Assessment of insect occurrence in boreal forests based on satellite imagery and field measurements.

The presence/absence data of twenty-seven forest insect taxa (e.g. Retinia resinella, Formica spp., Pissodes spp., several scolytids) and recorded environmental variation were used to investigate the applicability of modelling insect occurrence based on satellite imagery. The sampling was based on 1800 sample plots (25 m by 25 m) placed along the sides of 30 equilateral triangles (side 1 km) in a fragmented forest area (approximately 100 km2) in Evo, S Finland. The triangles were overlaid on land use maps interpreted from satellite images (Landsat TM 30 m multispectral scanner imagery 1991) and digitized geological maps. Insect occurrence was explained using either environmental variables measured in the field or those interpreted from the land use and geological maps. The fit of logistic regression models varied between species, possibly because some species may be associated with the characteristics of single trees while other species with stand characteristics. The occurrence of certain insect species at least, especially those associated with Scots pine, could be relatively accurately assessed indirectly on the basis of satellite imagery and geological maps. Models based on both remotely sensed and geological data better predicted the distribution of forest insects except in the case of Xylechinus pilosus, Dryocoetes sp. and Trypodendron lineatum, where the differences were relatively small in favour of the models based on field measurements. The number of species was related to habitat compartment size and distance from the habitat edge calculated from the land use maps, but logistic regressions suggested that other environmental variables in general masked the effect of these variables in species occurrence at the present scale.

Estimation of soil hydraulic properties and their uncertainty: comparison between laboratory and field experiment

Often the soil hydraulic parameters are obtained by the inversion of measured data (e.g. soil moisture, pressure head, and cumulative infiltration, etc.). However, the inverse problem in unsaturated zone is ill-posed due to various reasons, and hence the parameters become non-unique. The presence of multiple soil layers brings the additional complexities in the inverse modelling. The generalized likelihood uncertainty estimate (GLUE) is a useful approach to estimate the parameters and their uncertainty when dealing with soil moisture dynamics which is a highly non-linear problem. Because the estimated parameters depend on the modelling scale, inverse modelling carried out on laboratory data and field data may provide independent estimates. The objective of this paper is to compare the parameters and their uncertainty estimated through experiments in the laboratory and in the field and to assess which of the soil hydraulic parameters are independent of the experiment. The first two layers in the field site are characterized by Loamy sand and Loamy. The mean soil moisture and pressure head at three depths are measured with an interval of half hour for a period of 1 week using the evaporation method for the laboratory experiment, whereas soil moisture at three different depths (60, 110, and 200 cm) is measured with an interval of 1 h for 2 years for the field experiment. A one-dimensional soil moisture model on the basis of the finite difference method was used. The calibration and validation are approximately for 1 year each. The model performance was found to be good with root mean square error (RMSE) varying from 2 to 4 cm(3) cm(-3). It is found from the two experiments that mean and uncertainty in the saturated soil moisture (theta(s)) and shape parameter (n) of van Genuchten equations are similar for both the soil types. Copyright (C) 2010 John Wiley & Sons, Ltd.

Modeling and Field Oriented Control of Salient Pole Wound Field Synchronous Machine in Stator Flux Coordinates

This paper describes the field oriented control of a salient pole wound field synchronous machine in stator flux coordinates. The procedure for derivation of flux linkage equations along any general rotating axes including stator flux axes is given. The stator flux equations are used to identify the cross-coupling occurring between the axes due to saliency in the machine. The coupling terms are canceled as feedforward terms in the generation of references for current controllers to achieve good decoupling during transients. The design of current controller for stator-flux-oriented control is presented. This paper proposes the method of extending rotor flux closed loop observer for sensorless control of wound field synchronous machine. This paper also proposes a new sensorless control by using stator flux closed loop observer and estimation of torque angle using stator current components in stator flux coordinates. Detailed experimental results from a sensorless 15.8 hp salient pole wound field synchronous machine drive are presented to demonstrate the performance of the proposed control strategy from a low speed of 0.8 Hz to 50 Hz.

Supersolid Phase in One-Dimensional Bose-Hubbard Model With Extended Range Interactions: DMRG And Field Theoretic Study at Different Densities

We use the Density Matrix Renormalization Group and the Abelian bosonization method to study the effect of density on quantum phases of one-dimensional extended Bose-Hubbard model. We predict the existence of supersolid phase and also other quantum phases for this system. We have analyzed the role of extended range interaction parameters on solitonic phase near half-filling. We discuss the effects of dimerization in nearest neighbor hopping and interaction as well as next nearest neighbor interaction on the plateau phase at half-filling.

Synthesis and characterization of self-assembled nanofiber-bundles of V(2)O(5): their electrochemical and field emission properties

High-quality self-assembled V(2)O(5) nanofiber-bundles (NBs) are synthesized by a simple and direct hydrothermal method using a vanadium(V) hydroxylamido complex as a vanadium source in the presence of HNO(3). The possible reaction pathway for the formation of V(2)O(5) NBs is discussed and demonstrated that HNO(3) functions both as an oxidizing and as an acidification agent. V(2)O(5) NBs are single-crystals of an orthorhombic phase that have grown along the [010] direction. A bundle is made of indefinite numbers of homogeneous V(2)O(5) nanofibers where nanofibers have lengths up to several micrometres and widths ranging between 20 and 50 nm. As-prepared V(2)O(5) NBs display a high electrochemical performance in a non-aqueous electrolyte as a cathode material for lithium ion batteries. Field emission properties are also investigated which shows that a low turn-on field of similar to 1.84 V mu m(-1) is required to draw the emission current density of 10 mu Lambda cm(-2).

Modeling of temperature and field-dependent electron mobility in a single-layer graphene sheet

In this paper, we address a physics-based analytical model of electric-field-dependent electron mobility (mu) in a single-layer graphene sheet using the formulation of Landauer and Mc Kelvey's carrier flux approach under finite temperature and quasi-ballistic regime. The energy-dependent, near-elastic scattering rate of in-plane and out-of-plane (flexural) phonons with the electrons are considered to estimate mu over a wide range of temperature. We also demonstrate the variation of mu with carrier concentration as well as the longitudinal electric field. We find that at high electric field (>10(6) Vm(-1)), the mobility falls sharply, exhibiting the scattering between the electrons and flexural phonons. We also note here that under quasi-ballistic transport, the mobility tends to a constant value at low temperature, rather than in between T-2 and T-1 in strongly diffusive regime. Our analytical results agree well with the available experimental data, while the methodologies are put forward to estimate the other carrier-transmission-dependent transport properties.

Efficient charge transfer and field-induced tunneling transport in hybrid composite device of organic semiconductor and cadmium telluride quantum dots

Temperature and photo-dependent current-voltage characteristics are investigated in thin film devices of a hybrid-composite comprising of organic semiconductor poly(3,4-ethylenedioxythiophene): polystyrenesulfonate (PEDOT: PSS) and cadmium telluride quantum dots (CdTe QDs). A detailed study of the charge injection mechanism in ITO/PEDOT: PSS-CdTe QDs/Al device exhibits a transition from direct tunneling to Fowler-Nordheim tunneling with increasing electric field due to formation of high barrier at the QD interface. In addition, the hybrid-composite exhibits a huge photoluminescence quenching compared to aboriginal CdTe QDs and high increment in photoconductivity (similar to 400%), which is attributed to the charge transfer phenomena. The effective barrier height (Phi(B) approximate to 0.68 eV) is estimated from the transition voltage and the possible origin of its variation with temperature and photo-illumination is discussed. (C) 2015 AIP Publishing LLC.

Synthesis, characterization and field emission properties of tin oxide nanowires

Tin oxide (SnO2) nanowires are synthesized by Au catalyzed chemical vapor deposition of Sn and C mixture at 900 degrees C by employing a continuous flow of Ar: O-2 (10:1) for an hour. X-ray diffraction and Raman spectroscopy studies indicate that the as-grown SnO2 nanowires are crystalline in nature with tetragonal rutile phase. Electron microscopy studies reveal towards high aspect ratio of nanowires. The field emission studies show that SnO2 nanowires grown on Si substrate exhibit low turn-on field of 1.75 V/mu m (at 0.1 mu A/cm(2)) and long-term emission stability over a period of more than 50 h with a current density of 4 mu A/cm(2) at a constant electric field of 2.25 V/mu m. Hardly any considerable degradation in the emission current is noticed even after 50 h which may be attributed to the high crystallinity of SnO2 nanowires. (C) 2015 Elsevier B.V. All rights reserved.

Electrical and field emission investigation of individual carbon nanotubes from plasma enhanced chemical vapour deposition

Plasma enhanced chemical vapour deposition (PECVD) is a controlled technique for the production of vertically aligned multiwall carbon nanotubes for field emission applications. In this paper, we investigate the electrical properties of individual carbon nanotubes which is important for designing field emission devices. PECVD nanotubes exhibit a room temperature resistance of 1-10 kΩ/μm length (resistivity 10-6 to 10-5 Ω m) and have a maximum current carrying capability of 0.2-2 mA (current density 107-108 A/cm2). The field emission characteristics show that the field enhancement of the structures is strongly related to the geometry (height/radius) of the structures and maximum emission currents of ∼ 10 μA were obtained. The failure of nanotubes under field emission is also discussed. © 2002 Elsevier Science B.V. All rights reserved.

Modelling rail corrugation with specific track parameters focusing on ballasted track and slab track

The objective of this paper is to compare 3 types of track (high performance ballasted track, STEDEF and AFTRAV) from the corrugation growth point of view. This work has considered different vehicle speeds and track radii, and the results have taken into account the four wheels of a bogie. These tracks have been studied using Finite Elements with Nastran-Patran and RACING, a tool developed in Matlab by the authors which estimates the corrugation growth tendency. The tracks are studied using the Finite Strip Method and the Periodic Structure Theory. Lateral and vertical receptances for track and vehicle have been obtained, as well as the corrugation growth functions. In the paper the tracks are ranked according to corrugation development.

Efficient methods for empirical tests of behavioral economics theories in laboratory and field experiments

In the quest for a descriptive theory of decision-making, the rational actor model in economics imposes rather unrealistic expectations and abilities on human decision makers. The further we move from idealized scenarios, such as perfectly competitive markets, and ambitiously extend the reach of the theory to describe everyday decision making situations, the less sense these assumptions make. Behavioural economics has instead proposed models based on assumptions that are more psychologically realistic, with the aim of gaining more precision and descriptive power. Increased psychological realism, however, comes at the cost of a greater number of parameters and model complexity. Now there are a plethora of models, based on different assumptions, applicable in differing contextual settings, and selecting the right model to use tends to be an ad-hoc process. In this thesis, we develop optimal experimental design methods and evaluate different behavioral theories against evidence from lab and field experiments.

We look at evidence from controlled laboratory experiments. Subjects are presented with choices between monetary gambles or lotteries. Different decision-making theories evaluate the choices differently and would make distinct predictions about the subjects' choices. Theories whose predictions are inconsistent with the actual choices can be systematically eliminated. Behavioural theories can have multiple parameters requiring complex experimental designs with a very large number of possible choice tests. This imposes computational and economic constraints on using classical experimental design methods. We develop a methodology of adaptive tests: Bayesian Rapid Optimal Adaptive Designs (BROAD) that sequentially chooses the "most informative" test at each stage, and based on the response updates its posterior beliefs over the theories, which informs the next most informative test to run. BROAD utilizes the Equivalent Class Edge Cutting (EC²) criteria to select tests. We prove that the EC² criteria is adaptively submodular, which allows us to prove theoretical guarantees against the Bayes-optimal testing sequence even in the presence of noisy responses. In simulated ground-truth experiments, we find that the EC² criteria recovers the true hypotheses with significantly fewer tests than more widely used criteria such as Information Gain and Generalized Binary Search. We show, theoretically as well as experimentally, that surprisingly these popular criteria can perform poorly in the presence of noise, or subject errors. Furthermore, we use the adaptive submodular property of EC² to implement an accelerated greedy version of BROAD which leads to orders of magnitude speedup over other methods.

We use BROAD to perform two experiments. First, we compare the main classes of theories for decision-making under risk, namely: expected value, prospect theory, constant relative risk aversion (CRRA) and moments models. Subjects are given an initial endowment, and sequentially presented choices between two lotteries, with the possibility of losses. The lotteries are selected using BROAD, and 57 subjects from Caltech and UCLA are incentivized by randomly realizing one of the lotteries chosen. Aggregate posterior probabilities over the theories show limited evidence in favour of CRRA and moments' models. Classifying the subjects into types showed that most subjects are described by prospect theory, followed by expected value. Adaptive experimental design raises the possibility that subjects could engage in strategic manipulation, i.e. subjects could mask their true preferences and choose differently in order to obtain more favourable tests in later rounds thereby increasing their payoffs. We pay close attention to this problem; strategic manipulation is ruled out since it is infeasible in practice, and also since we do not find any signatures of it in our data.

In the second experiment, we compare the main theories of time preference: exponential discounting, hyperbolic discounting, "present bias" models: quasi-hyperbolic (α, β) discounting and fixed cost discounting, and generalized-hyperbolic discounting. 40 subjects from UCLA were given choices between 2 options: a smaller but more immediate payoff versus a larger but later payoff. We found very limited evidence for present bias models and hyperbolic discounting, and most subjects were classified as generalized hyperbolic discounting types, followed by exponential discounting.

In these models the passage of time is linear. We instead consider a psychological model where the perception of time is subjective. We prove that when the biological (subjective) time is positively dependent, it gives rise to hyperbolic discounting and temporal choice inconsistency.

We also test the predictions of behavioral theories in the "wild". We pay attention to prospect theory, which emerged as the dominant theory in our lab experiments of risky choice. Loss aversion and reference dependence predicts that consumers will behave in a uniquely distinct way than the standard rational model predicts. Specifically, loss aversion predicts that when an item is being offered at a discount, the demand for it will be greater than that explained by its price elasticity. Even more importantly, when the item is no longer discounted, demand for its close substitute would increase excessively. We tested this prediction using a discrete choice model with loss-averse utility function on data from a large eCommerce retailer. Not only did we identify loss aversion, but we also found that the effect decreased with consumers' experience. We outline the policy implications that consumer loss aversion entails, and strategies for competitive pricing.

In future work, BROAD can be widely applicable for testing different behavioural models, e.g. in social preference and game theory, and in different contextual settings. Additional measurements beyond choice data, including biological measurements such as skin conductance, can be used to more rapidly eliminate hypothesis and speed up model comparison. Discrete choice models also provide a framework for testing behavioural models with field data, and encourage combined lab-field experiments.