Extended memory lifetime in spiking neural networks employing memristive synapses with nonlinear conductance dynamics.

Spiking neural networks (SNNs) employing memristive synapses are capable of life-long online learning. Because of their ability to process and classify large amounts of data in real-time using compact and low-power electronic systems, they promise a substantial technology breakthrough. However, the critical issue that memristor-based SNNs have to face is the fundamental limitation in their memory capacity due to finite resolution of the synaptic elements, which leads to the replacement of old memories with new ones and to a finite memory lifetime. In this study we demonstrate that the nonlinear conductance dynamics of memristive devices can be exploited to improve the memory lifetime of a network. The network is simulated on the basis of a spiking neuron model of mixed-signal digital-analogue sub-threshold neuromorphic CMOS circuits, and on memristive synapse models derived from the experimental nonlinear conductance dynamics of resistive memory devices when stimulated by trains of identical pulses. The network learning circuits implement a spike-based plasticity rule compatible with both spike-timing and rate-based learning rules. In order to get an insight on the memory lifetime of the network, we analyse the learning dynamics in the context of a classical benchmark of neural network learning, that is hand-written digit classification. In the proposed architecture, the memory lifetime and the performance of the network are improved for memristive synapses with nonlinear dynamics with respect to linear synapses with similar resolution. These results demonstrate the importance of following holistic approaches that combine the study of theoretical learning models with the development of neuromorphic CMOS SNNs with memristive devices used to implement life-long on-chip learning.

Toxic hazards of ammonia release and population vulnerability assessment using geographical information system.

Today, chemical industries manufacture, store and transport evermore hazardous substances and hence the risk of accidental releases of these chemicals can become more and more catastrophic in the context of increasing population and their requirements. The damage potential is proportional to the population characteristics of the location as well as various meteorological factors and geographical features. For the risk assessment of ammonia toxicity, the storage facility at Eloor industrial area is taken as a sample. Pollutant dispersion model - Areal Locations of Hazardous Atmosphere (ALOHA) is utilized to predict the toxicity impacted distance of ammonia. The model estimates the vulnerable areas, which may be affected toxically by an Ammonia release by integrating information about chemical properties of the substance, weather conditions prevalent in the area and release conditions. Risk assessment is done for four different atmospheric conditions, typical to the prevailing seasons and affected area is estimated in each scenario. To determine the affected population, the areal interpolation method in GIS database is also employed in this study, which illustrates the toxically impacted areas and the population in need of immediate help and evacuation. Such studies can serve as an effective tool for decision makers to prepare an emergency plan in case of accidental releases.

Capillary microextraction: A new method for sampling methamphetamine vapour.

Clandestine laboratories pose a serious health risk to first responders, investigators, decontamination companies, and the public who may be inadvertently exposed to methamphetamine and other chemicals used in its manufacture. Therefore there is an urgent need for reliable methods to detect and measure methamphetamine at such sites. The most common method for determining methamphetamine contamination at former clandestine laboratory sites is selected surface wipe sampling, followed by analysis with gas chromatography-mass spectrometry (GC-MS). We are investigating the use of sampling for methamphetamine vapour to complement such wipe sampling. In this study, we report the use of capillary microextraction (CME) devices for sampling airborne methamphetamine, and compare their sampling efficiency with a previously reported dynamic SPME method. The CME devices consisted of PDMS-coated glass filter strips inside a glass tube. The devices were used to dynamically sample methamphetamine vapour in the range of 0.42-4.2µgm-3, generated by a custom-built vapour dosing system, for 1-15min, and methamphetamine was analysed using a GC-MS fitted with a ChromatoProbe thermal desorption unit. The devices showed good reproducibility (RSD<15%), and a curvilinear pre-equilibrium relationship between sampling times and peak area, which can be utilised for calibration. Under identical sampling conditions, the CME devices were approximately 30 times more sensitive than the dynamic SPME method. The CME devices could be stored for up to 3days after sampling prior to analysis. Consecutive sampling of methamphetamine and its isotopic substitute, d-9 methamphetamine showed no competitive displacement. This suggests that CME devices, pre-loaded with an internal standard, could be a feasible method for sampling airborne methamphetamine at former clandestine laboratories.

Spatial changes of estuary in Ernakulam district, Southern India for last seven decades, using multi-temporal satellite data.

The study area, located in the western side of Kerala State, South India, is a part of Vembanad-Kol wetlands - the largest estuary in India's western coastal wetland system and one of the Ramsar Sites of Kerala. Major portion of this estuary comes under the Ernakulam district which includes the Cochin City - the business and Industrial hub of Kerala, which has seen fast urbanization since independence (1947). Recently, this region is subjected to a characteristic fast urban sprawl, whereas, the estuarine zone is subjected to tremendous land use/land cover changes (LULC). Periodic monitoring of the estuary is essential for the formulation of viable management options for the sustainable utilization of this vital environmental resource. Remote sensing coupled with GIS applications has proved to be a useful tool in monitoring wetland changes. In the present study, the changes this estuarine region have undergone from 1944 to 2009 have been monitored with the help of multi-temporal satellite data. Estuarine areas were mapped with the help of Landsat MSS (1973), Landsat ETM (1990) and IRS LISS-III (1998 and 2009) using visual interpretation and digitization techniques in ArcGIS 9.3 Environment. The study shows a progressive decrease in the estuarine area, the reasons of which are identified chronologically.