88 research outputs found

    Estimation and Inference in Short Panel Vector Autoregressions with Unit Roots and Cointegration

    Get PDF
    This paper considers estimation and inference in panel vector autoregressions (PVARs) with fixed effects when the time dimension of the panel is finite, and the cross-sectional dimension is large. A Maximum Likelihood (ML) estimator based on a transformed likelihood function is proposed and shown to be consistent and asymptotically normally distributed irrespective of the unit root and cointegrating properties of the underlying PVAR model. The transformed likelihood framework is also used to derive unit root and cointegration tests in panels with short time dimension; these tests have the attractive feature that they are based on standard chi-squared and normal distributed statistics. Examining Generalised Method of Moments (GMM) estimation as an alternative to our proposed ML estimator, it is shown that conventional GMM estimators based on standard orthogonality conditions break down if the underlying time series contain unit roots.Panel vector autoregressions, Fixed effects, Unit roots, Cointegration

    ALP-enigma protein ALP-1 functions in actin filament organization to promote muscle structural integrity in Caenorhabditis elegans

    Get PDF
    Journal ArticleMutations that affect the Z-disk-associated ALP-Enigma proteins have been linked to human muscular and cardiac diseases. Despite their clear physiological significance for human health, the mechanism of action of ALP-Enigma proteins is largely unknown. In Caenorhabditis elegans, the ALP-Enigma protein family is encoded by a single gene, alp-1; thus C. elegans provides an excellent model to study ALP-Enigma function. Here we present a molecular and genetic analysis of ALP-Enigma function in C. elegans

    Photon-noise limited sensitivity in titanium nitride kinetic inductance detectors

    Get PDF
    We demonstrate photon-noise limited performance at sub-millimeter wavelengths in feedhorn-coupled, microwave kinetic inductance detectors (MKIDs) made of a TiN/Ti/TiN trilayer superconducting film, tuned to have a transition temperature of 1.4~K. Micro-machining of the silicon-on-insulator wafer backside creates a quarter-wavelength backshort optimized for efficient coupling at 250~\micron. Using frequency read out and when viewing a variable temperature blackbody source, we measure device noise consistent with photon noise when the incident optical power is >>~0.5~pW, corresponding to noise equivalent powers >>~3×1017\times 10^{-17} W/Hz\sqrt{\mathrm{Hz}}. This sensitivity makes these devices suitable for broadband photometric applications at these wavelengths

    Global Ethics and Nanotechnology: A Comparison of the Nanoethics Environments of the EU and China

    Get PDF
    The following article offers a brief overview of current nanotechnology policy, regulation and ethics in Europe and The People’s Republic of China with the intent of noting (dis)similarities in approach, before focusing on the involvement of the public in science and technology policy (i.e. participatory Technology Assessment). The conclusions of this article are, that (a) in terms of nanosafety as expressed through policy and regulation, China PR and the EU have similar approaches towards, and concerns about, nanotoxicity—the official debate on benefits and risks is not markedly different in the two regions; (b) that there is a similar economic drive behind both regions’ approach to nanodevelopment, the difference being the degree of public concern admitted; and (c) participation in decision-making is fundamentally different in the two regions. Thus in China PR, the focus is on the responsibility of the scientist; in the EU, it is about government accountability to the public. The formulation of a Code of Conduct for scientists in both regions (China PR’s predicted for 2012) reveals both similarity and difference in approach to nanotechnology development. This may change, since individual responsibility alone cannot guide S&T development, and as public participation is increasingly seen globally as integral to governmental decision-making

    A fibril-specific, conformation-dependent antibody recognizes a subset of Aβ plaques in Alzheimer disease, Down syndrome and Tg2576 transgenic mouse brain

    Get PDF
    Beta-amyloid (Aβ) is thought to be a key contributor to the pathogenesis of Alzheimer disease (AD) in the general population and in adults with Down syndrome (DS). Different assembly states of Aβ have been identified that may be neurotoxic. Aβ oligomers can assemble into soluble prefibrillar oligomers, soluble fibrillar oligomers and insoluble fibrils. Using a novel antibody, OC, recognizing fibrils and soluble fibrillar oligomers, we characterized fibrillar Aβ deposits in AD and DS cases. We further compared human specimens to those obtained from the Tg2576 mouse model of AD. Our results show that accumulation of fibrillar immunoreactivity is significantly increased in AD relative to nondemented aged subjects and those with select cognitive impairments (p < 0.0001). Further, there was a significant correlation between the extent of frontal cortex fibrillar deposit accumulation and dementia severity (MMSE r = −0.72). In DS, we observe an early age of onset and age-dependent accumulation of fibrillar OC immunoreactivity with little pathology in similarly aged non-DS individuals. Tg2576 mice show fibrillar accumulation that can be detected as young as 6 months. Interestingly, fibril-specific immunoreactivity was observed in diffuse, thioflavine S-negative Aβ deposits in addition to more mature neuritic plaques. These results suggest that fibrillar deposits are associated with disease in both AD and in adults with DS and their distribution within early Aβ pathology associated with diffuse plaques and correlation with MMSE suggest that these deposits may not be as benign as previously thought

    A Novel Approach to Link Process Parameters to BSIM Model Parameters

    No full text
    In this paper, we demonstrate a methodology to link process parameters to BSIM model parameters. Here, we have combined well-known statistical methods like principal component analysis (PCA), design of experiments (DOE), and response surface methodology (RSM) to bridge the missing link between process parameters and model parameters. The proposed methodology uses the concept of a correlation matrix, which transforms the process level information to the device and circuit level information through the BSIM model parameters. The proposed methodology has been successfully implemented on an advanced CMOS process. Our results show a strong linear correlation for the data obtained from two techniques namely TCAD technique and the standard HSPICE simulation technique. In both cases the process conditions were kept identical for comparison
    corecore