Estimation and inference of error-prone covariate effect in the presence of confounding variables

© 2017, Institute of Mathematical Statistics. All rights reserved. We introduce a general single index semiparametric measurement error model for the case that the main covariate of interest is measured with error and modeled parametrically, and where there are many other variables also important to the modeling. We propose a semiparametric bias-correction approach to estimate the effect of the covariate of interest. The resultant estimators are shown to be root-n consistent, asymptotically normal and locally efficient. Comprehensive simulations and an analysis of an empirical data set are performed to demonstrate the finite sample performance and the bias reduction of the locally efficient estimators

Realising biaxial reinforcement via orientation-induced anisotropic swelling in graphene-based elastomers

The biaxial mechanical properties constitute another remarkable advantage of graphene, but their evaluation has been overlooked in polymer nanocomposites. Herein, we provided an innovative and practical method to characterise biaxial reinforcement from graphene via swelling of elastomers, where graphene nanoplatelets were controlled to be oriented in-plane. The in-plane-aligned graphene imposed a biaxial constraining force to the elastomer during the swelling process that led to the anisotropic swelling behaviour of the bulk nanocomposites

Multivariate MR Biomarkers Better Predict Cognitive Dysfunction in Mouse Models of Alzheimers Disease

To understand multifactorial conditions such as Alzheimers disease (AD) we need brain signatures that predict the impact of multiple pathologies and their interactions. To help uncover the relationships between brain circuits and cognitive markers we have used mouse models that represent, at least in part, the complex interactions altered in AD. In particular, we aimed to understand the relationship between vulnerable brain circuits and memory deficits measured in the Morris water maze, and we tested several predictive modeling approaches. We used in vivo manganese enhanced MRI voxel based analyses to reveal regional differences in volume (morphometry), signal intensity (activity), and magnetic susceptibility (iron deposition, demyelination). These regions included the hippocampus, olfactory areas, entorhinal cortex and cerebellum. The image based properties of these regions were used to predict spatial memory. We next used eigenanatomy, which reduces dimensionality to produce sets of regions that explain the variance in the data. For each imaging marker, eigenanatomy revealed networks underpinning a range of cognitive functions including memory, motor function, and associative learning. Finally, the integration of multivariate markers in a supervised sparse canonical correlation approach outperformed single predictor models and had significant correlates to spatial memory. Among a priori selected regions, the fornix also provided good predictors, raising the possibility of investigating how disease propagation within brain networks leads to cognitive deterioration. Our results support that modeling approaches integrating multivariate imaging markers provide sensitive predictors of AD-like behaviors. Such strategies for mapping brain circuits responsible for behaviors may help in the future predict disease progression, or response to interventions.Comment: 23 pages, 3 Tables, 6 Figures; submitted for publicatio

Endothelin receptor a blockade is an ineffective treatment for adriamycin nephropathy

Endothelin is a vasoconstricting peptide that plays a key role in vascular homeostasis, exerting its biologic effects via two receptors, the endothelin receptor A (ETA) and endothelin receptor B (ETB). Activation of ETA and ETB has opposing actions, in which hyperactive ETA is generally vasoconstrictive and pathologic. Selective ETA blockade has been shown to be beneficial in renal injuries such as diabetic nephropathy and can improve proteinuria. Atrasentan is a selective pharmacologic ETA blocker that preferentially inhibits ETA activation. In this study, we evaluated the efficacy of ETA blockade by atrasentan in ameliorating proteinuria and kidney injury in murine adriamycin nephropathy, a model of human focal segmental glomerulosclerosis. We found that ETA expression was unaltered during the course of adriamycin nephropathy. Whether initiated prior to injury in a prevention protocol (5 mg/kg/day, i.p.) or after injury onset in a therapeutic protocol (7 mg/kg or 20 mg/kg three times a week, i.p.), atrasentan did not significantly affect the initiation and progression of adriamycin-induced albuminuria (as measured by urinary albumin-to-creatinine ratios). Indices of glomerular damage were also not improved in atrasentan-treated groups, in either the prevention or therapeutic protocols. Atrasentan also failed to improve kidney function as determined by serum creatinine, histologic damage, and mRNA expression of numerous fibrosis-related genes such as collagen-I and TGF-β1. Therefore, we conclude that selective blockade of ETA by atrasentan has no effect on preventing or ameliorating proteinuria and kidney injury in adriamycin nephropathy. © 2013 Tan et al

Experience replay is associated with efficient nonlocal learning

To make effective decisions, people need to consider the relationship between actions and outcomes. These are often separated by time and space. The neural mechanisms by which disjoint actions and outcomes are linked remain unknown. One promising hypothesis involves neural replay of nonlocal experience. Using a task that segregates direct from indirect value learning, combined with magnetoencephalography, we examined the role of neural replay in human nonlocal learning. After receipt of a reward, we found significant backward replay of nonlocal experience, with a 160-millisecond state-to-state time lag, which was linked to efficient learning of action values. Backward replay and behavioral evidence of nonlocal learning were more pronounced for experiences of greater benefit for future behavior. These findings support nonlocal replay as a neural mechanism for solving complex credit assignment problems during learning

Mechanisms of mechanical reinforcement by graphene and carbon nanotubes in polymer nanocomposites

Polymer nanocomposites reinforced with carbon-based nanofillers are gaining increasing interest for a number of applications due to their excellent properties. The understanding of the reinforcing mechanisms is, therefore, very important for the maximization of performance. This present review summarizes the current literature status on the mechanical properties of composites reinforced with graphene-related materials (GRMs) and carbon nanotubes (CNTs) and identifies the parameters that clearly affect the mechanical properties of the final materials. It is also shown how Raman spectroscopy can be utilized for the understanding of the stress transfer efficiency from the matrix to the reinforcement and it can even be used to map stress and strain in graphene. Importantly, it is demonstrated clearly that continuum micromechanics that was initially developed for fibre-reinforced composites is still applicable at the nanoscale for both GRMs and CNTs. Finally, current problems and future perspectives are discussed

Estimating black hole masses of blazars

Estimating black hole masses of blazars is still a big challenge. Because of the contamination of jets, using the previously suggested size -- continuum luminosity relation can overestimate the broad line region (BLR) size and black hole mass for radio-loud AGNs, including blazars. We propose a new relation between the BLR size and $H_{\beta}$ emission line luminosity and present evidences for using it to get more accurate black hole masses of radio-loud AGNs. For extremely radio-loud AGNs such as blazars with weak/absent emission lines, we suggest to use the fundamental plane relation of their elliptical host galaxies to estimate the central velocity dispersions and black hole masses, if their velocity dispersions are not known but the host galaxies can be mapped. The black hole masses of some well-known blazars, such as OJ 287, AO 0235+164 and 3C 66B, are obtained using these two methods and the M - $\sigma$ relation. The implications of their black hole masses on other related studies are also discussed.Comment: 7 pages, invited talk presented in the workshop on Multiwavelength Variability of Blazars (Guangzhou, China, Sept. 22-24, 2010). To be published in the Journal of Astrophysics and Astronom

SPECTRAL CORRECTION FACTORS FOR CONVENTIONAL NEUTRON DOSE METERS USED IN HIGH-ENERGY NEUTRON ENVIRONMENTS-IMPROVED AND EXTENDED RESULTS BASED ON A COMPLETE SURVEY OF ALL NEUTRON SPECTRA IN IAEA-TRS-403

This paper presents improved and extended results of our previous study on corrections for conventional neutron dose meters used in environments with high-energy neutrons (En > 10 MeV). Conventional moderated-type neutron dose meters tend to underestimate the dose contribution of high-energy neutrons because of the opposite trends of dose conversion coefficients and detection efficiencies as the neutron energy increases. A practical correction scheme was proposed based on analysis of hundreds of neutron spectra in the IAEA-TRS-403 report. By comparing 252Cf-calibrated dose responses with reference values derived from fluence-to-dose conversion coefficients, this study provides recommendations for neutron field characterization and the corresponding dose correction factors. Further sensitivity studies confirm the appropriateness of the proposed scheme and indicate that (1) the spectral correction factors are nearly independent of the selection of three commonly used calibration sources: 252Cf, 241Am-Be and 239Pu-Be; (2) the derived correction factors for Bonner spheres of various sizes (6”−9”) are similar in trend and (3) practical high-energy neutron indexes based on measurements can be established to facilitate the application of these correction factors in workplaces

The optical microscopy with virtual image breaks a record: 50-nm resolution imaging is demonstrated

We demonstrate a new 'microsphere nanoscope' that uses ordinary SiO2 microspheres as superlenses to create a virtual image of the object in near field. The magnified virtual image greatly overcomes the diffraction limit. We are able to resolve clearly 50-nm objects under a standard white light source in both transmission and reflection modes. The resolution achieved for white light opens a new opportunity to image viruses, DNA and molecules in real time

Ultrahigh power and energy density in partially ordered lithium-ion cathode materials

The rapid market growth of rechargeable batteries requires electrode materials that combine high power and energy and are made from earth-abundant elements. Here we show that combining a partial spinel-like cation order and substantial lithium excess enables both dense and fast energy storage. Cation overstoichiometry and the resulting partial order is used to eliminate the phase transitions typical of ordered spinels and enable a larger practical capacity, while lithium excess is synergistically used with fluorine substitution to create a high lithium mobility. With this strategy, we achieved specific energies greater than 1,100 Wh kg–1 and discharge rates up to 20 A g–1. Remarkably, the cathode materials thus obtained from inexpensive manganese present a rare case wherein an excellent rate capability coexists with a reversible oxygen redox activity. Our work shows the potential for designing cathode materials in the vast space between fully ordered and disordered compounds