Distribution, relative abundance, and conservation status of Asian elephants in Karnataka, southern India

Karnataka state in southern India supports a globally significant and the country's largest population of the Asian elephant Elephas maximus. A reliable map of Asian elephant distribution and measures of spatial variation in their abundance, both vital needs for conservation and management action, are unavailable not only in Karnataka, but across its global range. Here, we use various data gathered between 2000 and 2015 to map the distribution of elephants in Karnataka at the scale of the smallest forest management unit, the `beat', while also presenting data on elephant dung density for a subset of `elephant beats.' Elephants occurred in 972 out of 2855 forest beats of Karnataka. Sixty percent of these 972 beats and 55% of the forest habitat lay outside notified protected areas (PM), and included lands designated for agricultural production and human dwelling. While median elephant dung density inside protected areas was nearly thrice as much as outside, elephants routinely occurred in or used habitats outside PM where human density, land fraction under cultivation, and the interface between human-dominated areas and forests were greater. Based on our data, it is clear that India's framework for elephant conservation which legally protects the species wherever it occurs, but protects only some of its habitats while being appropriate in furthering their conservation within PM, seriously falters in situations where elephants reside in and/or seasonally use areas outside PAs. Attempts to further elephant conservation in production and dwelling areas have extracted high costs in human, elephant, material and monetary terms in Karnataka. In such settings, conservation planning exercises are necessary to determine where the needs of elephants or humans must take priority over the other, and to achieve that in a manner that is based not only on reliable scientific data but also on a process of public reasoning. (C) 2015 Elsevier Ltd. All rights reserved.

Investigation of orographic features influencing spatial distribution of rainfall over the Western Ghats of India using satellite data

Using remotely sensed Tropical Rainfall Measuring Mission (TRMM) 3B42 rainfall and topographic data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Digital Elevation Model (DEM), the impact of oroghraphical aspects such as topography, spatial variability of elevation and altitude of apexes are examined to investigate capacious summer monsoon rainfall over the Western Ghats (WG) of India. TRMM 3B42 v7 rainfall data is validated with Indian Meteorological Department (IMD) gridded rainfall data at 0.5 degrees resolution over the WG. The analysis of spatial pattern of monsoon rainfall with orography of the WG ascertains that the grade of orographic precipitation depends mainly on topography of the mountain barrier followed by steepness of windward side slope and altitude of the mountain. Longer and broader, i.e. cascaded topography, elevated summits and gradually increasing slopes impel the enhancement in precipitation. Comparing topography of various states of the WG, it has been observed that windward side of Karnataka receives intense rainfall in the WG during summer monsoon. It has been observed that the rainfall is enhanced before the peak of the mountain and confined up to the height about 800m over the WG. In addition to this, the spatial distribution of heavy and very heavy rainfall events in the last 14 years has also been explored. Heavy and very heavy rain events on this hilly terrain are categorized with a threshold of precipitation (R) in the range 150>R>120mmday(-1) and exceeding 150mmday(-1) using probability distribution of TRMM 3B42 v7 rainfall. The areas which are prone to heavy precipitation are identified. The study would help policy makers to manage the hazard scenario and, to improve weather predictions on mountainous terrain of the WG.

Inner Bound on the GDOF of the K-User MIMO Gaussian Symmetric Interference Channel

The K-user multiple input multiple output (MIMO) Gaussian symmetric interference channel where each transmitter has M antennas and each receiver has N antennas is studied from a generalized degrees of freedom (GDOF) perspective. An inner bound on the GDOF is derived using a combination of techniques such as treating interference as noise, zero forcing (ZF) at the receivers, interference alignment (IA), and extending the Han-Kobayashi (HK) scheme to K users, as a function of the number of antennas and the log INR/log SNR level. Several interesting conclusions are drawn from the derived bounds. It is shown that when K > N/M + 1, a combination of the HK and IA schemes performs the best among the schemes considered. When N/M < K <= N/M + 1, the HK-scheme outperforms other schemes and is found to be GDOF optimal in many cases. In addition, when the SNR and INR are at the same level, ZF-receiving and the HK-scheme have the same GDOF performance.

Outer Bounds on the Sum Rate of the K-User MIMO Gaussian Interference Channel

This paper derives outer bounds on the sum rate of the K-user MIMO Gaussian interference channel (GIC). Three outer bounds are derived, under different assumptions of cooperation and providing side information to receivers. The novelty in the derivation lies in the careful selection of side information, which results in the cancellation of the negative differential entropy terms containing signal components, leading to a tractable outer bound. The overall outer bound is obtained by taking the minimum of the three outer bounds. The derived bounds are simplified for the MIMO Gaussian symmetric IC to obtain outer bounds on the generalized degrees of freedom (GDOF). The relative performance of the bounds yields insight into the performance limits of multiuser MIMO GICs and the relative merits of different schemes for interference management. These insights are confirmed by establishing the optimality of the bounds in specific cases using an inner bound on the GDOF derived by the authors in a previous work. It is also shown that many of the existing results on the GDOF of the GIC can be obtained as special cases of the bounds, e. g., by setting K = 2 or the number of antennas at each user to 1.

Study of Wrist Pulse Signals Using a Bi-Modal Gaussian Model

Wrist pulse signals contain important information about the health of a person and hence diagnosis based on pulse signals has assumed great importance. In this paper we demonstrate the efficacy of a two term Gaussian model to extract information from pulse signals. Results have been obtained by conducting experiments on several subjects to record wrist pulse signals for the cases of before exercise and after exercise. Parameters have been extracted from the recorded signals using the model and a paired t-test is performed, which shows that the parameters are significantly different between the two groups. Further, a recursive cluster elimination based support vector machine is used to perform classification between the groups. An average classification accuracy of 99.46% is obtained, along with top classifiers. It is thus shown that the parameters of the Gaussian model show changes across groups and hence the model is effective in distinguishing the changes taking place due to the two different recording conditions. The study has potential applications in healthcare.

Robust Savitzky-Golay Filters

Local polynomial approximation of data is an approach towards signal denoising. Savitzky-Golay (SG) filters are finite-impulse-response kernels, which convolve with the data to result in polynomial approximation for a chosen set of filter parameters. In the case of noise following Gaussian statistics, minimization of mean-squared error (MSE) between noisy signal and its polynomial approximation is optimum in the maximum-likelihood (ML) sense but the MSE criterion is not optimal for non-Gaussian noise conditions. In this paper, we robustify the SG filter for applications involving noise following a heavy-tailed distribution. The optimal filtering criterion is achieved by l(1) norm minimization of error through iteratively reweighted least-squares (IRLS) technique. It is interesting to note that at any stage of the iteration, we solve a weighted SG filter by minimizing l(2) norm but the process converges to l(1) minimized output. The results show consistent improvement over the standard SG filter performance.

Projected climate change impacts on vegetation distribution over Kashmir Himalayas

Despite high vulnerability, the impact of climate change on Himalayan ecosystem has not been properly investigated, primarily due to the inadequacy of observed data and the complex topography. In this study, we mapped the current vegetation distribution in Kashmir Himalayas from NOAA AVHRR and projected it under A1B SRES, RCP-4.5 and RCP-8.5 climate scenarios using the vegetation dynamics model-IBIS at a spatial resolution of 0.5A degrees. The distribution of vegetation under the changing climate was simulated for the 21st century. Climate change projections from the PRECIS experiment using the HADRM3 model, for the Kashmir region, were validated using the observed climate data from two observatories. Both the observed as well as the projected climate data showed statistically significant trends. IBIS was validated for Kashmir Himalayas by comparing the simulated vegetation distribution with the observed distribution. The baseline simulated scenario of vegetation (1960-1990), showed 87.15 % agreement with the observed vegetation distribution, thereby increasing the credibility of the projected vegetation distribution under the changing climate over the region. According to the model projections, grasslands and tropical deciduous forests in the region would be severely affected while as savannah, shrubland, temperate evergreen broadleaf forest, boreal evergreen forest and mixed forest types would colonize the area currently under the cold desert/rock/ice land cover types. The model predicted that a substantial area of land, presently under the permanent snow and ice cover, would disappear by the end of the century which might severely impact stream flows, agriculture productivity and biodiversity in the region.

Factors affecting distribution of fish within a tidally drained mangrove forest in the Andaman and Nicobar Islands, India

Mangrove forests in meso-tidal areas are completely drained during low tides, forming only temporary habitats for fish. We hypothesised that in such temporary habitats, where stranding risks are high, distance from tidal creeks that provided access to inundated areas during receding tides would be the primary determinant of fish distribution. Factors such as depth, root density and shade were hypothesised to have secondary effects. We tested these hypotheses in a tidally drained mangrove patch in the Andaman Islands, India. Using stake nets, we measured fish abundance and species richness relative to distance from creeks, root density/m(2), shade, water depth and size (total length) of fish. We also predicted that larger fish (including potential predators) would be closer to creeks, as they faced a greater chance of mortality if stranded. Thus we conducted tethering trials to examine if predation would be greater close to the creeks. Generalised linear mixed effects models showed that fish abundance was negatively influenced by increasing creek distance interacting with fish size and positively influenced by depth. Quantile regression analysis showed that species richness was limited by increasing creek distance. Proportion of predation was greatest close to the creeks (0-25 m) and declined with increasing distance. Abundance was also low very close to the creeks, suggesting that close to the creeks predation pressure may be an important determinant of fish abundance. The overall pattern however indicates that access to permanently inundated areas, may be an important determinant of fish distribution in tidally drained mangrove forests.

Fluctuation theory of Rashba Fermi gases: Gaussian and beyond

Fermi gases with generalized Rashba spin-orbit coupling induced by a synthetic gauge field have the potential of realizing many interesting states, such as rashbon condensates and topological phases. Here, we address the key open problem of the fluctuation theory of such systems and demonstrate that beyond-Gaussian effects are essential to capture the finite temperature physics of such systems. We obtain their phase diagram by constructing an approximate non-Gaussian theory. We conclusively establish that spin-orbit coupling can enhance the exponentially small transition temperature (T-c) of a weakly attracting superfluid to the order of the Fermi temperature, paving a pathway towards high T-c superfluids.

Patch-based and multiresolution optimum bilateral filters for denoising images corrupted by Gaussian noise

We propose optimal bilateral filtering techniques for Gaussian noise suppression in images. To achieve maximum denoising performance via optimal filter parameter selection, we adopt Stein's unbiased risk estimate (SURE)-an unbiased estimate of the mean-squared error (MSE). Unlike MSE, SURE is independent of the ground truth and can be used in practical scenarios where the ground truth is unavailable. In our recent work, we derived SURE expressions in the context of the bilateral filter and proposed SURE-optimal bilateral filter (SOBF). We selected the optimal parameters of SOBF using the SURE criterion. To further improve the denoising performance of SOBF, we propose variants of SOBF, namely, SURE-optimal multiresolution bilateral filter (SMBF), which involves optimal bilateral filtering in a wavelet framework, and SURE-optimal patch-based bilateral filter (SPBF), where the bilateral filter parameters are optimized on small image patches. Using SURE guarantees automated parameter selection. The multiresolution and localized denoising in SMBF and SPBF, respectively, yield superior denoising performance when compared with the globally optimal SOBF. Experimental validations and comparisons show that the proposed denoisers perform on par with some state-of-the-art denoising techniques. (C) 2015 SPIE and IS&T

Asymptotic Bounds on the Power-Delay Tradeoff for Fading Point-to-Point Links From Geometric Bounds on the Stationary Distribution of the Queue Length

The optimal power-delay tradeoff is studied for a time-slotted independently and identically distributed fading point-to-point link, with perfect channel state information at both transmitter and receiver, and with random packet arrivals to the transmitter queue. It is assumed that the transmitter can control the number of packets served by controlling the transmit power in the slot. The optimal tradeoff between average power and average delay is analyzed for stationary and monotone transmitter policies. For such policies, an asymptotic lower bound on the minimum average delay of the packets is obtained, when average transmitter power approaches the minimum average power required for transmitter queue stability. The asymptotic lower bound on the minimum average delay is obtained from geometric upper bounds on the stationary distribution of the queue length. This approach, which uses geometric upper bounds, also leads to an intuitive explanation of the asymptotic behavior of average delay. The asymptotic lower bounds, along with previously known asymptotic upper bounds, are used to identify three new cases where the order of the asymptotic behavior differs from that obtained from a previously considered approximate model, in which the transmit power is a strictly convex function of real valued service batch size for every fade state.

Spectral intensity distribution of trapped

To calculate static response properties of a many-body system, local density approximation (LDA) can be safely applied. But, to obtain dynamical response functions, the applicability of LDA is limited bacause dynamics of the system needs to be considered as well. To examine this in the context of cold atoms, we consider a system of non-interacting spin4 fermions confined by a harmonic trapping potential. We have calculated a very important response function, the spectral intensity distribution function (SIDF), both exactly and using LDA at zero temperature and compared with each other for different dimensions, trap frequencies and momenta. The behaviour of the SIDF at a particular momentum can be explained by noting the behaviour of the density of states (DoS) of the free system (without trap) in that particular dimension. The agreement between exact and LDA SIDFs becomes better with increase in dimensions and number of particles.

Strategy for Obtaining Bimodal Bubble Size Distribution in Water Blown Polyurethane Foams

Polyurethane foams with multimodal cell distribution exhibit superior mechanical and thermal properties. A technique for generating bimodal bubble size distribution exists in the literature, but it uses supercritical conditions. In the present work, an alternative based on milder operating conditions is proposed. It is a modification of reaction injection molding (RIM), using reactants already seeded with bubbles. The number density of the seeds determines if two nucleating events can occur. A bimodal bubble size distribution is obtained when this happens A mathematical model is used to test this hypothesis by simulating water blown free rise polyurethane foams. The effects of initial concentration of bubbles, temperature of the reactants, and the weight fraction of water are studied. The study reveals that for certain concentrations of initial number of bubbles, when initial temperature and weight fraction of water are high, it is possible to obtain a second nucleation event, leading to bimodal bubble size distribution.

Tailor-Made Distribution of Nanoparticles in Blend Structure toward Outstanding Electromagnetic Interference Shielding

Engineering blend structure with tailor-made distribution of nanoparticles is the prime requisite to obtain materials with extraordinary properties. Herein, a unique strategy of distributing nanoparticles in different phases of a blend structure has resulted in >99% blocking of incoming electromagnetic (EM) radiation. This is accomplished by designing a ternary polymer blend structure using polycarbonate (PC), poly(vinylidene fluoride) (PVDF), and poly(methyl methacrylate) (PMMA) to simultaneously improve the structural, electrical, and electromagnetic interference shielding (EMI). The blend structure was made conducting by preferentially localizing the multi-wall nanotubes (MWNTs) in the PVDF phase. By taking advantage of pp stacking MWNTs was noncovalently modified with an imidazolium based ionic liquid (IL). Interestingly, the enhanced dispersion of IL-MWNTs in PVDF improved the electrical conductivity of the blends significantly. While one key requisite to attenuate EM radiation (i.e., electrical conductivity) was achieved using MWNTs, the magnetic properties of the blend structure was tuned by introducing barium ferrite (BaFe) nanoparticles, which can interact with the incoming EM radiation. By suitably modifying the surface of BaFe nanoparticles, we can tailor their localization under the macroscopic processing condition. The precise localization of BaFe nanoparticles in the PC phase, due to nucleophilic substitution reaction, and the MWNTs in the PVDF phase not only improved the conductivity but also facilitated in absorption of the incoming microwave radiation due to synergetic effect from MWNT and BaFe. The shielding effectiveness (SE) was measured in X and K-u band, and an enhanced SE of -37 dB was noted at 18 GHz frequency. PMMA, which acted as an interfacial modifier in PC/PVDF blends further, resulting in a significant enhancement in the mechanical properties besides retaining high SE. This study opens a new avenue in designing mechanically strong microwave absorbers with a suitable combination of materials.

Quark and gluon distribution functions in a viscous quark-gluon plasma medium and dilepton production via q(q)over-bar annihilation

Viscous modifications to the thermal distributions of quark-antiquarks and gluons have been studied in a quasiparticle description of the quark-gluon-plasma medium created in relativistic heavy-ion collision experiments. The model is described in terms of quasipartons that encode the hot QCD medium effects in their respective effective fugacities. Both shear and bulk viscosities have been taken in to account in the analysis, and the modifications to thermal distributions have been obtained by modifying the energy-momentum tensor in view of the nontrivial dispersion relations for the gluons and quarks. The interactions encoded in the equation of state induce significant modifications to the thermal distributions. As an implication, the dilepton production rate in the q (q) over bar annihilation process has been investigated. The equation of state is found to have a significant impact on the dilepton production rate along with the viscosities.