Progress report on the EAVI BCI toolkit for music: musical applications of algorithms for use with consumer brain computer interfaces

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The Use of Interactive Genetic Algorithms in Sound Design: A Comparison Study

Two sound design methods were compared: modular synthesis and Evosynth, a novel variable architecture synthesizer programming system using an interactive genetic algorithm. They were compared using surveys, classification into established ontologies of creative systems and output analysis. Two surveys examined users’ opinions about the two synthesis methods. 430 modular synthesizer users and 14 Evosynth users responded. Both user groups valued unexpected output from the systems and tended to use exploratory approaches to sound design. Placed into ontologies of creative systems, the systems share characteristics such as autonomous signal and pattern generation, interactivity and the ability to generate novel output that was valued by their users. During a month long analysis period where Evosynth was online, 3552 breed events were recorded from 229 unique IP addresses and 90 ‘fit’ sounds were saved to the Evosynth server. The output and other analyses suggested that both systems can generate a wide range of timbres and that they allow a gradual exploration of timbre space

Synthetic and genomic regulatory elements reveal aspects of cis-regulatory grammar in mouse embryonic stem cells

In embryonic stem cells (ESCs), a core transcription factor (TF) network establishes the gene expression program necessary for pluripotency. To address how interactions between four key TFs contribute t

Organic cation transporter 1 (OCT1) modulates multiple cardiometabolic traits through effects on hepatic thiamine content.

A constellation of metabolic disorders, including obesity, dysregulated lipids, and elevations in blood glucose levels, has been associated with cardiovascular disease and diabetes. Analysis of data from recently published genome-wide association studies (GWAS) demonstrated that reduced-function polymorphisms in the organic cation transporter, OCT1 (SLC22A1), are significantly associated with higher total cholesterol, low-density lipoprotein (LDL) cholesterol, and triglyceride (TG) levels and an increased risk for type 2 diabetes mellitus, yet the mechanism linking OCT1 to these metabolic traits remains puzzling. Here, we show that OCT1, widely characterized as a drug transporter, plays a key role in modulating hepatic glucose and lipid metabolism, potentially by mediating thiamine (vitamin B1) uptake and hence its levels in the liver. Deletion of Oct1 in mice resulted in reduced activity of thiamine-dependent enzymes, including pyruvate dehydrogenase (PDH), which disrupted the hepatic glucose-fatty acid cycle and shifted the source of energy production from glucose to fatty acids, leading to a reduction in glucose utilization, increased gluconeogenesis, and altered lipid metabolism. In turn, these effects resulted in increased total body adiposity and systemic levels of glucose and lipids. Importantly, wild-type mice on thiamine deficient diets (TDs) exhibited impaired glucose metabolism that phenocopied Oct1 deficient mice. Collectively, our study reveals a critical role of hepatic thiamine deficiency through OCT1 deficiency in promoting the metabolic inflexibility that leads to the pathogenesis of cardiometabolic disease

Automated optical identification of a large complete northern hemisphere sample of flat spectrum radio sources with S_6cm > 200 mJy

This paper describes the automated optical APM identification of radio sources from the Jodrell Bank - VLA Astrometric Survey (JVAS), as used for the search for distant radio-loud quasars. The sample has been used to investigate possible relations between optical and radio properties of flat spectrum radio sources. From the 915 sources in the sample, 756 have an optical APM identification at a red (e) and/or blue (o) plate,resulting in an identification fraction of 83% with a completeness and reliability of 98% and 99% respectively. About 20% are optically identified with extended APM objects on the red plates, e.g. galaxies. However the distinction between galaxies and quasars can not be done properly near the magnitude limit of the POSS-I plates. The identification fraction appears to decrease from >90% for sources with a 5 GHz flux density of >1 Jy, to <80% for sources at 0.2 Jy. The identification fraction, in particular that for unresolved quasars, is found to be lower for sources with steeper radio spectra. In agreement with previous studies, we find that the quasars at low radio flux density levels also tend to have fainter optical magnitudes, although there is a large spread. In addition, objects with a steep radio-to-optical spectral index are found to be mainly highly polarised quasars, supporting the idea that in these objects the polarised synchrotron component is more prominent. It is shown that the large spread in radio-to-optical spectral index is possibly caused by source to source variations in the Doppler boosting of the synchrotron component [Abridged].Comment: LaTex, 17 pages, 5 gif figures, 4 tables. Accepted for publication in MNRAS. High resolution figures can be found at http://www.roe.ac.uk/~ignas

X-ray and weak lensing measurements of the mass profile of MS1008.1-1224: Chandra and VLT data

We analyse the Chandra dataset of the galaxy cluster MS1008.1-1224 to recover an estimate of the gravitating mass as function of the radius and compare these results with the weak lensing reconstruction of the mass distribution obtained from deep FORS1-VLT multicolor imaging. Even though the X-ray morphology is disturbed with a significant excess in the northern direction suggesting that the cluster is not in a relaxed state, we are able to match the two mass profiles both in absolute value and in shape within 1 sigma uncertainty and up to 1100 h50^-1 kpc. The recovered X-ray mass estimate does not change by using either the azimuthally averaged gas density and temperature profiles or the results obtained in the northern sector alone where the signal-to-noise ratio is higher.Comment: 5 pages. Accepted for publication in A&A Letter

Are my Apps Peeking? Comparing Nudging Mechanisms to Raise Awareness of Access to Mobile Front-facing Camera

Mobile applications that are granted permission to access the device’s camera can access it at any time without necessarily showing the camera feed to the user or communicating that it is being used. This lack of transparency raises privacy concerns, which are exacerbated by the increased adoption of applications that leverage front-facing cameras. Through a focus group we identified three promising approaches for nudging the user that the camera is being accessed, namely: notification bar, frame, and camera preview. We experimented with accompanying each nudging method with vibrotactile and audio feedback. Results from a user study (N=15) show that while using frame nudges is the least annoying and interrupting, but was less understandable than the camera feed and notifications. On the other hand, participants found that indicating camera usage by showing its feed or by using notifications is easy to understand. We discuss how these nudges raise user awareness and the effects on app usage and perception

Latent Transformer Models for out-of-distribution detection

Any clinically-deployed image-processing pipeline must be robust to the full range of inputs it may be presented with. One popular approach to this challenge is to develop predictive models that can provide a measure of their uncertainty. Another approach is to use generative modelling to quantify the likelihood of inputs. Inputs with a low enough likelihood are deemed to be out-of-distribution and are not presented to the downstream predictive model. In this work, we evaluate several approaches to segmentation with uncertainty for the task of segmenting bleeds in 3D CT of the head. We show that these models can fail catastrophically when operating in the far out-of-distribution domain, often providing predictions that are both highly confident and wrong. We propose to instead perform out-of-distribution detection using the Latent Transformer Model: a VQ-GAN is used to provide a highly compressed latent representation of the input volume, and a transformer is then used to estimate the likelihood of this compressed representation of the input. We demonstrate this approach can identify images that are both far- and near- out-of-distribution, as well as provide spatial maps that highlight the regions considered to be out-of-distribution. Furthermore, we find a strong relationship between an image's likelihood and the quality of a model's segmentation on it, demonstrating that this approach is viable for filtering out unsuitable images