A Contraction Mapping Approach for Robust Estimation of Lagged Autocorrelation

We consider the zero-crossing rate (ZCR) of a Gaussian process and establish a property relating the lagged ZCR (LZCR) to the corresponding normalized autocorrelation function. This is a generalization of Kedem's result for the lag-one case. For the specific case of a sinusoid in white Gaussian noise, we use the higher-order property between lagged ZCR and higher-lag autocorrelation to develop an iterative higher-order autoregressive filtering scheme, which stabilizes the ZCR and consequently provide robust estimates of the lagged autocorrelation. Simulation results show that the autocorrelation estimates converge in about 20 to 40 iterations even for low signal-to-noise ratio.

Intense Acoustic Burst Ultrasound Modulated Optical Tomography for Elasticity Mapping of Soft Biological Tissue Mimicking Phantom: A Laser Speckle Contrast Analysis Study

This report addresses the assessment of variation in elastic property of soft biological tissues non-invasively using laser speckle contrast measurement. The experimental as well as the numerical (Monte-Carlo simulation) studies are carried out. In this an intense acoustic burst of ultrasound (an acoustic pulse with high power within standard safety limits), instead of continuous wave, is employed to induce large modulation of the tissue materials in the ultrasound insonified region of interest (ROI) and it results to enhance the strength of the ultrasound modulated optical signal in ultrasound modulated optical tomography (UMOT) system. The intensity fluctuation of speckle patterns formed by interference of light scattered (while traversing through tissue medium) is characterized by the motion of scattering sites. The displacement of scattering particles is inversely related to the elastic property of the tissue. We study the feasibility of laser speckle contrast analysis (LSCA) technique to reconstruct a map of the elastic property of a soft tissue-mimicking phantom. We employ source synchronized parallel speckle detection scheme to (experimentally) measure the speckle contrast from the light traversing through ultrasound (US) insonified tissue-mimicking phantom. The measured relative image contrast (the ratio of the difference of the maximum and the minimum values to the maximum value) for intense acoustic burst is 86.44 % in comparison to 67.28 % for continuous wave excitation of ultrasound. We also present 1-D and 2-D image of speckle contrast which is the representative of elastic property distribution.

Interference-Constrained Optimal Power-Adaptive Amplify-and-Forward Relaying and Selection for Underlay Cognitive Radios

In an underlay cognitive radio (CR) system, a secondary user can transmit when the primary is transmitting but is subject to tight constraints on the interference it causes to the primary receiver. Amplify-and-forward (AF) relaying is an effective technique that significantly improves the performance of a CR by providing an alternate path for the secondary transmitter's signal to reach the secondary receiver. We present and analyze a novel optimal relay gain adaptation policy (ORGAP) in which the relay is interference aware and optimally adapts both its gain and transmit power as a function of its local channel gains. ORGAP minimizes the symbol error probability at the secondary receiver subject to constraints on the average relay transmit power and on the average interference caused to the primary. It is different from ad hoc AF relaying policies and serves as a new and fundamental theoretical benchmark for relaying in an underlay CR. We also develop a near-optimal and simpler relay gain adaptation policy that is easy to implement. An extension to a multirelay scenario with selection is also developed. Our extensive numerical results for single and multiple relay systems quantify the power savings achieved over several ad hoc policies for both MPSK and MQAM constellations.

Genomic mapping of cAMP receptor protein (CRPMt) in Mycobacterium tuberculosis: relation to transcriptional start sites and the role of CRPMt as a transcription factor

Chromatin immunoprecipitation identified 191 binding sites of Mycobacterium tuberculosis cAMP receptor protein (CRPMt) at endogenous expression levels using a specific alpha-CRPMt antibody. Under these native conditions an equal distribution between intragenic and intergenic locations was observed. CRPMt binding overlapped a palindromic consensus sequence. Analysis by RNA sequencing revealed widespread changes in transcriptional profile in a mutant strain lacking CRPMt during exponential growth, and in response to nutrient starvation. Differential expression of genes with a CRPMt-binding site represented only a minor portion of this transcriptional reprogramming with similar to 19% of those representing transcriptional regulators potentially controlled by CRPMt. The subset of genes that are differentially expressed in the deletion mutant under both culture conditions conformed to a pattern resembling canonical CRP regulation in Escherichia coli, with binding close to the transcriptional start site associated with repression and upstream binding with activation. CRPMt can function as a classical transcription factor in M. tuberculosis, though this occurs at only a subset of CRPMt-binding sites.

Group Testing-Based Spectrum Hole Search for Cognitive Radios

This paper investigates the use of adaptive group testing to find a spectrum hole of a specified bandwidth in a given wideband of interest. We propose a group testing-based spectrum hole search algorithm that exploits sparsity in the primary spectral occupancy by testing a group of adjacent subbands in a single test. This is enabled by a simple and easily implementable sub-Nyquist sampling scheme for signal acquisition by the cognitive radios (CRs). The sampling scheme deliberately introduces aliasing during signal acquisition, resulting in a signal that is the sum of signals from adjacent subbands. Energy-based hypothesis tests are used to provide an occupancy decision over the group of subbands, and this forms the basis of the proposed algorithm to find contiguous spectrum holes of a specified bandwidth. We extend this framework to a multistage sensing algorithm that can be employed in a variety of spectrum sensing scenarios, including noncontiguous spectrum hole search. Furthermore, we provide the analytical means to optimize the group tests with respect to the detection thresholds, number of samples, group size, and number of stages to minimize the detection delay under a given error probability constraint. Our analysis allows one to identify the sparsity and SNR regimes where group testing can lead to significantly lower detection delays compared with a conventional bin-by-bin energy detection scheme; the latter is, in fact, a special case of the group test when the group size is set to 1 bin. We validate our analytical results via Monte Carlo simulations.

Mapping Post-translational Modifications of Mammalian Testicular Specific Histone Variant TH2B in Tetraploid and Haploid Germ Cells and Their Implications on the Dynamics of Nucleosome Structure

Histones regulate a variety of chromatin templated events by their post-translational modifications (PTMs). Although there are extensive reports on the PTMs of canonical histones, the information on the histone variants remains very scanty. Here, we report the identification of different PTMs, such as acetylation, methylation, and phosphorylation of a major mammalian histone variant TH2B. Our mass spectrometric analysis has led to the identification of both conserved and unique modifications across tetraploid spermatocytes and haploid spermatids. We have also computationally derived the 3-dimensional model of a TH2B containing nucleosome in order to study the spatial orientation of the PTMs identified and their effect on nucleosome stability and DNA binding potential. From our nucleosome model, it is evident that substititution of specific amino acid residues in TH2B results in both differential histone-DNA and histone-histone contacts. Furthermore, we have also observed that acetylation on the N-terminal tail of TH2B weakens the interactions with the DNA. These results provide direct evidence that, similar to somatic H2B, the testis specific histone TH2B also undergoes multiple PTMs, suggesting the possibility of chromatin regulation by such covalent modifications in mammalian male germ cells.

Mapping the intriguing transient morphologies and the demixing behavior in PS/PVME blends in the presence of rod-like nanoparticles

The demixing behavior, transient morphologies and mechanism of phase separation in PS/PVME blends were greatly altered in the presence of a very low concentration of rod-like particles (multiwall carbon nanotubes, MWNTs). This phenomenon is due to the specific interaction of one of the phases (PVME) with the anisotropic MWNTs, which creates a heterogeneous environment in the blend. This specific interaction alters the chain dynamics in the interfacial region as against the bulk. A comprehensive analysis using isochronal temperature sweep was performed to understand the demixing temperature in the blends. The evolution of phase morphology as a function of time and temperature was assessed by polarizing optical microscopy (POM), atomic force microscopy (AFM) and scanning electron microscopy (SEM). The addition of MWNTs increased the rheological demixing temperature and the spinodal temperature in almost all the compositions. The intriguing transient morphologies were mapped, which varied from nucleation and growth to coalescence-induced viscoelastic phase separation (C-VPS) in PVME-rich blends, to spinodal decomposition in the near-critical compositions, to transient gel-induced VPS (T-VPS) in the PS-rich compositions. Mapping of the morphology development displayed two types of fracture mechanisms: ductile fracture for near-critical compositions and brittle fracture for off-critical composition. The change in the phase separation mechanism in the presence of MWNTs was due to the variation in dynamic asymmetry brought about by these anisotropic particles. All these observations were correlated by POM, SEM and AFM studies. The length of the cooperatively rearranging region (CRR), as evaluated using modulated differential scanning calorimetry (MDSC) measurements, was found to be composition-independent. The observed variation of effective glass transition of PVME (low T-g component) on blending with PS (high Tg component) and by the addition of MWNTs accounts for the dynamic heterogeneity introduced by MWNTs in the system.

Soft Real Time Implementation of a Cognitive Radio Testbed for Frequency Hopping Primary Satisfying QoS Requirements

The Cognitive Radio (CR) is a promising technology which provides a novel way to subjugate the issue of spectrum underutilization caused due to the fixed spectrum assignment policies. In this paper we report the design and implementation of a soft-real time CR MAC, consisting of multiple secondary users, in a frequency hopping (Fit) primary scenario. This MAC is capable of sensing the spectrum and dynamically allocating the available frequency bands to multiple CR users based on their QoS requirements. As the primary is continuously hopping, a method has also been implemented to detect the hop instant of the primary network. Synchronization usually requires real time support, however we have been able to achieve this with a soft-real time technique which enables a fully software implementation of CR MAC layer. We demonstrate the wireless transmission and reception of video over this CR testbed through opportunistic spectrum access. The experiments carried out use an open source software defined radio package called GNU Radio and a basic radio hardware component USRP.

Database Independent Human Emotion Recognition with Meta-Cognitive Neuro-Fuzzy Inference System

Facial emotions are the most expressive way to display emotions. Many algorithms have been proposed which employ a particular set of people (usually a database) to both train and test their model. This paper focuses on the challenging task of database independent emotion recognition, which is a generalized case of subject-independent emotion recognition. The emotion recognition system employed in this work is a Meta-Cognitive Neuro-Fuzzy Inference System (McFIS). McFIS has two components, a neuro-fuzzy inference system, which is the cognitive component and a self-regulatory learning mechanism, which is the meta-cognitive component. The meta-cognitive component, monitors the knowledge in the neuro-fuzzy inference system and decides on what-to-learn, when-to-learn and how-to-learn the training samples, efficiently. For each sample, the McFIS decides whether to delete the sample without being learnt, use it to add/prune or update the network parameter or reserve it for future use. This helps the network avoid over-training and as a result improve its generalization performance over untrained databases. In this study, we extract pixel based emotion features from well-known (Japanese Female Facial Expression) JAFFE and (Taiwanese Female Expression Image) TFEID database. Two sets of experiment are conducted. First, we study the individual performance of both databases on McFIS based on 5-fold cross validation study. Next, in order to study the generalization performance, McFIS trained on JAFFE database is tested on TFEID and vice-versa. The performance The performance comparison in both experiments against SVNI classifier gives promising results.

Action Recognition from Motion Capture Data using Meta-cognitive RBF Network Classifier

Action recognition plays an important role in various applications, including smart homes and personal assistive robotics. In this paper, we propose an algorithm for recognizing human actions using motion capture action data. Motion capture data provides accurate three dimensional positions of joints which constitute the human skeleton. We model the movement of the skeletal joints temporally in order to classify the action. The skeleton in each frame of an action sequence is represented as a 129 dimensional vector, of which each component is a 31) angle made by each joint with a fixed point on the skeleton. Finally, the video is represented as a histogram over a codebook obtained from all action sequences. Along with this, the temporal variance of the skeletal joints is used as additional feature. The actions are classified using Meta-Cognitive Radial Basis Function Network (McRBFN) and its Projection Based Learning (PBL) algorithm. We achieve over 97% recognition accuracy on the widely used Berkeley Multimodal Human Action Database (MHAD).

A Pd-24 Pregnant Molecular Nanoball: Self-Templated Stellation by Precise Mapping of Coordination Sites

We found that Pd(II) ion (M) and the smallest 120 bidentate donor pyrimidine (L-a) self-assemble into a mononuclear M(L-a)(4) complex (1a) instead of the expected smallest M-12(L-a)(24) molecular ball (1), presumably due to the weak coordination nature of the pyrimidine. To construct such a pyrimidine bridged nanoball, we employed a new donor tris(4-(pyrimidin-5-yl)phenyl)amine (L); which upon selective complexation with Pd(II) ions resulted in the formation of a pregnant M24L24 molecular nanoball (2) consisting of a pyrimidine-bridged Pd-12 baby-ball supported by a Pd-12 larger mother-ball. The formation of the baby-ball was not successful without the support of the mother-ball. Thus, we created an example of a self-assembly where the inner baby-ball resembling to the predicted M-12(L-a)(24) ball (1) was incarcerated by the giant outer mother-ball by means of geometrical constraints. Facile conversion of the pregnant ball 2 to a smaller M-12(L-b)(24) ball 3 with dipyridyl donor was achieved in a single step.

Novel Relay Selection Rules for Average Interference-Constrained Cognitive AF Relay Networks

Cooperative relaying combined with selection exploits spatial diversity to significantly improve the performance of interference-constrained secondary users in an underlay cognitive radio (CR) network. However, unlike conventional relaying, the state of the links between the relay and the primary receiver affects the choice of the relay. Further, while the optimal amplify-and-forward (AF) relay selection rule for underlay CR is well understood for the peak interference-constraint, this is not so for the less conservative average interference constraint. For the latter, we present three novel AF relay selection (RS) rules, namely, symbol error probability (SEP)-optimal, inverse-of-affine (IOA), and linear rules. We analyze the SEPs of the IOA and linear rules and also develop a novel, accurate approximation technique for analyzing the performance of AF relays. Extensive numerical results show that all the three rules outperform several RS rules proposed in the literature and generalize the conventional AF RS rule.

Human action recognition in H.264/AVC compressed domain using meta-cognitive radial basis function network

In this paper, we propose a H.264/AVC compressed domain human action recognition system with projection based metacognitive learning classifier (PBL-McRBFN). The features are extracted from the quantization parameters and the motion vectors of the compressed video stream for a time window and used as input to the classifier. Since compressed domain analysis is done with noisy, sparse compression parameters, it is a huge challenge to achieve performance comparable to pixel domain analysis. On the positive side, compressed domain allows rapid analysis of videos compared to pixel level analysis. The classification results are analyzed for different values of Group of Pictures (GOP) parameter, time window including full videos. The functional relationship between the features and action labels are established using PBL-McRBFN with a cognitive and meta-cognitive component. The cognitive component is a radial basis function, while the meta-cognitive component employs self-regulation to achieve better performance in subject independent action recognition task. The proposed approach is faster and shows comparable performance with respect to the state-of-the-art pixel domain counterparts. It employs partial decoding, which rules out the complexity of full decoding, and minimizes computational load and memory usage. This results in reduced hardware utilization and increased speed of classification. The results are compared with two benchmark datasets and show more than 90% accuracy using the PBL-McRBFN. The performance for various GOP parameters and group of frames are obtained with twenty random trials and compared with other well-known classifiers in machine learning literature. (C) 2015 Elsevier B.V. All rights reserved.

Remotely sensed debris thickness mapping of Bara Shigri Glacier, Indian Himalaya

Despite the important role of supraglacial debris in ablation, knowledge of debris thickness on Himalayan glaciers is sparse. A recently developed method based on reanalysis data and thermal band satellite imagery has proved to be potentially suitable for debris thickness estimation without the need for detailed field data. In this study, we further develop the method and discuss possibilities and limitations arising from its application to a glacier in the Himalaya with scarce in situ data. Surface temperature patterns are consistent for 13 scenes of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Landsat 7 imagery and correlate well with incoming shortwave radiation and air temperature. We use an energy-balance approach to subtract these radiation or air temperature effects, in order to estimate debris thickness patterns as a function of surface temperature. Both incoming shortwave and longwave radiation are estimated with reasonable accuracy when applying parameterizations and reanalysis data. However, the model likely underestimates debris thickness, probably due to incorrect representation of vertical debris temperature profiles, the rate of heat storage and turbulent sensible heat flux. Moreover, the uncertainty of the result was found to increase significantly with thicker debris, a promising result since ablation is enhanced by thin debris of 1-2 cm.