Dependence of low-lying energy eigenvalues on the short- and long-range parts of confining potentials

The potential description of a quark-antiquark system seems to work very well in describing a number of hadronic properties. However, the precise form of the potential is unknown. The changes in the low-lying eigenvalues as a result of changes in the long-range part of the potential are investigated in a non-perturbative manner. It is shown by considering a variety of examples that the low-lying eigenvalues are insensitive to the long-range part of the potential.

Multi-time scale analysis applied to long time simulation of power systems

The results are presented of applying multi-time scale analysis using the singular perturbation technique for long time simulation of power system problems. A linear system represented in state-space form can be decoupled into slow and fast subsystems. These subsystems can be simulated with different time steps and then recombined to obtain the system response. Simulation results with a two-time scale analysis of a power system show a large saving in computational costs.

Bounding Run-Times of Local Adiabatic Algorithms

A common trick for designing faster quantum adiabatic algorithms is to apply the adiabaticity condition locally at every instant. However it is often difficult to determine the instantaneous gap between the lowest two eigenvalues, which is an essential ingredient in the adiabaticity condition. In this paper we present a simple linear algebraic technique for obtaining a lower bound on the instantaneous gap even in such a situation. As an illustration, we investigate the adiabatic un-ordered search of van Dam et al. [17] and Roland and Cerf [15] when the non-zero entries of the diagonal final Hamiltonian are perturbed by a polynomial (in log N, where N is the length of the unordered list) amount. We use our technique to derive a bound on the running time of a local adiabatic schedule in terms of the minimum gap between the lowest two eigenvalues.

A novel neural network design for long range prediction of rainfall pattern

The importance of long-range prediction of rainfall pattern for devising and planning agricultural strategies cannot be overemphasized. However, the prediction of rainfall pattern remains a difficult problem and the desired level of accuracy has not been reached. The conventional methods for prediction of rainfall use either dynamical or statistical modelling. In this article we report the results of a new modelling technique using artificial neural networks. Artificial neural networks are especially useful where the dynamical processes and their interrelations for a given phenomenon are not known with sufficient accuracy. Since conventional neural networks were found to be unsuitable for simulating and predicting rainfall patterns, a generalized structure of a neural network was then explored and found to provide consistent prediction (hindcast) of all-India annual mean rainfall with good accuracy. Performance and consistency of this network are evaluated and compared with those of other (conventional) neural networks. It is shown that the generalized network can make consistently good prediction of annual mean rainfall. Immediate application and potential of such a prediction system are discussed.

Long term monitering of vegetation in a tropical deciduous forest in Mudumalai,southern India

As part of an international network of large plots to study tropical vegetation dynamics on a long-term basis, a 50-hectare permanent plot was set up during 1988-89 in the deciduous forests of Mudumalai, southern India. Within this plot 25,929 living woody plants (71 species) above 1 cm DBH (diameter at breast height) were identified, measured, tagged and mapped. Species abundances corresponded to the characteristic log-normal distribution. The four most abundant species (Kydia calycina, Lagerstroemia microcarpa, Terminalia crenulata and Helicteres isora) constituted nearly 56% of total stems, while seven species were represented by only one individual each in the plot. Variance/mean ratios of density showed most species to have clumped distributions. The population declined overall by 14% during the first two years, largely due to elephant and fire-mediated damage to Kydia calycina and Helicteres isora. In this article we discuss the need for large plots to study vegetation dynamics.

Precision and long-term stability of clumped-isotope analysis of CO2 using a small-sector isotope ratio mass spectrometer

RATIONALE The ratio of the measured abundance of 13C18O bonding CO2 to its stochastic abundance, prescribed by the delta 13C and delta 18O values from a carbonate mineral, is sensitive to its growth temperature. Recently, clumped-isotope thermometry, which uses this ratio, has been adopted as a new tool to elucidate paleotemperatures quantitatively. METHODS Clumped isotopes in CO2 were measured with a small-sector isotope ratio mass spectrometer. CO2 samples digested from several kinds of calcium carbonates by phosphoric acid at 25 degrees C were purified using both cryogenic and gas-chromatographic separations, and their isotopic composition (delta 13C, delta 18O, Delta 47, Delta 48 and Delta 49 values) were then determined using a dual-inlet Delta XP mass spectrometer. RESULTS The internal precisions of the single gas Delta 47 measurements were 0.005 and 0.02 parts per thousand (1 SE) for the optimum and the routine analytical conditions, respectively, which are comparable with those obtained using a MAT 253 mass spectrometer. The long-term variations in the Delta 47 values for the in-house working standard and the heated CO2 gases since 2007 were close to the routine, single gas uncertainty while showing seasonal-like periodicities with a decreasing trend. Unlike the MAT 253, the Delta XP did not show any significant relationship between the Delta 47 and delta 47 values. CONCLUSIONS The Delta XP gave results that were approximately as precise as those of the MAT 253 for clumped-isotope analysis. The temporal stability of the Delta XP seemed to be lower, although an advantage of the Delta XP was that no dependency of delta 47 on Delta 47 was found. Copyright (c) 2012 John Wiley & Sons, Ltd.

Calcium Permeable AMPA Receptor-Dependent Long Lasting Plasticity of Intrinsic Excitability in Fast Spiking Interneurons of the Dentate Gyrus Decreases Inhibition in the Granule Cell Layer

The local fast-spiking interneurons (FSINs) are considered to be crucial for the generation, maintenance, and modulation of neuronal network oscillations especially in the gamma frequency band. Gamma frequency oscillations have been associated with different aspects of behavior. But the prolonged effects of gamma frequency synaptic activity on the FSINs remain elusive. Using whole cell current clamp patch recordings, we observed a sustained decrease of intrinsic excitability in the FSINs of the dentate gyrus (DG) following repetitive stimulations of the mossy fibers at 30 Hz (gamma bursts). Surprisingly, the granule cells (GCs) did not express intrinsic plastic changes upon similar synaptic excitation of their apical dendritic inputs. Interestingly, pairing the gamma bursts with membrane hyperpolarization accentuated the plasticity in FSINs following the induction protocol, while the plasticity attenuated following gamma bursts paired with membrane depolarization. Paired pulse ratio measurement of the synaptic responses did not show significant changes during the experiments. However, the induction protocols were accompanied with postsynaptic calcium rise in FSINs. Interestingly, the maximum and the minimum increase occurred during gamma bursts with membrane hyperpolarization and depolarization respectively. Including a selective blocker of calcium-permeable AMPA receptors (CP-AMPARs) in the bath; significantly attenuated the calcium rise and blocked the membrane potential dependence of the calcium rise in the FSINs, suggesting their involvement in the observed phenomenon. Chelation of intracellular calcium, blocking HCN channel conductance or blocking CP-AMPARs during the experiment forbade the long lasting expression of the plasticity. Simultaneous dual patch recordings from FSINs and synaptically connected putative GCs confirmed the decreased inhibition in the GCs accompanying the decreased intrinsic excitability in the FSINs. Experimentally constrained network simulations using NEURON predicted increased spiking in the GC owing to decreased input resistance in the FSIN. We hypothesize that the selective plasticity in the FSINs induced by local network activity may serve to increase information throughput into the downstream hippocampal subfields besides providing neuroprotection to the FSINs. (c) 2014 Wiley Periodicals, Inc.

Using long time series of agricultural-derived nitrates for estimating catchment transit times

The estimation of water and solute transit times in catchments is crucial for predicting the response of hydrosystems to external forcings (climatic or anthropogenic). The hydrogeochemical signatures of tracers (either natural or anthropogenic) in streams have been widely used to estimate transit times in catchments as they integrate the various processes at stake. However, most of these tracers are well suited for catchments with mean transit times lower than about 4-5 years. Since the second half of the 20th century, the intensification of agriculture led to a general increase of the nitrogen load in rivers. As nitrate is mainly transported by groundwater in agricultural catchments, this signal can be used to estimate transit times greater than several years, even if nitrate is not a conservative tracer. Conceptual hydrological models can be used to estimate catchment transit times provided their consistency is demonstrated, based on their ability to simulate the stream chemical signatures at various time scales and catchment internal processes such as N storage in groundwater. The objective of this study was to assess if a conceptual lumped model was able to simulate the observed patterns of nitrogen concentration, at various time scales, from seasonal to pluriannual and thus if it was relevant to estimate the nitrogen transit times in headwater catchments. A conceptual lumped model, representing shallow groundwater flow as two parallel linear stores with double porosity, and riparian processes by a constant nitrogen removal function, was applied on two paired agricultural catchments which belong to the Research Observatory ORE AgrHys. The Global Likelihood Uncertainty Estimation (GLUE) approach was used to estimate parameter values and uncertainties. The model performance was assessed on (i) its ability to simulate the contrasted patterns of stream flow and stream nitrate concentrations at seasonal and inter-annual time scales, (ii) its ability to simulate the patterns observed in groundwater at the same temporal scales, and (iii) the consistency of long-term simulations using the calibrated model and the general pattern of the nitrate concentration increase in the region since the beginning of the intensification of agriculture in the 1960s. The simulated nitrate transit times were found more sensitive to climate variability than to parameter uncertainty, and average values were found to be consistent with results from others studies in the same region involving modeling and groundwater dating. This study shows that a simple model can be used to simulate the main dynamics of nitrogen in an intensively polluted catchment and then be used to estimate the transit times of these pollutants in the system which is crucial to guide mitigation plans design and assessment. (C) 2015 Elsevier B.V. All rights reserved.

Long-term effects of Macroternies termites, herbivores and annual early fire on woody undergrowth community in Sudanian woodland, Burkina Faso

Termites, herbivores and fire are recognized as major guilds that structure woody plant communities in African savanna and woodland ecosystems. An understanding of their interaction is crucial to design appropriate management regimes. The aim of this study was to evaluate the long-term impacts of herbivore, fire and termite activities on regeneration of trees. Permanent experimental quadrats were established in 1992 in the Sudanian woodland of Burkina Faso subjected to grazing by livestock and annual early fire and the control. Within the treatment quadrats, an inventory of the woody undergrowth community was conducted on termitaria occupied by Macrotermes subhyalinus, extended termitosphere (within 5 m radius from the mound base) and adjacent area (beyond 5 m from the mound base). Hierarchical analysis was performed to determine significant differences in species richness, abundance and diversity indices among vegetation patches within fire and herbivory treatments. Grazed quadrats had significantly (P < 0.001) more species and stem density of woody undergrowth than non-grazed quadrats but maintained similar level of species richness and stem density of woody undergrowth on termitaria. There were not significant differences (P>0.05) in species richness and stem density between burnt and unburnt quadrats. Termitaria supported a highly diverse woody undergrowth with higher stem density than either the extended termitosphere or rest of quadrats. The density of woody undergrowth was significantly related with mature trees of selected species on termitaria (R-2 = 0.593; P<0.001) than that on the extended termitosphere (R-2 = 0.333; P<0.001) and adjacent area (R-2 = 0.197; P<0.001). It can be concluded that termites facilitate the regeneration of woody species while grazing and annual early fire play a minor role in the regeneration of woody species. The current policy that prohibits grazing should be revised to accommodate the interests of livestock herders. (C) 2014 Elsevier GmbH. All rights reserved.

Flow Cytometry Analysis of Cytotoxicity In Vitro and Long-Term Toxicity of HA-40wt% BaTiO3 Nanoparticles In Vivo

The development of new implantable biomaterials requires bone-mimicking physical properties together with desired biocompatible property. In continuation to our earlier published research to establish compositional dependent multifunctional bone-like properties and cytocompatibility response of hydroxyapatite (HA)-BaTiO3 composites, the toxicological property evaluation, both invitro and invivo, were conducted on HA-40wt% BaTiO3 and reported in this work. In particular, this work reports invitro cytotoxicity of mouse myoblast cells as well as invivo long-term tissue and nanoparticles interaction of intra-articularly injected HA-40wt% BaTiO3 and BaTiO3 up to the concentration of 25mg/mL in physiological saline over 12weeks in mouse model. The careful analysis of flow cytometry results could not reveal any statistically significant difference in terms of early/late apoptotic cells or necrotic cells over 8d in culture. Extensive histological analysis could not record any signature of cellular level toxicity or pronounced inflammatory response in vital organs as well as at knee joints of Balb/c mice after 12weeks. Taken together, this study establishes nontoxic nature of HA-40wt% BaTiO3 and therefore, HA-40wt% BaTiO3 can be used safely for various biomedical applications.

Stochastic Approximation Algorithms for Constrained Optimization via Simulation

We develop four algorithms for simulation-based optimization under multiple inequality constraints. Both the cost and the constraint functions are considered to be long-run averages of certain state-dependent single-stage functions. We pose the problem in the simulation optimization framework by using the Lagrange multiplier method. Two of our algorithms estimate only the gradient of the Lagrangian, while the other two estimate both the gradient and the Hessian of it. In the process, we also develop various new estimators for the gradient and Hessian. All our algorithms use two simulations each. Two of these algorithms are based on the smoothed functional (SF) technique, while the other two are based on the simultaneous perturbation stochastic approximation (SPSA) method. We prove the convergence of our algorithms and show numerical experiments on a setting involving an open Jackson network. The Newton-based SF algorithm is seen to show the best overall performance.

Locating and sizing plants for bottling propane in south India

Shri Shakti LPG Ltd. (SSLPG) imports and markets propane (referred to as liquefied petroleum gas (LPG) in India) in south India. It sells LPG in packed (cylinder) form to domestic customers and commercial establishments through a network of dealers. Dealers replenish their stocks of filled cylinders from bottling plants, which in turn receive LPG in bulk from the cheaper of SSLPG's two import-and-storage facilities that are located on the Indian coast. We implemented integer programming to help SSLPG decide on the locations and long-run sizes of its bottling plants. We estimate that our recommended configuration of bottling plants is about $1 million cheaper annually than the one that SSLPG had initially planned.

An Online Actor-Critic Algorithm with Function Approximation for Constrained Markov Decision Processes

We develop an online actor-critic reinforcement learning algorithm with function approximation for a problem of control under inequality constraints. We consider the long-run average cost Markov decision process (MDP) framework in which both the objective and the constraint functions are suitable policy-dependent long-run averages of certain sample path functions. The Lagrange multiplier method is used to handle the inequality constraints. We prove the asymptotic almost sure convergence of our algorithm to a locally optimal solution. We also provide the results of numerical experiments on a problem of routing in a multi-stage queueing network with constraints on long-run average queue lengths. We observe that our algorithm exhibits good performance on this setting and converges to a feasible point.

Simultaneous perturbation methods for adaptive labor staffing in service systems

We consider the problem of optimizing the workforce of a service system. Adapting the staffing levels in such systems is non-trivial due to large variations in workload and the large number of system parameters do not allow for a brute force search. Further, because these parameters change on a weekly basis, the optimization should not take longer than a few hours. Our aim is to find the optimum staffing levels from a discrete high-dimensional parameter set, that minimizes the long run average of the single-stage cost function, while adhering to the constraints relating to queue stability and service-level agreement (SLA) compliance. The single-stage cost function balances the conflicting objectives of utilizing workers better and attaining the target SLAs. We formulate this problem as a constrained parameterized Markov cost process parameterized by the (discrete) staffing levels. We propose novel simultaneous perturbation stochastic approximation (SPSA)-based algorithms for solving the above problem. The algorithms include both first-order as well as second-order methods and incorporate SPSA-based gradient/Hessian estimates for primal descent, while performing dual ascent for the Lagrange multipliers. Both algorithms are online and update the staffing levels in an incremental fashion. Further, they involve a certain generalized smooth projection operator, which is essential to project the continuous-valued worker parameter tuned by our algorithms onto the discrete set. The smoothness is necessary to ensure that the underlying transition dynamics of the constrained Markov cost process is itself smooth (as a function of the continuous-valued parameter): a critical requirement to prove the convergence of both algorithms. We validate our algorithms via performance simulations based on data from five real-life service systems. For the sake of comparison, we also implement a scatter search based algorithm using state-of-the-art optimization tool-kit OptQuest. From the experiments, we observe that both our algorithms converge empirically and consistently outperform OptQuest in most of the settings considered. This finding coupled with the computational advantage of our algorithms make them amenable for adaptive labor staffing in real-life service systems.

Ergodic control of partially observed Markov chains

The ergodic or long-run average cost control problem for a partially observed finite-state Markov chain is studied via the associated fully observed separated control problem for the nonlinear filter. Dynamic programming equations for the latter are derived, leading to existence and characterization of optimal stationary policies.