Tonically Active Kainate Receptors (tKARs) : A Novel Mechanism Regulating Neuronal Function in the Brain

Fast excitatory transmission between neurons in the central nervous system is mainly mediated by L-glutamate acting on ligand gated (ionotropic) receptors. These are further categorized according to their pharmacological properties to AMPA (2-amino-3-(5-methyl-3-oxo-1,2- oxazol-4-yl)propanoic acid), NMDA (N-Methyl-D-aspartic acid) and kainate (KAR) subclasses. In the rat and the mouse hippocampus, development of glutamatergic transmission is most dynamic during the first postnatal weeks. This coincides with the declining developmental expression of the GluK1 subunit-containing KARs. However, the function of KARs during early development of the brain is poorly understood. The present study reveals novel types of tonically active KARs (hereafter referred to as tKARs) which play a central role in functional development of the hippocampal CA3-CA1 network. The study shows for the first time how concomitant pre- and postsynaptic KAR function contributes to development of CA3-CA1 circuitry by regulating transmitter release and interneuron excitability. Moreover, the tKAR-dependent regulation of transmitter release provides a novel mechanism for silencing and unsilencing early synapses and thus shaping the early synaptic connectivity. The role of GluK1-containing KARs was studied in area CA3 of the neonatal hippocampus. The data demonstrate that presynaptic KARs in excitatory synapses to both pyramidal cells and interneurons are tonically activated by ambient glutamate and that they regulate glutamate release differentially, depending on target cell type. At synapses to pyramidal cells these tKARs inhibit glutamate release in a G-protein dependent manner but in contrast, at synapses to interneurons, tKARs facilitate glutamate release. On the network level these mechanisms act together upregulating activity of GABAergic microcircuits and promoting endogenous hippocampal network oscillations. By virtue of this, tKARs are likely to have an instrumental role in the functional development of the hippocampal circuitry. The next step was to investigate the role of GluK1 -containing receptors in the regulation of interneuron excitability. The spontaneous firing of interneurons in the CA3 stratum lucidum is markedly decreased during development. The shift involves tKARs that inhibit medium-duration afterhyperpolarization (mAHP) in these neurons during the first postnatal week. This promotes burst spiking of interneurons and thereby increases GABAergic activity in the network synergistically with the tKAR-mediated facilitation of their excitatory drive. During development the amplitude of evoked medium afterhyperpolarizing current (ImAHP) is dramatically increased due to decoupling tKAR activation and ImAHP modulation. These changes take place at the same time when the endogeneous network oscillations disappear. These tKAR-driven mechanisms in the CA3 area regulate both GABAergic and glutamatergic transmission and thus gate the feedforward excitatory drive to the area CA1. Here presynaptic tKARs to CA1 pyramidal cells suppress glutamate release and enable strong facilitation in response to high-frequency input. Therefore, CA1 synapses are finely tuned to high-frequency transmission; an activity pattern that is common in neonatal CA3-CA1 circuitry both in vivo and in vitro. The tKAR-regulated release probability acts as a novel presynaptic silencing mechanism that can be unsilenced in response to Hebbian activity. The present results shed new light on the mechanisms modulating the early network activity that paves the way for oscillations lying behind cognitive tasks such as learning and memory. Kainate receptor antagonists are already being developed for therapeutic use for instance against pain and migraine. Because of these modulatory actions, tKARs also represent an attractive candidate for therapeutic treatment of developmentally related complications such as learning disabilities.

Peeking through the Iron Curtain: Memories of Watching Finnish Television in Estonia during Soviet Occupation

The present study analyses the memories of watching Finnish television in Estonia during the last decades of the Soviet occupation from the late 1960s until the beginning of 1990s. The study stems from a culturalist approach, perceiving television as a relevant aspect in the audiences’ everyday lives. It explores the significance of Finnish television on the society of occupied Estonia from the point of view of its historical audiences. The literature review concentrates on concepts such as the power of television, transnational media, historical audience reception and memory as an object of research. It also explains the concept of spillover, which refers to the unintentional bilateral flow of television signals from one country to another. Despite the numerous efforts of the Soviet authorities to prevent the viewing of the "bourgeois television", there still remained a small gap in the Iron Curtain. The study describes the phenomenon of watching Finnish television in Estonia. It provides understanding about the significance of watching Finnish television in Soviet Estonia through the experiences of its former audience. In addition, it explores what do people remember about watching Finnish television, and why. The empirical data was acquired from peoples’ personal memories through the analysis of private interviews and written responses during the period from February 2010 to February 2011. A total of 85 responses (5 interviews and 83 written responses) were analysed. The research employed the methods of oral history and memory studies. The main theoretical sources of the study include the works of Mati Graf and Heikki Roiko-Jokela, Hagi Šein, Sonia Livingstone, Janet Staiger and Emily Keightley. The study concludes that besides fulfilling the role of an entertainer and an informer, Finnish television enabled its Estonian audiences to gain entry into the imaginary world. Access to this imaginary world was so important, that the viewers engaged in illegal activities and gained special skills, whereby a phenomenon of "television tourism" developed. Most of the memories about Finnish television are vivid and similar. The latter indicates both the reliability and the collectiveness of such memories, which in return give shape to collective identities. Thus, for the Estonian viewers, the experience of watching Finnish television during the Soviet occupation has became part of their identity.

Two beam photoluminescence of PbS quantum dots in polyvinyl alcohol

We report the effect of dual beam excitation on the photoluminescence (PL) from PbS quantum dots in polyvinyl alcohol by using two excitation lasers, namely Ar+ (514.5 nm) and He-Ne laser (670 nm). Both sources of excitation gave similar PL spectra around 1.67 eV (related to shallow traps) and 1.1 eV (related to deep traps). When both lasers were used at the same time, we found that the PL induced by each of the lasers was partly quenched by the illumination of the other laser. The proposed mechanism of this quenching effect involves traps that are populated by one specific laser excitation, being photo-ionized by the presence of the other laser. Temperature, laser intensity and modulation frequency dependent quenching efficiencies are presented in this paper. This reversible modulation has potential for optical switching and memory device applications. (C) 2010 Elsevier B.V. All rights reserved.

Modified kinetic flux vector splitting (m-KFVS) method for compressible flows

To resolve many flow features accurately, like accurate capture of suction peak in subsonic flows and crisp shocks in flows with discontinuities, to minimise the loss in stagnation pressure in isentropic flows or even flow separation in viscous flows require an accurate and low dissipative numerical scheme. The first order kinetic flux vector splitting (KFVS) method has been found to be very robust but suffers from the problem of having much more numerical diffusion than required, resulting in inaccurate computation of the above flow features. However, numerical dissipation can be reduced by refining the grid or by using higher order kinetic schemes. In flows with strong shock waves, the higher order schemes require limiters, which reduce the local order of accuracy to first order, resulting in degradation of flow features in many cases. Further, these schemes require more points in the stencil and hence consume more computational time and memory. In this paper, we present a low dissipative modified KFVS (m-KFVS) method which leads to improved splitting of inviscid fluxes. The m-KFVS method captures the above flow features more accurately compared to first order KFVS and the results are comparable to second order accurate KFVS method, by still using the first order stencil. (C) 2011 Elsevier Ltd. All rights reserved.

A Real-time clustering system for spatio-temporal signals from network of neurons

Over past few years, the studies of cultured neuronal networks have opened up avenues for understanding the ion channels, receptor molecules, and synaptic plasticity that may form the basis of learning and memory. The hippocampal neurons from rats are dissociated and cultured on a surface containing a grid of 64 electrodes. The signals from these 64 electrodes are acquired using a fast data acquisition system MED64 (Alpha MED Sciences, Japan) at a sampling rate of 20 K samples with a precision of 16-bits per sample. A few minutes of acquired data runs in to a few hundreds of Mega Bytes. The data processing for the neural analysis is highly compute-intensive because the volume of data is huge. The major processing requirements are noise removal, pattern recovery, pattern matching, clustering and so on. In order to interface a neuronal colony to a physical world, these computations need to be performed in real-time. A single processor such as a desk top computer may not be adequate to meet this computational requirements. Parallel computing is a method used to satisfy the real-time computational requirements of a neuronal system that interacts with an external world while increasing the flexibility and scalability of the application. In this work, we developed a parallel neuronal system using a multi-node Digital Signal processing system. With 8 processors, the system is able to compute and map incoming signals segmented over a period of 200 ms in to an action in a trained cluster system in real time.

Region Based Structure Layout Optimization by Selective Data Copying

As the gap between processor and memory continues to grow Memory performance becomes a key performance bottleneck for many applications. Compilers therefore increasingly seek to modify an application’s data layout to improve cache locality and cache reuse. Whole program Structure Layout [WPSL] transformations can significantly increase the spatial locality of data and reduce the runtime of programs that use link-based data structures, by increasing the cache line utilization. However, in production compilers WPSL transformations do not realize the entire performance potential possible due to a number of factors. Structure layout decisions made on the basis of whole program aggregated affinity/hotness of structure fields, can be sub optimal for local code regions. WPSL is also restricted in applicability in production compilers for type unsafe languages like C/C++ due to the extensive legality checks and field sensitive pointer analysis required over the entire application. In order to overcome the issues associated with WPSL, we propose Region Based Structure Layout (RBSL) optimization framework, using selective data copying. We describe our RBSL framework, implemented in the production compiler for C/C++ on HP-UX IA-64. We show that acting in complement to the existing and mature WPSL transformation framework in our compiler, RBSL improves application performance in pointer intensive SPEC benchmarks ranging from 3% to 28% over WPSL

A Review of Photo-Induced Inter-Diffusion in Nano-Layered Chalcogenide Films

Abstract | A growing interest in the research of chalcogenide glasses can be currently witnessed, which to a large extent is caused by newly opened fields of applications for these materials. Applications in the field of micro- and opto-electronics, xerography and lithography, acousto-optic and memory switching devices and detectors for medical imaging seem to be most remarkable. Accordingly, photo induced phenomena in chalcogenide glasses are attracting much interest. These phenomena can be found both in uniform thin films as well as multilayered films. Among amorphous multilayers, chalcogenide multilayers are attractive because of the potential it has for tailoring the optical properties. I will be presenting some basic idea of photoinduced effects followed by the diffusion mechanisms of Se, Sb and Bi in to As2S3 films.

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.

Making STMs Cache Friendly with Compiler Transformations

Software transactional memory (STM) is a promising programming paradigm for shared memory multithreaded programs. In order for STMs to be adopted widely for performance critical software, understanding and improving the cache performance of applications running on STM becomes increasingly crucial, as the performance gap between processor and memory continues to grow. In this paper, we present the most detailed experimental evaluation to date, of the cache behavior of STM applications and quantify the impact of the different STM factors on the cache misses experienced by the applications. We find that STMs are not cache friendly, with the data cache stall cycles contributing to more than 50% of the execution cycles in a majority of the benchmarks. We find that on an average, misses occurring inside the STM account for 62% of total data cache miss latency cycles experienced by the applications and the cache performance is impacted adversely due to certain inherent characteristics of the STM itself. The above observations motivate us to propose a set of specific compiler transformations targeted at making the STMs cache friendly. We find that STM's fine grained and application unaware locking is a major contributor to its poor cache behavior. Hence we propose selective Lock Data co-location (LDC) and Redundant Lock Access Removal (RLAR) to address the lock access misses. We find that even transactions that are completely disjoint access parallel, suffer from costly coherence misses caused by the centralized global time stamp updates and hence we propose the Selective Per-Partition Time Stamp (SPTS) transformation to address this. We show that our transformations are effective in improving the cache behavior of STM applications by reducing the data cache miss latency by 20.15% to 37.14% and improving execution time by 18.32% to 33.12% in five of the 8 STAMP applications.

Spin-Valve-Like Magnetoresistance in Mn2NiGa at Room Temperature

Spin valves have revolutionized the field of magnetic recording and memory devices. Spin valves are generally realized in thin film heterostructures, where two ferromagnetic (FM) layers are separated by a nonmagnetic conducting layer. Here, we demonstrate spin-valve-like magnetoresistance at room temperature in a bulk ferrimagnetic material that exhibits a magnetic shape memory effect. The origin of this unexpected behavior in Mn2NiGa has been investigated by neutron diffraction, magnetization, and ab initio theoretical calculations. The refinement of the neutron diffraction pattern shows the presence of antisite disorder where about 13% of the Ga sites are occupied by Mn atoms. On the basis of the magnetic structure obtained from neutron diffraction and theoretical calculations, we establish that these antisite defects cause the formation of FM nanoclusters with parallel alignment of Mn spin moments in a Mn2NiGa bulk lattice that has antiparallel Mn spin moments. The direction of the Mn moments in the soft FM cluster reverses with the external magnetic field. This causes a rotation or tilt in the antiparallel Mn moments at the cluster-lattice interface resulting in the observed asymmetry in magnetoresistance.

Reuse, recycle to de-bloat software

Most Java programmers would agree that Java is a language that promotes a philosophy of “create and go forth”. By design, temporary objects are meant to be created on the heap, possibly used and then abandoned to be collected by the garbage collector. Excessive generation of temporary objects is termed “object churn” and is a form of software bloat that often leads to performance and memory problems. To mitigate this problem, many compiler optimizations aim at identifying objects that may be allocated on the stack. However, most such optimizations miss large opportunities for memory reuse when dealing with objects inside loops or when dealing with container objects. In this paper, we describe a novel algorithm that detects bloat caused by the creation of temporary container and String objects within a loop. Our analysis determines which objects created within a loop can be reused. Then we describe a source-to-source transformation that efficiently reuses such objects. Empirical evaluation indicates that our solution can reduce upto 40% of temporary object allocations in large programs, resulting in a performance improvement that can be as high as a 20% reduction in the run time, specifically when a program has a high churn rate or when the program is memory intensive and needs to run the GC often.

Mobile agent based TCP attacker identification in MANET using the traffic history (MAITH)

TCP attacks are the major problem faced by Mobile Ad hoc Networks (MANETs) due to its limited network and host resources. Attacker traceback is a promising solution which allows a victim to identify the exact location of the attacker and hence enables the victim to take proper countermeasure near attack origins, for forensics and to discourage attackers from launching the attacks. However, attacker traceback in MANET is a challenging problem due to dynamic network topology, limited network and host resources such as memory, bandwidth and battery life. We introduce a novel method of TCP attacker Identification in MANET using the Traffic History - MAITH. Based on the comprehensive evaluation based on simulations, we showed that MAITH can successfully track down the attacker under diverse mobile multi-hop network environment with low communication, computation, and memory overhead.

Investigation of the origin of glassiness in La0.5Sr0.5CoO3

A comprehensive magnetic study has been carried out on the two sets of La0.5Sr0.5CoO3 samples with a view to understand the origin of low temperature glassiness in the ferromagnetic state. The samples prepared by the conventional solid-state synthesis method show a low temperature shoulder in both dc magnetization as well as in the ac susceptibility measurements, which exhibit characteristics of glassiness such as the frequency dependence and memory effect. These observations suggest the existence of a distinct low temperature cluster-glass like phase within dominant ferromagnetic phase. But, once the same sample is properly homogenized by repeated grinding and annealing process, the low temperature glassy phase disappears, and it shows a pure ferromagnetic behavior. Our comparative study clearly reveals that the reentrant spin-glass like nature is not intrinsic to La0.5Sr0.5CoO3 system, in fact this is an outcome of the compositional inhomogeneity.

In vitro Evidence that an Aqueous Extract of Centella asiatica Modulates alpha-Synuclein Aggregation Dynamics

alpha-Synuclein aggregation is one of the major etiological factors implicated in Parkinson's disease (PD). The prevention of aggregation of alpha-synuclein is a potential therapeutic intervention for preventing PD. The discovery of natural products as alternative drugs to treat PD and related disorders is a current trend. The aqueous extract of Centella asiatica (CA) is traditionally used as a brain tonic and CA is known to improve cognition and memory. There are limited data on the role of CA in modulating amyloid-beta (A beta) levels in the brain and in A beta aggregation. Our study focuses on CA as a modulator of the alpha-synuclein aggregation pattern in vitro. Our investigation is focused on: (i) whether the CA leaf aqueous extract prevents the formation of aggregates from monomers (Phase I: alpha-synuclein + extract co-incubation); (ii) whether the CA aqueous extract prevents the formation of fibrils from oligomers (Phase II: extract added after oligomers formation); and (iii) whether the CA aqueous extract disintegrates the pre-formed fibrils (Phase III: extract added to mature fibrils and incubated for 9 days). The aggregation kinetics are studied using a thioflavin-T assay, circular dichroism, and transmission electron microscopy. The results showed that the CA aqueous extract completely inhibited the alpha-synuclein aggregation from monomers. Further, CA extract significantly inhibited the formation of oligomer to aggregates and favored the disintegration of the preformed fibrils. The study provides an insight in finding new natural products for future PD therapeutics.

RAPID HUMAN ACTION RECOGNITION IN H.264/AVC COMPRESSED DOMAIN FOR VIDEO SURVEILLANCE

This paper discusses a novel high-speed approach for human action recognition in H. 264/AVC compressed domain. The proposed algorithm utilizes cues from quantization parameters and motion vectors extracted from the compressed video sequence for feature extraction and further classification using Support Vector Machines (SVM). The ultimate goal of our work is to portray a much faster algorithm than pixel domain counterparts, with comparable accuracy, utilizing only the sparse information from compressed video. Partial decoding rules out the complexity of full decoding, and minimizes computational load and memory usage, which can effect in reduced hardware utilization and fast recognition results. The proposed approach can handle illumination changes, scale, and appearance variations, and is robust in outdoor as well as indoor testing scenarios. We have tested our method on two benchmark action datasets and achieved more than 85% accuracy. The proposed algorithm classifies actions with speed (>2000 fps) approximately 100 times more than existing state-of-the-art pixel-domain algorithms.