Transmission of PhC coupled-resonator waveguide (PhCCRW) structure enhanced via mode matching

A method for increasing the coupling efficiency between ridge optical waveguides and PhCCRWs is described. This increase is achieved via W1 channel waveguide sections, formed within a two-dimensional triangular lattice photonic crystal using mode-matching. The mode-matching is achieved by low quality-factor modified cavities added to both the input and output ports of the PhCCRW. A three dimensional finite-difference time-domain method has been used to simulate light propagation through the modified PhCCRW. We have fabricated PhCCRWs working at 1.5µm in silicon-on-insulator material. Measurements and simulations show that the overall transmission is improved by a factor of two

Operations management system

The objective of an operations management system is to provide an orderly and efficient method to operate and maintain aerospace vehicles. Concepts are described for an operations management system and the key technologies are highlighted which will be required if this capability is brought to fruition. Without this automation and decision aiding capability, the growing complexity of avionics will result in an unmanageable workload for the operator, ultimately threatening mission success or survivability of the aircraft or space system. The key technologies include expert system application to operational tasks such as replanning, equipment diagnostics and checkout, global system management, and advanced man machine interfaces. The economical development of operations management systems, which are largely software, will require advancements in other technological areas such as software engineering and computer hardware

How do random Fibonacci sequences grow?

We study two kinds of random Fibonacci sequences defined by $F_1=F_2=1$ and for $n\ge 1$, $F_{n+2} = F_{n+1} \pm F_{n}$ (linear case) or $F_{n+2} = |F_{n+1} \pm F_{n}|$ (non-linear case), where each sign is independent and either + with probability $p$ or - with probability $1-p$ ($0<p\le 1$). Our main result is that the exponential growth of $F_n$ for $0<p\le 1$ (linear case) or for $1/3\le p\le 1$ (non-linear case) is almost surely given by $$\int_0^\infty \log x d\nu_\alpha (x),$$ where $\alpha$ is an explicit function of $p$ depending on the case we consider, and $\nu_\alpha$ is an explicit probability distribution on \RR_+ defined inductively on Stern-Brocot intervals. In the non-linear case, the largest Lyapunov exponent is not an analytic function of $p$, since we prove that it is equal to zero for $0<p\le1/3$. We also give some results about the variations of the largest Lyapunov exponent, and provide a formula for its derivative

Environmental data from laboratory- and bench-scale Pressurized Fluidized-Bed Hydroretorting of Eastern oil shale

As part of a 3-year program to develop the Pressurized Fluidized-Bed Hydroretorting (PFH) Process for Eastern oil shales, IGT conducted tests in laboratory-scale batch and continuous units as well as a 45-kg/h bench-scale unit to generate a data base for 6 Eastern shales. Data were collected during PFH processing of raw Alabama and Indiana shales and a beneficiated Indiana shale for environmental mitigation analyses. The data generated include trace element analyses of the raw feeds and spent shales, product oils, and sour waters. The sulfur compounds present in the product gas and trace components in the sour water were also determined. In addition, the leaching characteristics of the feed and residue solids were determined. The data obtained were used to evaluate the environmental impact of a shale processing plant based on the PFH process. This paper presents the environmental data obtained from bench-scale tests conducted during the program

Fermions and Loops on Graphs. I. Loop Calculus for Determinant

This paper is the first in the series devoted to evaluation of the partition function in statistical models on graphs with loops in terms of the Berezin/fermion integrals. The paper focuses on a representation of the determinant of a square matrix in terms of a finite series, where each term corresponds to a loop on the graph. The representation is based on a fermion version of the Loop Calculus, previously introduced by the authors for graphical models with finite alphabets. Our construction contains two levels. First, we represent the determinant in terms of an integral over anti-commuting Grassman variables, with some reparametrization/gauge freedom hidden in the formulation. Second, we show that a special choice of the gauge, called BP (Bethe-Peierls or Belief Propagation) gauge, yields the desired loop representation. The set of gauge-fixing BP conditions is equivalent to the Gaussian BP equations, discussed in the past as efficient (linear scaling) heuristics for estimating the covariance of a sparse positive matrix.Comment: 11 pages, 1 figure; misprints correcte

Modelling of photonic wire Bragg Gratings

Some important properties of photonic wire Bragg grating structures have been investigate. The design, obtained as a generalisation of the full-width gap grating, has been modelled using 3D finite-difference time-domain simulations. Different types of stop-band have been observed. The impact of the grating geometry on the lowest order (longest wavelength) stop-band has been investigated - and has identified deeply indented configurations where reduction of the stop-bandwidth and of the reflectivity occurred. Our computational results have been substantially validated by an experimental demonstration of the fundamental stop-band of photonic wire Bragg gratings fabricated on silicon-on-insulator material. The accuracy of two distinct 2D computational models based on the effective index method has also been studied - because of their inherently much greater rapidity and consequent utility for approximate initial designs. A 2D plan-view model has been found to reproduce a large part of the essential features of the spectral response of full 3D models

A Bayesian General Linear Modeling Approach to Cortical Surface fMRI Data Analysis

Cortical surface functional magnetic resonance imaging (cs-fMRI) has recently grown in popularity versus traditional volumetric fMRI. In addition to offering better whole-brain visualization, dimension reduction, removal of extraneous tissue types, and improved alignment of cortical areas across subjects, it is also more compatible with common assumptions of Bayesian spatial models. However, as no spatial Bayesian model has been proposed for cs-fMRI data, most analyses continue to employ the classical general linear model (GLM), a “massive univariate” approach. Here, we propose a spatial Bayesian GLM for cs-fMRI, which employs a class of sophisticated spatial processes to model latent activation fields. We make several advances compared with existing spatial Bayesian models for volumetric fMRI. First, we use integrated nested Laplacian approximations, a highly accurate and efficient Bayesian computation technique, rather than variational Bayes. To identify regions of activation, we utilize an excursions set method based on the joint posterior distribution of the latent fields, rather than the marginal distribution at each location. Finally, we propose the first multi-subject spatial Bayesian modeling approach, which addresses a major gap in the existing literature. The methods are very computationally advantageous and are validated through simulation studies and two task fMRI studies from the Human Connectome Project. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement

Within study comparisons and risk of bias in international development: Systematic review and critical appraisal

Background Many systematic reviews incorporate nonrandomised studies of effects, sometimes called quasi‐experiments or natural experiments. However, the extent to which nonrandomised studies produce unbiased effect estimates is unclear in expectation or in practice. The usual way that systematic reviews quantify bias is through “risk of bias assessment” and indirect comparison of findings across studies using meta‐analysis. A more direct, practical way to quantify the bias in nonrandomised studies is through “internal replication research”, which compares the findings from nonrandomised studies with estimates from a benchmark randomised controlled trial conducted in the same population. Despite the existence of many risks of bias tools, none are conceptualised to assess comprehensively nonrandomised approaches with selection on unobservables, such as regression discontinuity designs (RDDs). The few that are conceptualised with these studies in mind do not draw on the extensive literature on internal replications (within‐study comparisons) of randomised trials. Objectives Our research objectives were as follows: Objective 1: to undertake a systematic review of nonrandomised internal study replications of international development interventions. Objective 2: to develop a risk of bias tool for RDDs, an increasingly common method used in social and economic programme evaluation. Methods We used the following methods to achieve our objectives. Objective 1: we searched systematically for nonrandomised internal study replications of benchmark randomised experiments of social and economic interventions in low‐ and middle‐income countries (L&MICs). We assessed the risk of bias in benchmark randomised experiments and synthesised evidence on the relative bias effect sizes produced by benchmark and nonrandomised comparison arms. Objective 2: We used document review and expert consultation to develop further a risk of bias tool for quasi‐experimental studies of interventions (ROBINS‐I) for RDDs. Results Objective 1: we located 10 nonrandomised internal study replications of randomised trials in L&MICs, six of which are of RDDs and the remaining use a combination of statistical matching and regression techniques. We found that benchmark experiments used in internal replications in international development are in the main well‐conducted but have “some concerns” about threats to validity, usually arising due to the methods of outcomes data collection. Most internal replication studies report on a range of different specifications for both the benchmark estimate and the nonrandomised replication estimate. We extracted and standardised 604 bias coefficient effect sizes from these studies, and present average results narratively. Objective 2: RDDs are characterised by prospective assignment of participants based on a threshold variable. Our review of the literature indicated there are two main types of RDD. The most common type of RDD is designed retrospectively in which the researcher identifies post‐hoc the relationship between outcomes and a threshold variable which determines assignment to intervention at pretest. These designs usually draw on routine data collection such as administrative records or household surveys. The other, less common, type is a prospective design where the researcher is also involved in allocating participants to treatment groups from the outset. We developed a risk of bias tool for RDDs. Conclusions Internal study replications provide the grounds on which bias assessment tools can be evidenced. We conclude that existing risk of bias tools needs to be further developed for use by Campbell collaboration authors, and there is a wide range of risk of bias tools and internal study replications to draw on in better designing these tools. We have suggested the development of a promising approach for RDD. Further work is needed on common methodologies in programme evaluation, for example on statistical matching approaches. We also highlight that broader efforts to identify all existing internal replication studies should consider more specialised systematic search strategies within particular literatures; so as to overcome a lack of systematic indexing of this evidence

Gene Regulatory Networks from Multifactorial Perturbations Using Graphical Lasso: Application to the DREAM4 Challenge

A major challenge in the field of systems biology consists of predicting gene regulatory networks based on different training data. Within the DREAM4 initiative, we took part in the multifactorial sub-challenge that aimed to predict gene regulatory networks of size 100 from training data consisting of steady-state levels obtained after applying multifactorial perturbations to the original in silico network

Modulational instability in a silicon-on-insulator directional coupler: Role of the coupling-induced group velocity dispersion

We report frequency conversion experiments in silicon-on-insulator (SOI) directional couplers. We demonstrate that the evanescent coupling between two subwavelength SOI waveguides is strongly dispersive and significantly modifies modulational instability (MI) spectra through the coupling induced group velocity dispersion (GVD). As the separation between two 380-nm-wide silicon photonic wires decreases, the increasing dispersion of the coupling makes the GVD in the symmetric supermode more normal and suppresses the bandwidth of the MI gain observed for larger separations