Controllability and observabiliy of an artificial advection-diffusion problem

In this paper we study the controllability of an artificial advection-diffusion system through the boundary. Suitable Carleman estimates give us the observability on the adjoint system in the one dimensional case. We also study some basic properties of our problem such as backward uniqueness and we get an intuitive result on the control cost for vanishing viscosity.Comment: 20 pages, accepted for publication in MCSS. DOI: 10.1007/s00498-012-0076-

Designing an efficient hybrid optical cavity

We present an efficient terahertz (THz) detector based on an optically thin hybrid cavity. We use experimental and numerical methods to design efficient detectors, finding a hybrid cavity structure with a photoconductive (PC) layer as thin as 50 nm which absorbs almost 80% of light at the operation wavelength. These optically thin detectors are well suited to near-field microscopy and terahertz component integration

Discrete and fuzzy dynamical genetic programming in the XCSF learning classifier system

A number of representation schemes have been presented for use within learning classifier systems, ranging from binary encodings to neural networks. This paper presents results from an investigation into using discrete and fuzzy dynamical system representations within the XCSF learning classifier system. In particular, asynchronous random Boolean networks are used to represent the traditional condition-action production system rules in the discrete case and asynchronous fuzzy logic networks in the continuous-valued case. It is shown possible to use self-adaptive, open-ended evolution to design an ensemble of such dynamical systems within XCSF to solve a number of well-known test problems

Effective, Robust Design of Community Mitigation for Pandemic Influenza: A Systematic Examination of Proposed US Guidance

BACKGROUND: The US government proposes pandemic influenza mitigation guidance that includes isolation and antiviral treatment of ill persons, voluntary household member quarantine and antiviral prophylaxis, social distancing of individuals, school closure, reduction of contacts at work, and prioritized vaccination. Is this the best strategy combination? Is choice of this strategy robust to pandemic uncertainties? What are critical enablers of community resilience? METHODS AND FINDINGS: We systematically simulate a broad range of pandemic scenarios and mitigation strategies using a networked, agent-based model of a community of explicit, multiply-overlapping social contact networks. We evaluate illness and societal burden for alterations in social networks, illness parameters, or intervention implementation. For a 1918-like pandemic, the best strategy minimizes illness to <1% of the population and combines network-based (e.g. school closure, social distancing of all with adults' contacts at work reduced), and case-based measures (e.g. antiviral treatment of the ill and prophylaxis of household members). We find choice of this best strategy robust to removal of enhanced transmission by the young, additional complexity in contact networks, and altered influenza natural history including extended viral shedding. Administration of age-group or randomly targeted 50% effective pre-pandemic vaccine with 7% population coverage (current US H5N1 vaccine stockpile) had minimal effect on outcomes. In order, mitigation success depends on rapid strategy implementation, high compliance, regional mitigation, and rigorous rescinding criteria; these are the critical enablers for community resilience. CONCLUSIONS: Systematic evaluation of feasible, recommended pandemic influenza interventions generally confirms the US community mitigation guidance yields best strategy choices for pandemic planning that are robust to a wide range of uncertainty. The best strategy combines network- and case-based interventions; network-based interventions are paramount. Because strategies must be applied rapidly, regionally, and stringently for greatest benefit, preparation and public education is required for long-lasting, high community compliance during a pandemic

An efficient terahertz detector based on an optical hybrid cavity

We demonstrate an efficient terahertz (THz) detector based on an optical hybrid cavity, which consists of an optically thin photoconductive layer between a distributed Bragg reflector (DBR) and an array of electrically isolated nanoantennas. Using a combination of numerical simulations and optical experiments, we find a hybrid cavity design which absorbs <75% of incident light with a 50 nm photoconductive layer. By integrating this optical hybrid cavity design into a THz detector, we see enhanced detection sensitivity at the operation wavelength (∼815 nm) over designs which do not include the nanoantenna array

Optically thin hybrid cavity for terahertz photo-conductive detectors

The efficiency of photoconductive (PC) devices, including terahertz detectors, is constrained by the bulk optical constants of PC materials. Here, we show that optical absorption in a PC layer can be modified substantially within a hybrid cavity containing nanoantennas and a Distributed Bragg Reflector. We find that a hybrid cavity, consisting of a GaAs PC layer of just 50 nm, can be used to absorb >75% of incident photons by trapping the light within the cavity. We provide an intuitive model, which describes the dependence of the optimum operation wavelength on the cavity thickness. We also find that the nanoantenna size is a critical parameter, small variations of which lead to both wavelength shifting and reduced absorption in the cavity, suggesting that impedance matching is key for achieving efficient absorption in the optically thin hybrid cavities

Transparent dense sodium

Under pressure, metals exhibit increasingly shorter interatomic distances. Intuitively, this response is expected to be accompanied by an increase in the widths of the valence and conduction bands and hence a more pronounced free-electron-like behaviour. But at the densities that can now be achieved experimentally, compression can be so substantial that core electrons overlap. This effect dramatically alters electronic properties from those typically associated with simple free-electron metals such as lithium and sodium, leading in turn to structurally complex phases and superconductivity with a high critical temperature. But the most intriguing prediction - that the seemingly simple metals Li and Na will transform under pressure into insulating states, owing to pairing of alkali atoms - has yet to be experimentally confirmed. Here we report experimental observations of a pressure-induced transformation of Na into an optically transparent phase at 200 GPa (corresponding to 5.0-fold compression). Experimental and computational data identify the new phase as a wide bandgap dielectric with a six-coordinated, highly distorted double-hexagonal close-packed structure. We attribute the emergence of this dense insulating state not to atom pairing, but to p-d hybridizations of valence electrons and their repulsion by core electrons into the lattice interstices. We expect that such insulating states may also form in other elements and compounds when compression is sufficiently strong that atomic cores start to overlap strongly.Comment: Published in Nature 458, 182-185 (2009

Effects of surgery on the mental status of older persons. A meta-analytic review

The data bases of 18 empirical studies were combined into one comprehensive data set and subjected to meta-analysis. The following trends were observed: (1) surgery has a significantly decompensating impact on the mental status of older persons, and the average effect size observed is modest (r = .37); (2) for all mental status measures included in the review (cognition, delirium and affect), effect size appears to be significantly moderated by patient age; (3) patient sex may be predictive of the kind of mental impairment that is most likely to occur within an older surgery population, with women manifesting a greater affinity for delirious and men for cognitive decompensation; (4) most existing research within this domain of study is either purely descriptive or anecdotal: of 46 studies reviewed, only 18, or 39.1% of the total published output, were of sufficient methodologic rigor to allow for scientifically valid effect-size computations. The implications of these findings for future research are discussed

Evaluation and use of surveillance system data toward the identification of high-risk areas for potential cholera vaccination: a case study from Niger.

In 2008, Africa accounted for 94% of the cholera cases reported worldwide. Although the World Health Organization currently recommends the oral cholera vaccine in endemic areas for high-risk populations, its use in Sub-Saharan Africa has been limited. Here, we provide the principal results of an evaluation of the cholera surveillance system in the region of Maradi in Niger and an analysis of its data towards identifying high-risk areas for cholera

The interplay of intrinsic and extrinsic bounded noises in genetic networks

After being considered as a nuisance to be filtered out, it became recently clear that biochemical noise plays a complex role, often fully functional, for a genetic network. The influence of intrinsic and extrinsic noises on genetic networks has intensively been investigated in last ten years, though contributions on the co-presence of both are sparse. Extrinsic noise is usually modeled as an unbounded white or colored gaussian stochastic process, even though realistic stochastic perturbations are clearly bounded. In this paper we consider Gillespie-like stochastic models of nonlinear networks, i.e. the intrinsic noise, where the model jump rates are affected by colored bounded extrinsic noises synthesized by a suitable biochemical state-dependent Langevin system. These systems are described by a master equation, and a simulation algorithm to analyze them is derived. This new modeling paradigm should enlarge the class of systems amenable at modeling. We investigated the influence of both amplitude and autocorrelation time of a extrinsic Sine-Wiener noise on: $(i)$ the Michaelis-Menten approximation of noisy enzymatic reactions, which we show to be applicable also in co-presence of both intrinsic and extrinsic noise, $(ii)$ a model of enzymatic futile cycle and $(iii)$ a genetic toggle switch. In $(ii)$ and $(iii)$ we show that the presence of a bounded extrinsic noise induces qualitative modifications in the probability densities of the involved chemicals, where new modes emerge, thus suggesting the possibile functional role of bounded noises