Electrochemical detection and removal of lead in water using poly(propylene imine) modified re-compressed exfoliated graphite electrodes

Modification of exfoliated graphite (EG) electrode with generation 2 poly(propylene imine) dendrimer by electrodeposition resulted in an electrochemical sensor which was used to detect lead ions in water to a limit of 1 ppb and a linear response between 2.5 and 40 ppb using square wave anodic stripping voltammetry (SW-ASV). Pb(II) was also removed from spiked water sample using a 40-mm diameter unmodified EG electrode with an applied potential of -1,000 mV for 180 min. A removal efficiency of 99% was calculated from a 150 mL sample. The results obtained in both cases using SW-ASV, correlated with atomic absorption spectroscopy.

Wireless sensor networks forhuman intruder detection

In this paper we report on the outcomes of a research and demonstration project on human intrusion detection in a large secure space using an ad hoc wireless sensor network. This project has been a unique experience in collaborative research, involving ten investigators (with expertise in areas such as sensors, circuits, computer systems,communication and networking, signal processing and security) to execute a large funded project that spanned three to four years. In this paper we report on the specific engineering solution that was developed: the various architectural choices and the associated specific designs. In addition to developing a demonstrable system, the various problems that arose have given rise to a large amount of basic research in areas such as geographical packet routing, distributed statistical detection, sensors and associated circuits, a low power adaptive micro-radio, and power optimising embedded systems software. We provide an overview of the research results obtained.

In-situ formation of graphene-lead oxide composite and its use in trace arsenic detection

Reduced graphene oxide-lead dioxide composite is formed when EGO coated surface is electrochemically reduced along with lead ions in the solution. This composite has been shown to be an excellent material for low level detection of arsenic. Various functional groups present on EGO, in a wide pH range of 2-11, are responsible for the favorable interaction between metal ion and the modified electrode surface and subsequent trace level detection. X-ray photoelectron spectroscopy and Raman spectroscopic techniques confirm the formation of composite and its composition. Thin layer of lead dioxide along with reduced exfoliated graphene oxide has been shown to be responsible for the enhanced activity of the surface. The detection limit of arsenic is found to be 10 nM. This study opens up the possibility of using the composites for sensing applications and possibly simultaneous detection of arsenic and lead. (C) 2011 Elsevier B.V. All rights reserved.

Role of Spectral Studies in Detection of Antibacterial Phytoelements and Phytochemicals of Moringa oleifera

This paper reports, the Laser Induced Breakdown Spectroscopy (LIBS) studies and structure elucidation of compounds isolated from the fruit extract of Moringa oleifera and also deals with their possible effects on some bacterial strains viz. Staphylococcus aureus, Klebsiella pneumonia, Escherichia coli and Pseudomonas aeruginosa. The extract was found to be active against all four microorganisms used. Extent of inhibitory effect of extract was assessed at different concentrations of 25, 50, 75 mg/ml by measuring diameter of inhibition zone (DIZ). Our results clearly showed that the 75 mg/ml concentration of the extract had 14, 12 and 18 mm of the DIZ against Staphylococcus aureus, Klebsiella pneumonia and Pseudomonas aeruginosa and 14 mm with 50 mg/ml concentration against Escherichia coli. The results were compared with the standard antibiotic `ampicillin' of 1 mg/ml concentration. LIBS was recorded with high power pulsed laser beam from Nd: YAG Laser (Continuum Surelite III-10), focused on the surface of the material, which was in liquid form, to generate plasma on the surface of the sample. LIBS data clearly demonstrate the presence of trace elements, magnesium and iron, in high concentration in the extract. Whereas, from the phytochemical profile reveals the presence of two new compounds, S-ethyl-N-{4-[(alpha-L-rhamnosyloxy) benzyl]} thiocarbamate and 2-acetoxy {4-[(2',3',4'-tri-O-acetyl-alpha-L-rhamnosyloxy) benzyl]} acetonitrile as the major constituents. This study is the first report on synergetic effect of the phytoconstituents and certain set of elements present in their defined role in bacterial management against different bacterial strains.

Efficient Runtime Detection and Toleration of Asymmetric Races

We introduce ToleRace, a runtime system that allows programs to detect and even tolerate asymmetric data races. Asymmetric races are race conditions where one thread correctly acquires and releases a lock for a shared variable while another thread improperly accesses the same variable. ToleRace provides approximate isolation in the critical sections of lock-based parallel programs by creating a local copy of each shared variable when entering a critical section, operating on the local copies, and propagating the appropriate copies upon leaving the critical section. We start by characterizing all possible interleavings that can cause races and precisely describe the effect of ToleRace in each case. Then, we study the theoretical aspects of an oracle that knows exactly what type of interleaving has occurred. Finally, we present software implementations of ToleRace and evaluate them on multithreaded applications from the SPLASH2 and PARSEC suites.

Simultaneous multilayer scanning and detection for multiphoton fluorescence microscopy

Fast three-dimensional (3D) imaging requires parallel optical slicing of a specimen with an efficient detection scheme. The generation of multiple localized dot-like excitation structures solves the problem of simultaneous slicing multiple specimen layers, but an efficient detection scheme is necessary. Confocal theta detection (detection at 90 degrees to the optical axis) provides a suitable detection platform that is capable of cross-talk-free fluorescence detection from each nanodot (axial dimension approximate to 150 nm). Additionally, this technique has the unique feature of imaging a specimen at a large working distance with super-resolution capabilities. Polarization studies show distinct field structures for fixed and fluid samples, indicating a non-negligible field-dipole interaction. The realization of the proposed imaging technique will advance and diversify multiphoton fluorescence microscopy for numerous applications in nanobioimaging and optical engineering.

Object Tracking Using Motion Direction Detection

We present an algorithm for tracking objects in a video sequence, based on a novel approach for motion detection. We do not estimate the velocity �eld. In-stead we detect only the direction of motion at edge points and thus isolate sets of points which are moving coherently. We use a Hausdor� distance based matching algorithm to match point sets in local neighborhood and thus track objects in a video sequence. We show through some examples the e�ectiveness of the algo- rithm.

Delay Optimal Event Detection on Ad Hoc Wireless Sensor Networks

We consider a small extent sensor network for event detection, in which nodes periodically take samples and then contend over a random access network to transmit their measurement packets to the fusion center. We consider two procedures at the fusion center for processing the measurements. The Bayesian setting, is assumed, that is, the fusion center has a prior distribution on the change time. In the first procedure, the decision algorithm at the fusion center is network-oblivious and makes a decision only when a complete vector of measurements taken at a sampling instant is available. In the second procedure, the decision algorithm at the fusion center is network-aware and processes measurements as they arrive, but in a time-causal order. In this case, the decision statistic depends on the network delays, whereas in the network-oblivious case, the decision statistic does not. This yields a Bayesian change-detection problem with a trade-off between the random network delay and the decision delay that is, a higher sampling rate reduces the decision delay but increases the random access delay. Under periodic sampling, in the network-oblivious case, the structure of the optimal stopping rule is the same as that without the network, and the optimal change detection delay decouples into the network delay and the optimal decision delay without the network. In the network-aware case, the optimal stopping problem is analyzed as a partially observable Markov decision process, in which the states of the queues and delays in the network need to be maintained. A sufficient decision statistic is the network state and the posterior probability of change having occurred, given the measurements received and the state of the network. The optimal regimes are studied using simulation.