The Cannabinoid-Memory and the Angiotensin-Memory Paradoxes: Another Penrose Triangle?

This study aims to evaluate the efficacy of two different drugs in their effects on memory and discrimination learning in a dual, controlled mouse model of amnesia, and to relate the findings to their pharmacokinetic and pharmacodynamics profiles. It also aims at validating a sub-acute scopolamine dose protocol as a model of rodent amnesia, specifically of emotional memory.The Exteroceptive models used include a Y-maze and an Elevated plus Maze (EPM). The Interoceptive models used are two different dose protocols of an amnesic drug, Scopolamine in forty-eight Swiss Albino mice, categorized into an acute and a sub-acute induction division, each of which later received fixed human equivalent doses of two drugs, apart from saline and scopolamine. Each animal was then evaluated for their Novelty Object Recognition (NOR) memory, and visuo-spatial memory, on the Y-maze and the EPM, respectively. The results of the Novelty Preference Test (NPT) and EPM test were analysed using Analysis of Variance.The efficacy of Rimonabant in improving NOR memory was statistically higher than in saline and model control groups, more so in the acute induction. Its efficacy in enhancing visuo-spatial memory was less, although comparable to that on NOR memory.  The efficacy of Valsartan was lower than the NOR Recognition Indices of other groups, although insignificant statistically. Sub-acute induction resulted in increased amnesia and anxiety in the Valsartan group on both mazes, the former being comparable to that noted in scopolamine group.Rimonabant is a memory enhancer, in terms of both recognition and spatial memory. Valsartan is a pro-amnesic drug in a sub-acute induction, in which it lead to increased anxiety additionally. Hence, sub acute scopolamine protocol could be a novel model of emotional memory. Though many drawbacks were noted in the study, the drug effects could be explained by pharmacokinetic data and pharmacodynamic effects. This pilot study could be used for correlating the results in human conditions involving memory

Towards a highly scalable network tester

High end networked-systems have quickly climbed from a throughput of gigabits/sec to terabits/sec, and are approaching petabits/sec. Alas, network testing equipment has not scaled: it remained either low throughput or extremely expensive. With suitable network testing equipment either not at scale or too expensive even for commercial vendors, systems may be released without proper testing and validation. We propose a methodology for large scale testing of networked systems, based on using a low-cost open source network tester and a commodity switch. Our approach is scalable, open source, and accurate, and can be adapted to a variety of networking equipment, widely available to users.1. Leverhulme Trust Early Career Fellowship ECF-2016-289, 2. (EPSRC) EARL: sdn EnAbled MeasuRement for alL project (Project Reference EP/P025374/1)

DRY SLIDING WEAR BEHAVIOR OF DIFFUSION BONDED AZ-91 MAGNESIUM ALLOY REINFORCED WITH SIC PARTICLES

Magnesium composites reinforced with 2, 4, 6 Wt.% of silicon carbide particles at different particle size of 10, 25 and 45 mm was synthesized using diffusion bonding process. Further the samples for scanning electron microscopic analysis and tribological analysis were made from the composites. Dry sliding wear test was carried out with L27 orthogonal design array on pin on disc tribometer. Mass loss of the pins was measured and wear rate was calculated. A statistical analysis was performed with the measured wear rate, the optimal parameter combination level was identified with main effect plot. From ANOVA analysis the significant parameters was identified

An ε -Uniform Numerical Method for a System of Convection-Diffusion Equations with Discontinuous Convection Coefficients and Source Terms

In this paper, a parameter-uniform numerical method is suggested to solve a system of singularly perturbed convection-diffusion equations with discontinuous convection coefficients and source terms subject to the Dirichlet boundary condition. The second derivative of each equation is multiplied by a distinctly small parameter, which leads to an overlap and interacting interior layer. A numerical method based on a piecewise uniform Shishkin mesh is constructed. Numerical results are presented to support the theoretical results

AN INITIAL VALUE TECHNIQUE FOR SINGULARLY PERTURBED REACTION-DIFFUSION PROBLEMS WITH A NEGATIVE SHIFT

Abstract. In this paper, a numerical method named as Initial Value Technique (IVT) is suggested to solve singularly perturbed boundary value problems for second order ordinary differential equations of reactiondiffusion type with a delay (negative shift). In this technique, the original problem of solving the second order differential equation is reduced to solving four first order singularly perturbed differential equations without delay and one algebraic equation with a delay. The singularly perturbed problems are solved by a second order hybrid finite difference scheme. An error estimate is derived by using supremum norm and it is of order O(ε + N −2 ln 2 N ), where N is a discretization parameter and ε is the perturbation parameter. Numerical results are provided to illustrate the theoretical results

RESISTIVITY STEPS AS A PRECURSOR AND IMPENDING EARTHQUAKES OF AFTERSHOCKS OF GREAT EARTHQUAKE OF 26 TH DECEMBER 2004 RECORDED AT IDUKKI OBSERVATARY, KERALA, INDIA

ABSTARCT The study of resistivity relaxation before the impending earthquake events occurred during January-February 2005 in the Andaman-Sumatra subduction zone have proven the existence of the long range effects of strain related precursors, fortuitously recorded by the Variometer designed to reflect the premonitory rupture in Kottayam, Kerala, India at epicentral distances greater than 2000km. The swarms of the aftershock of Great earthquake of 2004 supplied sources of seismic waves that have been subsequently scattered, polarized and lead to the process of birefringence through the anisotropic rocks. The average values of earthquake magnitudes (M5.3), epicentral distances (1941km), radius of preparation zones (281km) and focal depths (23km) are calculated from the regression equations evolved from the bivariate plots. The abnormal increase of crustal strain even for a lower earthquake of M5.3 which has definitive radius of the preparation zone of 240km to an ultimate radius of more than 5400km from epicenters to observatory is discussed. Keyword: earthquake, precursor, resistivity, magnitude, Idukki. INTRODUCTION The rock deformation allows the accumulation of stress energy, before the large earthquake and continued until stress energy was released by faulting at the time of earthquake The stress energy accumulated is released within the short span of time before the main shocks could be useful as precursor signals of an impending earthquak

Gratings and waveguides

Our immediate objective is to understand the limitations of guided-wave and grating coupler devices in their application to optical data storage. Our long-range goal is to develop and validate design codes for integrated optic devices. The principal research activity was in the development of numerical models for the design of a blue wavelength integrated optical source for data storage applications

Graphdti: A Robust Deep Learning Predictor Of Drug-Target Interactions From Multiple Heterogeneous Data

Traditional techniqueset identification, we developed GraphDTI, a robust machine learning framework integrating the molecular-level information on drugs, proteins, and binding sites with the system-level information on gene expression and protein-protein interactions. In order to properly evaluate the performance of GraphDTI, we compiled a high-quality benchmarking dataset and devised a new cluster-based cross-validation p to identify macromolecular targets for drugs utilize solely the information on a query drug and a putative target. Nonetheless, the mechanisms of action of many drugs depend not only on their binding affinity toward a single protein, but also on the signal transduction through cascades of molecular interactions leading to certain phenotypes. Although using protein-protein interaction networks and drug-perturbed gene expression profiles can facilitate system-level investigations of drug-target interactions, utilizing such large and heterogeneous data poses notable challenges. To improve the state-of-the-art in drug targrotocol. Encouragingly, GraphDTI not only yields an AUC of 0.996 against the validation dataset, but it also generalizes well to unseen data with an AUC of 0.939, significantly outperforming other predictors. Finally, selected examples of identified drug-target interactions are validated against the biomedical literature. Numerous applications of GraphDTI include the investigation of drug polypharmacological effects, side effects through off-target binding, and repositioning opportunities