Who really ate the fruit? A novel approach to camera trapping for quantifying frugivory by ruminants

Tropical forest ruminants disperse several plants; yet, their effectiveness as seed dispersers is not systematically quantified. Information on frequency and extent of frugivory by ruminants is lacking. Techniques such as tree watches or fruit traps adapted from avian frugivore studies are not suitable to study terrestrial frugivores, and conventional camera traps provide little quantitative information. We used a novel time-delay camera-trap technique to assess the effectiveness of ruminants as seed dispersers for Phyllanthus emblica at Mudumalai, southern India. After being triggered by animal movement, cameras were programmed to take pictures every 2 min for the next 6 min, yielding a sequence of four pictures. Actual frugivores were differentiated from mere visitors, who did not consume fruit, by comparing the number of fruit remaining across the time-delay photograph sequence. During a 2-year study using this technique, we found that six terrestrial mammals consumed fallen P. emblica fruit. Additionally, seven mammals and one bird species visited fruiting trees but did not consume fallen fruit. Two ruminants, the Indian chevrotain Moschiola indica and chital Axis axis, were P. emblica's most frequent frugivores and they accounted for over 95% of fruit removal, while murid rodents accounted for less than 1%. Plants like P. emblica that are dispersed mainly by large mammalian frugivores are likely to have limited ability to migrate across fragmented landscapes in response to rapidly changing climates. We hope that more quantitative information on ruminant frugivory will become available with a wider application of our time-delay camera-trap technique.

Invariant norm quantifying nonlinear content of Hamiltonian systems

Given a Hamiltonian system, one can represent it using a symplectic map. This symplectic map is specified by a set of homogeneous polynomials which are uniquely determined by the Hamiltonian. In this paper, we construct an invariant norm in the space of homogeneous polynomials of a given degree. This norm is a function of parameters characterizing the original Hamiltonian system. Such a norm has several potential applications. (C) 2010 Elsevier Inc. All rights reserved.

Nanoindentation in Crystal Engineering: Quantifying Mechanical Properties of Molecular Crystals

Nanoindentation is a technique for measuring the elastic modulus and hardness of small amounts of materials. This method, which has been used extensively for characterizing metallic and inorganic solids, is now being applied to organic and metalorganic crystals, and has also become relevant to the subject of crystal engineering, which is concerned with the design of molecular solids with desired properties and functions. Through nanoindentation it is possible to correlate molecular-level properties such as crystal packing, interaction characteristics, and the inherent anisotropy with micro/macroscopic events such as desolvation, domain coexistence, layer migration, polymorphism, and solid-state reactivity. Recent developments and exciting opportunities in this area are highlighted in this Minireview.

Quantifying Vocal Mimicry in the Greater Racket-Tailed Drongo: A Comparison of Automated Methods and Human Assessment

Objective identification and description of mimicked calls is a primary component of any study on avian vocal mimicry but few studies have adopted a quantitative approach. We used spectral feature representations commonly used in human speech analysis in combination with various distance metrics to distinguish between mimicked and non-mimicked calls of the greater racket-tailed drongo, Dicrurus paradiseus and cross-validated the results with human assessment of spectral similarity. We found that the automated method and human subjects performed similarly in terms of the overall number of correct matches of mimicked calls to putative model calls. However, the two methods also misclassified different subsets of calls and we achieved a maximum accuracy of ninety five per cent only when we combined the results of both the methods. This study is the first to use Mel-frequency Cepstral Coefficients and Relative Spectral Amplitude - filtered Linear Predictive Coding coefficients to quantify vocal mimicry. Our findings also suggest that in spite of several advances in automated methods of song analysis, corresponding cross-validation by humans remains essential.

Quantifying the Transmit Diversity Order of Euclidean Distance Based Antenna Selection in Spatial Modulation

In this letter, we quantify the transmit diversity order of the SM system operating in a closed-loop scenario. Specifically, the SM system relying on Euclidean distance based antenna subset selection (EDAS) is considered and the achievable diversity gain is evaluated. Furthermore, the resultant trade-off between the achievable diversity gain and switching gain is studied. Simulation results confirm our theoretical results. Specifically, at a symbol error rate of about 10(-4) the signal-to-noise ratio gain achieved by EDAS is about 7 dB in case of 16-QAM and about 5 dB in case of 64-QAM.

On the sensitivity of elastic waves due to structural damages:Time-frequency based indexing method

Time-frequency analysis of various simulated and experimental signals due to elastic wave scattering from damage are performed using wavelet transform (WT) and Hilbert-Huang transform (HHT) and their performances are compared in context of quantifying the damages. Spectral finite element method is employed for numerical simulation of wave scattering. An analytical study is carried out to study the effects of higher-order damage parameters on the reflected wave from a damage. Based on this study, error bounds are computed for the signals in the spectral and also on the time-frequency domains. It is shown how such an error bound can provide all estimate of error in the modelling of wave propagation in structure with damage. Measures of damage based on WT and HHT is derived to quantify the damage information hidden in the signal. The aim of this study is to obtain detailed insights into the problem of (1) identifying localised damages (2) dispersion of multifrequency non-stationary signals after they interact with various types of damage and (3) quantifying the damages. Sensitivity analysis of the signal due to scattered wave based on time-frequency representation helps to correlate the variation of damage index measures with respect to the damage parameters like damage size and material degradation factors.

Structural Damage Detection Using Modal Curvature and Fuzzy Logic

A fuzzy logic system (FLS) with a new sliding window defuzzifier is proposed for structural damage detection using modal curvatures. Changes in the modal curvatures due to damage are fuzzified using Gaussian fuzzy sets and mapped to damage location and size using the FLS. The first four modal vectors obtained from finite element simulations of a cantilever beam are used for identifying the location and size of damage. Parametric studies show that modal curvatures can be used to accurately locate the damage; however, quantifying the size of damage is difficult. Tests with noisy simulated data show that the method detects damage very accurately at different noise levels and when some modal data are missing.

Urban Growth Analysis Using Spatial and Temporal Data

Urban growth identification, quantification, knowledge of rate and the trends of growth would help in regional planning for better infrastructure provision in environmentally sound way. This requires analysis of spatial and temporal data, which help in quantifying the trends of growth on spatial scale. Emerging technologies such as Remote Sensing, Geographic Information System (GIS) along with Global Positioning System (GPS) help in this regard. Remote sensing aids in the collection of temporal data and GIS helps in spatial analysis. This paper focuses on the analysis of urban growth pattern in the form of either radial or linear sprawl along the Bangalore - Mysore highway. Various GIS base layers such as builtup areas along the highway, road network, village boundary etc. were generated using collateral data such as the Survey of India toposheet, etc. Further, this analysis was complemented with the computation of Shannon's entropy, which helped in identifying prevalent sprawl zone, rate of growth and in delineating potential sprawl locations. The computation Shannon's entropy helped in delineating regions with dispersed and compact growth. This study reveals that the Bangalore North and South taluks contributed mainly to the sprawl with 559% increase in built-up area over a period of 28 years and high degree of dispersion. The Mysore and Srirangapatna region showed 128% change in built-up area and a high potential for sprawl with slightly high dispersion. The degree of sprawl was found to be directly proportional to the distances from the cities.

Effect of soil variability on the bearing capacity of clay and in slope stability problems

Site-specific geotechnical data are always random and variable in space. In the present study, a procedure for quantifying the variability in geotechnical characterization and design parameters is discussed using the site-specific cone tip resistance data (qc) obtained from static cone penetration test (SCPT). The parameters for the spatial variability modeling of geotechnical parameters i.e. (i) existing trend function in the in situ qc data; (ii) second moment statistics i.e. analysis of mean, variance, and auto-correlation structure of the soil strength and stiffness parameters; and (iii) inputs from the spatial correlation analysis, are utilized in the numerical modeling procedures using the finite difference numerical code FLAC 5.0. The influence of consideration of spatially variable soil parameters on the reliability-based geotechnical deign is studied for the two cases i.e. (a) bearing capacity analysis of a shallow foundation resting on a clayey soil, and (b) analysis of stability and deformation pattern of a cohesive-frictional soil slope. The study highlights the procedure for conducting a site-specific study using field test data such as SCPT in geotechnical analysis and demonstrates that a few additional computations involving soil variability provide a better insight into the role of variability in designs.

Discovering mentorship information from author collaboration networks

Researchers are assessed from a researcher-centric perspective - by quantifying a researcher's contribution to the field. Citation and publication counts are some typical examples. We propose a student-centric measure to assess researchers on their mentoring abilities. Our approach quantifies benefits bestowed by researchers upon their students by characterizing the publication dynamics of research advisor-student interactions in author collaboration networks. We show that our measures could help aspiring students identify research advisors with proven mentoring skills. Our measures also help in stratification of researchers with similar ranks based on typical indices like publication and citation counts while being independent of their direct influences.

Comparative measurements of HV impulses to evaluate different sets of response parameters

Results are reported of comparative measurements made in 14 HV (high-voltage) laboratories in ten different countries. The theory of the proposed methods of characterizing the dynamic behavior is given, and the parameters to be used are discussed. Comparative measurements made using 95 systems based on 53 dividers are analyzed. This analysis shows that many of the system now in use, even though they fulfil the basic response requirements of the standards, do not meet the accuracy requirements. Because no transfer measurements were made between laboratories, there is no way to detect similar errors in both the system under test and the reference system. Hence, the situation may be worse than reported. This has led to the recommendation that comparative measurements should be the main route for quantifying industrial impulse measuring systems

Signal characterization using fractal dimension

Fractal Dimensions (FD) are one of the popular measures used for characterizing signals. They have been used as complexity measures of signals in various fields including speech and biomedical applications. However, proper interpretation of such analyses has not been thoroughly addressed. In this paper, we study the effect of various signal properties on FD and interpret results in terms of classical signal processing concepts such as amplitude, frequency, number of harmonics, noise power and signal bandwidth. We have used Higuchi's method for estimating FDs. This study may help in gaining a better understanding of the FD complexity measure itself, and for interpreting changing structural complexity of signals in terms of FD. Our results indicate that FD is a useful measure in quantifying structural changes in signal properties.

Reactivity Of Silica From Rice Husk With Lime

The paper correlates the reactivity of rice husk ash with its physicochemical properties such as crystallinity, surface area, microstructure, particle size distribution, porosity and solubility. These properties, in tum, are dependent on the time-temperature conditions under which the ash is prepared. It is found that the reactivity of the ash cannot be quantified by any one of these parameters alone, though they all indicate it qualitatively. Therefore, a method for quantifying this property was developed, by which the Reactivity Index is obtained. There is only a gradual change in the reactivity index of RHA with ashing temperature, as in many other properties, like surface area, porosity and total volume of gas absorbed by unit mass of the silica ash. This reactive index is found to be useful in determining the optimum ash/lime ratios required to give the best performance for RHA-lime composites.

Multivariate nonlinear ensemble prediction of daily chaotic rainfall with climate inputs

The basic characteristic of a chaotic system is its sensitivity to the infinitesimal changes in its initial conditions. A limit to predictability in chaotic system arises mainly due to this sensitivity and also due to the ineffectiveness of the model to reveal the underlying dynamics of the system. In the present study, an attempt is made to quantify these uncertainties involved and thereby improve the predictability by adopting a multivariate nonlinear ensemble prediction. Daily rainfall data of Malaprabha basin, India for the period 1955-2000 is used for the study. It is found to exhibit a low dimensional chaotic nature with the dimension varying from 5 to 7. A multivariate phase space is generated, considering a climate data set of 16 variables. The chaotic nature of each of these variables is confirmed using false nearest neighbor method. The redundancy, if any, of this atmospheric data set is further removed by employing principal component analysis (PCA) method and thereby reducing it to eight principal components (PCs). This multivariate series (rainfall along with eight PCs) is found to exhibit a low dimensional chaotic nature with dimension 10. Nonlinear prediction employing local approximation method is done using univariate series (rainfall alone) and multivariate series for different combinations of embedding dimensions and delay times. The uncertainty in initial conditions is thus addressed by reconstructing the phase space using different combinations of parameters. The ensembles generated from multivariate predictions are found to be better than those from univariate predictions. The uncertainty in predictions is decreased or in other words predictability is increased by adopting multivariate nonlinear ensemble prediction. The restriction on predictability of a chaotic series can thus be altered by quantifying the uncertainty in the initial conditions and also by including other possible variables, which may influence the system. (C) 2011 Elsevier B.V. All rights reserved.

Experimental investigation of link between growth and decay of fiber Bragg gratings

We report here an experimental investigation for establishing and quantifying a link between the growth and decay characteristics of fiber Bragg gratings. One of the key aspects of our work is the determination of the defect energy distribution from the grating characteristics measured during their fabrication. We observe a strong correlation between the growth-based defect energy distribution and that obtained through accelerated aging experiments, paving the way for predicting the decay characteristics of fiber Bragg gratings from their growth data. Such a prediction is significant in simplifying the postfabrication steps required to enhance the thermal stability of fiber Bragg gratings. (c) 2011 Optical Society of America