Ionically-Mediated Electromechanical Hysteresis in Transition Metal Oxides

Nanoscale electromechanical activity, remanent polarization states, and hysteresis loops in paraelectric TiO2 and SrTiO3 thin films are observed using scanning probe microscopy. The coupling between the ionic dynamics and incipient ferroelectricity in these materials is analyzed using extended Landau-Ginzburg-Devonshire (LGD) theory. The possible origins of electromechanical coupling including ionic dynamics, surface-charge induced electrostriction, and ionically induced ferroelectricity are identified. For the latter, the ionic contribution can change the sign of first order LGD expansion coefficient, rendering material effectively ferroelectric. The lifetime of these ionically induced ferroelectric states is then controlled by the transport time of the mobile ionic species and well above that of polarization switching. These studies provide possible explanation for ferroelectric-like behavior in centrosymmetric transition metal oxides.

Blind Characterisation of Sensors with Second-Order Dynamic Response

Compensation for the dynamic response of a temperature sensor usually involves the estimation of its input on the basis of the measured output and model parameters. In the case of temperature measurement, the sensor dynamic response is strongly dependent on the measurement environment and fluid velocity. Estimation of time-varying sensor model parameters therefore requires continuous textit{in situ} identification. This can be achieved by employing two sensors with different dynamic properties, and exploiting structural redundancy to deduce the sensor models from the resulting data streams. Most existing approaches to this problem assume first-order sensor dynamics. In practice, however second-order models are more reflective of the dynamics of real temperature sensors, particularly when they are encased in a protective sheath. As such, this paper presents a novel difference equation approach to solving the blind identification problem for sensors with second-order models. The approach is based on estimating an auxiliary ARX model whose parameters are related to the desired sensor model parameters through a set of coupled non-linear algebraic equations. The ARX model can be estimated using conventional system identification techniques and the non-linear equations can be solved analytically to yield estimates of the sensor models. Simulation results are presented to demonstrate the efficiency of the proposed approach under various input and parameter conditions.

Fractional order modelling of fractional-order holds

Discrete time control systems require sample- and-hold circuits to perform the conversion from digital to analog. Fractional-Order Holds (FROHs) are an interpolation between the classical zero and first order holds and can be tuned to produce better system performance. However, the model of the FROH is somewhat hermetic and the design of the system becomes unnecessarily complicated. This paper addresses the modelling of the FROHs using the concepts of Fractional Calculus (FC). For this purpose, two simple fractional-order approximations are proposed whose parameters are estimated by a genetic algorithm. The results are simple to interpret, demonstrating that FC is a useful tool for the analysis of these devices.

Magnetic superelasticity and inverse magnetocaloric effect in Ni-Mn-In

Applying a magnetic field to a ferromagnetic Ni50Mn34In16 alloy in the martensitic state induces a structural phase transition to the austenitic state. This is accompanied by a strain which recovers on removing the magnetic field, giving the system a magnetically superelastic character. A further property of this alloy is that it also shows the inverse magnetocaloric effect. The magnetic superelasticity and the inverse magnetocaloric effect in Ni-Mn-In and their association with the first-order structural transition are studied by magnetization, strain, and neutron-diffraction studies under magnetic field.

X-ray diffraction, thermal analysis, and Raman scattering study of K2BeF4 and comparation to other member of the (beta)-K2SO4 family with ferroelectric -paraelectric transition

Thermal analysis, powder diffraction, and Raman scattering as a function of the temperature were carried out on K2BeF4. Moreover, the crystal structure was determined at 293 K from powder diffraction. The compound shows a transition from Pna21 to Pnam space group at 921 K with a transition enthalpy of 5 kJ/mol. The transition is assumed to be first order because the compound shows metastability. Structurally and spectroscopically the transition is similar to those observed in (NH4)2SO4, which suggests that the low-temperature phase is ferroelectric. In order to confirm it, the spontaneous polarization has been computed using an ionic model.

Modelling impacts of pollution in river systems: a new dispersion model and a case study of mine discharges in the Abrud, Aries and Mures river system in Transylvania, Romania

A new model of dispersion has been developed to simulate the impact of pollutant discharges on river systems. The model accounts for the main dispersion processes operating in rivers as well as the dilution from incoming tributaries and first-order kinetic decay processes. The model is dynamic and simulates the hourly behaviour of river flow and pollutants along river systems. The model has been applied to the Aries and Mures River System in Romania and has been used to assess the impacts of potential dam releases from the Roia Montan Mine in Transylvania, Romania. The question of mine water release is investigated under a range of scenarios. The impacts on pollution levels downstream at key sites and at the border with Hungary are investigated.

Effect of breed, gender, housing system and dietary crude protein content on performance of finishing beef cattle fed maize-silage-based diets

Maize silage-based diets with three dietary crude protein (CP) supplements were offered to 96 finishing cattle of contrasting breed (Holstein Friesian (HF) v. Simmental x HF (SHF)) and gender (bull v. steer) housed in two types of feeding system (group fed v. individually fed). The three protein supplements differed either in CP or protein degradability (degradable (LUDP) v. rumen undegradable (HUDP)) and provided CP concentrations of 142 (Con), 175 (LUDP) and 179 (HUDP) g/kg dry matter (DM) respectively, with ratios of degradable to undegradable of 3.0, 1.4 and 0.9:1 for diets Con, LOP and HUDP respectively. DM intakes were marginally higher (P = 0. 102) for LOP when compared with Con and HOP Rates of daily live-weight gain (DLWG) were higher (P = 0.005) in LUDP and HOP when compared with Con. HF had higher DM intakes than SHF although this did not result in any improvement in HF DLWG. Bulls had significantly better DM intakes, DLWG and feed conversion efficiency than steers. Conformation scores were better in SHF than HF (P < 0.001) and fat scores lower in bulls than steers (p < 0.001). There was a number of first order interactions established between dietary treatment, breed, gender and housing system with respect to rates of gain and carcass fat scores.

An on-line algorithm of uncertain time delay estimation in a continuous system

In this paper, we present an on-line estimation algorithm for an uncertain time delay in a continuous system based on the observational input-output data, subject to observational noise. The first order Pade approximation is used to approximate the time delay. At each time step, the algorithm combines the well known Kalman filter algorithm and the recursive instrumental variable least squares (RIVLS) algorithm in cascade form. The instrumental variable least squares algorithm is used in order to achieve the consistency of the delay parameter estimate, since an error-in-the-variable model is involved. An illustrative example is utilized to demonstrate the efficacy of the proposed approach.

Determination of the degradation kinetics of anthocyanins in a model juice system using isothermal and non-isothermal methods

The effect of temperature on the degradation of blackcurrant anthocyanins in a model juice system was determined over a temperature range of 4–140 °C. The thermal degradation of anthocyanins followed pseudo first-order kinetics. From 4–100 °C an isothermal method was used to determine the kinetic parameters. In order to mimic the temperature profile in retort systems, a non-isothermal method was applied to determine the kinetic parameters in the model juice over the temperature range 110–140 °C. The results from both isothermal and non-isothermal methods fit well together, indicating that the non-isothermal procedure is a reliable mathematical method to determine the kinetics of anthocyanin degradation. The reaction rate constant (k) increased from 0.16 (±0.01) × 10−3 to 9.954 (±0.004) h−1 at 4 and 140 °C, respectively. The temperature dependence of the rate of anthocyanin degradation was modelled by an extension of the Arrhenius equation, which showed a linear increase in the activation energy with temperature.

System identification of Wiener systems with B-spline functions using De Boor recursion

In this article a simple and effective algorithm is introduced for the system identification of the Wiener system using observational input/output data. The nonlinear static function in the Wiener system is modelled using a B-spline neural network. The Gauss–Newton algorithm is combined with De Boor algorithm (both curve and the first order derivatives) for the parameter estimation of the Wiener model, together with the use of a parameter initialisation scheme. Numerical examples are utilised to demonstrate the efficacy of the proposed approach.

An Earth Observation Land Data Assimilation System (EO-LDAS)

Current methods for estimating vegetation parameters are generally sub-optimal in the way they exploit information and do not generally consider uncertainties. We look forward to a future where operational dataassimilation schemes improve estimates by tracking land surface processes and exploiting multiple types of observations. Dataassimilation schemes seek to combine observations and models in a statistically optimal way taking into account uncertainty in both, but have not yet been much exploited in this area. The EO-LDAS scheme and prototype, developed under ESA funding, is designed to exploit the anticipated wealth of data that will be available under GMES missions, such as the Sentinel family of satellites, to provide improved mapping of land surface biophysical parameters. This paper describes the EO-LDAS implementation, and explores some of its core functionality. EO-LDAS is a weak constraint variational dataassimilationsystem. The prototype provides a mechanism for constraint based on a prior estimate of the state vector, a linear dynamic model, and EarthObservationdata (top-of-canopy reflectance here). The observation operator is a non-linear optical radiative transfer model for a vegetation canopy with a soil lower boundary, operating over the range 400 to 2500 nm. Adjoint codes for all model and operator components are provided in the prototype by automatic differentiation of the computer codes. In this paper, EO-LDAS is applied to the problem of daily estimation of six of the parameters controlling the radiative transfer operator over the course of a year (> 2000 state vector elements). Zero and first order process model constraints are implemented and explored as the dynamic model. The assimilation estimates all state vector elements simultaneously. This is performed in the context of a typical Sentinel-2 MSI operating scenario, using synthetic MSI observations simulated with the observation operator, with uncertainties typical of those achieved by optical sensors supposed for the data. The experiments consider a baseline state vector estimation case where dynamic constraints are applied, and assess the impact of dynamic constraints on the a posteriori uncertainties. The results demonstrate that reductions in uncertainty by a factor of up to two might be obtained by applying the sorts of dynamic constraints used here. The hyperparameter (dynamic model uncertainty) required to control the assimilation are estimated by a cross-validation exercise. The result of the assimilation is seen to be robust to missing observations with quite large data gaps.

Radiative-dynamical climatology of the first-generation Canadian middle atmosphere model

The Canadian Middle Atmosphere Modelling (MAM) project is a collaboration between thé Atmospheric Environment Service (AES) of Environment Canada and several Canadian universities. Its goal is thé development of a comprehensive General Circulation Model of the troposphere-stratosphere-mesosphere System, starting from the AES/CCCma third-generation atmospheric General Circulation Model. This paper describes the basic features of the first-generation Canadian MAM and some aspects of its radiative-dynamical climatology. Standard first-order mean diagnostics are presented for monthly means and for the annual cycle of zonal-mean winds and temperatures. The mean meridional circulation is examined, and comparison is made between thé steady diabatic, downward controlled, and residual stream functions. It is found that downward control holds quite well in the monthly mean through most of the middle atmosphere, even during equinoctal periods. The relative roles of different drag processes in determining the mean downwelling over the wintertime polar middle stratosphere is examined, and the vertical structure of the drag is quantified.

Transition redshift: new kinematic constraints from supernovae

The transition redshift (deceleration/acceleration) is discussed by expanding the deceleration parameter to first order around its present value. A detailed study is carried out by considering two different parametrizations, q = q(0) + q(1)z and q = q(0) + q(1)z(1 + z)(-1), and the associated free parameters (q(0), q(1)) are constrained by three different supernovae (SNe) samples. A previous analysis by Riess et al. using the first expansion is slightly improved and confirmed in light of their recent data (Gold07 sample). However, by fitting the model with the Supernova Legacy Survey (SNLS) type Ia sample, we find that the best fit to the redshift transition is z(t) = 0.61, instead of z(t) = 0.46 as derived by the High-z Supernovae Search (HZSNS) team. This result based in the SNLS sample is also in good agreement with the sample of Davis et al., z(t) = 0.60(-0.11)(+0.28) (1 sigma). Such results are in line with some independent analyses and accommodate more easily the concordance flat model (Lambda CDM). For both parametrizations, the three SNe Ia samples considered favour recent acceleration and past deceleration with a high degree of statistical confidence level. All the kinematic results presented here depend neither on the validity of general relativity nor on the matter-energy contents of the Universe.

Second and Third Order Ionospheric Effects on GNSS Positioning: A Case Study in Brazil

The Global Positioning System (GPS) transmits signals in two frequencies. It allows the correction of the first order ionospheric effect by using the ionosphere free combination. However, the second and third order ionospheric effects, which combined may cause errors of the order of centimeters in the GPS measurements, still remain. In this paper the second and third order ionospheric effects, which were taken into account in the GPS data processing in the Brazilian region, were investigated. The corrected and not corrected GPS data from these effects were processed in the relative and precise point positioning (PPP) approaches, respectively, using Bernese V5.0 software and the PPP software (GPSPPP) from NRCAN (Natural Resources Canada). The second and third order corrections were applied in the GPS data using an in-house software that is capable of reading a RINEX file and applying the corrections to the GPS observables, creating a corrected RINEX file. For the relative processing case, a Brazilian network with long baselines was processed in a daily solution considering a period of approximately one year. For the PPP case, the processing was accomplished using data collected by the IGS FORT station considering the period from 2001 to 2006 and a seasonal analysis was carried out, showing a semi-annual and an annual variation in the vertical component. In addition, a geographical variation analysis in the PPP for the Brazilian region has confirmed that the equatorial regions are more affected by the second and third order ionospheric effects than other regions.

Propriedades críticas do processo epidêmico difusivo com interação de Lévy

The diffusive epidemic process (PED) is a nonequilibrium stochastic model which, exhibits a phase trnasition to an absorbing state. In the model, healthy (A) and sick (B) individuals diffuse on a lattice with diffusion constants DA and DB, respectively. According to a Wilson renormalization calculation, the system presents a first-order phase transition, for the case DA > DB. Several researches performed simulation works for test this is conjecture, but it was not possible to observe this first-order phase transition. The explanation given was that we needed to perform simulation to higher dimensions. In this work had the motivation to investigate the critical behavior of a diffusive epidemic propagation with Lévy interaction(PEDL), in one-dimension. The Lévy distribution has the interaction of diffusion of all sizes taking the one-dimensional system for a higher-dimensional. We try to explain this is controversy that remains unresolved, for the case DA > DB. For this work, we use the Monte Carlo Method with resuscitation. This is method is to add a sick individual in the system when the order parameter (sick density) go to zero. We apply a finite size scalling for estimates the critical point and the exponent critical =, e z, for the case DA > DB