Fast spatial combinative lifting algorithm of wavelet transform using the 9/7 filter for image block compression

This is the post-print version of the article - Copyright @ 2000 IETA new fast spatial combinative lifting algorithm (SCLA) of the wavelet transform using the 9/7 filter for image block compression is proposed. In comparison with its lifting-based implementation, the number of multiplications is reduced by a ratio of 5/12 and the speed of implementation of the wavelet transform is increased

Electric dipole moment constraints on CP-violating light-quark Yukawas

Nonstandard CP violation in the Higgs sector can play an essential role in electroweak baryogenesis. We calculate the full two-loop matching conditions of the standard model, with Higgs Yukawa couplings to light quarks modified to include arbitrary CP-violating phases, onto an effective Lagrangian comprising CP-odd electric and chromoelectric light-quark (up, down, and strange) dipole operators. We find large isospin-breaking contributions of the electroweak diagrams. Using these results, we obtain significant constraints on the phases of the light-quark Yukawas from experimental bounds on the neutron and mercury electric dipole moments.Comment: 14 pages, 4 figures; corrected typographical errors, updated numerics, version as published in JHE

Computational Approaches and Models for Ovarian Ageing: From 2D to 4D

The theme of the work presented in this multi-disciplinary PhD is the development of new computational tools and techniques to study and understand spatio-temporal follicle growth in neonatal mouse ovaries. The female ovary is endowed at birth with a finite, non-renewable supply of oocytes, each enclosed in a layer of supporting somatic (granulosa) cells to form a quiescent follicle. From birth, a steady trickle of follicles initiate growth to maintain a supply of mature oocytes for regular ovulation. Disruption in the regulation of initiation of follicle growth can result in various pathologies, such as premature ovarian failure and polycystic ovary syndrome. The mechanism of regulation of the initiation of follicle growth remains unclear, but may involve inter-follicle signaling via paracrine growth factors. To investigate this hypothesis, a new technique for quantifying and analyzing spatial distributions of quiescent and growing follicles in the adult human has been developed, as an extension of a novel technique previously developed in neonatal mice in our laboratory. As in the mouse study, we have found evidence that in the human ovary neighbouring quiescent follicles inhibit follicle growth, at a small range. This approach has been further extended to cultured neonatal mouse ovaries, which in vitro lack a systemic blood supply, to investigate the relative contributions of inter-follicle paracrine signaling and endocrine growth factor/nutrient signaling to the regulation of initiation of follicle growth. Accurate counts of the numbers of follicles in ovaries are important for a wide variety of studies of ovarian physiology, including investigating the effects of age, toxins, chemotherapeutics, endocrine disruptors and specific genes (knock out/transgenic studies) on follicle formation, endowment and development. Many published studies use frequent sampling of a small number of ovaries (often as few as three) to obtain estimates of the number of follicles. We have tested the validity of this approach by generating 3D spherical simulated ovaries which contain realistic numbers of follicles at different stages and which are realistically positioned within these ovaries. The number and position of follicles is based on real biological data. This model enables us to rapidly ‘virtually’ section the ovary in silico and obtain computer-generated counts of the numbers of follicles in sections at different frequencies, such as one every fifth section (1/5), 1/20 or 1/50. As we know precisely how many follicles each simulated ovary contains, we can compare the accuracy using different sampling frequencies of varying numbers of ovaries. This has enabled us to demonstrate that the error is smaller when infrequent sampling of a large number of ovaries (≥8) is carried out, and that this actually involves analyzing fewer sections overall. We have gone on to generate simulated ovaries from knockout mice, with more or fewer follicles, and can predict how many ovaries are required to make robust comparisons between knockout and control animals. This has shown that biological variability contributes more to counting error than the method of sampling. These simulated ovaries provide a unique resource to model large studies. Currently follicle counts are obtained by fixing and serially sectioning ovaries, and manually counting the follicles in sections. This is laborious and time-consuming. Faster methods of obtaining follicle estimates are required. With the use of confocal microscopy and immunohistochemistry for an oocyte-specific protein, we were able to establish a protocol that allows us to image and computationally reconstruct a whole neonatal mouse ovary in 3D. Follicle number can be estimated rapidly using a stereologic method. The stereologic technique error was estimated using the simulated ovary model, leading to the conclusion that the method can be safely used to obtain rapid estimates of follicle number. The time required can be further reduced by using image processing to detect the stained follicles on the sections. We have developed an algorithmic technique that can instantaneously identify stained oocytes, count them, and calculate their spatial distribution. A fundamental unanswered question is whether follicles move in the ovary, particularly as they grow. This question has arisen from the observation that small follicles tend to be situated close to the ovarian surface, while large ones are closer to the medulla. This question has implications for interfollicle signaling. We have developed a protocol to image the ovary while in culture using timelapse confocal and live lipid stains to visualize the follicles. Results show that small follicles are not moving significantly over a period of 12h. This project can be extended in the future with the use of transgenic mice for GFP tagging, to accurately monitor changes in structures of interest within cultured ovaries

Two-band fast Hartley transform

This article has been made available through the Brunel Open Access Publishing Fund.Efficient algorithms have been developed over the past 30 years for computing the forward and inverse discrete Hartley transforms (DHTs). These are similar to the fast Fourier transform (FFT) algorithms for computing the discrete Fourier transform (DFT). Most of these methods seek to minimise the complexity of computations and or the number of operations. A new approach for the computation of the radix-2 fast Hartley transform (FHT) is presented. The proposed algorithm, based on a two-band decomposition of the input data, possesses a very regular structure, avoids the input or out data shuffling, requires slightly less multiplications than the existing approaches, but increases the number of additions

The Effect of Space-filling Curves on the Efficiency of Hand Gesture Recognition Based on sEMG Signals

Over the past few years, Deep learning (DL) has revolutionized the field of data analysis. Not only are the algorithmic paradigms changed, but also the performance in various classification and prediction tasks has been significantly improved with respect to the state-of-the-art, especially in the area of computer vision. The progress made in computer vision has produced a spillover in many other domains, such as biomedical engineering. Some recent works are directed towards surface electromyography (sEMG) based hand gesture recognition, often addressed as an image classification problem and solved using tools such as Convolutional Neural Networks (CNN). This paper extends our previous work on the application of the Hilbert space-filling curve for the generation of image representations from multi-electrode sEMG signals, by investigating how the Hilbert curve compares to the Peano- and Z-order space-filling curves. The proposed space-filling mapping methods are evaluated on a variety of network architectures and in some cases yield a classification improvement of at least 3%, when used to structure the inputs before feeding them into the original network architectures

Chromospheric Evershed flow

We studied the chromospheric Evershed flow from filtergrams obtained at nine wavelengths along the Hα profile. We computed line-of-sight velocities based on Becker's cloud model and we determined the components of the flow velocity vector as a function of distance from the center of the sunspot, assuming an axial symmetry of both the spot and the flow. We found that the flow velocity decreases with decreasing height and that the maximum of the velocity shifts towards the inner penumbral boundary. The flow related to some fibrils deviates significantly from the average Evershed flow. The profile of the magnitude of the flow velocity as a function of distance from the spot center, indicates that the velocity attains its maximum value in the downstream part of the flow channels (assumed to have the form of a loop). This behavior can be understood in terms of a critical flow that pass from subsonic to supersonic near the apex of the loop, attains its higher velocity at the downstream part of the loop and finally relaxes to subsonic through a tube shock. We computed the average flow vector from segmented line-of-sight velocity maps, excluding bright or dark fibrils alternatively. We found that the radial component of the velocity does not show a significant difference, but the magnitude of the vertical component of the velocity related to dark fibrils is higher than that related to bright fibrils.