Joint Approximately Sparse Channel Estimation and Data Detection in OFDM Systems Using Sparse Bayesian Learning

It is well known that the impulse response of a wide-band wireless channel is approximately sparse, in the sense that it has a small number of significant components relative to the channel delay spread. In this paper, we consider the estimation of the unknown channel coefficients and its support in OFDM systems using a sparse Bayesian learning (SBL) framework for exact inference. In a quasi-static, block-fading scenario, we employ the SBL algorithm for channel estimation and propose a joint SBL (J-SBL) and a low-complexity recursive J-SBL algorithm for joint channel estimation and data detection. In a time-varying scenario, we use a first-order autoregressive model for the wireless channel and propose a novel, recursive, low-complexity Kalman filtering-based SBL (KSBL) algorithm for channel estimation. We generalize the KSBL algorithm to obtain the recursive joint KSBL algorithm that performs joint channel estimation and data detection. Our algorithms can efficiently recover a group of approximately sparse vectors even when the measurement matrix is partially unknown due to the presence of unknown data symbols. Moreover, the algorithms can fully exploit the correlation structure in the multiple measurements. Monte Carlo simulations illustrate the efficacy of the proposed techniques in terms of the mean-square error and bit error rate performance.

A Probe for the Selective and Parts-per-Billion-Level Detection of Copper(II) and Mercury(II) using a Micellar Medium and Its Utility in Cell Imaging

A novel colorimetric probe 1 based on the picolyl moiety has been designed and synthesized. Probe 1 is composed of a pyrene and a bispicolyl amine (BPA) unit, in which the BPA moiety acts as a binding unit and the binding phenomenon is sensed from the changes in the signaling subunit. The probe detects Cu2+ specifically in water and both Cu2+ and Hg2+ efficiently in neutral Brij-58 micellar media. The probe shows a color change visible to the naked eye upon addition of metal ions. Notably, in a micellar medium, probe 1 can detect both the Cu2+ and Hg2+ ions even at parts-per-billion levels. Furthermore, the probe shows ratiometric detection of both the metal ions making the sensing quantitative. The two metal ions could be discriminated both visibly under a UV lamp and with the use of fluorescence spectroscopy. The probe could be also used in biological cell lines for the detection of both Hg2+ and Cu2+ ions.

A Comparative Assessment of Hand Preference in Captive Red Howler Monkeys, Alouatta seniculus and Yellow-Breasted Capuchin Monkeys, Sapajus xanthosternos

There are two major theories that attempt to explain hand preference in non-human primates-the `task complexity' theory and the `postural origins' theory. In the present study, we proposed a third hypothesis to explain the evolutionary origin of hand preference in non-human primates, stating that it could have evolved owing to structural and functional adaptations to feeding, which we refer to as the `niche structure' hypothesis. We attempted to explore this hypothesis by comparing hand preference across species that differ in the feeding ecology and niche structure: red howler monkeys, Alouatta seniculus and yellow-breasted capuchin monkeys, Sapajus xanthosternos. The red howler monkeys used the mouth to obtain food more frequently than the yellow-breasted capuchin monkeys. The red howler monkeys almost never reached for food presented on the opposite side of a wire mesh or inside a portable container, whereas the yellow-breasted capuchin monkeys reached for food presented in all four spatial arrangements (scattered, on the opposite side of a wire mesh, inside a suspended container, and inside a portable container). In contrast to the red howler monkeys that almost never acquired bipedal and clinging posture, the yellow-breasted capuchin monkeys acquired all five body postures (sitting, bipedal, tripedal, clinging, and hanging). Although there was no difference between the proportion of the red howler monkeys and the yellow-breasted capuchin monkeys that preferentially used one hand, the yellow-breasted capuchin monkeys exhibited an overall weaker hand preference than the red howler monkeys. Differences in hand preference diminished with the increasing complexity of the reaching-for-food tasks, i.e., the relatively more complex tasks were perceived as equally complex by both the red howler monkeys and the yellow-breasted capuchin monkeys. These findings suggest that species-specific differences in feeding ecology and niche structure can influence the perception of the complexity of the task and, consequently, hand preference.

Spectrum sensing using distributed sequential detection via noisy reporting MAC

This paper considers cooperative spectrum sensing algorithms for Cognitive Radios which focus on reducing the number of samples to make a reliable detection. We propose algorithms based on decentralized sequential hypothesis testing in which the Cognitive Radios sequentially collect the observations, make local decisions and send them to the fusion center for further processing to make a final decision on spectrum usage. The reporting channel between the Cognitive Radios and the fusion center is assumed more realistically as a Multiple Access Channel (MAC) with receiver noise. Furthermore the communication for reporting is limited, thereby reducing the communication cost. We start with an algorithm where the fusion center uses an SPRT-like (Sequential Probability Ratio Test) procedure and theoretically analyze its performance. Asymptotically, its performance is close to the optimal centralized test without fusion center noise. We further modify this algorithm to improve its performance at practical operating points. Later we generalize these algorithms to handle uncertainties in SNR and fading. (C) 2014 Elsevier B.V. All rights reserved.

Exclusive Detection of Sub-Nanomolar Levels of Palladium(II) in Water: An Excellent Probe for Multiple Applications

A new colorimetric probe has been developed for the detection and estimation of Pd-II at sub-nanomolar concentrations. The probe consisted of rhodamine (signaling unit), which was linked with a bis-picolyl moiety (binding site) through a phenyl ring. Pd-II induced opening of the spirolactam ring of the probe with the generation of a prominent pink color. The excellent selectivity of the probe towards Pd-II over Pd-0 or Rh-II ensured its potential utility for the detection of residual palladium contamination in pharma-ceutical drugs and in Pd-catalyzed reactions. The probe showed a ``turn-on'' (bright yellow) fluorescence upon the addition of Pd-II, which made it suitable for the detection of Pd contaminants in mammalian cells.

Race Detection for Android Applications

Programming environments for smartphones expose a concurrency model that combines multi-threading and asynchronous event-based dispatch. While this enables the development of efficient and feature-rich applications, unforeseen thread interleavings coupled with non-deterministic reorderings of asynchronous tasks can lead to subtle concurrency errors in the applications. In this paper, we formalize the concurrency semantics of the Android programming model. We further define the happens-before relation for Android applications, and develop a dynamic race detection technique based on this relation. Our relation generalizes the so far independently studied happens-before relations for multi-threaded programs and single-threaded event-driven programs. Additionally, our race detection technique uses a model of the Android runtime environment to reduce false positives. We have implemented a tool called DROIDRACER. It generates execution traces by systematically testing Android applications and detects data races by computing the happens-before relation on the traces. We analyzed 1 5 Android applications including popular applications such as Facebook, Twitter and K-9 Mail. Our results indicate that data races are prevalent in Android applications, and that DROIDRACER is an effective tool to identify data races.

Multiscale Symmetry Detection in Scalar Fields by Clustering Contours

The complexity in visualizing volumetric data often limits the scope of direct exploration of scalar fields. Isocontour extraction is a popular method for exploring scalar fields because of its simplicity in presenting features in the data. In this paper, we present a novel representation of contours with the aim of studying the similarity relationship between the contours. The representation maps contours to points in a high-dimensional transformation-invariant descriptor space. We leverage the power of this representation to design a clustering based algorithm for detecting symmetric regions in a scalar field. Symmetry detection is a challenging problem because it demands both segmentation of the data and identification of transformation invariant segments. While the former task can be addressed using topological analysis of scalar fields, the latter requires geometry based solutions. Our approach combines the two by utilizing the contour tree for segmenting the data and the descriptor space for determining transformation invariance. We discuss two applications, query driven exploration and asymmetry visualization, that demonstrate the effectiveness of the approach.

A fluorescent organic cage for picric acid detection

Dynamic covalent imine chemistry has been utilized to synthesize a fluorescent 3+2] self-assembled nanoscopic organic cage. The fluorescent nature of the reduced analogue of the cage was further exploited for the highly selective detection of the explosive picric acid (PA).

Optical detection of submicromolar levels of nitro explosives by a submicron sized metal-organic phosphor material

Two isomorphous submicron sized metal-organic network compounds, Y-2(PDA)(3)(H2O)1]center dot 2H(2)O (PDA = 1,4-phenylenediacetate), 1 and Y1.8Tb0.2(PDA)(3)(H2O)1]center dot 2H(2)O, Tb@1 have been synthesized by employing solvent assisted liquid grinding followed by heating at 180 degrees C for 1' min and washing with water. Single crystal X-ray data of bulk 1 confirmed a three dimensional porous structure. The structure and morphology of 1 and Tb@1 were systematically characterized by PXRD, TGA, DSC, IR, SEM and EDX analysis. Dehydrated Tb@1 Tb@1'] shows a high intense visible green emission upon exposure to UV light. The green emission of Tb@1' was used for the detection of nitro explosives, such as 2,4,6-trinitrophenol (TNP), 1,3-dinitro benzene (DNB), 2,4-dinitro toluene (DNT), nitro benzene (NB), and 4-nitro toluene (NT) in acetonitrile. The results show that the emission intensity of dehydrated Tb@1' can be quenched by all the nitro analytes used in the present work. Remarkably, Tb@1' exhibited a high efficiency for TNP, DNB and DNT detection with K-SV K-SV = quenching constant based on linear Stern-Volmer plot] values of 70 920, 44 000 and 35 430 M-1, respectively, which are the highest values amongst known metal-organic materials. Using this material submicromolar level (equivalent to 0.18 ppm), a detection of nitro explosives has been achieved.

Enriching the annotation of Mycobacterium tuberculosis H37Rv proteome using remote homology detection approaches: Insights into structure and function

The availability of the genome sequence of Mycobacterium tuberculosis H37Rv has encouraged determination of large numbers of protein structures and detailed definition of the biological information encoded therein; yet, the functions of many proteins in M. tuberculosis remain unknown. The emergence of multidrug resistant strains makes it a priority to exploit recent advances in homology recognition and structure prediction to re-analyse its gene products. Here we report the structural and functional characterization of gene products encoded in the M. tuberculosis genome, with the help of sensitive profile-based remote homology search and fold recognition algorithms resulting in an enhanced annotation of the proteome where 95% of the M. tuberculosis proteins were identified wholly or partly with information on structure or function. New information includes association of 244 proteins with 205 domain families and a separate set of new association of folds to 64 proteins. Extending structural information across uncharacterized protein families represented in the M. tuberculosis proteome, by determining superfamily relationships between families of known and unknown structures, has contributed to an enhancement in the knowledge of structural content. In retrospect, such superfamily relationships have facilitated recognition of probable structure and/or function for several uncharacterized protein families, eventually aiding recognition of probable functions for homologous proteins corresponding to such families. Gene products unique to mycobacteria for which no functions could be identified are 183. Of these 18 were determined to be M. tuberculosis specific. Such pathogen-specific proteins are speculated to harbour virulence factors required for pathogenesis. A re-annotated proteome of M. tuberculosis, with greater completeness of annotated proteins and domain assigned regions, provides a valuable basis for experimental endeavours designed to obtain a better understanding of pathogenesis and to accelerate the process of drug target discovery. (C) 2014 Elsevier Ltd. All rights reserved.

Matrix Crack Detection in Composite Plate with Spatially Random Material Properties using Fractal Dimension

Fractal dimension based damage detection method is investigated for a composite plate with random material properties. Composite material shows spatially varying random material properties because of complex manufacturing processes. Matrix cracks are considered as damage in the composite plate. Such cracks are often seen as the initial damage mechanism in composites under fatigue loading and also occur due to low velocity impact. Static deflection of the cantilevered composite plate with uniform loading is calculated using the finite element method. Damage detection is carried out based on sliding window fractal dimension operator using the static deflection. Two dimensional homogeneous Gaussian random field is generated using Karhunen-Loeve (KL) expansion to represent the spatial variation of composite material property. The robustness of fractal dimension based damage detection method is demonstrated considering the composite material properties as a two dimensional random field.

Sensitive detection of C-reactive protein using optical fiber Bragg gratings

An accurate and highly sensitive sensor platform has been demonstrated for the detection of C-reactive protein (CRP) using optical fiber Bragg gratings (FBGs). The CRP detection has been carried out by monitoring the shift in Bragg wavelength (Delta lambda(B)) of an etched FBG (eFBG) coated with an anti-CRP antibody (aCRP)-graphene oxide (GO) complex. The complex is characterized by Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy and atomic force microscopy. A limit of detection of 0.01 mg/L has been achieved with a linear range of detection from 0.01 mg/L to 100 mg/L which includes clinical range of CRP. The eFBG sensor coated with only aCRP (without GO) show much less sensitivity than that of aCRP-GO complex coated eFBG. The eFBG sensors show high specificity to CRP even in the presence of other interfering factors such as urea, creatinine and glucose. The affinity constant of similar to 1.1 x 10(10) M-1 has been extracted from the data of normalized shift (Delta lambda(B)/lambda(B)) as a function of CRP concentration. (C) 2014 Elsevier B.V. All rights reserved.

Multithreaded Test Synthesis for Deadlock Detection

Designing and implementing thread-safe multithreaded libraries can be a daunting task as developers of these libraries need to ensure that their implementations are free from concurrency bugs, including deadlocks. The usual practice involves employing software testing and/or dynamic analysis to detect. deadlocks. Their effectiveness is dependent on well-designed multithreaded test cases. Unsurprisingly, developing multithreaded tests is significantly harder than developing sequential tests for obvious reasons. In this paper, we address the problem of automatically synthesizing multithreaded tests that can induce deadlocks. The key insight to our approach is that a subset of the properties observed when a deadlock manifests in a concurrent execution can also be observed in a single threaded execution. We design a novel, automatic, scalable and directed approach that identifies these properties and synthesizes a deadlock revealing multithreaded test. The input to our approach is the library implementation under consideration and the output is a set of deadlock revealing multithreaded tests. We have implemented our approach as part of a tool, named OMEN1. OMEN is able to synthesize multithreaded tests on many multithreaded Java libraries. Applying a dynamic deadlock detector on the execution of the synthesized tests results in the detection of a number of deadlocks, including 35 real deadlocks in classes documented as thread-safe. Moreover, our experimental results show that dynamic analysis on multithreaded tests that are either synthesized randomly or developed by third-party programmers are ineffective in detecting the deadlocks.

Trace Driven Dynamic Deadlock Detection and Reproduction

Dynamic analysis techniques have been proposed to detect potential deadlocks. Analyzing and comprehending each potential deadlock to determine whether the deadlock is feasible in a real execution requires significant programmer effort. Moreover, empirical evidence shows that existing analyses are quite imprecise. This imprecision of the analyses further void the manual effort invested in reasoning about non-existent defects. In this paper, we address the problems of imprecision of existing analyses and the subsequent manual effort necessary to reason about deadlocks. We propose a novel approach for deadlock detection by designing a dynamic analysis that intelligently leverages execution traces. To reduce the manual effort, we replay the program by making the execution follow a schedule derived based on the observed trace. For a real deadlock, its feasibility is automatically verified if the replay causes the execution to deadlock. We have implemented our approach as part of WOLF and have analyzed many large (upto 160KLoC) Java programs. Our experimental results show that we are able to identify 74% of the reported defects as true (or false) positives automatically leaving very few defects for manual analysis. The overhead of our approach is negligible making it a compelling tool for practical adoption.

Matrix crack detection in spatially random composite structures using fractal dimension

Fractal dimension based damage detection method is studied for a composite structure with random material properties. A composite plate with localized matrix crack is considered. Matrix cracks are often seen as the initial damage mechanism in composites. Fractal dimension based method is applied to the static deformation curve of the structure to detect localized damage. Static deflection of a cantilevered composite plate under uniform loading is calculated using the finite element method. Composite material shows spatially varying random material properties because of complex manufacturing processes. Spatial variation of material property is represented as a two dimensional homogeneous Gaussian random field. Karhunen-Loeve (KL) expansion is used to generate a random field. The robustness of fractal dimension based damage detection methods is studied considering the composite plate with spatial variation in material properties.