Digitizing signals - a short tutorial guide

Converting the analogue signal, as captured from a patient, into digital format is known as digitizing, or analogue to digital conversion. This is a vital first step in for digital signal processing. The acquisition of high-quality data requires appropriate choices of system and parameters (sampling rate, anti-alias filter, amplification, number of ‘bits’). Thus tutorial aims to provide a practical guide to making these choices, and explains the underlying principles (rather than the mathematical theory and proofs) and potential pitfalls. Illustrative examples from different physiological signals are provided

A statistical technique for measuring synchronism between cortical regions in the EEG during rhythmic stimulation

The coherence function has been widely applied in quantifying the degree of synchronism between electroencephalogram (EEG) signals obtained from different brain regions. However, when applied to investigating synchronization resulting from rhythmic stimulation, misleading results can arise from the high correlation of background EEG activity. The authors, thus propose a modified measure, which emphasizes the synchronized stimulus responses and reduces the influence of the spontaneous EEG activity. Critical values for this estimator are derived and tested in Monte Carlo simulations. The effectiveness of the method is illustrated on data recorded from 12 young normal subjects during rhythmic photic stimulation

Optimising the assessment of cerebral autoregulation from black box models

Cerebral autoregulation (CA) mechanisms maintain blood flow approximately stable despite changes in arterial blood pressure. Mathematical models that characterise this system have been used extensively in the quantitative assessment of function/impairment of CA. Using spontaneous fluctuations in arterial blood pressure (ABP) as input and cerebral blood flow velocity (CBFV) as output, the autoregulatory mechanism can be modelled using linear and non-linear approaches, from which indexes can be extracted to provide an overall assessment of CA. Previous studies have considered a single – or at most a couple of measures, making it difficult to compare the performance of different CA parameters. We compare the performance of established autoregulatory parameters and propose novel measures. The key objective is to identify which model and index can best distinguish between normal and impaired CA. To this end 26 recordings of ABP and CBFV from normocapnia and hypercapnia (which temporarily impairs CA) in 13 healthy adults were analysed. In the absence of a ‘gold’ standard for the study of dynamic CA, lower inter- and intra-subject variability of the parameters in relation to the difference between normo- and hypercapnia were considered as criteria for identifying improved measures of CA. Significantly improved performance compared to some conventional approaches was achieved, with the simplest method emerging as probably the most promising for future studies

Position clamping of optically trapped microscopic non-spherical probes

We investigate the degree of control that can be exercised over an optically trapped microscopic non-spherical force probe. By position clamping translational and rotational modes in different ways, we are able to dramatically improve the position resolution of our probe with no reduction in sensitivity. We also demonstrate control over rotational-translational coupling, and exhibit a mechanism whereby the average centre of rotation of the probe can be displaced away from its centre

A case study exploring facilitators’ experiences of implementing a student-led Power Hour of Progress initiative within an undergraduate psychology community

This case study explores the perceptions of three student-facilitators who aimed to implement an initiative delivering regular, short and structured writing sessions (Power Hour of Progress; PHoP) within the undergraduate student body. Power Hours were already established as a practice amongst staff and post-graduate students. However, Power Hour practices have not been implemented in undergraduates. Based on the previously observed benefits with staff, we anticipated Power Hour sessions would help develop study- and time-management skills and build a sense of community within the student body. A staff-student collaboration was initiated wherein three students were trained to facilitate sessions. Fifteen PHoP sessions were run, and semi-structured interviews were conducted to explore student-facilitator views on the attempts to embed PHoP within the student body. Question-based thematic analysis identified key challenges to implementation including poor attendance and general research challenges. However, Power Hour encourages intentional learning practices, and promotes engagement in multiple academic communities. Based on these findings, we provide best practice recommendations for anybody who wishes to encourage Power Hour practices within their academic body. We conclude with a summative staff reflection on the advantages of trusting students to take ownership over staff-student partnerships

Constructing 3D crystal templates for photonic band gap materials using holographic optical tweezers

A simple and robust method is presented for the construction of 3-dimensional crystals from silica and polystyrene microspheres. The crystals are suitable for use as templates in the production of three-dimensional photonic band gap (PBG) materials. Manipulation of the microspheres was achieved using a dynamic holographic assembler (DHA) consisting of computer controlled holographic optical tweezers. Attachment of the microspheres was achieved by adjusting their colloidal interactions during assembly. The method is demonstrated by constructing a variety of 3-dimensional crystals using spheres ranging in size from 3 µm down to 800 nm. A major advantage of the technique is that it may be used to build structures that cannot be made using self-assembly. This is illustrated through the construction of crystals in which line defects have been deliberately included, and by building simple cubic structures

Probabilistic non-linear registration with spatially adaptive regularisation

This paper introduces a novel method for inferring spatially varying regularisation in non-linear registration. This is achieved through full Bayesian inference on a probabilistic registration model, where the prior on the transformation parameters is parameterised as a weighted mixture of spatially localised components. Such an approach has the advantage of allowing the registration to be more flexibly driven by the data than a traditional globally defined regularisation penalty, such as bending energy. The proposed method adaptively determines the influence of the prior in a local region. The strength of the prior may be reduced in areas where the data better support deformations, or can enforce a stronger constraint in less informative areas. Consequently, the use of such a spatially adaptive prior may reduce unwanted impacts of regularisation on the inferred transformation. This is especially important for applications where the deformation field itself is of interest, such as tensor based morphometry. The proposed approach is demonstrated using synthetic images, and with application to tensor based morphometry analysis of subjects with Alzheimer’s disease and healthy controls. The results indicate that using the proposed spatially adaptive prior leads to sparser deformations, which provide better localisation of regional volume change. Additionally, the proposed regularisation model leads to more data driven and localised maps of registration uncertainty. This paper also demonstrates for the first time the use of Bayesian model comparison for selecting different types of regularisation

ALMA and Herschel reveal that AGN and main-sequence galaxies have different star formation rate distributions

Using deep Herschel and ALMA observations, we investigate the star formation rate (SFR) distributions of X-ray AGN host galaxies at 0.5<z<1.5 and 1.5<z<4, comparing them to that of normal, star-forming (i.e., "main-sequence", or MS) galaxies. We find 34-55 per cent of AGNs have SFRs at least a factor of two below that of the average MS galaxy, compared to ~15 per cent of all MS galaxies, suggesting significantly different SFR distributions. Indeed, when both are modelled as log-normal distributions, the mass and redshift-normalised SFR distributions of AGNs are roughly twice as broad, and peak ~0.4 dex lower, than that of MS galaxies. However, like MS galaxies, the normalised SFR distribution of AGNs appears not to evolve with redshift. Despite AGNs and MS galaxies having different SFR distributions, the linear-mean SFR of AGNs derived from our distributions is remarkably consistent with that of MS galaxies, and thus with previous results derived from stacked Herschel data. This apparent contradiction is due to the linear-mean SFR being biased by bright outliers, and thus does not necessarily represent a true characterisation of the typical SFR of AGNs

Gravity wave analogs of black holes

It is demonstrated that gravity waves of a flowing fluid in a shallow basin can be used to simulate phenomena around black holes in the laboratory. Since the speed of the gravity waves as well as their high-wavenumber dispersion (subluminal vs. superluminal) can be adjusted easily by varying the height of the fluid (and its surface tension) this scenario has certain advantages over the sonic and dielectric black hole analogs, for example, although its use in testing quantum effects is dubious. It can be used to investigate the various classical instabilities associated with black (and white) holes experimentally, including positive and negative norm mode mixing at horizons. PACS: 04.70.-s, 47.90.+a, 92.60.Dj, 04.80.-y.Comment: 14 pages RevTeX, 5 figures, section VI modifie