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.

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.

Redox regulation of protein tyrosine phosphatase 1B (PTP1B): Importance of steric and electronic effects on the unusual cyclization of the sulfenic acid intermediate to a sulfenyl amide

The redox regulation of protein tyrosine phosphatase 1B (PTP1B) via the unusual transformation of its sulfenic acid (PTP1B-SOH) to a cyclic sulfenyl amide intermediate is studied by using small molecule chemical models. These studies suggest that the sulfenic acids derived from the H2O2-mediated reactions o-amido thiophenols do not efficiently cyclize to sulfenyl amides and the sulfenic acids produced in situ can be trapped by using methyl iodide. Theoretical calculations suggest that the most stable conformer of such sulfenic acids are stabilized by n(O) -> sigma* (S-OH) orbital interactions, which force the -OH group to adopt a position trans to the S center dot center dot center dot O interaction, leading to an almost linear arrangement of the O center dot center dot center dot S-O moiety and this may be the reason for the slow cyclization of such sulfenic acids to their corresponding sulfenyl amides. On the other hand, additional substituents at the 6-position of o-amido phenylsulfenic acids that can induce steric environment and alter the electronic properties around the sulfenic acid moiety by S center dot center dot center dot N or S center dot center dot center dot O nonbonded interactions destabilize the sulfenic acids by inducing strain in the molecule. This may lead to efficient the cyclization of such sulfenic acids. This model study suggests that the amino acid residues in the close proximity of the sulfenic acid moiety in PTP1B may play an important role in the cyclization of PTP1B-SOH to produce the corresponding sulfenyl amide.

Species importance in a heterospecific foraging association network

There is a growing recognition of the need to integrate non-trophic interactions into ecological networks for a better understanding of whole-community organization. To achieve this, the first step is to build networks of individual non-trophic interactions. In this study, we analyzed a network of interdependencies among bird species that participated in heterospecific foraging associations (flocks) in an evergreen forest site in the Western Ghats, India. We found the flock network to contain a small core of highly important species that other species are strongly dependent on, a pattern seen in many other biological networks. Further, we found that structural importance of species in the network was strongly correlated to functional importance of species at the individual flock level. Finally, comparisons with flock networks from other Asian forests showed that the same taxonomic groups were important in general, suggesting that species importance was an intrinsic trait and not dependent on local ecological conditions. Hence, given a list of species in an area, it may be possible to predict which ones are likely to be important. Our study provides a framework for the investigation of other heterospecific foraging associations and associations among species in other non-trophic contexts.

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.

Image deconvolution research: its scope and importance in live cell microscopy

Fluorescence microscopy has become an indispensable tool in cell biology research due its exceptional specificity and ability to visualize subcellular structures with high contrast. It has highest impact when applied in 4D mode, i.e. when applied to record 3D image information as a function of time, since it allows the study of dynamic cellular processes in their native environment. The main issue in 4D fluorescence microscopy is that the phototoxic effect of fluorescence excitation gets accumulated during 4D image acquisition to the extent that normal cell functions are altered. Hence to avoid the alteration of normal cell functioning, it is required to minimize the excitation dose used for individual 2D images constituting a 4D image. Consequently, the noise level becomes very high degrading the resolution. According to the current status of technology, there is a minimum required excitation dose to ensure a resolution that is adequate for biological investigations. This minimum is sufficient to damage light-sensitive cells such as yeast if 4D imaging is performed for an extended period of time, for example, imaging for a complete cell cycle. Nevertheless, our recently developed deconvolution method resolves this conflict forming an enabling technology for visualization of dynamical processes of light-sensitive cells for durations longer than ever without perturbing normal cell functioning. The main goal of this article is to emphasize that there are still possibilities for enabling newer kinds of experiment in cell biology research involving even longer 4D imaging, by only improving deconvolution methods without any new optical technologies.

Crystal structures of SCP2-thiolases of Trypanosomatidae, human pathogens causing widespread tropical diseases: the importance for catalysis of the cysteine of the unique HDCF loop

Thiolases are essential CoA-dependent enzymes in lipid metabolism. In the present study we report the crystal structures of trypanosomal and leishmanial SCP2 (sterol carrier protein, type-2)-thiolases. Trypanosomatidae cause various widespread devastating (sub)-tropical diseases, for which adequate treatment is lacking. The structures reveal the unique geometry of the active site of this poorly characterized subfamily of thiolases. The key catalytic residues of the classical thiolases are two cysteine residues, functioning as a nucleophile and an acid/base respectively. The latter cysteine residue is part of a CxG motif. Interestingly, this cysteine residue is not conserved in SCP2-thiolases. The structural comparisons now show that in SCP2-thiolases the catalytic acid/base is provided by the cysteine residue of the HDCF motif, which is unique for this thiolase subfamily. This HDCF cysteine residue is spatially equivalent to the CxG cysteine residue of classical thiolases. The HDCF cysteine residue is activated for acid/base catalysis by two main chain NH-atoms, instead of two water molecules, as present in the CxG active site. The structural results have been complemented with enzyme activity data, confirming the importance of the HDCF cysteine residue for catalysis. The data obtained suggest that these trypanosomatid SCP2-thiolases are biosynthetic thiolases. These findings provide promise for drug discovery as biosynthetic thiolases catalyse the first step of the sterol biosynthesis pathway that is essential in several of these parasites.

Photophysical, electrochemical and solid state properties of diketopyrrolopyrrole based molecular materials: importance of the donor group

Diketopyrrolopyrrole (DPP) based molecular semiconductors have emerged as promising materials for high performance active layers in organic solar cells. It is imperative to comprehend the origin of such a property by investigating the fundamental structure property correlation. In this report we have investigated the role of the donor group in DPP based donor-acceptor- donor (D-A-D) structure to govern the solid state, photophysical and electrochemical properties. We have prepared three derivatives of DPP with varying strengths of the donor groups, such as phenyl (PDPP-Hex), thiophene (TDPP-Hex) and selenophene (SeDPP-Hex). The influence of the donor units on the solid state packing was studied by single crystal X-ray diffraction. The photophysical, electrochemical and density functional theory ( DFT) results were combined to elucidate the structural and electronic properties of three DPP derivatives. We found that these DPP derivatives crystallized in the monoclinic space group P21/c and show herringbone packing in the crystal lattice. The derivatives exhibit weak p-p stacking interactions as two neighboring molecules slip away from each other with varied torsional angles at the donor units. The high torsional angle of 32 degrees ( PDPP-Hex) between the phenyl and lactam ring results in weak intramolecular interactions between the donor and acceptor, while TDPP-Hex and SeDPP-Hex show lower torsional angles of 9 degrees and 12 degrees with a strong overlap between the donor and acceptor units. The photophysical properties reveal that PDPP-Hex exhibits a high Stokes shift of 0.32 eV and SeDPP- Hex shows a high molar absorption co-efficient of 33 600 L mol -1 1 cm -1 1 with a low band gap of similar to 2.2 eV. The electrochemical studies of SeDPP- Hex indicate the pronounced effect of selenium in stabilizing the LUMO energy levels and this further emphasizes the importance of chalcogens in developing new n-type organic semiconductors for optoelectronic devices.

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.

The importance of crystallographic texture in the use of titanium as an orthopedic biomaterial

Crystallographic texture is perceived to play an important role in controlling material properties. However, the influence of texture in modulating the properties of biomedical materials has not been well investigated. In this work, commercially pure titanium (cp-Ti) was processed through six different routes to generate a variety of textures. The effect of texture on mechanical properties, corrosion behavior, cell proliferation and osteogenesis was characterized for potential use in orthopedic applications. The presence of closely packed, low-energy crystallographic planes at the material surface was influenced by the volume fraction of the components in the overall texture, thereby influencing surface energy and corrosion behavior. Texture modulated osteoblast proliferation through variations in surface water wettability. It also affected mineralization by possibly influencing the coherency between the substrate and calcium phosphate deposits. This study demonstrates that crystallographic texture can be an important tool in improving the properties of biomaterials to achieve the enhanced performance of biomedical implants.

Influence of Spatial Variability on Pavement Responses Using Latin Hypercube Sampling on Two-Dimensional Random Fields

Although uncertainties in material properties have been addressed in the design of flexible pavements, most current modeling techniques assume that pavement layers are homogeneous. The paper addresses the influence of the spatial variability of the resilient moduli of pavement layers by evaluating the effect of the variance and correlation length on the pavement responses to loading. The integration of the spatially varying log-normal random field with the finite-difference method has been achieved through an exponential autocorrelation function. The variation in the correlation length was found to have a marginal effect on the mean values of the critical strains and a noticeable effect on the standard deviation which decreases with decreases in correlation length. This reduction in the variance arises because of the spatial averaging phenomenon over the softer and stiffer zones generated because of spatial variability. The increase in the mean value of critical strains with decreasing correlation length, although minor, illustrates that pavement performance is adversely affected by the presence of spatially varying layers. The study also confirmed that the higher the variability in the pavement layer moduli, introduced through a higher value of coefficient of variation (COV), the higher the variability in the pavement response. The study concludes that ignoring spatial variability by modeling the pavement layers as homogeneous that have very short correlation lengths can result in the underestimation of the critical strains and thus an inaccurate assessment of the pavement performance. (C) 2014 American Society of Civil Engineers.