Long-Term Environmental Correlates of Invasion by Lantana camara (Verbenaceae) in a Seasonally Dry Tropical Forest

Invasive species, local plant communities and invaded ecosystems change over space and time. Quantifying this change may lead to a better understanding of the ecology and the effective management of invasive species. We used data on density of the highly invasive shrub Lantana camara (lantana) for the period 1990-2008 from a 50 ha permanent plot in a seasonally dry tropical forest of Mudumalai in southern India. We used a cumulative link mixed-effects regression approach to model the transition of lantana from one qualitative density state to another as a function of biotic factors such as indicators of competition from local species (lantana itself, perennial grasses, invasive Chromolaena odorata, the native shrub Helicteres isora and basal area of native trees) and abiotic factors such as fire frequency, inter-annual variability of rainfall and relative soil moisture. The density of lantana increased substantially during the study period. Lantana density was negatively associated with the density of H. isora, positively associated with basal area of native trees, but not affected by the presence of grasses or other invasive species. In the absence of fire, lantana density increased with increasing rainfall. When fires occurred, transitions to higher densities occurred at low rainfall values. In drier regions, lantana changed from low to high density as rainfall increased while in wetter regions of the plot, lantana persisted in the dense category irrespective of rainfall. Lantana seems to effectively utilize resources distributed in space and time to its advantage, thus outcompeting local species and maintaining a population that is not yet self-limiting. High-risk areas and years could potentially be identified based on inferences from this study for facilitating management of lantana in tropical dry forests.

Molecular dynamic simulations of elastomer structure and its influence on anisotropic stress under time-varying strain

We investigate the evolution of polymer structure and its influence on uniaxial anisotropic stress under time-varying uniaxial strain, and the role of external control variables such as temperature, strain rate, chain length, and density, using molecular dynamics simulation. At temperatures higher than glass transition, stress anisotropy in the system is reduced even though the bond stretch is greater at higher temperatures. There is a significant increase in the stress level with increasing density. At higher densities, the uncoiling of the chains is suppressed and the major contribution to the deformation is by internal deformation of the chains. At faster rates of loading stress anisotropy increases. The deformation mechanism is mostly due to bond stretch and bond bending rather than overall shape and size. Stress levels increase with longer chain length. There is a critical value of the functionality of the cross-linkers beyond which the uniaxial stress developed increases caused primarily by bond stretching due to increased constraint on the motion of the monomers. Stacking of the chains in the system also plays a dominant role in the behaviour in terms of excluded volume interactions. Low density, high temperature, low values of functionality of cross-linkers, and short chain length facilitate chain uncoiling and chain slipping in cross-linked polymers.

Transverse single spin asymmetry in e+p↑→e+J/ψ+X and transverse momentum dependent evolution of the Sivers function

We extend our analysis of transverse single spin asymmetry in electroproduction of J/ψ to include the effect of the scale evolution of the transverse momentum dependent (TMD) parton distribution functions and gluon Sivers function. We estimate single spin asymmetry for JLab, HERMES, COMPASS, and eRHIC energies using the color evaporation model of charmonium production, using an analytically obtained approximate solution of TMD evolution equations discussed in the literature. We find that there is a reduction in the asymmetry compared with our predictions for the earlier case considered by us, wherein the Q2 dependence came only from DGLAP evolution of the unpolarized gluon densities and a different parametrization of the TMD Sivers function was used.

Hydro-mechanical characterization of Barmer 1 bentonite from Rajasthan, India

The conceptual model for deep geological disposal of high level nuclear waste (HLW) is based on multiple barrier system consisting of natural and engineered barriers. Buffer/backfill material is regarded as the most important engineered barrier in HLW repositories. Due to large swelling ability, cation adsorption capacity, and low permeability bentonite is considered as suitable buffer material in HLW repositories. Japan has identified Kunigel VI bentonite, South Korea - Kyungju bentonite, China - GMZ bentonite, Belgium - FoCa clay, Sweden - MX-80 bentonite, Spain - FEBEX bentonite and Canada - Avonseal bentonite as candidate bentonite buffer for deep geological repository program. An earlier study on Indian bentonites by one of the authors suggested that bentonite from Barmer district of Rajasthan (termed Barmer 1 bentonite), India is suited for use as buffer material in deep geological repositories. However, the hydro-mechanical properties of the Barmer 1 bentonite are unavailable. This paper characterizes Barmer 1 bentonite for hydro-mechanical properties, such as, swell pressure, saturated permeability, soil water characteristic curve (SWCC) and unconfined compression strength at different dry densities. The properties of Barmer 1 bentonite were compared with bentonite buffers reported in literature and equations for designing swell pressure and saturated permeability coefficient of bentonite buffers were arrived at. (C) 2013 Elsevier B.V. All rights reserved.

Sputter Deposited High Capacity Li2-xMnO3-y Films for Thin Film Battery Application

Lithium manganese oxide (Li2-xMnO3-y) thin films have been deposited from activated Li2MnO3 powder by radio frequency magnetron sputtering for the first time in the literature and subjected to electrochemical characterization. Physicochemical characterization by X-ray diffraction has revealed the formation of the thin films with crystallographic phase identical to that of the powder target made of Li2-xMnO3-y. The Li:Mn atomic ratio for the powder and film are calculated by X-ray photoelectron spectroscopy and it is found to be 1.6:1.0. From galvanostatic charge discharge studies, a specific discharge capacity of 139 mu Ah mu m(-1) cm(-2) was obtained when cycled between 2.00 and 3.50 V vs Li/Li+. Additionally the rate capability of the thin film electrodes was studied by subjecting the cells to charge-discharge cycling at different current densities in the range from 10 mu A cm(-2) to 100 mu A cm(-2). (C) 2013 The Electrochemical Society. All rights reserved.

Modeling Time-Varying Aggregate Interference in Cognitive Radio Systems, and Application to Primary Exclusive Zone Design

Accurately characterizing the time-varying interference caused to the primary users is essential in ensuring a successful deployment of cognitive radios (CR). We show that the aggregate interference at the primary receiver (PU-Rx) from multiple, randomly located cognitive users (CUs) is well modeled as a shifted lognormal random process, which is more accurate than the lognormal and the Gaussian process models considered in the literature, even for a relatively dense deployment of CUs. It also compares favorably with the asymptotically exact stable and symmetric truncated stable distribution models, except at high CU densities. Our model accounts for the effect of imperfect spectrum sensing, which depends on path-loss, shadowing, and small-scale fading of the link from the primary transmitter to the CU; the interweave and underlay modes or CR operation, which determine the transmit powers of the CUs; and time-correlated shadowing and fading of the links from the CUs to the PU-Rx. It leads to expressions for the probability distribution function, level crossing rate, and average exceedance duration. The impact of cooperative spectrum sensing is also characterized. We validate the model by applying it to redesign the primary exclusive zone to account for the time-varying nature of interference.

Universal Conductance Fluctuations as a direct probe to valley coherence and universality class of disordered graphene

We demonstrate that the universal conductance fluctuations (UCF) can be used as a direct probe to study the valley quantum states in disordered graphene. The UCF magnitude in graphene is suppressed by a factor of four at high carrier densities where the short-range disorder essentially breaks the valley degeneracy of the K and K' valleys, leading to a density dependent crossover of symmetry class from symplectic near the Dirac point to orthogonal at high densities.

Supersolid in a one-dimensional model of hard-core bosons

We study a system of hard-core boson on a one-dimensional lattice with frustrated next-nearest-neighbor hopping and nearest-neighbor interaction. At half filling, for equal magnitude of nearest- and next-nearest-neighbor hopping, the ground state of this system exhibits a first-order phase transition from a bond-ordered solid to a charge-density-wave solid as a function of the nearest- neighbor interaction. Moving away from half filling we investigate the system at incommensurate densities, where we find a supersolid phase which has concurrent off-diagonal long-range order and density-wave order which is unusual in a system of hard-core bosons in one dimension. Using the finite-size density-matrix renormalization group method, we obtain the complete phase diagram for this model.

Generative Maximum Entropy Learning for Multiclass Classification

Maximum entropy approach to classification is very well studied in applied statistics and machine learning and almost all the methods that exists in literature are discriminative in nature. In this paper, we introduce a maximum entropy classification method with feature selection for large dimensional data such as text datasets that is generative in nature. To tackle the curse of dimensionality of large data sets, we employ conditional independence assumption (Naive Bayes) and we perform feature selection simultaneously, by enforcing a `maximum discrimination' between estimated class conditional densities. For two class problems, in the proposed method, we use Jeffreys (J) divergence to discriminate the class conditional densities. To extend our method to the multi-class case, we propose a completely new approach by considering a multi-distribution divergence: we replace Jeffreys divergence by Jensen-Shannon (JS) divergence to discriminate conditional densities of multiple classes. In order to reduce computational complexity, we employ a modified Jensen-Shannon divergence (JS(GM)), based on AM-GM inequality. We show that the resulting divergence is a natural generalization of Jeffreys divergence to a multiple distributions case. As far as the theoretical justifications are concerned we show that when one intends to select the best features in a generative maximum entropy approach, maximum discrimination using J-divergence emerges naturally in binary classification. Performance and comparative study of the proposed algorithms have been demonstrated on large dimensional text and gene expression datasets that show our methods scale up very well with large dimensional datasets.

Cost-effective wear and oxidation resistant electrodeposited Ni-pumice coating

In the search for newer distributed phases that can be used in Ni-composite coatings, inexpensive and naturally available pumice has been identified as a potential candidate material. The composition of the pumice mineral as determined by Rietveld analysis shows the presence of corundum, quartz, mulllite, moganite and coesite phases. Pumice stone is crushed, ball-milled, dried and dispersed in a nickel sulfamate bath and Ni-pumice coatings are electrodeposited at different current densities and magnetic agitation speeds. Pumice particles are uniformly incorporated in the nickel matrix and Ni-pumice composite coatings with microhardness as high as 540 HK are obtained at the lowest applied current density. In the electrodeposited Ni-pumice coatings, the grain size of Ni increases with the applied current density. The overall intensity of texture development is slightly stronger for the Ni-pumice composite coating compared to plain Ni coating and the texture evolution is possibly not the strongest deciding factor for the enhanced properties of Ni-pumice coatings. The wear and oxidation resistances of Ni-pumice coating are commensurate with that of Ni-SiC coating electrodeposited under similar conditions. (C) 2014 Elsevier B.V. All rights reserved.

Evaluating methane storage targets: from powder samples to onboard storage systems

The development of a viable adsorbed natural gas onboard fuel system involves synthesizing materials that meet specific storage target requirements. We assess the impact on natural gas storage due to intermediate processes involved in taking a laboratory powder sample to an onboard packed or adsorbent bed module. We illustrate that reporting the V/V (volume of gas/volume of container) capacities based on powder adsorption data without accounting for losses due to pelletization and bed porosity, grossly overestimates the working storage capacity for a given material. Using data typically found for adsorbent materials that are carbon and MOF based materials, we show that in order to meet the Department of Energy targets of 180 V/V (equivalent STP) loading at 3.5 MPa and 298 K at the onboard packed bed level, the volumetric capacity of the pelletized sample should be at least 245 V/V and the corresponding gravimetric loading varies from 0.175 to 0.38 kg/kg for pellet densities ranging from 461.5 to 1,000 . With recent revision of the DOE target to 263 V/V at the onboard packed bed level, the volumetric loadings for the pelletized sample should be about 373 V/V.

Role of Crosslinking and Entanglements in the Mechanics of Silicone Networks

The goal of this study is to investigate the applicability of different constitutive models for silicone networks using comprehensive multiaxial experimental tests, including non-equibiaxial mechanical tests which introduce differential constraints on the networks in the two orthogonal directions, on samples prepared using various crosslinking densities. Uniaxial stress-strain experiments show that a decrease in crosslinker amounts used in the preparation of silicone networks lead to more compliant material response as compared to that obtained using higher amounts of crosslinker. Biaxial data were used to obtain fits to the neo- Hookean, Mooney-Rivlin, Arruda-Boyce and the Edward-Vilgis slip-link constitutive models. Our results show that the slip-link model, based on separation of the individual contributions of chemical crosslinks and physical entanglements, is better at describing the stress-strain response of highly crosslinked networks at low stretches as compared to other constitutive models. Modulus obtained using the slip-link model for highly crosslinked networks agrees with experimentally determined values obtained using uniaxial tension experiments. In contrast, moduli obtained using coefficients to the other constitutive models underpredict experimentally determined moduli by over 40 %. However, the slip-link model did not predict the experimentally observed stiffening response at higher stretches which was better captured using the Arruda-Boyce model.

Dislocation dynamical approach to force fluctuations in nanoindentation experiments

We develop an approach that combines the power of nonlinear dynamics with the evolution equations for the mobile and immobile dislocation densities and force to explain force fluctuations in nanoindentation experiments. The model includes nucleation, multiplication, and propagation thresholds for mobile dislocations, and other well known dislocation transformation mechanisms. The model predicts all the generic features of nanoindentation such as the Hertzian elastic branch followed by several force drops of decreasing magnitudes, and residual plasticity after unloading. The stress corresponding to the elastic force maximum is close to the yield stress of an ideal solid. The predicted values for all the quantities are close to those reported by experiments. Our model allows us to address the indentation-size effect including the ambiguity in defining the hardness in the force drop dominated regime. At large indentation depths, the hardness remains nearly constant with a marginal decreasing trend.

The generalized Onsager model for a binary gas mixture

The Onsager model for the secondary flow field in a high-speed rotating cylinder is extended to incorporate the difference in mass of the two species in a binary gas mixture. The base flow is an isothermal solid-body rotation in which there is a balance between the radial pressure gradient and the centrifugal force density for each species. Explicit expressions for the radial variation of the pressure, mass/mole fractions, and from these the radial variation of the viscosity, thermal conductivity and diffusion coefficient, are derived, and these are used in the computation of the secondary flow. For the secondary flow, the mass, momentum and energy equations in axisymmetric coordinates are expanded in an asymptotic series in a parameter epsilon = (Delta m/m(av)), where Delta m is the difference in the molecular masses of the two species, and the average molecular mass m(av) is defined as m(av) = (rho(w1)m(1) + rho(w2)m(2))/rho(w), where rho(w1) and rho(w2) are the mass densities of the two species at the wall, and rho(w) = rho(w1) + rho(w2). The equation for the master potential and the boundary conditions are derived correct to O(epsilon(2)). The leading-order equation for the master potential contains a self-adjoint sixth-order operator in the radial direction, which is different from the generalized Onsager model (Pradhan & Kumaran, J. Fluid Mech., vol. 686, 2011, pp. 109-159), since the species mass difference is included in the computation of the density, viscosity and thermal conductivity in the base state. This is solved, subject to boundary conditions, to obtain the leading approximation for the secondary flow, followed by a solution of the diffusion equation for the leading correction to the species mole fractions. The O(epsilon) and O(epsilon(2)) equations contain inhomogeneous terms that depend on the lower-order solutions, and these are solved in a hierarchical manner to obtain the O(epsilon) and O(epsilon(2)) corrections to the master potential. A similar hierarchical procedure is used for the Carrier-Maslen model for the end-cap secondary flow. The results of the Onsager hierarchy, up to O(epsilon(2)), are compared with the results of direct simulation Monte Carlo simulations for a binary hard-sphere gas mixture for secondary flow due to a wall temperature gradient, inflow/outflow of gas along the axis, as well as mass and momentum sources in the flow. There is excellent agreement between the solutions for the secondary flow correct to O(epsilon(2)) and the simulations, to within 15 %, even at a Reynolds number as low as 100, and length/diameter ratio as low as 2, for a low stratification parameter A of 0.707, and when the secondary flow velocity is as high as 0.2 times the maximum base flow velocity, and the ratio 2 Delta m/(m(1) + m(2)) is as high as 0.5. Here, the Reynolds number Re = rho(w)Omega R-2/mu, the stratification parameter A = root m Omega R-2(2)/(2k(B)T), R and Omega are the cylinder radius and angular velocity, m is the molecular mass, rho(w) is the wall density, mu is the viscosity and T is the temperature. The leading-order solutions do capture the qualitative trends, but are not in quantitative agreement.

Ag nanoparticles-anchored reduced graphene oxide catalyst for oxygen electrode reaction in aqueous electrolytes and also a non-aqueous electrolyte for Li-O-2 cells

Silver nanoparticles-anchored reduced graphene oxide (Ag-RGO) is prepared by simultaneous reduction of graphene oxide and Ag+ ions in an aqueous medium by ethylene glycol as the reducing agent. Ag particles of average size of 4.7 nm were uniformly distributed on the RGO sheets. Oxygen reduction reaction (ORR) is studied on Ag-RGO catalyst in both aqueous and non-aqueous electrolytes by using cyclic voltammetry and rotating disk electrode techniques. As the interest in non-aqueous electrolyte is to study the catalytic performance of Ag-RGO for rechargeable Li-O-2 cells, these cells are assembled and characterized. Li-O-2 cells with Ag-RGO as the oxygen electrode catalyst are subjected to charge-discharge cycling at several current densities. A discharge capacity of 11 950 mA h g(-1) (11.29 mA h cm(-2)) is obtained initially at low current density. Although there is a decrease in the capacity on repeated discharge-charge cycling initially, a stable capacity is observed for about 30 cycles. The results indicate that Ag-RGO is a suitable catalyst for rechargeable Li-O-2 cells.