Influence of Backflow on Roton Quantum Evaporation

Sobnack et al. recently investigated theoretically the effect of roton backflow on the scattering of atoms, rotons, and phonons at the free surface of superfluid helium-II at T=0 K. They treated backflow semi-phenomenologically by modifying the potential in their earlier theory. This paper compares their predictions for the wave-vector dependence of roton quantum-evaporation with time-resolved experiments. It is found that the wave-vector dependence observed in the experiments is much less extreme than was predicted, and we discuss the implications of this result for this type of theory.     

The Effect of Roton Backflow on Quantum Evaporation from Superfluid 4He

We investigate the effect of roton backflow on the scattering of atoms, rotons and phonons at the free surface of superfluid ⁴ He at T=0 K by including backflow semi-phenomenologically in the form of a backflow potential in the theory of Sobnack et al. [M. B. Sobnack, J. C. Inkson, and J. C. H. Fung, Phys. Rev. B 60, 3465 (1999)]. We assume that all the surface scattering processes are elastic and that the quasiparticles and atoms are incident obliquely to the free surface. We calculate probabilities for the various one-to-one surface scattering processes allowed for a range of energies and compare the scattering rates with those obtained when backflow is neglected.     

Is the Roton in Superfluid 4He the Ghost of a Bragg Spot?

It has always been assumed that the roton in ⁴He had to do with local vorticity—hence the name! We present here an alternate view: the roton is viewed as a “soft mode”, precursor of a crystallization instability. In such a picture the liquid is “nearly solid”, and the long observed similarities of heat propagation in liquid and solid phases are naturally explained. In this qualitative paper we consider three models successively. A lattice gas with one atom per site displays a Mott localization transition, as shown by the Bangalore group. The important result is the vanishing of the superfluid order parameter (condensate fraction N _o) at the transition. There is no breakdown of translational symmetry and consequently no soft mode. Another lattice model with half filling, with an added nearest neighbour repulsion, was studied by Matsubara and Matsuda in the early 1950s it displays a first order transition between a superfluid and a localized charge density wave state. The excitation spectrum has a soft mode at zone edge near the transition, signalling the proximity of the CDW instability. Finally, we consider the realistic situation of a continuous system with no preexisting lattice. We approach the problem from the limit N _o = 0 instead of the ideal gas N _o = N. When N _o = 0 the quasiparticle spectrum and the charge density spectrum are decoupled. The latter should have a soft mode ω=ω_m if crystallization is close. That soft mode is a normal state property that has nothing to do with superfluidity. A small N _o acts to hybridize quasiparticles and density fluctuations: the resulting anticrossing lowers ω_m ² as well as the ground state energy. We show that N _o is bounded for two reasons: (i) if ω _m ² turns negative, the liquid is unstable towards freezing (ii) depletion due to quantum fluctuation exceeds N _o if the latter is too large. The resulting upper bound noindent for N/N _{o is} ? 1, a consequence of the deep roton minimum. The whole paper is qualitative, based on outrageous simplifications in order to make algebra tractable.     

A Magnetostatic Model for Square Spiral Inductors Incorporating a Magnetic Layer

Embedding magnetic layers in inductors is an attractive option for increasing inductance density, which is a critical issue for radio-frequency applications. In this letter, we develop a magnetostatic model for square spiral inductors incorporating a magnetic layer. In our model, we assume that the permeability of the magnetic layer is isotropic and infinite. The model provides a fast and effective numerical calculation of the inductance of inductors incorporating a magnetic layer. We show the derivation of the model and provide calculation results for various inductor structures.      

On the Existence of Roton Excitations in Bose–Einstein Condensates: Signature of Proximity to a Mott Insulating Phase

Within the last decade, artificially engineered Bose–Einstein condensation has been achieved in atomic systems, Bose–Einstein Condensates (BECs) are superfluids just like bosonic helium is and all interacting bosonic fluids are expected to be at low enough temperatures. One difference between the two systems is that superfluid helium exhibits roton excitations while Bose–Einstein condensates have never been observed to have such excitations. The reason for the roton minimum in helium is its proximity to a solid phase. The roton minimum is a consequence of enhanced density fluctuations at the reciprocal lattice vector of the stillborn solid. Bose–Einstein condensates in atomic traps are not near a solid phase and therefore do not exhibit roton minimum. We conclude that if Bose–Einstein condensates in an optical lattice are tuned near a transition to a Mott insulating phase, a roton minimum will develop at a reciprocal lattice vector of the lattice. Equivalently, a peak in the structure factor will appear at such a wavevector. The smallness of the roton gap or the largeness of the structure factor peak are experimental signatures of the proximity to the Mott transition.     

Incorporating data from a primary frequency standard into a timescale

It is difficult to combine data from a primary frequency standard with the time-difference measurements that are usually used as input to most time scales because a primary standard usually operates only occasionally on an irregular schedule and because the fundamental output of a primary frequency standard is a frequency rather than a time, and there is often no natural way of inserting this kind of datum into the scale in a manner that is statistically robust. We will present a new time-scale algorithm that seeks to address these problems. We call this frequency-based algorithm AF1, by analogy with the time-based algorithm AT1 that has been used at NIST for many years. Unlike AT1 in which frequency is simply a parameter that specifies how the time of a clock evolves between measurements, however, the frequency of each clock is a fundamental parameter in AF1. This change in focus provides a natural way for incorporating data from a primary frequency standard into the ensemble. We will present the details of the algorithm and results using data from our primary frequency standard, NIST-7     

Development of A High Throughput Method Incorporating Traditional Analytical Devices

A high-throughput (high throughput is the ability to process large numbers of samples) and companion informatics system has been developed and implemented. High throughput is defined as the ability to autonomously evaluate large numbers of samples, while an informatics system provides the software control of the physical devices, in addition to the organization and storage of the generated electronic data. This high throughput system includes both an ultra-violet and visible light spectrometer (UV-Vis) and a Fourier transform infrared spectrometer (FTIR) integrated with a multi sample positioning table. This method is designed to quantify changes in polymeric materials occurring from controlled temperature, humidity and high flux UV exposures. The integration of the software control of these analytical instruments within a single computer system is presented. Challenges in enhancing the system to include additional analytical devices are discussed.     

A New Contribution to the Theory of Anode Effect in Aluminium Electrolysis

This paper discusses the general characteristicsof anode effect in aluminium electrolysis and pre-vious theories about the mechanism of anode effect.On the basis of laboratory experiments,the authorsuggests a new contribution to the primary and di-rect reason for anode effect.     

Incorporating planned backorders in a family production context with shelf-life considerations

This paper considers the problem of determining the optimal production rate for each item and the optimal cycle time for the family of items in a family production context with restrictions on the shelf-life of various items in the family. We investigate the impact of incorporating planned backorders into the system. We show that the model with planned backorders reduces to a model without backorders with modified holding costs and shelf-life. Therefore, the model with planned backorders can be analysed using the earlier model developed by Viswanathan and Goyal (1997). We also present several examples to demonstrate how incorporating planned backorders can reduce the total costs.     

Incorporating a delay mechanism in ordering policies into multi-echelon distribution systems

In this paper, we devise a framework for obtaining the optimal ordering policy in a single location, continuous-review inventory system with arbitrary inter-demand times. We show that it is optimal to order at demand arrival epochs only if the inter-demand time has a constant or decreasing failure rate. When the inter-demand time has an increasing failure rate, we show that the optimal policy is to delay the order. We then extend this policy to multi-echelon distribution systems consisting of one supplier and many retailers. Both decentralized and centralized systems are considered. We derive expressions and procedures for the evaluation of the total cost and the computation of optimal delay in all the considered settings. More importantly, we study the impact of our delay policy in all the settings. The numerical results indicate that for the single-location model, the optimal delay can significantly reduce the total cost. Results from the single-location model can be applied to the decentralized multi-echelon system, where the upstream supplier acts as a single-location system. The supplier order delay can also have a significant impact (either positive or negative) on the retailers' total cost as well as the system's total costs. Finally, the impact of supplier order delay is minimal in the centralized multi-echelon setting. We offer an intuitive explanation for this observation.     

Incorporating demographic stochasticity into multi-strain epidemic models: application to influenza A

We develop mathematical models of the transmission and evolution of multi-strain pathogens that incorporate strain extinction and the stochastic generation of new strains via mutation. The dynamics resulting from these models is then examined with the applied aim of understanding the mechanisms underpinning the evolution and dynamics of rapidly mutating pathogens, such as human influenza viruses. Our approach, while analytically relatively simple, gives results that are qualitatively similar to those obtained from much more complex individually based simulation models. We examine strain dynamics as a function of cross-immunity and key transmission parameters, and show that introducing strain extinction and modelling mutation as a stochastic process significantly changes the model dynamics, leading to lower strain diversity, reduced infection prevalence and shorter strain lifetimes. Finally, we incorporate transient strain-transcending immunity in the model and demonstrate that it reduces strain diversity further, giving patterns of sequential strain replacement similar to that seen in human influenza A viruses.     

A Framework for Reliability Prediction During Product Development Process Incorporating Engineering Judgments

This paper presents a comprehensive framework for reliability prediction during the product development process. Early in the product development process, there is typically little or no quantitative evidence to predict the reliability of the new concept except indirect or qualitative information. The proposed framework addresses the issue of utilizing qualitative information in the reliability analysis. The framework is based on the Bayesian approach. The fuzzy logic theory is used to enhance the capability of the Bayesian approach to deal with qualitative information. This paper proposes to extract the information from various design tools and design review records and incorporate it into the Bayesian framework through a fuzzy inference system. The Weibull distribution is considered as failure/survival time distribution with the assumption of a known value of shape factor. Initial parameters of the Weibull distribution are estimated from warranty data of prior systems to estimate the initial Bayesian parameter ( λ_t). The applicability of the framework is illustrated via an example.     

A Contribution to the Theory of a Bent Flame

Within the framework of the Zel'dovich–Frank-Kamenetskii theory of a laminar flame, an eigenvalue linearized stationary boundary-value problem is considered to establish the dependence of the flame velocity on the curvature of its front of sinusoidal shape. The analysis has been carried out for arbitrary Lewis numbers. Various mechanisms contributing to the smoothing out of the bent front of the flame are considered.     

Incorporating pattern recognition capability in a flexible vibratory bowl feeder using a neural network

Programmable parts feeders that can orientate most of the parts of one or more part families, with short changeover times from one part to the next, are highly sought after in batch production. This study investigates a suitable neural-network-based pattern recognition algorithm for the recognition of parts in a programmable vibratory bowl feeder. Three fibre-optic sensors were mounted on a vibratory bowl feeder to scan the surface of each feeding part. The scanned signatures were used as the input for the different neural network models. The performances of ARTMAP, ART2 and backpropagation neural network models were compared. The results showed that, among the three models, ARTMAP is deemed to be superior, based on the criteria of learning speed, high generalization and flexibility. The better performance obtained with the ARTMAP neural network is mainly the result of its online training and supervised learning capabilities.     

Incorporating human factors into the AAMT selection: a framework and process

Human factors such as employee morale and workers skills greatly influence the successful adoption of automated and advanced manufacturing technologies. For newly industrialised countries, the evaluation of these factors before technology selection is particularly paramount. Countries such as Brazil are in the critical early stages of technology adoption and low rates of secondary education and scarcity of technicians reinforce the importance of assessing human factors before the actual technology implementation. Although methods have been proposed to evaluate intangible aspects, the lack of a structured approach to identify and quantify human factors still constitutes a major hurdle. The paper describes a framework and process to assist managers in identifying and evaluating human factors in the selection. The approach was tested in eight companies in Brazil. The results indicated that the main advantages of the proposed approach are: (a) provide a comprehensive justification of technology adoption by identifying and quantifying intangible aspects; and (b) supply a practical process to be incorporated into the selection decision-making process.     

Incorporating individual health-protective decisions into disease transmission models: a mathematical framework

It is anticipated that the next generation of computational epidemic models will simulate both infectious disease transmission and dynamic human behaviour change. Individual agents within a simulation will not only infect one another, but will also have situational awareness and a decision algorithm that enables them to modify their behaviour. This paper develops such a model of behavioural response, presenting a mathematical interpretation of a well-known psychological model of individual decision making, the health belief model, suitable for incorporation within an agent-based disease-transmission model. We formalize the health belief model and demonstrate its application in modelling the prevalence of facemask use observed over the course of the 2003 Hong Kong SARS epidemic, a well-documented example of behaviour change in response to a disease outbreak.     

A Reliable Stochastic Numerical Analysis for Typhoid Fever Incorporating With Protection Against Infection

In this paper, a reliable stochastic numerical analysis for typhoid fever incorporating with protection against infection has been considered. We have compared the solutions of stochastic and deterministic typhoid fever model. It has been shown that the stochastic typhoid fever model is more realistic as compared to the deterministic typhoid fever model. The effect of threshold number T* hold in stochastic typhoid fever model. The proposed framework of the stochastic non-standard finite difference scheme (SNSFD) preserves all dynamical properties like positivity, bounded-ness and dynamical consistency defined by Mickens, R. E. The stochastic numerical simulation of the model showed that increase in protection leads to low disease prevalence in a population.