A Fast Algorithm for Robust Regression with Penalised Trimmed Squares

The presence of groups containing high leverage outliers makes linear regression a difficult problem due to the masking effect. The available high breakdown estimators based on Least Trimmed Squares often do not succeed in detecting masked high leverage outliers in finite samples. An alternative to the LTS estimator, called Penalised Trimmed Squares (PTS) estimator, was introduced by the authors in \cite{ZiouAv:05,ZiAvPi:07} and it appears to be less sensitive to the masking problem. This estimator is defined by a Quadratic Mixed Integer Programming (QMIP) problem, where in the objective function a penalty cost for each observation is included which serves as an upper bound on the residual error for any feasible regression line. Since the PTS does not require presetting the number of outliers to delete from the data set, it has better efficiency with respect to other estimators. However, due to the high computational complexity of the resulting QMIP problem, exact solutions for moderately large regression problems is infeasible. In this paper we further establish the theoretical properties of the PTS estimator, such as high breakdown and efficiency, and propose an approximate algorithm called Fast-PTS to compute the PTS estimator for large data sets efficiently. Extensive computational experiments on sets of benchmark instances with varying degrees of outlier contamination, indicate that the proposed algorithm performs well in identifying groups of high leverage outliers in reasonable computational time.Comment: 27 page

Uniform acquisition modelling across PET imaging systems: unified scatter modelling

RIN factor of all samples used for Illumina sequencing. (PDF 225 kb

Uniform acquisition modelling across PET imaging systems: Unified scatter modelling

© 2016 IEEE. PET imaging is an important tool commonly used for studying disease by research consortia which implement multi-centre studies to improve the statistical power of findings. The UK government launched the Dementias Platform UK to facilitate one of the world's largest dementia population study involving national centres equipped with state-of-the-art PET/MR scanners from two major vendors. However, the difference in PET detector technology between the two scanners involved makes the standardisation of data acquisition and image reconstruction necessary. We propose a new approach to PET acquisition system modelling across different PET systems and technologies, focusing in particular on unified scatter estimation across TOF (time-of-flight) and non-TOF PET systems. The proposed scatter modelling is fully 3D and voxel based, as opposed to the popular line-of-response driven methods. This means that for each emitting voxel an independent 3D scatter estimate is found, inherently preserving the necessary information for TOF calculations as well as accounting for the large axial field of view. With adequate sampling of the input images, the non-TOF scatter estimate is identical to the summed TOF estimates across TOF bins, without an additional computational cost used for the TOF estimation. The model is implemented using the latest NVIDA GPU CUDA platform, allowing finer sampling of image space which is more essential for accurate TOF modelling. The high accuracy of the proposed scatter model is validated using Monte Carlo simulations. The model is deployed in our stand-alone image reconstruction pipeline for the Biograph mMR scanner, demonstrating accurate 3D scatter estimates resulting in uniform reconstruction for a high statistics phantom scan

Rapid processing of PET list-mode data for efficient uncertainty estimation and data analysis

In this technical note we propose a rapid and scalable software solution for the processing of PET list-mode data, which allows the efficient integration of list mode data processing into the workflow of image reconstruction and analysis. All processing is performed on the graphics processing unit (GPU), making use of streamed and concurrent kernel execution together with data transfers between disk and CPU memory as well as CPU and GPU memory. This approach leads to fast generation of multiple bootstrap realisations, and when combined with fast image reconstruction and analysis, it enables assessment of uncertainties of any image statistic and of any component of the image generation process (e.g., random correction, image processing) within reasonable time frames (e.g., within five minutes per realisation). This is of particular value when handling complex chains of image generation and processing. The software outputs the following: (1) estimate of expected random event data for noise reduction; (2) dynamic prompt and random sinograms of span-1 and span-11 and (3) variance estimates based on multiple bootstrap realisations of (1) and (2) assuming reasonable count levels for acceptable accuracy. In addition, the software produces statistics and visualisations for immediate quality control and crude motion detection, such as: (1) count rate curves; (2) centre of mass plots of the radiodistribution for motion detection; (3) video of dynamic projection views for fast visual list-mode skimming and inspection; (4) full normalisation factor sinograms. To demonstrate the software, we present an example of the above processing for fast uncertainty estimation of regional SUVR (standard uptake value ratio) calculation for a single PET scan of ¹⁸F-florbetapir using the Siemens Biograph mMR scanner

Ocean net heat flux influences seasonal to interannual patterns of plankton abundance

This is the final version. Available from the publisher via the DOI in this record.Changes in the net heat flux (NHF) into the ocean have profound impacts on global climate. We analyse a long-term plankton time-series and show that the NHF is a critical indicator of ecosystem dynamics. We show that phytoplankton abundance and diversity patterns are tightly bounded by the switches between negative and positive NHF over an annual cycle. Zooplankton increase before the transition to positive NHF in the spring but are constrained by the negative NHF switch in autumn. By contrast bacterial diversity is decoupled from either NHF switch, but is inversely correlated (r = 20.920) with the magnitude of the NHF. We show that the NHF is a robust mechanistic tool for predicting climate change indicators such as spring phytoplankton bloom timing and length of the growing season.Natural Environment Research Council (NERC)European Union: 7th Framework ProgrammeINTERREG IV

Fitting a 3D Morphable Model to Edges: A Comparison Between Hard and Soft Correspondences

We propose a fully automatic method for fitting a 3D morphable model to single face images in arbitrary pose and lighting. Our approach relies on geometric features (edges and landmarks) and, inspired by the iterated closest point algorithm, is based on computing hard correspondences between model vertices and edge pixels. We demonstrate that this is superior to previous work that uses soft correspondences to form an edge-derived cost surface that is minimised by nonlinear optimisation.Comment: To appear in ACCV 2016 Workshop on Facial Informatic

Next Generation Sequencing Reveals the Hidden Diversity of Zooplankton Assemblages

Zooplankton play an important role in our oceans, in biogeochemical cycling and providing a food source for commercially important fish larvae. However, difficulties in correctly identifying zooplankton hinder our understanding of their roles in marine ecosystem functioning, and can prevent detection of long term changes in their community structure. The advent of massively parallel next generation sequencing technology allows DNA sequence data to be recovered directly from whole community samples. Here we assess the ability of such sequencing to quantify richness and diversity of a mixed zooplankton assemblage from a productive time series site in the Western English Channel. Methodology/Principle Findings Plankton net hauls (200 µm) were taken at the Western Channel Observatory station L4 in September 2010 and January 2011. These samples were analysed by microscopy and metagenetic analysis of the 18S nuclear small subunit ribosomal RNA gene using the 454 pyrosequencing platform. Following quality control a total of 419,041 sequences were obtained for all samples. The sequences clustered into 205 operational taxonomic units using a 97% similarity cut-off. Allocation of taxonomy by comparison with the National Centre for Biotechnology Information database identified 135 OTUs to species level, 11 to genus level and 1 to order, <2.5% of sequences were classified as unknowns. By comparison a skilled microscopic analyst was able to routinely enumerate only 58 taxonomic groups. Conclusions Metagenetics reveals a previously hidden taxonomic richness, especially for Copepoda and hard-to-identify meroplankton such as Bivalvia, Gastropoda and Polychaeta. It also reveals rare species and parasites. We conclude that Next Generation Sequencing of 18S amplicons is a powerful tool for elucidating the true diversity and species richness of zooplankton communities. While this approach allows for broad diversity assessments of plankton it may become increasingly attractive in future if sequence reference libraries of accurately identified individuals are better populated

A metabarcoding comparison of taxonomic richness and composition between the water column and the benthic boundary layer

Zooplankton monitoring in shelf seas predominantly uses nets that miss the benthic boundary layer (BBL) just above the seabed. However, this boundary between pelagic and benthic assemblages can be faunistically rich, having its own distinct hyperbenthic fauna and acting as a low-light refuge for overwintering or dielly migrating zooplankton. To compare species richness and composition between pelagic and BBL habitats, we sampled a long-term monitoring site in the Western English Channel seasonally. Metabarcoding methods applied to vertical net samples (top 50 m in a �54-m water column) and those from a hyperbenthic sledge generated >100 000 sequences clustered into 294 opera�tional taxonomic units. Of these, 215 were found in the BBL and 170 in the water column. Some key taxa (e.g. mysids) were native to the BBL; by contrast, other delicate taxa (e.g. ctenophores) seemed to avoid the BBL. The major contrasts in plankton composition related to the seasonal cycle rather than to pelagic-BBL differences, suggesting that the basic dynamics of the site are captured by our ongoing long-term weekly resolution monitoring. Overall, metabarcoding approaches, applied to both water column and BBL, provide an independent view of plankton dynamics, and augment existing traditional methods

Gad65 is recognized by t-cells, but not by antibodies from nod-mice

Since the 64kDa-protein glutamic acid decarboxylase (GAD) is one of the major autoantigens in T-cell mediated Type 1 diabetes, its relevance as a T-cell antigen needs to be clarified. After isolation of splenic T-cells from non-obese diabetic (NOD) mice, a useful model for human Type 1 diabetes, we found that these T-cells proliferate spontaneously when incubated with human GAD65, but only marginally after incubation with GAD67, both recombinated in the baculovirus system. No effect was observed with non-diabetic NOD mice or with T-cells from H-2 identical NON-NOD-H-2g7 control mice. It has been published previously that NOD mice develop autoantibodies against a 64kDa protein detected with mouse beta cells. In immunoprecipitation experiments with sera from the same NOD mice and 33S-methionine-labelled GAD, no autoantibody binding could be detected. We conclude firstly that GAD65 is an important T-cell antigen which is relevant early in the development of Type 1 diabetes and secondly that there is an antigenic epitope in the human GAD65 molecule recognized by NOD T-cells, but not by NOD autoantibodies precipitating conformational epitopes. Our results therefore provide further evidence that GAD65 is a T-cell antigen in NOD mice, being possibly also involved in very early processes leading to the development of human Type 1 diabetes