markets.

Enhancing Speedup in Network Processing Applications by Exploiting Instruction Reuse with Flow Aggregation

Instruction reuse is a microarchitectural technique that improves the execution time of a program by removing redundant computations at run-time. Although this is the job of an optimizing compiler, they do not succeed many a time due to limited knowledge of run-time data. In this paper we examine instruction reuse of integer ALU and load instructions in network processing applications. Specifically, this paper attempts to answer the following questions: (1) How much of instruction reuse is inherent in network processing applications?, (2) Can reuse be improved by reducing interference in the reuse buffer?, (3) What characteristics of network applications can be exploited to improve reuse?, and (4) What is the effect of reuse on resource contention and memory accesses? We propose an aggregation scheme that combines the high-level concept of network traffic i.e. "flows" with a low level microarchitectural feature of programs i.e. repetition of instructions and data along with an architecture that exploits temporal locality in incoming packet data to improve reuse. We find that for the benchmarks considered, 1% to 50% of instructions are reused while the speedup achieved varies between 1% and 24%. As a side effect, instruction reuse reduces memory traffic and can therefore be considered as a scheme for low power.

Biocorrosion in industrial applications

Industrial situations afflicted by corrosion induced by microorganisms are illustrated with examples. The types and characteristics of microorganisms involved in biocorrosion processes are discussed. Possible mechanisms in biocorrosion as occurring under sub-soil, sea water and fresh water conditions are analyzed. Methods to combat biocorrosion are also outlined.

Session 6 grouting and deep mixing: New concept and applications

The theme of the session is the New Concept and Applications both for the grouting and deep mixing technologies. Nineteen papers were submitted to this session, and those covered a variety of topics; 1) New concepts and development, 2) Refinement of techniques, and 3) analysis and applications. Eight papers out of them were presented orally.

Non-Thermal Plasma Applications at Very Low Temperature

Application of non-thermal plasma for gas cleaning is gaining prominence in the recent years. Normally, the gas treatment was carried out at or above room temperature, by the dry type plasma reactor. However, this treatment is still inadequate in the removal of certain stable gases present in the flue gas mixture. We propose the non-thermal plasma process at very low temperature, and report here some interesting results of treatment of NO or N2O with pulsed plasma below — 100°C ambient temperature. Direct methanol synthesis from CH4 and CO2 at very low temperature is also reported. A comparative analysis of the various tests are presented together with a note on the energy consideration

Non-thermal plasma applications at Very Low Temperature

Application of non-thermal plasma for gas cleaning is gaining prominence in the recent years. Normally, the gas treatment was carried out at or above room temperature, by the dry type plasma reactor. However, this treatment is still inadequate in the removal of certain stable gases present in the flue gas mixture. We propose the non-thermal plasma process at very low temperature, and report here some interesting results of treatment of NO or N2O with pulsed plasma below — 100°C ambient temperature. Direct methanol synthesis from CH4 and CO2 at very low temperature is also reported. A comparative analysis of the various tests are presented together with a note on the energy consideration

Optimal static voltage stability improvement using a numerically stable SLP algorithm, for real time applications

A numerically stable sequential Primal–Dual LP algorithm for the reactive power optimisation (RPO) is presented in this article. The algorithm minimises the voltage stability index C 2 [1] of all the load buses to improve the system static voltage stability. Real time requirements such as numerical stability, identification of the most effective subset of controllers for curtailing the number of controllers and their movement can be handled effectively by the proposed algorithm. The algorithm has a natural characteristic of selecting the most effective subset of controllers (and hence curtailing insignificant controllers) for improving the objective. Comparison with transmission loss minimisation objective indicates that the most effective subset of controllers and their solution identified by the static voltage stability improvement objective is not the same as that of the transmission loss minimisation objective. The proposed algorithm is suitable for real time application for the improvement of the system static voltage stability.

Acenaphtho[1,2-b]quinoxaline based low band gap copolymers for organic thin film transistor applications

We report the synthesis of a novel class of low band gap copolymers based on anacenaphtho[1,2-b]quinoxaline core and oligothiophene derivatives acting as the acceptor and the donor moieties, respectively. The optical properties of the copolymers were characterized by ultraviolet-visible spectroscopy while the electrochemical properties were determined by cyclic voltammetry. The band gap of these polymers was found to be in the range 1.8-2.0 eV as calculated from the optical absorption band edge. X-ray diffraction measurements show weak pi-pi stacking interactions between the polymer chains. The hole mobility of the copolymers was evaluated using field-effect transistor measurements yielding values in the range 10(-5)-10(-3) cm(2)/Vs.

Measurement and Applications of Long-Range Heteronuclear Scalar Couplings: Recent Experimental and Theoretical Developments

The use of long-range heteronuclear couplings, in association with 1H1H scalar couplings and NOE restraints, has acquired growing importance for the determination of the relative stereochemistry, and structural and conformational information of organic and biological molecules. However, the routine use of such couplings is hindered by the inherent difficulties in their measurement. Prior to the advancement in experimental techniques, both long-range homo- and heteronuclear scalar couplings were not easily accessible, especially for very large molecules. The development of a large number of multidimensional NMR experimental methodologies has alleviated the complications associated with the measurement of couplings of smaller strengths. Subsequent application of these methods and the utilization of determined J-couplings for structure calculations have revolutionized this area of research. Problems in organic, inorganic and biophysical chemistry have also been solved by utilizing the short- and long-range heteronuclear couplings. In this minireview, we discuss the advantages and limitations of a number of experimental techniques reported in recent times for the measurement of long-range heteronuclear couplings and a few selected applications of such couplings. This includes the study of medium- to larger-sized molecules in a variety of applications, especially in the study of hydrogen bonding in biological systems. The utilization of these couplings in conjunction with theoretical calculations to arrive at conclusions on the hyperconjugation, configurational analysis and the effect of the electronegativity of the substituents is also discussed.