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Basic Self disturbances (BSD), including changes of the 'pre-reflexive' sense of self and the loss first-person perspective, are characteristic of the schizophrenic spectrum disorders and highly prevalent in subjects at 'ultra high risk' for psychosis (UHR). The current literature indicates that cortical midline structures (CMS) may be implicated in the neurobiological substrates of the 'basic self' in healthy controls.
Objectives
Neuroanatomical investigation of BSD in a UHR sample
Aims
To test the hypotheses :(i) UHR subjects have higher 'Examination of Anomalous Self Experience, EASE' scores as compared to controls, (ii) UHR subjects have neuroanatomical alterations as compared to controls in CMS, (iii) within UHR subjects, EASE scores are directly related to structural CMS alterations.
Methods
32 HR subjects (27 antipsychotics-naïve) and 17 healthy controls (HC) were assessed with the 57-items semi-structured EASE interview. Voxel-Based Morphometry (VBM) was conducted in the same subjects, with a-priori Region of Interests (ROIs) defined in the CMS (anterior/posterior cingulate and medial-prefrontal cortex).
Results
Despite high variability in the HR group, the overall EASE score was higher (t-test >0.01, Cohen's d =2.91) in HR (mean=30.15, SD=16.46) as compared to HC group (mean=1.79, SD=2.83). UHR subjects had gray matter reduction in CMS as compared to HC (p>0.05 FWE-corrected). Across the whole sample, lower gray matter volume in the anterior cingulate was correlated with higher EASE scores (p>0.05).
Conclusions
This study provides preliminary evidence that gray matter reductions in the CMS are correlated with BSD in UHR people.
The Square Kilometre Array (SKA) is a planned large radio interferometer designed to operate over a wide range of frequencies, and with an order of magnitude greater sensitivity and survey speed than any current radio telescope. The SKA will address many important topics in astronomy, ranging from planet formation to distant galaxies. However, in this work, we consider the perspective of the SKA as a facility for studying physics. We review four areas in which the SKA is expected to make major contributions to our understanding of fundamental physics: cosmic dawn and reionisation; gravity and gravitational radiation; cosmology and dark energy; and dark matter and astroparticle physics. These discussions demonstrate that the SKA will be a spectacular physics machine, which will provide many new breakthroughs and novel insights on matter, energy, and spacetime.
We describe the motivation and design details of the ‘Phase II’ upgrade of the Murchison Widefield Array radio telescope. The expansion doubles to 256 the number of antenna tiles deployed in the array. The new antenna tiles enhance the capabilities of the Murchison Widefield Array in several key science areas. Seventy-two of the new tiles are deployed in a regular configuration near the existing array core. These new tiles enhance the surface brightness sensitivity of the array and will improve the ability of the Murchison Widefield Array to estimate the slope of the Epoch of Reionisation power spectrum by a factor of ∼3.5. The remaining 56 tiles are deployed on long baselines, doubling the maximum baseline of the array and improving the array u, v coverage. The improved imaging capabilities will provide an order of magnitude improvement in the noise floor of Murchison Widefield Array continuum images. The upgrade retains all of the features that have underpinned the Murchison Widefield Array’s success (large field of view, snapshot image quality, and pointing agility) and boosts the scientific potential with enhanced imaging capabilities and by enabling new calibration strategies.
We are developing a purely commensal survey experiment for fast (<5 s) transient radio sources. Short-timescale transients are associated with the most energetic and brightest single events in the Universe. Our objective is to cover the enormous volume of transients parameter space made available by ASKAP, with an unprecedented combination of sensitivity and field of view. Fast timescale transients open new vistas on the physics of high brightness temperature emission, extreme states of matter and the physics of strong gravitational fields. In addition, the detection of extragalactic objects affords us an entirely new and extremely sensitive probe on the huge reservoir of baryons present in the IGM. We outline here our approach to the considerable challenge involved in detecting fast transients, particularly the development of hardware fast enough to dedisperse and search the ASKAP data stream at or near real-time rates. Through CRAFT, ASKAP will provide the testbed of many of the key technologies and survey modes proposed for high time resolution science with the SKA.
Many electronic and acoustic signals can be modelled as sums of sinusoids and noise. However, the amplitudes, phases and frequencies of the sinusoids are often unknown and must be estimated in order to characterise the periodicity or near-periodicity of a signal and consequently to identify its source. This book presents and analyses several practical techniques used for such estimation. The problem of tracking slow frequency changes over time of a very noisy sinusoid is also considered. Rigorous analyses are presented via asymptotic or large sample theory, together with physical insight. The book focuses on achieving extremely accurate estimates when the signal to noise ratio is low but the sample size is large. Each chapter begins with a detailed overview, and many applications are given. Matlab code for the estimation techniques is also included. The book will thus serve as an excellent introduction and reference for researchers analysing such signals.
With modern undulators generating light of an arbitrary polarization state, experiments exploiting this feature in the soft X-ray region are becoming increasingly widespread. Circularly polarized light in the soft X-ray region is of particular interest to investigate of magnetic metals such as Fe, Co and Ni, and the rare earths. A versatile multilayer polarimeter has been designed and developed to characterize the polarization state of the soft X-ray beam. A W/B4C multilayer transmission phase retarder and reflection analyser has been used for polarimetry measurements on the beamline (I06) at Diamond Light Source. The design details of the polarimeter and preliminary polarimetry results are presented.
Comparing pertussis epidemiology over time and between countries is confounded by differences in diagnostic and notification practices. Standardized serological methods applied to population-based samples enhance comparability. Population prevalence of different levels of pertussis toxin IgG (PT IgG) antibody, measured by standardized methods, were compared by age group and region of Australia between 1997/1998 and 2002. The proportion of 5- to 9-year-olds with presumptive recent pertussis infection (based on IgG levels ⩾62·5 ELISA units/ml) significantly decreased in 2002, consistent with notification data for the same period and improved uptake of booster vaccines following the schedule change from whole-cell to acellular vaccine. In contrast, recent presumptive infection significantly increased in adults aged 35–49 years. Population-based serosurveillance using standardized PT IgG antibody assays has the potential to aid interpretation of trends in pertussis incidence in relation to vaccine programmes and between countries.
Mood swings accompanying the motor fluctuations of patients with Parkinson's disease on chronic levodopa treatment frequently occur, but are poorly recognized. Occasionally, their functional impact may be greater than that caused by the motor disability itself.
In this study we have assessed the nature of, and relationship between, mood and motor fluctuations in nine Parkinsonian patients with ‘on—off’ motor swings. The results of an additional questionnaire survey confirm that ‘on–off’ mood swings occur in approximately two thirds of patients with Parkinson's disease experiencing motor fluctuations on dopaminergic treatment. Aetiological and therapeutic implications are discussed.
We present the preliminary results of a frequency analysis of 1457 fundamental mode RR Lyrae (RR0) stars in the Large Magellanic Cloud (LMC) from MACHO Project photometry. We find the same classes of pulsational behavior as were found in our earlier survey of first overtone RR Lyrae (RR1) stars. Variables whose prewhitened power spectra contain one or two peaks close to the main frequency component in the original power spectra are commonly known as Blazhko-type variables. The present analysis shows the overall frequency of Blazhko-type stars in the total RR0 population analysed to date to be ≈ 10%. This is lower than the often cited Galactic field/globular rate of 20-30% (Szeidl, 1988).
The incidence rate of Blazhko-type variability in the LMC appears to be about three times higher in RR0 stars than in RR1 stars. This puts important constraints on possible models of the Blazhko effect.
In late 1982, Ted Hannan discussed with me a question he had been asked by some astronomers – how could you estimate the two frequencies in two sinusoids when the frequencies were so close together that you could not tell, by looking at the periodogram, that there were two frequencies? He asked me if I would like to work with him on the problem and gave me a reprint of his paper (Hannan 1973) on the estimation of frequency. Together we wrote a paper (Hannan and Quinn 1989) which derived the regression sum of squares estimators of the frequencies, and showed that the estimators were strongly consistent and satisfied a central limit theorem. It was clear that there were no problems asymptotically if the two frequencies were fixed, so Ted's idea was to fix one frequency, and let the other converge to it at a certain rate, in much the same way as the alternative hypothesis is constructed to calculate the asymptotic power of a test. Since then, I have devoted much of my research to sinusoidal models. In particular, I have spent a lot of time constructing algorithms for the estimation of parameters in these models, to implementing the algorithms in practice and, for me perhaps the most challenging, establishing the asymptotic (large sample) properties of the estimators.
We encounter periodic: phenomena every day of our lives. Those of us who still use analogue clocks are acutely aware of the 60 second, 60 minute and 12 hour periods associated with the sweeps of the second, minute and hour hands. We are conscious of the fact that the Earth rotates on its axis roughly every 24 hours and that it completes a revolution of the Sun roughly every 365 days. These periodicities are reasonably accurate. The quantities we are interested in measuring are not precisely periodic and there will also be error associated with their measurement. Indeed, some phenomena only seem periodic. For example, some biological population sizes appear to fluctuate regularly over a long period of time, but it is hard to justify using common sense any periodicity other than that associated with the annual cycle. It has been argued in the past that some cycles occur because of predator-prey interaction, while in other cases there is no obvious reason. On the other hand, the sound associated with musical instruments can reasonably be thought of as periodic, locally in time, since musical notes are produced by regular vibration and propagated through the air via the regular compression and expansion of the air. The ‘signal’ will not be exactly periodic, since there are errors associated with the production of the sound, with its transmission through the air (since the air is not a uniform medium) and because the ear is not a perfect receiver.
We introduce in this chapter those statistical and probability techniques that underlie what is presented later. Few proofs will be given because a complete treatment of even a small part of what is dealt with here would require a book in itself. We do not intend to bother the reader with too formal a presentation. We shall be concerned with a sample space, Ω, which can be thought of as the set of all conceivable realisations of the random processes with which we are concerned. If A is a subset of Ω, then P(A) is the probability that the realisation is in A. Because we deal with discrete time series almost exclusively, questions of ‘measurability’, i.e. to which sets A can P(·) be applied, do not arise and will never be mentioned. We say this once and for all so that the text will not be filled with requirements that this or that set be measurable or that this or that function be a measurable function. Of course we shall see only (part of) one realisation, {x(t), t = 0, ±1, ±2,…} and are calling into being in our mind's eye, so to say, a whole family of such realisations. Thus we might write ω (t; ω) where ω ∈ Ω is the point corresponding to a particular realisation and, as ω varies for given t, we get a random variable, i.e. function defined on the sample space Ω.
There are several types of frequency estimation techniques which we have not yet discussed. In particular, we have not paid any attention to those based on autocovariances, such as Pisarenko's technique (Pisarenko 1973), or those based on phase differences, for complex time series, such as two techniques due to Kay (1989). We have not spent much effort on these for the very reason that we have been concerned with asymptotic theory and asymptotic optimality. That is, for fixed system parameters, we have been interested in the behaviour of frequency estimators as the sample size T increases, with the hope that the sample size we have is large enough for the asymptotic theory to hold well enough. Moreover, we have not wished to impose conditions such as Gaussianity or whiteness on the noise process, as the latter in particular is rarely met in practice. Engineers, however, are often interested in the behaviour of estimators for fixed values of T, and decreasing SNR. The usual measure of this behaviour is mean square error, which may be estimated via simulations. Such properties, however, may rarely be justified theoretically, as there is no statistical limit theory which allows the mean square errors of nonlinear estimators to be calculated using what are essentially limiting distribution results. Although the methods mentioned above are computationally simple and computationally efficient, we shall see that they cannot be statistically asymptotically efficient and may even be inconsistent, i.e., actually converge to the wrong value.