Peak Alignment of Gas Chromatography-Mass Spectrometry Data with Deep Learning

We present ChromAlignNet, a deep learning model for alignment of peaks in Gas Chromatography-Mass Spectrometry (GC-MS) data. In GC-MS data, a compound's retention time (RT) may not stay fixed across multiple chromatograms. To use GC-MS data for biomarker discovery requires alignment of identical analyte's RT from different samples. Current methods of alignment are all based on a set of formal, mathematical rules. We present a solution to GC-MS alignment using deep learning neural networks, which are more adept at complex, fuzzy data sets. We tested our model on several GC-MS data sets of various complexities and analysed the alignment results quantitatively. We show the model has very good performance (AUC $\sim 1$ for simple data sets and AUC $\sim 0.85$ for very complex data sets). Further, our model easily outperforms existing algorithms on complex data sets. Compared with existing methods, ChromAlignNet is very easy to use as it requires no user input of reference chromatograms and parameters. This method can easily be adapted to other similar data such as those from liquid chromatography. The source code is written in Python and available online

Pairing Gaps, Pseudogaps, and Phase Diagrams for Cuprate Superconductors

We use a symmetry-constrained variational procedure to construct a generalization of BCS to include Cooper pairs with non-zero momentum and angular momentum. The resulting gap equations are solved at zero and finite temperature, and the doping-dependent solutions are used to construct gap and phase diagrams. We find a pseudogap terminating at a critical doping that may be interpreted in terms of both competing order and preformed pairs. The strong similarity between observation and predicted gap and phase structure suggests that this approach may provide a unified description of the complex structure observed for cuprate superconductors.Comment: 5 pages, 1 figur

SU(4) Model of High-Temperature Superconductivity: Manifestation of Dynamical Symmetry in Cuprates

The mechanism that leads to high-temperature superconductivity in cuprates remains an open question despite intense study for nearly two decades. Here, we introduce an SU(4) model for cuprate systems having many similarities to dynamical symmetries known to play an important role in nuclear structure physics and in elementary particle physics. Analytical solutions in three dynamical symmetry limits of this model are found: an SO(4) limit associated with antiferromagnetic order; an SU(2) limit that may be interpreted as a d-wave pairing condensate; and an SO(5) limit that may be interpreted as a doorway state between the antiferromagnetic order and the superconducting order. It is demonstrated that with a slightly broken SO(5) but under constraint of the parent SU(4) symmetry, the model is capable of describing the rich physics that is crucial in explaining why cuprate systems that are antiferromagnetic Mott insulators at half filling become superconductors through hole doping.Comment: 16 pages, 4 figures, proceedings of "Nuclei and Mesoscopic Physics" to be published by AI

Mott Insulators, No-Double-Occupancy, and Non-Abelian Superconductivity

SU(4) dynamical symmetry is shown to imply a no-double-occupancy constraint on the minimal symmetry description of antiferromagnetism and d-wave superconductivity. This implies a maximum doping fraction of 1/4 for cuprates and provides a microscopic critique of the projected SO(5) model. We propose that SU(4) superconductors are representative of a class of compounds that we term non-abelian superconductors. We further suggest that non-abelian superconductors may exist having SU(4) symmetry and therefore cuprate-like dynamics, but without d-wave hybridization.Comment: 4 pages, 2 figure

HTML5 video on mobile browsers

This paper reports on research investigating the current ability of HTML5 to play video in mobile browsers. Smartphones and the Mobile Internet are rapidly becoming an important platform for access to information anytime and anywhere. HTML5, the new HTML standard incorporates features like video playback that have been previously dependent on third-party browser plug-ins but there are no browsers that currently provide 100% support for HTML5. All the tests reported in this paper were carried out using smartphones with screen sizes 3.0 to 4.8 inches and the ability to replay videos of a range of formats, move directly to time points in the video and display closed captions were investigated. Key findings were that: video cannot be started programmatically; only selecting on the screen can trigger playback; no visual elements sitting over the <video> will receive click events while the video is visible (playing or paused); there are many HTML5 video players but MediaElement.js was found to currently be the open source player satisfying the greatest number of requirements

Synote mobile HTML5 responsive design video annotation application

Synote Mobile has been developed as an accessible cross device and cross browser HTML5 webbased collaborative replay and annotation tool to make web-based recordings easier to access, search, manage, and exploit for learners, teachers and others. It has been developed as a new mobile HTML5 version of the award winning open source and freely available Synote which has been used since 2008 by students throughout the world to learn interactively from recordings. While most UK students now carry mobile devices capable of replaying Internet video, the majority of these devices cannot replay Synote’s accessible, searchable, annotated recordings as Synote was created in 2008 when few students had phones or tablets capable of replaying these videos

Let Google index your media fragments

Current multimedia applications in Web 2.0 have generated a massive amount of multimedia resources, but most search results for multimedia resources still focus on the whole re-source level. Media fragments expose the inside content of multimedia resources for annotations, but they are yet fully explored and indexed by major search engines. W3C has published Media Fragment 1.0 as a standard way to describe media fragments on the Web. In this proposal, we make use of Google's Ajax Application Crawler to index media fragments represented by Media Fragment URIs. Each media fragment with related annotations will have an individual snapshot page, which could be indexed by the crawler. Initial evaluation has shown that the snapshot pages are successfully fetched by Googlebot and we are expecting more media fragments to be indexed using this method, so that the search for multimedia resources would be more efficient