High-energy cutoff in the spectrum of strong-field nonsequential double ionization

Electron energy distributions of singly and doubly ionized helium in an intense 390 nm laser field have been measured at two intensities (0.8 PW/cm(2) and 1.1 PW/cm(2), where PW equivalent to 10(15) W/cm(2)). Numerical solutions of the full-dimensional time-dependent helium Schrodinger equation show excellent agreement with the experimental measurements. The high-energy portion of the two-electron energy distributions reveals an unexpected 5U(p) cutoff for the double ionization (DI) process and leads to a proposed model for DI below the quasiclassical threshold.

An exactly solvable four transition point model

Heavy particle collisions, in particular low-energy ion-atom collisions, are amenable to semiclassical JWKB phase integral analysis in the complex plane of the internuclear separation. Analytic continuation in this plane requires due attention to the Stokes phenomenon which parametrizes the physical mechanisms of curve crossing, non-crossing, the hybrid Nikitin model, rotational coupling and predissociation. Complex transition points represent adiabatic degeneracies. In the case of two or more such points, the Stokes constants may only be completely determined by resort to the so-called comparison- equation method involving, in particular, parabolic cylinder functions or Whittaker functions and their strong-coupling asymptotics. In particular, the Nikitin model is a two transition-point one-double-pole problem in each half-plane corresponding to either ingoing or outgoing waves. When the four transition points are closely clustered, new techniques are required to determine Stokes constants. However, such investigations remain incomplete, A model problem is therefore solved exactly for scattering along a one-dimensional z-axis. The energy eigenvalue is b(2)-a(2) and the potential comprises -z(2)/2 (parabolic) and -a(2) + b(2)/2z(2) (centrifugal/centripetal) components. The square of the wavenumber has in the complex z-plane, four zeros each a transition point at z = +/-a +/- ib and has a double pole at z = 0. In cases (a) and (b), a and b are real and unitarity obtains. In case (a) the reflection and transition coefficients are parametrized by exponentials when a(2) + b(2) > 1/2. In case (b) they are parametrized by trigonometrics when a(2) + b(2) <1/2 and total reflection is achievable. In case (c) a and b are complex and in general unitarity is not achieved due to loss of flux to a continuum (O'Rourke and Crothers, 1992 Proc. R. Sec. 438 1). Nevertheless, case (c) coefficients reduce to (a) or (b) under appropriate limiting conditions. Setting z = ht, with h a real constant, an attempt is made to model a two-state collision problem modelled by a pair of coupled first-order impact parameter equations and an appropriate (T) over tilde-tau relation, where (T) over tilde is the Stueckelberg variable and tau is the reduced or scaled time. The attempt fails because (T) over tilde is an odd function of tau, which is unphysical in a real collision problem. However, it is pointed out that by applying the Kummer exponential model to each half-plane (O'Rourke and Crothers 1994 J. Phys. B: At. Mel. Opt. Phys. 27 2497) the current model is in effect extended to a collision problem with four transition points and a double pole in each half-plane. Moreover, the attempt in itself is not a complete failure since it is shown that the result is a perfect diabatic inelastic collision for a traceless Hamiltonian matrix, or at least when both diagonal elements are odd and the off-diagonal elements equal and even.

Cooperativism, entrepreneurship and economic development: a linking theoretical model

Cooperatives, as a kind of firms, are considered by many scholars as an remarkable alternative for overcoming the economic crisis started in 2008. Besides, there are other scholars which pointed out the important role that these firms play in the regional economic development. Nevertheless, when one examines the economic literature on cooperatives, it is detected that this kind of firms is mainly studied starting from the point of view of their own characteristics and particularities of participation and solidarity. In this sense, following a different analysis framework, this article proposes a theoretical model in order to explain the behavior of cooperatives based on the entrepreneurship theory with the aim of increasing the knowledge about this kind of firms and, more specifically, their contribution to regional economic development.

Relative energetics and structural properties of zirconia using a self-consistent tight-binding model

We describe an empirical, self-consistent, orthogonal tight-binding model for zirconia, which allows for the polarizability of the anions at dipole and quadrupole levels and for crystal field splitting of the cation d orbitals, This is achieved by mixing the orbitals of different symmetry on a site with coupling coefficients driven by the Coulomb potentials up to octapole level. The additional forces on atoms due to the self-consistency and polarizabilities are exactly obtained by straightforward electrostatics, by analogy with the Hellmann-Feynman theorem as applied in first-principles calculations. The model correctly orders the zero temperature energies of all zirconia polymorphs. The Zr-O matrix elements of the Hamiltonian, which measure covalency, make a greater contribution than the polarizability to the energy differences between phases. Results for elastic constants of the cubic and tetragonal phases and phonon frequencies of the cubic phase are also presented and compared with some experimental data and first-principles calculations. We suggest that the model will be useful for studying finite temperature effects by means of molecular dynamics.

Optimizing The Nasal Allergen Challenge Model For The Study Of Allergic Rhinitis

Background The Allergic Rhinitis Clinical Investigator Collaborative (AR-CIC) uses a Nasal Allergen Challenge (NAC) model to study the pathophysiology of AR and provides proof of concept for novel therapeutics. The NAC model needs to ensure optimal participant qualification, allergen challenge, clinical symptoms capture and biological samples collection. Repeatability of the protocol is key to ensuring unbiased efficacy analysis of novel therapeutics. The effect of allergen challenge on IL-33 gene expression and its relation to IL1RL1 receptor and cytokine secretion was investigated. Methods Several iterations of the NAC protocol was tested, comparing variations of qualifying criteria based on the Total Nasal Symptom Score (TNSS) and Peak Nasal Inspiratory Flow (PNIF). The lowest allergen concentration was delivered and TNSS and PNIF recorded 15 minutes later. Participants qualified if the particular criteria for the protocol were met, otherwise the next higher allergen concentration (4-fold increase), was administered until the targets were reached. Participants returned for a NAC visit and received varying allergen challenge concentrations depending on the protocol, TNSS/PNIF were recorded at 15 minutes, 30 minutes, 1 hour, and hourly up to 12 hours, a 24 hour time point was added in later iterations. Repeatability was evaluated using a 3-4week interval between screening, NAC1, and NAC2 visits. Various biomarker samples were collected. Results A combined TNSS and PNIF criterion was more successful in qualifying participants. The cumulative allergen challenge (CAC) protocol proved more reliable in producing a robust clinical and biomarker response. Repeatability of the CAC protocol was achieved with a 3-week interval between visits, on a clinical and biological basis. IL-33 cytokine is an important biomarker in initiating the inflammatory response in AR in humans. IL-33 and IL1RL1 expression might employ a negative feedback mechanism in human nasal epithelial cells. Comparing the clinical and biological response to ragweed vs cat allergen challenge, proved the CAC protocol’s suitability for use employing different allergens. Conclusion The AR-CIC’s CAC protocol is an effective method of studying AR, capable of generating measurable and repeatable clinical and biomarker responses, enabling better understanding of AR pathophysiology and ensuring that any change would be purely due to medication under investigation in a clinical trial setting.

PVT Property Measurements for Some Aliphatic Esters from (298 to 393) K and up to 35 MPa

The results of PVT measurements of the liquid phase within the temperature range of (298 to 393) K and up to 35 MPa are presented for some aliphatic esters. Measurements were made by means of a vibrating-tube densimeter, model DMA 512P from Anton Parr. The calibration of the densimeter was performed with water and n-heptane as reference fluids. The experimental PVT data have been correlated by a Tait equation. This equation gives excellent results when used to predict the density of the esters using the method proposed by Thomson et al. (AIChE J. 1982, 28, 671-676). Isothermal compressibilities, isobaric expansivities, thermal pressure coefficients, and changes in the isobaric heat capacity have been calculated from the volumetric data.

Model selection approaches for non-linear system identification: a review

The identification of non-linear systems using only observed finite datasets has become a mature research area over the last two decades. A class of linear-in-the-parameter models with universal approximation capabilities have been intensively studied and widely used due to the availability of many linear-learning algorithms and their inherent convergence conditions. This article presents a systematic overview of basic research on model selection approaches for linear-in-the-parameter models. One of the fundamental problems in non-linear system identification is to find the minimal model with the best model generalisation performance from observational data only. The important concepts in achieving good model generalisation used in various non-linear system-identification algorithms are first reviewed, including Bayesian parameter regularisation and models selective criteria based on the cross validation and experimental design. A significant advance in machine learning has been the development of the support vector machine as a means for identifying kernel models based on the structural risk minimisation principle. The developments on the convex optimisation-based model construction algorithms including the support vector regression algorithms are outlined. Input selection algorithms and on-line system identification algorithms are also included in this review. Finally, some industrial applications of non-linear models are discussed.

On velocity-based local model networks for nonlinear identification

This paper exposes the strengths and weaknesses of the recently proposed velocity-based local model (LM) network. The global dynamics of the velocity-based blended representation are directly related to the dynamics of the underlying local models, an important property in the design of local controller networks. Furthermore, the sub-models are continuous-time and linear providing continuity with established linear theory and methods. This is not true for the conventional LM framework, where the global dynamics are only weakly related to the affine sub-models. In this paper, a velocity-based multiple model network is identified for a highly nonlinear dynamical system. The results show excellent dynamical modelling performances, highlighting the value of the velocity-based approach for the design and analysis of LM based control. Three important practical issues are also addressed. These relate to the blending of the velocity-based local models, the use of normalised Gaussian basis functions and the requirement of an input derivative.

Unusual voltammetry of the reduction of O-2 in [C(4)dmim][N(Tf)(2)] reveals a strong interaction of O-2(center dot-) with the [C(4)dmim](+) cation

Voltammetric studies of the reduction of oxygen in the room temperature ionic liquid [C(4)dmim][N(Tf)(2)] have revealed a significant positive shift in the back peak potential, relative to that expected for a simple electron transfer. This shift is thought to be due to the strong association of the electrogenerated superoxide anion with the solvent cation. In this work we quantitatively simulate the microdisc electrode voltammetry using a model based upon a one-electron reduction followed by a reversible chemical step, involving the formation of the [C(4)dmim](+)center dot center dot center dot O-2(center dot-) ion-pair, and in doing so we extract a set of parameters completely describing the system. We have simulated the voltammetry in the absence of a following chemical step and have shown that it is impossible to simultaneously fit both the forward and reverse peaks. To further support the parameters extracted from fitting the experimental voltammetry, we have used these parameters to independently simulate the double step chronoamperometric response and found excellent agreement. The parameters used to describe the association of the O-2(center dot-) with the [C(4)dmim](+) were k(f) = 1.4 x 10(3) s(-1) for the first-order rate constant and K-eq = 25 for the equilibrium constant.

Electroreduction of Chlorine Gas at Platinum Electrodes in Several Room Temperature Ionic Liquids: Evidence of Strong Adsorption on the Electrode Surface Revealed by Unusual Voltammetry in Which Currents Decrease with Increasing Voltage Scan Rates

Voltammetry is reported for chlorine, Cl-2, dissolved in various room temperature ionic liquids using platinum microdisk electrodes. A single reductive voltammetric wave is seen and attributed to the two-electron reduction of chlorine to chloride. Studies of the effect of voltage scan rate reveal uniquely unusual behavior in which the magnitude of the currents decrease with increasing scan rates. A model for this is proposed and shown to indicate the presence of strongly adsorbed species in the electrode reaction mechanism, most likely chlorine atoms, Cl*((ads)).

Controls on the contemporary distribution of lake thecamoebians (testate amoebae) in the Greater Toronto Area and their potential as water quality indicators.

Thecamoebians were examined from 71 surface sediment samples collected from 21 lakes and ponds in the Greater Toronto Area to (1) elucidate the controls on faunal distribution in modern lake environments; and (2) to consider the utility of thecamoebians in quantitative studies of water quality change. This area was chosen because it includes a high density of kettle and other lakes which are threatened by urban development and where water quality has deteriorated locally as a result of contaminant inputs, particularly nutrients. Fifty-eight samples yielded statistically significant thecamoebian populations. The most diverse faunas (highest Shannon Diversity Index values) were recorded in lakes beyond the limits of urban development, although the faunas of all lakes showed signs of sub-optimal conditions. The assemblages were divided into five clusters using Q-mode cluster analysis, supported by Detrended Correspondence Analysis. Canonical Correspondence Analysis (CCA) was used to examine species-environment relationships and to explain the observed clusterings. Twenty-four measured environmental variables were considered, including water property attributes (e.g., pH, conductivity, dissolved oxygen), substrate characteristics, sediment-based phosphorus (Olsen P) and 11 environmentally available metals. The thecamoebian assemblages showed a strong association with phosphorus, reflecting the eutrophic status of many of the lakes, and locally to elevated conductivity measurements, which appear to reflect road salt inputs associated with winter de-icing operations. Substrate characteristics, total organic carbon and metal contaminants (particularly Cu and Mg) also influenced the faunas of some samples. A series of partial CCAs show that of the measured variables, sedimentary phosphorus has the largest influence on assemblage distribution, explaining 6.98% (P < 0.002) of the total variance. A transfer function was developed for sedimentary phosphorus (Olsen P) using 58 samples from 15 of the studied lakes. The best performing model was based on weighted averaging with inverse deshrinking (WA Inv, r jack 2= 0.33, RMSEP = 102.65 ppm). This model was applied to a small modern thecamoebian dataset from a eutrophic lake in northern Ontario to predict phosphorus and performed satisfactorily. This preliminary study confirms that thecamoebians have considerable potential as quantitative water quality indicators in urbanising regions, particularly in areas influenced by nutrient inputs and road salts.

Artificial Intelligence Model for Flowable Concrete Mixtures Used in Underwater Construction and Repair

This study explores using artificial neural networks to predict the rheological and mechanical properties of underwater concrete (UWC) mixtures and to evaluate the sensitivity of such properties to variations in mixture ingredients. Artificial neural networks (ANN) mimic the structure and operation of biological neurons and have the unique ability of self-learning, mapping, and functional approximation. Details of the development of the proposed neural network model, its architecture, training, and validation are presented in this study. A database incorporating 175 UWC mixtures from nine different studies was developed to train and test the ANN model. The data are arranged in a patterned format. Each pattern contains an input vector that includes quantity values of the mixture variables influencing the behavior of UWC mixtures (that is, cement, silica fume, fly ash, slag, water, coarse and fine aggregates, and chemical admixtures) and a corresponding output vector that includes the rheological or mechanical property to be modeled. Results show that the ANN model thus developed is not only capable of accurately predicting the slump, slump-flow, washout resistance, and compressive strength of underwater concrete mixtures used in the training process, but it can also effectively predict the aforementioned properties for new mixtures designed within the practical range of the input parameters used in the training process with an absolute error of 4.6, 10.6, 10.6, and 4.4%, respectively.

Mixed-dimensional coupling in finite element models

In many finite element analysis models it would be desirable to combine reduced- or lower-dimensional element types with higher-dimensional element types in a single model. In order to achieve compatibility of displacements and stress equilibrium at the junction or interface between the differing element types, it is important in such cases to integrate into the analysis some scheme for coupling the element types. A novel and effective scheme for establishing compatibility and equilibrium at the dimensional interface is described and its merits and capabilities are demonstrated. Copyright (C) 2000 John Wiley & Sons, Ltd.

Atomistic Insights into Rhodopsin Activation from a Dynamic Model

Rhodopsin, the light sensitive receptor responsible for blue-green vision, serves as a prototypical G protein-coupled receptor (GPCR). Upon light absorption, it undergoes a series of conformational changes that lead to the active form, metarhodopsin II (META II), initiating a signaling cascade through binding to the G protein transducin (G(t)). Here, we first develop a structural model of META II by applying experimental distance restraints to the structure of lumi-rhodopsin (LUMI), an earlier intermediate. The restraints are imposed by using a combination of biased molecular dynamics simulations and perturbations to an elastic network model. We characterize the motions of the transmembrane helices in the LUMI-to-META II transition and the rearrangement of interhelical hydrogen bonds. We then simulate rhodopsin activation in a dynamic model to study the path leading from LUMI to our META II model for wild-type rhodopsin and a series of mutants. The simulations show a strong correlation between the transition dynamics and the pharmacological phenotypes of the mutants. These results help identify the molecular mechanisms of activation in both wild type and mutant rhodopsin. While static models can provide insights into the mechanisms of ligand recognition and predict ligand affinity, a dynamic model of activation could be applicable to study the pharmacology of other GPCRs and their ligands, offering a key to predictions of basal activity and ligand efficacy.

Modelling the mechanical response of the Reed-mouthpiece-lip system of a clarinet. Part I. A one-dimensional distributed model

The motion of a clarinet reed that is clamped to a mouthpiece and supported by a lip is simulated in the time-domain using finite difference methods. The reed is modelled as a bar with non-uniform cross section, and is described using a one-dimensional, fourth-order partial differential equation. The interactions with the mouthpiece Jay and the player's lip are taken into account by incorporating conditional contact forces in the bar equation. The model is completed by clamped-free boundary conditions for the reed. An implicit finite difference method is used for discretising the system, and values for the physical parameters are chosen both from laboratory measurements and by accurate tuning of the numerical simulations. The accuracy of the numerical system is assessed through analysis of frequency warping effects and of resonance estimation. Finally, the mechanical properties of the system are studied by analysing its response to external driving forces. In particular, the effects of reed curling are investigated.