970 research outputs found
Application of asymptotic expansions of maximum likelihood estimators errors to gravitational waves from binary mergers: the single interferometer case
In this paper we describe a new methodology to calculate analytically the
error for a maximum likelihood estimate (MLE) for physical parameters from
Gravitational wave signals. All the existing litterature focuses on the usage
of the Cramer Rao Lower bounds (CRLB) as a mean to approximate the errors for
large signal to noise ratios. We show here how the variance and the bias of a
MLE estimate can be expressed instead in inverse powers of the signal to noise
ratios where the first order in the variance expansion is the CRLB. As an
application we compute the second order of the variance and bias for MLE of
physical parameters from the inspiral phase of binary mergers and for noises of
gravitational wave interferometers . We also compare the improved error
estimate with existing numerical estimates. The value of the second order of
the variance expansions allows to get error predictions closer to what is
observed in numerical simulations. It also predicts correctly the necessary SNR
to approximate the error with the CRLB and provides new insight on the
relationship between waveform properties SNR and estimation errors. For example
the timing match filtering becomes optimal only if the SNR is larger than the
kurtosis of the gravitational wave spectrum
Kapteyn's theory of skew frequency, and orthogonal polynomials in one and two variables
Chapter 1. SKEW FREQUENCY •
Chapter 2. PROPERTIES OF ORTHOGONAL POLYNOMIALS RELATED TO THEIR GENERATING FUNCTIONS •
Chanter 3. ORTHOGONAL POLYNOMIALS IN TWO VARIABLE
‘But I’ve been teaching for 20 years…’: encouraging teaching accreditation for experienced staff working in higher education
The status of teaching and learning is an issue those providing and supporting higher education grapple with. The UK Higher Education Academy offers accreditation aligned to the professional standards framework (PSF). The PSF contextualises the role of teaching and supporting learning, and offers a mechanism for individuals’ commitment to be recognised. Here, we present a case-study of 19 established academics who reflected on their experiences of gaining recognition through their university’s accreditation scheme. Respondents prioritised institutional structures and outcomes such as student recruitment, job security, and status as drivers for engagement. Institutional leadership was significant in driving the accreditation agenda
Stochastic models in population biology and their deterministic analogs
In this paper we introduce a class of stochastic population models based on
"patch dynamics". The size of the patch may be varied, and this allows one to
quantify the departures of these stochastic models from various mean field
theories, which are generally valid as the patch size becomes very large. These
models may be used to formulate a broad range of biological processes in both
spatial and non-spatial contexts. Here, we concentrate on two-species
competition. We present both a mathematical analysis of the patch model, in
which we derive the precise form of the competition mean field equations (and
their first order corrections in the non-spatial case), and simulation results.
These mean field equations differ, in some important ways, from those which are
normally written down on phenomenological grounds. Our general conclusion is
that mean field theory is more robust for spatial models than for a single
isolated patch. This is due to the dilution of stochastic effects in a spatial
setting resulting from repeated rescue events mediated by inter-patch
diffusion. However, discrete effects due to modest patch sizes lead to striking
deviations from mean field theory even in a spatial setting.Comment: 47 pages, 9 figure
Incidence, time course and predictors of impairments relating to caring for the profoundly affected arm after stroke: A systematic review
Background and purpose - A significant number of stroke survivors will not recover the use of their affected arm. A proportion will experience pain, stiffness and difficulty with basic care activities. The purpose of the review was to identify predictors of difficulty caring for the profoundly affected arm and establish the incidence and time-course of the related impairments of pain, spasticity and contracture. Method - Data sources: Databases (PubMED, MEDLINE, AMED, EMBASE, CINAHL and the Cochrane Controlled Trials Register) were searched from inception to December 2013. Additional studies were identified from citation tracking. Review methods: Independent reviewers used pre-defined criteria to identify eligible studies. Quality assessment and risk of bias were assessed using the McMasters Assessment Tool. A narrative evidence synthesis was performed. Results - Thirty-nine articles reporting 34 studies were included. No studies formally measured difficulty caring for the arm, but related impairments were common. Incidence of spasticity in those with weakness ranged from 33% to 78%, shoulder pain affected 22% to 90% and contracture was present in at least 50%. Spasticity and pain appear within 1 week of stroke, and contracture within two weeks. Impairments continued to develop over at least 3–6 months. The most frequent predictors of spasticity and contracture were weakness and reduced motor control, and the risk of pain is most commonly predicted by reduced sensation, shoulder subluxation, weakness and stroke severity. Discussion - There is no published evidence on predicting the likelihood of difficulty caring for the arm following stroke. However, the related impairments of spasticity, pain and contracture are common. Given the time-course of development, clinicians may need not only to intervene early but also be prepared to act over a longer time period. Further research is needed to examine difficulty caring for the arm and the relationship with associated impairments to enable researchers and clinicians to develop targeted interventions
Fiber-Flux Diffusion Density for White Matter Tracts Analysis: Application to Mild Anomalies Localization in Contact Sports Players
We present the concept of fiber-flux density for locally quantifying white
matter (WM) fiber bundles. By combining scalar diffusivity measures (e.g.,
fractional anisotropy) with fiber-flux measurements, we define new local
descriptors called Fiber-Flux Diffusion Density (FFDD) vectors. Applying each
descriptor throughout fiber bundles allows along-tract coupling of a specific
diffusion measure with geometrical properties, such as fiber orientation and
coherence. A key step in the proposed framework is the construction of an FFDD
dissimilarity measure for sub-voxel alignment of fiber bundles, based on the
fast marching method (FMM). The obtained aligned WM tract-profiles enable
meaningful inter-subject comparisons and group-wise statistical analysis. We
demonstrate our method using two different datasets of contact sports players.
Along-tract pairwise comparison as well as group-wise analysis, with respect to
non-player healthy controls, reveal significant and spatially-consistent FFDD
anomalies. Comparing our method with along-tract FA analysis shows improved
sensitivity to subtle structural anomalies in football players over standard FA
measurements
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Resting-State Brain Functional Connectivity Is Altered in Type 2 Diabetes
Type 2 diabetes mellitus (T2DM) is a risk factor for Alzheimer disease (AD). Populations at risk for AD show altered brain activity in the default mode network (DMN) before cognitive dysfunction. We evaluated this brain pattern in T2DM patients. We compared T2DM patients (n = 10, age = 56 ± 2.2 years, fasting plasma glucose [FPG] = 8.4 ± 1.3 mmol/L, HbA1c = 7.5 ± 0.54%) with nondiabetic age-matched control subjects (n = 11, age = 54 ± 1.8 years, FPG = 4.8 ± 0.2 mmol/L) using resting-state functional magnetic resonance imaging to evaluate functional connectivity strength among DMN regions. We also evaluated hippocampal volume, cognition, and insulin sensitivity by homeostasis model assessment of insulin resistance (HOMA-IR). Control subjects showed stronger correlations versus T2DM patients in the DMN between the seed (posterior cingulate) and bilateral middle temporal gyrus (β = 0.67 vs. 0.43), the right inferior and left medial frontal gyri (β = 0.75 vs. 0.54), and the left thalamus (β = 0.59 vs. 0.37), respectively, with no group differences in cognition or hippocampal size. In T2DM patients, HOMA-IR was inversely correlated with functional connectivity in the right inferior frontal gyrus and precuneus. T2DM patients showed reduced functional connectivity in the DMN compared with control subjects, which was associated with insulin resistance in selected brain regions, but there were no group effects of brain structure or cognition
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