Very large array detection of radio recombination lines from the radio nucleus of NGC 253: Ionization by a weak active galactic nucleus, an obscured super star cluster, or a compact supernova remnant?

We have imaged the H92alpha and H75alpha radio recombination line (RRL) emissions from the starburst galaxy NGC 253 with a resolution of similar to4 pc. The peak of the RRL emission at both frequencies coincides with the unresolved radio nucleus. Both lines observed toward the nucleus are extremely wide, with FWHMs of similar to200 km s(-1). Modeling the RRL and radio continuum data for the radio nucleus shows that the lines arise in gas whose density is similar to10(4) cm(-3) and mass is a few thousand M., which requires an ionizing flux of (6-20) x 10(51) photons s(-1). We consider a supernova remnant (SNR) expanding in a dense medium, a star cluster, and also an active galactic nucleus (AGN) as potential ionizing sources. Based on dynamical arguments, we rule out an SNR as a viable ionizing source. A star cluster model is considered, and the dynamics of the ionized gas in a stellar-wind driven structure are investigated. Such a model is only consistent with the properties of the ionized gas for a cluster younger than similar to10(5) yr. The existence of such a young cluster at the nucleus seems improbable. The third model assumes the ionizing source to be an AGN at the nucleus. In this model, it is shown that the observed X-ray flux is too weak to account for the required ionizing photon flux. However, the ionization requirement can be explained if the accretion disk is assumed to have a big blue bump in its spectrum. Hence, we favor an AGN at the nucleus as the source responsible for ionizing the observed RRLs. A hybrid model consisting of an inner advection-dominated accretion flow disk and an outer thin disk is suggested, which could explain the radio, UV, and X-ray luminosities of the nucleus.

Development of recombinant coat protein antibody based IC-RT-PCR for detection and discrimination of sugarcane streak mosaic virus isolates from Southern India

Sugarcane streak mosaic virus (SCSMV), causes mosaic disease of sugarcane and is thought to belong to a new undescribed genus in the family Potyviridae. The coat protein (CP) gene from the Andhra Pradesh (AP) isolate of SCSMV (SCSMV AP) was cloned and expressed in Escherichia coli. The recombinant coat protein was used to raise high quality antiserum. The CP antiserum was used to develop an immunocapture reverse transcription-polymerase chain reaction (IC-RT-PCR) based assay for the detection and discrimination of SCSMV isolates in South India. The sequence of the cloned PCR products encoding 3'untranslated region (UTR) and CP regions of the virus isolates from three different locations in South India viz. Tanuku (Coastal Andhra Pradesh), Coimbatore (Tamil Nadu) and Hospet (Karnataka) was compared with that of SCSMV AP The analysis showed that they share 89.4, 89.5 and 90% identity respectively at the nucleotide level. This suggests that the isolates causing mosaic disease of sugarcane in South India are indeed strains of SCSMV In addition, the sensitivity of the IC-RT-PCR was compared with direct antigen coating-enzyme linked immunosorbent assay (DAC-ELISA) and dot-blot immunobinding assays and was found to be more sensitive and hence could be used to detect the presence of virus in sugarcane breeding, germplasm centres and in quarantine programs.

Motion of a charged particle in superposed Heliotron and biconical cusp fields

We have studied the behaviour of a charged particle in an axially symmetric magnetic field having a neutral point, so as to find a possibility of confining a charged particle in a thermonuclear device. In order to study the motion we have reduced a three-dimensional motion to a two-dimensional one by introducing a fictitious potential. Following Schmidt we have classified the motion, as an ‘off-axis motion’ and ‘encircling motion’ depending on the behaviour of this potential. We see that the particle performs a hybrid type of motion in the negative z-axis, i.e. at some instant it is in ‘off-axis motion’ while at another instant it is in ‘encircling motion’. We have also solved the equation of motion numerically and the graphs of the particle trajectory verify our analysis. We find that in most of the cases the particle is contained. The magnetic moment is found to be moderately adiabatic.

Some properties of boundary layer flow during the transition from laminar to turbulent motion

Transition in the boundary layer on a flat plate is examined from the point of view of intermittent production of turbulent spots. On the hypothesis of localized laminar breakdown, for which there is some expermental evidence, Emmons’ probability calculations can be extended to explain the observed statistical similarity of transition regions. Application of these ideas allows detailed calculations of the boundary layer parameters including mean velocity profiles and skin friction during transition. The mean velocity profiles belong to a universal one-parameter family with the intermittency factor as the parameter. From an examination of experimental data the probable existence of a relation between the transition Reynolds number and the rate of production of the turbulent spots is deduced. A simple new technique for the measurement of the intermittency factor by a Pitot tube is reported.

Carbon based materials for low temperature detection

Resistance temperature detectors (RTDs) are being widely used to detect low temperature, while thermocouples (TCs) are being used to detect high temperature. The materials suitable for RTDs are platinum, germanium, carbon, carbon-glass, cernox, etc. Here, we have reported the possible application of another form of carbon i.e. carbon nanotubes in low temperature thermometry. It has been shown the resistance R and the sensitivity of carbon nanotube bundles can be tuned and made suitable for ultralow temperature detection. We report on the R-T measurement of carbon nanotube bundles from room temperature down to 1 K to felicitate the possible application of bundles in low temperature RTDs. ©2008 American Institute of Physics

Antigen detection assay with parasite specific monoclonal antibodies for diagnosis of lymphatic filariasis

Background: Lymphatic filariasis is a painful and profoundly disfiguring disease. Infection is usually acquired in childhood but its visible manifestations occur later in life, causing temporary or permanent disability. The importance of developing effective assays to diagnose, monitor and evaluate human lymphatic filariasis has been emphasized by the WHO. Methods: High-affinity monoclonal antibodies (mAbs) specific for recombinant filarial antigen WbSXP-1 were developed. An ELISA based capture assay using monoclonal and polyclonal antibodies for WbSXP-1 was used for detection of circulating filarial antigen. Results: High-affinity monoclonal antibodies (mAbs) were developed that specifically binds both W. bancrofti and B. malayi mf antigens. Two mAbs (1F6H3 and 2E12E3) of subclass IgG2a and IgM showed high affinity, avidity and reactivity to recombinant and mf native antigen. Both the mAbs were used in combination as capture antibodies and polyclonal as detection antibody to develop the assay. The assay showed very high sensitivity towards W. bancrofti mf positive samples compared to endemic normal samples (P<0.0001). Conclusion: A capture assay using high-affinity monoclonal antibodies for WbSXP-1 was developed for the detection of filarial circulating antigen in clinical samples from bancroftian infection. Besides, this would also help in epidemiological studies in endemic areas of filarial infections. (C) 2011 Elsevier B.V. All rights reserved.

An Adaptive Feature Based Low Power Motion Estimation Algorithm

Motion Estimation is one of the most power hungry operations in video coding. While optimal search (eg. full search)methods give best quality, non optimal methods are often used in order to reduce cost and power. Various algorithms have been used in practice that trade off quality vs. complexity. Global elimination is an algorithm based on pixel averaging to reduce complexity of motion search while keeping performance close to that of full search. We propose an adaptive version of the global elimination algorithm that extracts individual macro-block features using Hadamard transform to optimize the search. Performance achieved is close to the full search method and global elimination. Operational complexity and hence power is reduced by 30% to 45% compared to global elimination method.

CUSUM Based Distributed Detection in WSNs

We are concerned with the situation in which a wireless sensor network is deployed in a region, for the purpose of detecting an event occurring at a random time and at a random location. The sensor nodes periodically sample their environment (e.g., for acoustic energy),process the observations (in our case, using a CUSUM-based algorithm) and send a local decision (which is binary in nature) to the fusion centre. The fusion centre collects these local decisions and uses a fusion rule to process the sensors’ local decisions and infer the state of nature, i.e., if an event has occurred or not. Our main contribution is in analyzing two local detection rules in combination with a simple fusion rule. The local detection algorithms are based on the nonparametric CUSUMprocedure from sequential statistics. We also propose two ways to operate the local detectors after an alarm. These alternatives when combined in various ways yield several approaches. Our contribution is to provide analytical techniques to calculate false alarm measures, by the use of which the local detector thresholds can be set. Simulation results are provided to evaluate the accuracy of our analysis. As an illustration we provide a design example. We also use simulations to compare the detection delays incurred in these algorithms.

Optimal Sleep-Wake Scheduling for Quickest Intrusion Detection using wireless sensor Networks

We consider the problem of quickest detection of an intrusion using a sensor network, keeping only a minimal number of sensors active. By using a minimal number of sensor devices,we ensure that the energy expenditure for sensing, computation and communication is minimized (and the lifetime of the network is maximized). We model the intrusion detection (or change detection) problem as a Markov decision process (MDP). Based on the theory of MDP, we develop the following closed loop sleep/wake scheduling algorithms: 1) optimal control of Mk+1, the number of sensors in the wake state in time slot k + 1, 2) optimal control of qk+1, the probability of a sensor in the wake state in time slot k + 1, and an open loop sleep/wake scheduling algorithm which 3) computes q, the optimal probability of a sensor in the wake state (which does not vary with time),based on the sensor observations obtained until time slot k.Our results show that an optimum closed loop control onMk+1 significantly decreases the cost compared to keeping any number of sensors active all the time. Also, among the three algorithms described, we observe that the total cost is minimum for the optimum control on Mk+1 and is maximum for the optimum open loop control on q.