Negative index fishnet with nanopillars formed by direct nano-imprint lithography

In this paper we demonstrate the ability to fabricate fishnets by nanoimprinting directly into a pre-deposited three layer metal–dielectric–metal stack, enabling us to pattern large areas in two minutes. We have designed and fabricated two different fishnet structures of varying dimensions using this method and measured their resonant wavelengths in the near-infrared at 1.45 μm and 1.88 μm. An important by-product of directly imprinting into the metal–dielectric stack, without separation from the substrate, is the formation of rectangular nanopillars that sit within the rectangular apertures between the fishnet slabs. Simulations complement our measurements and suggest a negative refractive index real part with a magnitude of 1.6. Further simulations suggest that if the fishnet were to be detached from the supporting substrate a refractive index real part of 5 and FOM of 2.74 could be obtained

A Bayesian spatio-temporal model of panel design data: airborne particle number concentration in Brisbane, Australia

This paper outlines a methodology for semi-parametric spatio-temporal modelling of data which is dense in time but sparse in space, obtained from a split panel design, the most feasible approach to covering space and time with limited equipment. The data are hourly averaged particle number concentration (PNC) and were collected, as part of the Ultrafine Particles from Transport Emissions and Child Health (UPTECH) project. Two weeks of continuous measurements were taken at each of a number of government primary schools in the Brisbane Metropolitan Area. The monitoring equipment was taken to each school sequentially. The school data are augmented by data from long term monitoring stations at three locations in Brisbane, Australia. Fitting the model helps describe the spatial and temporal variability at a subset of the UPTECH schools and the long-term monitoring sites. The temporal variation is modelled hierarchically with penalised random walk terms, one common to all sites and a term accounting for the remaining temporal trend at each site. Parameter estimates and their uncertainty are computed in a computationally efficient approximate Bayesian inference environment, R-INLA. The temporal part of the model explains daily and weekly cycles in PNC at the schools, which can be used to estimate the exposure of school children to ultrafine particles (UFPs) emitted by vehicles. At each school and long-term monitoring site, peaks in PNC can be attributed to the morning and afternoon rush hour traffic and new particle formation events. The spatial component of the model describes the school to school variation in mean PNC at each school and within each school ground. It is shown how the spatial model can be expanded to identify spatial patterns at the city scale with the inclusion of more spatial locations.Comment: Draft of this paper presented at ISBA 2012 as poster, part of UPTECH projec

Mapping the sensitivity of split ring resonators using a localized analyte

Split ring resonator (SRR) based metamaterials have frequently been demonstrated for use as optical sensors of organic materials. This is made possible by matching the wavelength of the SRR plasmonic resonance with a molecular resonance of a specific analyte, which is usually placed on top of the metal structure. However, systematic studies of SRRs that identify the regions that exhibit a high electric field strength are commonly performed using simulations. In this paper we demonstrate that areas of high electric field strength, termed “hot-spots,” can be found by localizing a small quantity of organic analyte at various positions on or near the structure. Furthermore, the sensitivity of the SRR to the localized analyte can be quantified to determine, experimentally, suitable regions for optical sensing

Cell Cycle-Dependent Differentiation Dynamics Balances Growth and Endocrine Differentiation in the Pancreas

Organogenesis relies on the spatiotemporal balancing of differentiation and proliferation driven by an expanding pool of progenitor cells. In the mouse pancreas, lineage tracing at the population level has shown that the expanding pancreas progenitors can initially give rise to all endocrine, ductal, and acinar cells but become bipotent by embryonic day 13.5, giving rise to endocrine cells and ductal cells. However, the dynamics of individual progenitors balancing self-renewal and lineage-specific differentiation has never been described. Using three-dimensional live imaging and in vivo clonal analysis, we reveal the contribution of individual cells to the global behaviour and demonstrate three modes of progenitor divisions: symmetric renewing, symmetric endocrinogenic, and asymmetric generating a progenitor and an endocrine progenitor. Quantitative analysis shows that the endocrine differentiation process is consistent with a simple model of cell cycle-dependent stochastic priming of progenitors to endocrine fate. The findings provide insights to define control parameters to optimize the generation of β-cells in vitro

Time-varying effective EEG source connectivity: the optimization of model parameters*

Adaptive estimation methods based on general Kalman filter are powerful tools to investigate brain networks dynamics given the non-stationary nature of neural signals. These methods rely on two parameters, the model order p and adaptation constant c, which determine the resolution and smoothness of the time-varying multivariate autoregressive estimates. A sub-optimal filtering may present consistent biases in the frequency domain and temporal distortions, leading to fallacious interpretations. Thus, the performance of these methods heavily depends on the accurate choice of these two parameters in the filter design. In this work, we sought to define an objective criterion for the optimal choice of these parameters. Since residual- and information-based criteria are not guaranteed to reach an absolute minimum, we propose to study the partial derivatives of these functions to guide the choice of p and c. To validate the performance of our method, we used a dataset of human visual evoked potentials during face perception where the generation and propagation of information in the brain is well understood and a set of simulated data where the ground truth is available

The Hopkins Verbal Learning Test and screening for dementia

The present study investigated the sensitivity and specificity of the Hopkins Verbal Learning Test (HVLT) for demented patients (n=82, using NINCDS criteria) and 114 healthy controls - equivalent in age, years of education and gender–ratio - from the Oxford Project To Investigate Memory and Ageing. The HVLT ‘Total recall’ score had 87% sensitivity and 98% specificity for dementia using a cut-off score of 14.5. Using a 'Memory' score (the sum of the 'Total Recall' and the 'Discrimination Index') with a cutoff score of 24.5 gave a 91% sensitivity and 98% specificity for Alzheimer’s disease cases when compared to controls. Unlike the MMSE, the HVLT has no ceiling effects and does not have to be adjusted for education. We conclude that the HVLT is an easy to administer, quick and well tolerated tool for the screening of dementia

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

Mitochondrial dysfunction is a key determinant of the rare disease lymphangioleiomyomatosis and provides a novel therapeutic target

Acknowledgements The authors are grateful to Prof. Dr. Laszlo Seress, Professor Emeritus, Central Electron Microscope Laboratory, University of Pecs, Pecs, Hungary for his invaluable assistance with electron microscopic studies using the Jeol 1200 TEM and Jeol 1400 TEM electron microscopes. Jeol TEM was funded by the GINOP-2.3.3-15-2016-0002 (New generation electron microscope: 3D ultrastructure). We would also like to thank Dr. Veronika Csongei, PhD, Senior Lecturer, Department of Pharmaceutical Biotechnology and Janos Szentagothai Research Centre, University of Pecs, Pecs, Hungary for assistance with statistical analysis. Funding JEP was supported by the European Union and the State of Hungary, co-financed by the European Social Fund in the framework of TÁMOP-4.2.4.A/2-11/1-2012-0001 “National Excellence Program”.Peer reviewedPublisher PD

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