Optical bistability in a nonlinear photonic crystal waveguide notch filter

Optical bistability occurs when the effects of nonlinear behaviour of materials cause hysteresis in the transmission and reflection of a device. A possible mechanism for this is a strong dependence of the optical intensity on the index of refraction, e.g. in a cavity near resonance. In a 2- dimensional photonic crystal composed of rods of high-index material in air, a waveguide can be created by removing a line of rods. When a cavity is made by taking away several rods perpendicular to the waveguide, a notch filter characteristic in the transmission occurs. Due to the high intensity in the cavity in resonance, nonlinear effects are enhanced. This paper shows numerical simulations of bistability in the transmission and in the field inside the cavity both when a material inside the cavity has third-order (Kerr-type) nonlinear effects, and when the high-index rods themselves are nonlinear

Design concepts for low-cost composite turbofan engine frame

Design concepts for low cost, lightweight composite engine frames were applied to the design requirements for the frame of a commercial, high bypass engine. Four alternative composite frame design concepts identified which consisted of generic type components and subcomponents that could be adapted to use in different locations in the engine and the different engine sizes. A variety of materials and manufacturing methods were projected with a goal for the lowest number of parts at the lowest possible cost. After a preliminary evaluation of all four frame concepts, two designs were selected for an extended design and evaluation which narrowed the final selection down to one frame that was significantly lower in cost and slighty lighter than the other frame. An implementation plan for this lowest cost frame is projected for future development and includes prospects for reducing its weight with proposed unproven, innovative fabrication techniques

Localized Spectral Envelope

The concept of the spectral envelope was introduced as a statistical basis for the frequency domain analysis and scaling of qualitative-valued time series

Potency of Current Levothyroxine Preparations Evaluated by High-Performance Liquid Chromatography

Ten different levothyroxine products manufactured by six companies were analyzed by high-performance liquid chromatography. Although nine products met the United States Pharmacopeia requirements, one product was found to have only 47% of expected potency. Until these products become more uniform, we would not recommend interchangeability of levothyroxine preparations

Conditional Spectral Analysis of Replicated Multiple Time Series with Application to Nocturnal Physiology

This article considers the problem of analyzing associations between power spectra of multiple time series and cross-sectional outcomes when data are observed from multiple subjects. The motivating application comes from sleep medicine, where researchers are able to non-invasively record physiological time series signals during sleep. The frequency patterns of these signals, which can be quantified through the power spectrum, contain interpretable information about biological processes. An important problem in sleep research is drawing connections between power spectra of time series signals and clinical characteristics; these connections are key to understanding biological pathways through which sleep affects, and can be treated to improve, health. Such analyses are challenging as they must overcome the complicated structure of a power spectrum from multiple time series as a complex positive-definite matrix-valued function. This article proposes a new approach to such analyses based on a tensor-product spline model of Cholesky components of outcome-dependent power spectra. The approach flexibly models power spectra as nonparametric functions of frequency and outcome while preserving geometric constraints. Formulated in a fully Bayesian framework, a Whittle likelihood based Markov chain Monte Carlo (MCMC) algorithm is developed for automated model fitting and for conducting inference on associations between outcomes and spectral measures. The method is used to analyze data from a study of sleep in older adults and uncovers new insights into how stress and arousal are connected to the amount of time one spends in bed

Endogenous Technological Change in Energy Systems Models: Synthesis of Experience with ERIS, MARKAL, and MESSAGE

Technological change is widely recognised as a key factor in economic progress, as it enhances the productivity of factor inputs. In recent years also the notion has developed that targeted technological development is a main means to reconcile economic ambitions with ecological considerations. This raises the issue that assessments of future trajectories of for example en-ergy systems should take into account context-specific technological progress. Rather than tak-ing characteristics of existing and emerging technologies as a given, their development should be a function of dedicated Research, Development and Demonstration (RD&D) and market de-ployment under varying external conditions. Endogenous technological learning has recently shown to be a very promising new feature in energy system models. A learning, or experience curve, describes the specific (investment) cost as a function of the cumulative capacity for a given technology. It reflects the fact that tech-nologies may experience declining costs as a result of its increasing adoption into the society due to the accumulation of knowledge through, among others, processes of learning-by-doing and learning-by-using. This report synthesises the results and findings from experiments with endogenous technologi-cal learning, as reported separately within the EU TEEM project. These experiments have been carried out by three TEEM partners using three models: ERIS (PSI), MARKAL (ECN and PSI), and MESSAGE (IIASA). The main objectives of this synthesis are: to derive common methodo-logical insights; to indicate and assess benefits of the new feature, but also its limitations and issues to solve; and to recommend further research to solve the main issues. This synthesis shows that all model applications are examples of successful first experiments to incorporate the learning-by-doing concept in energy system models. Incorporating the learning-by-doing concept makes an important difference. The experiments demonstrate and quantify the benefits of investing early in emerging technologies that are not competitive at the moment of their deployment. They also show that the long-term impact of policy instruments, such as CO2 taxes or emission limits and RD&D instruments, on technological development can be assessed adequately with models including technology learning. Adopting the concept of endogenous learning, several types of RD&D interventions can be addressed that aim at accelerating the market penetration of new technologies. The directions into which such interventions might lead have been illustrated in some of the experiments. However, quantitative relationships between R&D policy and learning data parameters are still unknow

The solute transport and binding profile of a novel nucleobase cation symporter 2 from the honeybee pathogen Paenibacillus larvae

Here, we report that a novel nucleobase cation symporter 2 encoded in the genome of the honeybee bacterial pathogen Paenibacillus larvae reveals high levels of amino acid sequence similarity to the Escherichia coli and Bacillus subtilis uric acid and xanthine transporters. This transporter is named P. larvae uric acid permease-like protein (PlUacP). Even though PlUacP displays overall amino acid sequence similarities, has common secondary structures, and shares functional motifs and functionally important amino acids with E. coli xanthine and uric acid transporters, these commonalities are insufficient to assign transport function to PlUacP. The solute transport and binding profile of PlUacP was determined by radiolabeled uptake experiments via heterologous expression in nucleobase transporter-deficient Saccharomyces cerevisiae strains. PlUacP transports the purines adenine and guanine and the pyrimidine uracil. Hypoxanthine, xanthine, and cytosine are not transported by PlUacP, but, along with uric acid, bind in a competitive manner. PlUacP has strong affinity for adenine Km 7.04 ± 0.18 μm, and as with other bacterial and plant NCS2 proteins, PlUacP function is inhibited by the proton disruptor carbonyl cyanide m-chlorophenylhydrazone. The solute transport and binding profile identifies PlUacP as a novel nucleobase transporter

Adaptive Step Size for Hybrid Monte Carlo Algorithm

We implement an adaptive step size method for the Hybrid Monte Carlo a lgorithm. The adaptive step size is given by solving a symmetric error equation. An integr ator with such an adaptive step size is reversible. Although we observe appreciable variations of the step size, the overhead of the method exceeds its benefits. We propose an explanation for this phenomenon.Comment: 13 pages, 5 Postscript figures, late