A finite-rate-of-innovation signal sampling perspective of the source-filter model of speech production

We consider the speech production mechanism and the asso- ciated linear source-filter model. For voiced speech sounds in particular, the source/glottal excitation is modeled as a stream of impulses and the filter as a cascade of second-order resonators. We show that the process of sampling speech signals can be modeled as filtering a stream of Dirac impulses (a model for the excitation) with a kernel function (the vocal tract response),and then sampling uniformly. We show that the problem of esti- mating the excitation is equivalent to the problem of recovering a stream of Dirac impulses from samples of a filtered version. We present associated algorithms based on the annihilating filter and also make a comparison with the classical linear prediction technique, which is well known in speech analysis. Results on synthesized as well as natural speech data are presented.

On Selection of Search Space Dimension in Compressive Sampling Matching Pursuit

Compressive Sampling Matching Pursuit (CoSaMP) is one of the popular greedy methods in the emerging field of Compressed Sensing (CS). In addition to the appealing empirical performance, CoSaMP has also splendid theoretical guarantees for convergence. In this paper, we propose a modification in CoSaMP to adaptively choose the dimension of search space in each iteration, using a threshold based approach. Using Monte Carlo simulations, we show that this modification improves the reconstruction capability of the CoSaMP algorithm in clean as well as noisy measurement cases. From empirical observations, we also propose an optimum value for the threshold to use in applications.

Basic features of current induced/shared by cables mounted on down conductors/towers during stroke interception

The telecommunication, broadcasting and other instrumented towers carry power and/or signal cables from their ground end to their upper regions. During a direct hit to the tower, significant induction can occur to these mounted cables. In order to provide adequate protection to the equipments connected to them, protection schemes have been evolved in the literature. Development of more effective protection schemes requires a quantitative knowledge on various parameters. However, such quantitative knowledge is difficult to find at present. Amongst several of these aspects, the present work aims to investigate on the two important aspects: (i) what would be the nature of the induced currents and (ii) what will be the current sharing if as per the practice, the sheath of the cable is connected to the down conductor/tower. These aspects will be useful in design of protection schemes and also in analyzing the field structure around instrumented towers.

A multichannel sampling method for 2-D finite-rate-of-innovation signals

We address the problem of sampling and reconstruction of two-dimensional (2-D) finite-rate-of-innovation (FRI) signals. We propose a three-channel sampling method for efficiently solving the problem. We consider the sampling of a stream of 2-D Dirac impulses and a sum of 2-D unit-step functions. We propose a 2-D causal exponential function as the sampling kernel. By causality in 2-D, we mean that the function has its support restricted to the first quadrant. The advantage of using a multichannel sampling method with causal exponential sampling kernel is that standard annihilating filter or root-finding algorithms are not required. Further, the proposed method has inexpensive hardware implementation and is numerically stable as the number of Dirac impulses increases.

The effect of base roughness on the development of a dense granular flow down an inclined plane

The development of the flow of a granular material down an inclined plane starting from rest is studied as a function of the base roughness. In the simulations, the particles are rough frictional spheres interacting via the Hertz contact law. The rough base is made of a random configuration of fixed spheres with diameter different from the flowing particles, and the base roughness is decreased by decreasing the diameter of the base particles. The transition from an ordered to a disordered flowing state at a critical value of the base particle diameter, first reported by Kumaran and Maheshwari Phys. Fluids 24, 053302 (2012)] for particles with the linear contact model, is observed for the Hertzian contact model as well. The flow development for the ordered and disordered flows is very different. During the development of the disordered flow for the rougher base, there is shearing throughout the height. During the development of the ordered flow for the smoother base, there is a shear layer at the bottom and a plug region with no internal shearing above. In the shear layer, the particles are layered and hexagonally ordered in the plane parallel to the base, and the velocity profile is well approximated by Bagnold law. The flow develops in two phases. In the first phase, the thickness of the shear layer and the maximum velocity increase linearly in time till the shear front reaches the top. In the second phase, after the shear layer encompasses the entire flow, there is a much slower increase in the maximum velocity until the steady state is reached. (C) 2013 AIP Publishing LLC.

Is Granger Causality a Viable Technique for Analyzing fMRI Data?

Multivariate neural data provide the basis for assessing interactions in brain networks. Among myriad connectivity measures, Granger causality (GC) has proven to be statistically intuitive, easy to implement, and generate meaningful results. Although its application to functional MRI (fMRI) data is increasing, several factors have been identified that appear to hinder its neural interpretability: (a) latency differences in hemodynamic response function (HRF) across different brain regions, (b) low-sampling rates, and (c) noise. Recognizing that in basic and clinical neuroscience, it is often the change of a dependent variable (e.g., GC) between experimental conditions and between normal and pathology that is of interest, we address the question of whether there exist systematic relationships between GC at the fMRI level and that at the neural level. Simulated neural signals were convolved with a canonical HRF, down-sampled, and noise-added to generate simulated fMRI data. As the coupling parameters in the model were varied, fMRI GC and neural GC were calculated, and their relationship examined. Three main results were found: (1) GC following HRF convolution is a monotonically increasing function of neural GC; (2) this monotonicity can be reliably detected as a positive correlation when realistic fMRI temporal resolution and noise level were used; and (3) although the detectability of monotonicity declined due to the presence of HRF latency differences, substantial recovery of detectability occurred after correcting for latency differences. These results suggest that Granger causality is a viable technique for analyzing fMRI data when the questions are appropriately formulated.

A Novel Monte-Carlo-Sampling-Based Receiver for Large-Scale Uplink Multiuser MIMO Systems

In this paper, we propose low-complexity algorithms based on Monte Carlo sampling for signal detection and channel estimation on the uplink in large-scale multiuser multiple-input-multiple-output (MIMO) systems with tens to hundreds of antennas at the base station (BS) and a similar number of uplink users. A BS receiver that employs a novel mixed sampling technique (which makes a probabilistic choice between Gibbs sampling and random uniform sampling in each coordinate update) for detection and a Gibbs-sampling-based method for channel estimation is proposed. The algorithm proposed for detection alleviates the stalling problem encountered at high signal-to-noise ratios (SNRs) in conventional Gibbs-sampling-based detection and achieves near-optimal performance in large systems with M-ary quadrature amplitude modulation (M-QAM). A novel ingredient in the detection algorithm that is responsible for achieving near-optimal performance at low complexity is the joint use of a mixed Gibbs sampling (MGS) strategy coupled with a multiple restart (MR) strategy with an efficient restart criterion. Near-optimal detection performance is demonstrated for a large number of BS antennas and users (e. g., 64 and 128 BS antennas and users). The proposed Gibbs-sampling-based channel estimation algorithm refines an initial estimate of the channel obtained during the pilot phase through iterations with the proposed MGS-based detection during the data phase. In time-division duplex systems where channel reciprocity holds, these channel estimates can be used for multiuser MIMO precoding on the downlink. The proposed receiver is shown to achieve good performance and scale well for large dimensions.

Group testing based spectrum hole search using a simple sub-nyquist sampling scheme

In this paper, we consider the problem of finding a spectrum hole of a specified bandwidth in a given wide band of interest. We propose a new, simple and easily implementable sub-Nyquist sampling scheme for signal acquisition and a spectrum hole search algorithm that exploits sparsity in the primary spectral occupancy in the frequency domain by testing a group of adjacent subbands in a single test. The sampling scheme deliberately introduces aliasing during signal acquisition, resulting in a signal that is the sum of signals from adjacent sub-bands. 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. We extend this framework to a multi-stage sensing algorithm that can be employed in a variety of spectrum sensing scenarios, including non-contiguous spectrum hole search. Further, we provide the analytical means to optimize the hypothesis tests with respect to the detection thresholds, number of samples and group size to minimize the detection delay under a given error rate constraint. Depending on the sparsity and SNR, the proposed algorithms can lead to significantly lower detection delays compared to 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. We validate our analytical results via Monte Carlo simulations.

Methionine down-regulates TLR4/MyD88/NF-kappa B signalling in osteoclast precursors to reduce bone loss during osteoporosis

Background and PurposeStudies have demonstrated that a moderate intake of amino acids is associated with development of bone health. Methionine, a sulphur-containing essential amino acid, has been largely implicated for improving cartilage formation, however its physiological significance on bone integrity and functionality have not been elucidated. We investigated whether methionine can prevent osteoporotic bone loss. Experimental ApproachThe anti-resorptive effect of methionine, (250mgkg(-1) body wt administered in drinking water for 10 weeks), was evaluated in ovariectomized (OVX) rats by monitoring changes in bone turnover, formation of osteoclasts from blood-derived mononuclear cells and changes in the synthesis of pro-osteoclastogenic cytokines. Key resultsMethionine improved bone density and significantly decreased the degree of osteoclast development from blood mononuclear cells in OVX rats, as indicated by decreased production of osteoclast markers tartarate resistant acid phosphatase b (TRAP5b) and MIP-1. siRNA-mediated knockdown of myeloid differentiation primary response 88 MyD88], a signalling molecule in the toll-like receptor (TLR) signalling cascade, abolished the synthesis of both TRAP5b and MIP-1 in developing osteoclasts. Methionine supplementation disrupted osteoclast development by inhibiting TLR-4/MyD88/NF-B pathway. Conclusions and ImplicationsTLR-4/MyD88/NF-B signalling pathway is integral for osteoclast development and this is down-regulated in osteoporotic system on methionine treatment. Methionine treatment could be beneficial for the treatment of postmenopausal osteoporosis.

Effects of initial height on the steady-state persistence probability of linear growth models

The effects of the initial height on the temporal persistence probability of steady-state height fluctuations in up-down symmetric linear models of surface growth are investigated. We study the (1 + 1)-dimensional Family model and the (1 + 1)-and (2 + 1)-dimensional larger curvature (LC) model. Both the Family and LC models have up-down symmetry, so the positive and negative persistence probabilities in the steady state, averaged over all values of the initial height h(0), are equal to each other. However, these two probabilities are not equal if one considers a fixed nonzero value of h(0). Plots of the positive persistence probability for negative initial height versus time exhibit power-law behavior if the magnitude of the initial height is larger than the interface width at saturation. By symmetry, the negative persistence probability for positive initial height also exhibits the same behavior. The persistence exponent that describes this power-law decay decreases as the magnitude of the initial height is increased. The dependence of the persistence probability on the initial height, the system size, and the discrete sampling time is found to exhibit scaling behavior.

Analysis of fatigue crack growth in reinforced concrete beams

Mechanical behavior of reinforced concrete members is influenced by the action of unknown crack bridging reactions of rebars. Under cyclic loading, due to progressive growth of cracks, this bridging action contributes to the overall strength, stiffness and hysteretic behavior of the member. In this work, fatigue behavior of reinforced concrete beams are studied using a crack propagation law, developed using dimensional analysis for plain concrete with the effect of reinforcement being simulated through constraint exerted on the crack opening. The parameters considered in the model are fracture toughness, crack length, loading ratio and structural size. A numerical procedure is followed to compute fatigue life of RC beams and the dissipated energy in the steel reinforcement due to the shake down phenomenon under cyclic loading. Through a sensitivity study, it is concluded that the structural size is the most sensitive parameter in the fatigue crack propagation phenomenon. Furthermore, the residual moment carrying capacity of an RC member is determined as a function of crack extension by including the bond-slip mechanism.

Terminalia paniculata bark extract attenuates non-alcoholic fatty liver via down regulation of fatty acid synthase in high fat diet-fed obese rats

Background: This study was performed to understand the possible therapeutic activity of Terminalia paniculata ethanolic extract (TPEE) on non alcoholic fatty liver in rats fed with high fat diet. Methods: Thirty six SD rats were divided into 6 groups (n = 6): Normal control (NC), high fat diet (HFD), remaining four groups were fed on HFD along with different doses of TPEE (100,150 and 200 mg/kg b.wt) or orlistat, for ten weeks. Liver tissue was homogenized and analyzed for lipid profiles, activities of superoxide dismutase (SOD), catalase (CAT) and malondialdehyde (MDA) content. Further, the expression levels of FAS and AMPK-1 alpha were also studied in addition to histopathology examination of liver tissue in all the groups. Results: HFD significantly increased hepatic liver total cholesterol (TC), triglycerides (TG), free fatty acids (FFA) and MDA but decreased the activities of SOD and CAT which were subsequently reversed by supplementation with TPEE in a dose-dependent manner. In addition, TPEE administration significantly down regulated hepatic mRNA expression of FAS but up regulated AMPK-1 alpha compared to HFD alone fed group. Furthermore, western blot analysis of FAS has clearly demonstrated decreased expression of FAS in HFD + TPEE (200 mg/kg b. wt) treated group when compared to HFD group at protein level. Conclusions: Our biochemical studies on hepatic lipid profiles and antioxidant enzyme activities supported by histological and expression studies suggest a potential therapeutic role for TPEE in regulating obesity through FAS.

Evaluation of TRMM PR Sampling Error Over a Subtropical Basin Using Bootstrap Technique

Quantitative use of satellite-derived rainfall products for various scientific applications often requires them to be accompanied with an error estimate. Rainfall estimates inferred from low earth orbiting satellites like the Tropical Rainfall Measuring Mission (TRMM) will be subjected to sampling errors of nonnegligible proportions owing to the narrow swath of satellite sensors coupled with a lack of continuous coverage due to infrequent satellite visits. The authors investigate sampling uncertainty of seasonal rainfall estimates from the active sensor of TRMM, namely, Precipitation Radar (PR), based on 11 years of PR 2A25 data product over the Indian subcontinent. In this paper, a statistical bootstrap technique is investigated to estimate the relative sampling errors using the PR data themselves. Results verify power law scaling characteristics of relative sampling errors with respect to space-time scale of measurement. Sampling uncertainty estimates for mean seasonal rainfall were found to exhibit seasonal variations. To give a practical example of the implications of the bootstrap technique, PR relative sampling errors over a subtropical river basin of Mahanadi, India, are examined. Results reveal that the bootstrap technique incurs relative sampling errors < 33% (for the 2 degrees grid), < 36% (for the 1 degrees grid), < 45% (for the 0.5 degrees grid), and < 57% (for the 0.25 degrees grid). With respect to rainfall type, overall sampling uncertainty was found to be dominated by sampling uncertainty due to stratiform rainfall over the basin. The study compares resulting error estimates to those obtained from latin hypercube sampling. Based on this study, the authors conclude that the bootstrap approach can be successfully used for ascertaining relative sampling errors offered by TRMM-like satellites over gauged or ungauged basins lacking in situ validation data. This technique has wider implications for decision making before incorporating microwave orbital data products in basin-scale hydrologic modeling.

The opportunity for sampling: the ecological context of female mate choice

Female mate choice decisions, which influence sexual selection, involve complex interactions between the 2 sexes and the environment. Theoretical models predict that male movement and spacing in the field should influence female sampling tactics, and in turn, females should drive the evolution of male movement and spacing to sample them optimally. Theoretically, simultaneous sampling of males using the best-of-n or comparative Bayes strategy should yield maximum mating benefits to females. We examined the ecological context of female mate sampling based on acoustic signals in the tree cricket Oecanthus henryi to determine whether the conditions for such optimal strategies were met in the field. These strategies involve recall of the quality and location of individual males, which in turn requires male positions to be stable within a night. Calling males rarely moved within a night, potentially enabling female sampling strategies that require recall. To examine the possibility of simultaneous acoustic sampling of males, we estimated male acoustic active spaces using information on male spacing, call transmission, and female hearing threshold. Males were found to be spaced far apart, and active space overlap was rare. We then examined female sampling scenarios by studying female spacing relative to male acoustic active spaces. Only 15% of sampled females could hear multiple males, suggesting that simultaneous mate sampling is rare in the field. Moreover, the relatively large distances between calling males suggest high search costs, which may favor threshold strategies that do not require memory.