...the initial trials comparing COVID-19 vaccines versus placebo should seek reliable evidence not only of some efficacy but of worthwhile efficacy. ...although efficacy far greater than 50% would be ...better, efficacy of about 50% would represent substantial progress. Evaluation of multiple COVID-19 vaccines with standardised methodology will facilitate regulatory and deployment decisions.7 Unless such decisions are informed by reliable randomised evidence, the effect on public acceptance of COVID-19 vaccines could adversely affect COVID-19 control and the uptake of vaccines against other diseases.8 The WHO Solidarity Vaccines Trial9 (figure) aims to evaluate efficiently and rapidly (within 3–6 months of each vaccine's introduction into the study) the efficacy of multiple vaccines,10 helping to ensure that weakly effective vaccines are not deployed.
This paper defines and studies a new class of non-stationary random processes constructed from discrete non-decimated wavelets which generalizes the Cramér (Fourier) representation of stationary time ...series. We define an evolutionary wavelet spectrum (EWS) which quantifies how process power varies locally over time and scale. We show how the EWS may be rigorously estimated by a smoothed wavelet periodogram and how both these quantities may be inverted to provide an estimable time-localized autocovariance. We illustrate our theory with a pedagogical example based on discrete non-decimated Haar wavelets and also a real medical time series example.
Aliasing is often overlooked in time series analysis but can seriously distort the spectrum, the autocovariance and their estimates. We show that dyadic subsampling of a locally stationary wavelet ...process, which can cause aliasing, results in a process that is the sum of asymptotic white noise and another locally stationary wavelet process with a modified spectrum. We develop a test for the absence of aliasing in a locally stationary wavelet series at a fixed location, and illustrate its application on simulated data and a wind energy time series. A useful by-product is a new test for local white noise. The tests are robust with respect to model misspecification in that the analysis and synthesis wavelets do not need to be identical. Hence, in principle, the tests work irrespective of which wavelet is used to analyse the time series, although in practice there is a trade-off between increasing statistical power and time localization of the test.
Intracortical brain-machine interfaces (BMIs) are a promising source of prosthesis control signals for individuals with severe motor disabilities. Previous BMI studies have primarily focused on ...predicting and controlling whole-arm movements; precise control of hand kinematics, however, has not been fully demonstrated. Here, we investigate the continuous decoding of precise finger movements in rhesus macaques.
In order to elicit precise and repeatable finger movements, we have developed a novel behavioral task paradigm which requires the subject to acquire virtual fingertip position targets. In the physical control condition, four rhesus macaques performed this task by moving all four fingers together in order to acquire a single target. This movement was equivalent to controlling the aperture of a power grasp. During this task performance, we recorded neural spikes from intracortical electrode arrays in primary motor cortex.
Using a standard Kalman filter, we could reconstruct continuous finger movement offline with an average correlation of ρ = 0.78 between actual and predicted position across four rhesus macaques. For two of the monkeys, this movement prediction was performed in real-time to enable direct brain control of the virtual hand. Compared to physical control, neural control performance was slightly degraded; however, the monkeys were still able to successfully perform the task with an average target acquisition rate of 83.1%. The monkeys' ability to arbitrarily specify fingertip position was also quantified using an information throughput metric. During brain control task performance, the monkeys achieved an average 1.01 bits s
throughput, similar to that achieved in previous studies which decoded upper-arm movements to control computer cursors using a standard Kalman filter.
This is, to our knowledge, the first demonstration of brain control of finger-level fine motor skills. We believe that these results represent an important step towards full and dexterous control of neural prosthetic devices.
This article proposes maximum likelihood approaches for multiscale variance stabilization transformations for independently and identically distributed data. For two multiscale variance stabilization ...transformations we present new unified theoretical results on their Jacobians, a key component of the likelihood. The results provide a deeper understanding of the transformations and the ability to compute the likelihood in linear time. The transformations are shown empirically to compare favourably to the Box-Cox transformation.
Wavelet Shrinkage Using Cross-Validation Nason, G. P.
Journal of the Royal Statistical Society. Series B, Methodological,
1996, Letnik:
58, Številka:
2
Journal Article
Recenzirano
Wavelets are orthonormal basis functions with special properties that show potential in many areas of mathematics and statistics. This paper concentrates on the estimation of functions and images ...from noisy data by using wavelet shrinkage. A modified form of twofold cross-validation is introduced to choose a threshold for wavelet shrinkage estimators operating on data sets of length a power of 2. The cross-validation algorithm is then extended to data sets of any length and to multidimensional data sets. The algorithms are compared with established threshold choosers by using simulation. An application to a real data set arising from anaesthesia is presented.
This book contains information on how to tackle many important problems using a multiscale statistical approach. It focuses on how to use multiscale methods and discusses methodological and applied ...considerations. TOC:Wavelets, discrete wavelet transforms, non-decimated transforms, wavelet packet transforms, lifting transforms.- Multiscale methods for denoising (wavelet shrinkage).- Locally stationary wavelet time series and texture modelling.- Multiscale variable transformations for Gaussianization and variance stabilization.- Miscellaneous topics.
Controversy exists regarding optimal penile rehabilitation program following radical prostatectomy (RP). Vacuum erectile devices (VEDs) have become an important component of penile rehabilitation ...protocols. The aim of this study was to assess the efficacy and patient satisfaction of a dedicated VED clinic. A voluntary telephone questionnaire was performed of all patients who attended a VED clinic to date in two university teaching hospitals. Patient demographics, histopathological characteristics and functional status (International Index of Erectile Function (IIEF) scores) were obtained from a retrospective review of a prospectively maintained database. Sixty-five men attended the dedicated VED clinic in the two university teaching hospitals. Forty-men (76.3%) men purchased a VED following the dedicated clinic. There was significant differences noted between the mean preoperative and the 3-month postoperative IIEF scores (22.08±3.16 vs 11.3±3.08, P=0.0001) and between the 3-month postoperative IIEF score and the post-VED use IIEF score (11.3±3.08 vs 16.74±2.62, P=0.0001). Despite VED use, there was a significant reduction in erectile function from presurgery status (22.08±3.16 vs 16.74±2.62, P=0.0001). All patients reported that the dedicated VED was helpful and would recommend it to other patients. Our study demonstrates that, despite a reduction in erectile function after RP, successful erections are attainable with a VED. There is potential and need for the development of a standard penile rehabilitation program and treatment of ED after RP internationally.
Background
Radical prostatectomy for prostate cancer is associated with significant complications, such as urinary incontinence and erectile dysfunction. Debate remains regarding the influence of ...surgical technique on these important functional outcomes.
Aim
The aim of this study was to compare the early functional outcomes following robotic-assisted (RARP), laparoscopic (LRP), and open radical prostatectomy (ORP) in a rapid access cohort.
Methods
A retrospective review of a prospectively maintained database was performed between 2011 and 2014. Functional status was objectively assessed using the International Prostate Symptom Score (IPSS), International Index of Erectile Function (IIEF-5), and a self-reported continence score.
Results
Two hundred and ninety-two patients underwent RP (85 RARP, 100 LRP, 107 ORP). The mean age was 61.3 years with a mean initial PSA was 6.2 ng/ml. There was no difference noted in urinary function between ORP, LRP, and RARP at 3 months (
p
= 0.894), 6 months (
p
= 0.244), 9 months (
p
= 0.068) or 12 months (
p
= 0.154). All men noted a deterioration in erectile function; however, there was no difference at 3 months (
p
= 0.922), 6 months (
p
= 0.723), 9 months (
p
= 0.101) or 12 months (
p
= 0.395),
Conclusion
Equivalent good early functional outcomes are being achieved in patients undergoing RP irrespective of surgical approach. Longer follow-up in a prospective randomized fashion is required to fully assess the most appropriate surgical technique.
Real nonparametric regression using complex wavelets Barber, Stuart; Nason, Guy P.
Journal of the Royal Statistical Society. Series B, Statistical methodology,
November 2004, Letnik:
66, Številka:
4
Journal Article
Recenzirano
Wavelet shrinkage is an effective nonparametric regression technique, especially when the underlying curve has irregular features such as spikes or discontinuities. The basic idea is simple: take the ...discrete wavelet transform of data consisting of a signal corrupted by noise; shrink or remove the wavelet coefficients to remove the noise; then invert the discrete wavelet transform to form an estimate of the true underlying curve. Various researchers have proposed increasingly sophisticated methods of doing this by using real-valued wavelets. Complex-valued wavelets exist but are rarely used. We propose two new complex-valued wavelet shrinkage techniques: one based on multiwavelet style shrinkage and the other using Bayesian methods. Extensive simulations show that our methods almost always give significantly more accurate estimates than methods based on real-valued wavelets. Further, our multiwavelet style shrinkage method is both simpler and dramatically faster than its competitors. To understand the excellent performance of this method we present a new risk bound on its hard thresholded coefficients.
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