Selection of TDOA Parameters for MDM Speaker Diarization

Several methods to improve multiple distant microphone (MDM) speaker diarization based on Time Delay of Arrival (TDOA) features are evaluated in this paper. All of them avoid the use of a single reference channel to calculate the TDOA values and, based on different criteria, select among all possible pairs of microphones a set of pairs that will be used to estimate the TDOA's. The evaluated methods have been named the "Dynamic Margin" (DM), the "Extreme Regions" (ER), the "Most Common" (MC), the "Cross Correlation" (XCorr) and the "Principle Component Analysis" (PCA). It is shown that all methods improve the baseline results for the development set and four of them improve also the results for the evaluation set. Improvements of 3.49% and 10.77% DER relative are obtained for DM and ER respectively for the test set. The XCorr and PCA methods achieve an improvement of 36.72% and 30.82% DER relative for the test set. Moreover, the computational cost for the XCorr method is 20% less than the baseline.

(Table S2) Biometric data, time of ice breakup and carbon isotopic composition of adipose tissue of polar bears (Ursus maritimus) between 1991-2007

Two global environmental issues, climate change and contamination by persistent organic pollutants, represent major concerns for arctic ecosystems. Yet, it is unclear how these two stressors interact in the Arctic. For instance, the influence of climate-associated changes in food web structure on exposure to pollutants within arctic ecosystems is presently unknown. Here, we report on recent changes in feeding ecology (1991-2007) in polar bears (Ursus maritimus) from the western Hudson Bay subpopulation that have resulted in increases in the tissue concentrations of several chlorinated and brominated contaminants. Differences in timing of the annual sea ice breakup explained a significant proportion of the diet variation among years. As expected from climate change predictions, this diet change was consistent with an increase in the consumed proportions of open water-associated seal species compared to ice-associated seal species in years of earlier sea ice breakup. Our results demonstrate that climate change is a modulating influence on contaminants in this polar bear subpopulation and may pose an additional and previously unidentified threat to northern ecosystems through altered exposures to contaminants.

Mineralogy ol late Quaternary marine sediments from the West and East Greenland shelves offshore from early Tertiary basalt outcrops

We use quantitative X-ray diffraction to determine the mineralogy of late Quaternary marine sediments from the West and East Greenland shelves offshore from early Tertiary basalt outcrops. Despite the similar basalt outcrop area (60 000-70 000 km**2), there are significant differences between East and West Greenland sediments in the fraction of minerals (e.g. pyroxene) sourced from the basalt outcrops. We demonstrate the differences in the mineralogy between East and West Greenland marine sediments on three scales: (1) modern day, (2) late Quaternary inputs and (3) detailed down-core variations in 10 cores from the two margins. On the East Greenland Shelf (EGS), late Quaternary samples have an average quartz weight per cent of 6.2 ± 2.3 versus 12.8 ± 3.9 from the West Greenland Shelf (WGS), and 12.02 ± 4.8 versus 1.9 ± 2.3 wt% for pyroxene. K-means clustering indicated only 9% of the samples did not fit a simple EGS vs. WGS dichotomy. Sediments from the EGS and WGS are also isotopically distinct, with the EGS having higher eNd (-18 to 4) than those from the WGS (eNd = -25 to -35). We attribute the striking dichotomy in sediment composition to fundamentally different long-term Quaternary styles of glaciation on the two basalt outcrops.

Salmonella in companion animals

In an increasingly hygiene concerned society, a major barrier to pet ownership is the perceived role of companion animals in contributing to the risk of exposure to zoonotic bacterial pathogens, such as Salmonella. Manifestations of Salmonella can range from acute gastroenteritis to perfuse enteric fever, in both humans and dogs. Dogs are heavily associated with asymptomatic carriage of Salmonella as the microorganism can persist in the lower intestines of this host which can be then excreted into the environment. Studies in to the asymptomatic carriage of Salmonella in dogs are somewhat dated and there is limited UK data. The current UK carriage rate in dogs was investigated in a randomised dog population and it was revealed that the carriage rate in this population was very low with only one household dog positive for the carriage of Salmonella enterica arizonae (0.2%), out of 490 dogs sampled. Salmonella serotypes share phenotypic and genotypic similarities which are captured in epidemiological typing methods. Therefore, in parallel to the epidemiological investigations, a panel of clinical canine (VLA, UK) and human (Aston University, UK) Salmonella isolates were profiled based on their phenotypic and genotypic characteristics; using API 20E, Biolog Microbial ID System, antibiotic sensitivity testing and PFGE, respectively. Antibiotic sensitivity testing revealed a significant difference between the canine and human isolates with the canine group demonstrating a higher resistance to the panel of antibiotics tested. Further metabolic capabilities of the strains were tested using the Biolog Microbial ID System, which reveal no clear association between the two host groups. However, coupled with Principle Component Analysis two canine isolates were discriminated from the entire population on the basis of a high up-regulation of two carbohydrates. API 20E testing revealed no association between the two host groups. A PFGE harmonised protocol was used to genotypically profile the strains. A dendrogram depicting PFGE profiles of the panel of Salmonella isolates was performed where similarities were calculated by Dice coefficient and represented by UPGMA clustering. Clustering of the profiles from canine isolates and human isolates (HPA, UK) was diverse representing a natural heterogeneity of the genus, additionally, no clear clustering of the isolates was observed between host groups. Clustering was observed with isolates from the same serotype, independent of host origin. Host adaption is a common phenomenon in certain Salmonella serotypes, for example S. Typhi in humans and S. Dublin in cattle. It was of interest to investigate potential host adaptive or restricted strains for canine host by performing adhesion and invasion assays on Dog Intestinal Epithelial Cells (DIECs) (WALTHAM®, UK) and human CaCo-2 (HPA, UK) cell lines. Salmonella arizonae and Enteritidis from an asymptomatic dog and clinical isolate, respectively, demonstrated a significantly high proportion of invasion in DIEC in comparison to human CaCo-2 cells and other tested Salmonella serotypes. This may be suggestive of a potential host restrictive strain as their ability to invade the CaCo-2 cell line was significantly lower than the other serotypes. In conclusion to this thesis the investigations carried out suggest that asymptomatic carriage of Salmonella in UK dogs is low however the microorganism remains as a zoonotic and anthroponotic pathogen based on phenotypic and genotypic characterisation however there may be potential for particular serotype to become host restricted as observed in invasion assays

A quantum Jensen-Shannon graph kernel using the continuous-time quantum walk

In this paper, we use the quantum Jensen-Shannon divergence as a means to establish the similarity between a pair of graphs and to develop a novel graph kernel. In quantum theory, the quantum Jensen-Shannon divergence is defined as a distance measure between quantum states. In order to compute the quantum Jensen-Shannon divergence between a pair of graphs, we first need to associate a density operator with each of them. Hence, we decide to simulate the evolution of a continuous-time quantum walk on each graph and we propose a way to associate a suitable quantum state with it. With the density operator of this quantum state to hand, the graph kernel is defined as a function of the quantum Jensen-Shannon divergence between the graph density operators. We evaluate the performance of our kernel on several standard graph datasets from bioinformatics. We use the Principle Component Analysis (PCA) on the kernel matrix to embed the graphs into a feature space for classification. The experimental results demonstrate the effectiveness of the proposed approach. © 2013 Springer-Verlag.

Chlorine contribution to quantitative structure and activity relationship models of disinfection by -products' quantum chemical descriptors and toxicities

Quantitative Structure-Activity Relationship (QSAR) has been applied extensively in predicting toxicity of Disinfection By-Products (DBPs) in drinking water. Among many toxicological properties, acute and chronic toxicities of DBPs have been widely used in health risk assessment of DBPs. These toxicities are correlated with molecular properties, which are usually correlated with molecular descriptors. The primary goals of this thesis are: (1) to investigate the effects of molecular descriptors (e.g., chlorine number) on molecular properties such as energy of the lowest unoccupied molecular orbital (E LUMO) via QSAR modelling and analysis; (2) to validate the models by using internal and external cross-validation techniques; (3) to quantify the model uncertainties through Taylor and Monte Carlo Simulation. One of the very important ways to predict molecular properties such as ELUMO is using QSAR analysis. In this study, number of chlorine (NCl ) and number of carbon (NC) as well as energy of the highest occupied molecular orbital (EHOMO) are used as molecular descriptors. There are typically three approaches used in QSAR model development: (1) Linear or Multi-linear Regression (MLR); (2) Partial Least Squares (PLS); and (3) Principle Component Regression (PCR). In QSAR analysis, a very critical step is model validation after QSAR models are established and before applying them to toxicity prediction. The DBPs to be studied include five chemical classes: chlorinated alkanes, alkenes, and aromatics. In addition, validated QSARs are developed to describe the toxicity of selected groups (i.e., chloro-alkane and aromatic compounds with a nitro- or cyano group) of DBP chemicals to three types of organisms (e.g., Fish, T. pyriformis, and P.pyosphoreum) based on experimental toxicity data from the literature. The results show that: (1) QSAR models to predict molecular property built by MLR, PLS or PCR can be used either to select valid data points or to eliminate outliers; (2) The Leave-One-Out Cross-Validation procedure by itself is not enough to give a reliable representation of the predictive ability of the QSAR models, however, Leave-Many-Out/K-fold cross-validation and external validation can be applied together to achieve more reliable results; (3) E LUMO are shown to correlate highly with the NCl for several classes of DBPs; and (4) According to uncertainty analysis using Taylor method, the uncertainty of QSAR models is contributed mostly from NCl for all DBP classes.