Reconstruction of annular bi-layered media in cylindrical waveguide section

A radial transverse resonance model for two cylindrical concentric layers with different complex dielectric constants is presented. An inverse problem with four unknowns - 3 physical material parameters and one dimensional dielectric layer thickness parameter- is solved by employing TE110 and TE210 modes with different radial field distribution. First a Newton-Raphson algorithm is used to solve a least square problem with a Lorentzian function (as resonance model and "measured" data generator). Then found resonance frequencies and quality factors are used in a second inverse Newton-Raphson algorithm that solves four transverse resonance equations in order to get four unknown parameters. The use of TE110 and TE210 models offers one dimensional radial tomographic capability. An open ended coax quarter-wave resonator is added to the sensor topology, and the effect on the convergence is investigated

Gamma Rays from Heavy Neutralino Dark Matter

We consider the gamma-ray spectrum from neutralino dark matter annihilations and show that internal bremsstrahlung of W pair final states gives a previously neglected source of photons at energies near the mass of the neutralino. For masses larger than about 1 TeV, and for present day detector resolutions, this results in a characteristic signal that may dominate not only over the continuous spectrum from W fragmentation, but also over the \gamma-\gamma and \gamma-Z line signals which are known to give large rates for heavy neutralinos. Observational prospects thus seem promising.Comment: 4 pages, 4 figures; revised to match published versio

Quasi-Species and Aggregate Dynamics

At an early stage in pre-biotic evolution, groups of replicating molecules must coordinate their reproduction to form aggregated units of selection. Mechanisms that enable this to occur are currently not well understood. In this paper we introduce a deterministic model of primitive replicating aggregates, proto-organisms, that host populations of replicating information carrying molecules. Some of the molecules promote the reproduction of the proto-organism at the cost of their individual replication rate. A situation resembling that of group selection arises. We derive and analytically solve a partial differential equation that describes the system. We find that the relative prevalence of fast and slow replicators is determined by the relative strength of selection at the aggregate level to the selection strength at the molecular level. The analysis is concluded by a preliminary treatment of finite population size effects.Comment: 6 page

Establishment of a foundation for predictive design analysis within the engineering design process

In today’s highly competitive market place it is of great importance for companies to deliver reliable products while decreasing the development time and costs. The time to market is a driving force for many companies, and throughout the engineering design process as well as the manufacturing process, the focus is on finding timesaving actions. However, the search for timesaving actions will most certainly result in a loss in product reliability if it is not combined with improved techniques and tools used by members of the engineering design team in order to maintain an acceptable level of reliability. One of the areas within engineering design that is adopting new techniques and methodologies is the design analysis activity that has conventionally been performed by specialists, but has to some extent shifted to also be performed, where applicable, by design engineers. Further, design analysis has traditionally been utilized as a verification tool at the latter engineering design phases and also for failure mode analysis with the objective to investigate failed designs or produce results about whether or not it will withstand applied loading conditions. Today both the research community and industry perceive the value added when design analysis is used in early engineering design phases to predict the performance of the product to be. Statistically planned and Stochastic (alternatively called in literature probabilistic) Finite Element Analysis (FEA) are addressed frequently in this area of research, and different mathematical methodologies have been discussed to provide this value-added information within design analysis. Fractional factorial designed experiments, Response Surface Methodologies (RSM) and Monte Carlo Simulations (MCS) are among the most commonly discussed approaches. One of the vital issues here is the shift from the deterministic design analysis approach, in which accounting for variations is done through safety factors that are overly conservative, to a Statistical or Stochastic design analysis approach where variables are defined in terms of their characteristics: the nature of the distribution of values, a typical value, and also, in stochastic approaches, a measure of the variability. A presentation of Predictive Design Analysis (PDA) is made in this paper, which incorporates Statistical and Stochastic approaches to perform design analysis at different phases of the engineering design process. The PDA methodology addresses abounding uncertainties i.e. material properties, magnitude and direction of loading, part geometry as well as the issues regarding sensitivity to variables acting on the product in service, all of which result in performance that is considerably different from the ideal

Bifurcation in Quantum Measurement

We present a generic model of (non-destructive) quantum measurement. Being formulated within reversible quantum mechanics, the model illustrates a mechanism of a measurement process --- a transition of the measured system to an eigenstate of the measured observable. The model consists of a two-level system $\mu$ interacting with a larger system $A$, consisting of smaller subsystems. The interaction is modelled as a scattering process. Restricting the states of $A$ to product states leads to a bifurcation process: In the limit of a large system $A$, the initial states of $A$ that are efficient in leading to a final state are divided into two separated subsets. For each of these subsets, $\mu$ ends up in one of the eigenstates of the measured observable. The probabilities obtained in this branching confirm the Born rule.Comment: A revised version that includes a more general presentation of the model (in Sect. 4) and a larger revision of the Introductio

Nonresonant high-frequency excitation of mechanical vibrations in a movable quantum dot

Nonresonant high-frequency electrostatic actuation of a movable quantum dot (QD) is investigated analytically. The electronic dot state is in tunneling contact with a continuum of electronic states in bulk electrodes. Gate electrodes induce an electric ac-field at the dot. Absorbtion of the field is accompanied by increment or decrement of one vibrational quantum in the QD. It is shown that the rate of increment overcomes the rate of decrement of vibrational quanta when the driving frequency exceeds the inverse tunneling time between the bulk electrodes and the QD. This results in a mechanical instability, leading to relatively large amplitude oscillations of the QD, which are saturated by nonlinear dissipation

Uncertainty Detection as Approximate Max-Margin Sequence Labelling

This paper reports experiments for the CoNLL 2010 shared task on learning to detect hedges and their scope in natural language text. We have addressed the experimental tasks as supervised linear maximum margin prediction problems. For sentence level hedge detection in the biological domain we use an L1-regularised binary support vector machine, while for sentence level weasel detection in the Wikipedia domain, we use an L2-regularised approach. We model the in-sentence uncertainty cue and scope detection task as an L2-regularised approximate maximum margin sequence labelling problem, using the BIO-encoding. In addition to surface level features, we use a variety of linguistic features based on a functional dependency analysis. A greedy forward selection strategy is used in exploring the large set of potential features. Our official results for Task 1 for the biological domain are 85.2 F1-score, for the Wikipedia set 55.4 F1-score. For Task 2, our official results are 2.1 for the entire task with a score of 62.5 for cue detection. After resolving errors and final bugs, our final results are for Task 1, biological: 86.0, Wikipedia: 58.2; Task 2, scopes: 39.6 and cues: 78.5

Assessment framework for a methodology under development – Application to the PDA methodology

This paper presents an assessment framework for methodologies under development. It is adapted from the evaluation framework for the design of an engineering model developed by Ben Ahmed and colleagues [1]. The assessment framework allows to take into account in a systematic way characteristics (that is, main categories or classes of potential requirements) that are of importance for the assessment of the quality a methodology, beyond effectiveness and efficiency. The framework is intended to be employed similarly to engineering design requirements checklists: ensuring first that no important characteristics are left out; deriving from these characteristics more specific requirements when necessary; using these characteristics or the derived requirements both to drive the development of the methodology and as evaluation criteria to assess the elements of the developed methodology. These characteristics can then be screened again as the methodology is improved. As the methodology is being developed, the assessments can go from wide and qualitative to more stringent. The framework is applied to assess the predictive design analysis (PDA) methodology.[1] Ben Ahmed, W., Mekhilef, M., Yannou, B., and Bigand, M., (2010), "Evaluation framework for the design of an engineering model", Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 24(1), pp. 107-125

Selective nonresonant excitation of vibrational modes in suspended graphene via vibron-plasmon interaction

We theoretically study a doped graphene ribbon suspended over a trench and subject to an ac-electrical field polarized perpendicularly to the graphene plane. In such a system, the external ac-field is coupled to the relatively slow mechanical vibrations via plasmonic oscillations in the isolated graphene sheet. We show that the electrical field generates an effective pumping of the mechanical modes. It is demonstrated that in the case of underdamped plasma oscillation, a peculiar kind of geometrical resonance of the mechanical and plasma oscillations appear. The efficiency of pumping significantly increases when the wavenumber of the mechanical mode is in close agreement with the wavenumber of the plasma waves. The intensity of the pumping increases with the wavenumber of the mode. This phenomenon allows selective actuation of different mechanical modes, although the driving field is homogeneous