Use of anisotropic modelling in electrical impedance tomography: description of method and preliminary assessment of utility in imaging brain function in the adult human head.

Electrical Impedance Tomography (EIT) is an imaging method which enables a volume conductivity map of a subject to be produced from multiple impedance measurements. It has the potential to become a portable non-invasive imaging technique of particular use in imaging brain function. Accurate numerical forward models may be used to improve image reconstruction but, until now, have employed an assumption of isotropic tissue conductivity. This may be expected to introduce inaccuracy, as body tissues, especially those such as white matter and the skull in head imaging, are highly anisotropic. The purpose of this study was, for the first time, to develop a method for incorporating anisotropy in a forward numerical model for EIT of the head and assess the resulting improvement in image quality in the case of linear reconstruction of one example of the human head. A realistic Finite Element Model (FEM) of an adult human head with segments for the scalp, skull, CSF, and brain was produced from a structural MRI. Anisotropy of the brain was estimated from a diffusion tensor-MRI of the same subject and anisotropy of the skull was approximated from the structural information. A method for incorporation of anisotropy in the forward model and its use in image reconstruction was produced. The improvement in reconstructed image quality was assessed in computer simulation by producing forward data, and then linear reconstruction using a sensitivity matrix approach. The mean boundary data difference between anisotropic and isotropic forward models for a reference conductivity was 50%. Use of the correct anisotropic FEM in image reconstruction, as opposed to an isotropic one, corrected an error of 24 mm in imaging a 10% conductivity decrease located in the hippocampus, improved localisation for conductivity changes deep in the brain and due to epilepsy by 4-17 mm, and, overall, led to a substantial improvement on image quality. This suggests that incorporation of anisotropy in numerical models used for image reconstruction is likely to improve EIT image quality.

Image-Based Coral Reef Classification and Thematic Mapping

This paper presents a novel image classification scheme for benthic coral reef images that can be applied to both single image and composite mosaic datasets. The proposed method can be configured to the characteristics (e.g., the size of the dataset, number of classes, resolution of the samples, color information availability, class types, etc.) of individual datasets. The proposed method uses completed local binary pattern (CLBP), grey level co-occurrence matrix (GLCM), Gabor filter response, and opponent angle and hue channel color histograms as feature descriptors. For classification, either k-nearest neighbor (KNN), neural network (NN), support vector machine (SVM) or probability density weighted mean distance (PDWMD) is used. The combination of features and classifiers that attains the best results is presented together with the guidelines for selection. The accuracy and efficiency of our proposed method are compared with other state-of-the-art techniques using three benthic and three texture datasets. The proposed method achieves the highest overall classification accuracy of any of the tested methods and has moderate execution time. Finally, the proposed classification scheme is applied to a large-scale image mosaic of the Red Sea to create a completely classified thematic map of the reef benthos

Analysis of a finite volume method for a cross-diffusion model in population dynamics

The main goal of this paper is to propose a convergent finite volume method for a reactionâeuro"diffusion system with cross-diffusion. First, we sketch an existence proof for a class of cross-diffusion systems. Then the standard two-point finite volume fluxes are used in combination with a nonlinear positivity-preserving approximation of the cross-diffusion coefficients. Existence and uniqueness of the approximate solution are addressed, and it is also shown that the scheme converges to the corresponding weak solution for the studied model. Furthermore, we provide a stability analysis to study pattern-formation phenomena, and we perform two-dimensional numerical examples which exhibit formation of nonuniform spatial patterns. From the simulations it is also found that experimental rates of convergence are slightly below second order. The convergence proof uses two ingredients of interest for various applications, namely the discrete Sobolev embedding inequalities with general boundary conditions and a space-time $L^1$ compactness argument that mimics the compactness lemma due to Kruzhkov. The proofs of these results are given in the Appendix.

Mapping HIV/STI behavioural surveillance in Europe.

BACKGROUND: Used in conjunction with biological surveillance, behavioural surveillance provides data allowing for a more precise definition of HIV/STI prevention strategies. In 2008, mapping of behavioural surveillance in EU/EFTA countries was performed on behalf of the European Centre for Disease prevention and Control. METHOD: Nine questionnaires were sent to all 31 member States and EEE/EFTA countries requesting data on the overall behavioural and second generation surveillance system and on surveillance in the general population, youth, men having sex with men (MSM), injecting drug users (IDU), sex workers (SW), migrants, people living with HIV/AIDS (PLWHA), and sexually transmitted infection (STI) clinics patients. Requested data included information on system organisation (e.g. sustainability, funding, institutionalisation), topics covered in surveys and main indicators. RESULTS: Twenty-eight of the 31 countries contacted supplied data. Sixteen countries reported an established behavioural surveillance system, and 13 a second generation surveillance system (combination of biological surveillance of HIV/AIDS and STI with behavioural surveillance). There were wide differences as regards the year of survey initiation, number of populations surveyed, data collection methods used, organisation of surveillance and coordination with biological surveillance. The populations most regularly surveyed are the general population, youth, MSM and IDU. SW, patients of STI clinics and PLWHA are surveyed less regularly and in only a small number of countries, and few countries have undertaken behavioural surveys among migrant or ethnic minorities populations. In many cases, the identification of populations with risk behaviour and the selection of populations to be included in a BS system have not been formally conducted, or are incomplete. Topics most frequently covered are similar across countries, although many different indicators are used. In most countries, sustainability of surveillance systems is not assured. CONCLUSION: Although many European countries have established behavioural surveillance systems, there is little harmonisation as regards the methods and indicators adopted. The main challenge now faced is to build and maintain organised and functional behavioural and second generation surveillance systems across Europe, to increase collaboration, to promote robust, sustainable and cost-effective data collection methods, and to harmonise indicators.

Single acquisition electrical property mapping based on relative coil sensitivities: A proof-of-concept demonstration.

PURPOSE: All methods presented to date to map both conductivity and permittivity rely on multiple acquisitions to compute quantitatively the magnitude of radiofrequency transmit fields, B1+. In this work, we propose a method to compute both conductivity and permittivity based solely on relative receive coil sensitivities ( B1-) that can be obtained in one single measurement without the need to neither explicitly perform transmit/receive phase separation nor make assumptions regarding those phases. THEORY AND METHODS: To demonstrate the validity and the noise sensitivity of our method we used electromagnetic finite differences simulations of a 16-channel transceiver array. To experimentally validate our methodology at 7 Tesla, multi compartment phantom data was acquired using a standard 32-channel receive coil system and two-dimensional (2D) and 3D gradient echo acquisition. The reconstructed electric properties were correlated to those measured using dielectric probes. RESULTS: The method was demonstrated both in simulations and in phantom data with correlations to both the modeled and bench measurements being close to identity. The noise properties were modeled and understood. CONCLUSION: The proposed methodology allows to quantitatively determine the electrical properties of a sample using any MR contrast, with the only constraint being the need to have 4 or more receive coils and high SNR. Magn Reson Med, 2014. © 2014 Wiley Periodicals, Inc.

Mapping the diagnosis axis of an interface terminology to the NANDA International Taxonomy

Background: Nursing terminologies are designed to support nursing practice but, as with any other clinical tool, they should be evaluated. Cross-mapping is a formal method for examining the validity of the existing controlled vocabularies. Objectives: The study aims to assess the inclusiveness and expressiveness of the nursing diagnosis axis of a newly implemented interface terminology by cross-mapping with the NANDA-I taxonomy. Design/Methods: The study applied a descriptive design, using a cross-sectional, bidirectional mapping strategy. The sample included 728 concepts from both vocabularies. Concept cross-mapping was carried out to identify one-to-one, negative, and hierarchical connections. The analysis was conducted using descriptive statistics. Results: Agreement of the raters" mapping achieved 97%. More than 60% of the nursing diagnosis concepts in the NANDA-I taxonomy were mapped to concepts in the diagnosis axis of the new interface terminology; 71.1% were reversely mapped. Conclusions: Main results for outcome measures suggest that the diagnosis axis of this interface terminology meets the validity criterion of cross-mapping when mapped from and to the NANDA-I taxonomy.

Improved predictive mapping of indoor radon concentrations using ensemble regression trees based on automatic clustering of geological units.

PURPOSE: According to estimations around 230 people die as a result of radon exposure in Switzerland. This public health concern makes reliable indoor radon prediction and mapping methods necessary in order to improve risk communication to the public. The aim of this study was to develop an automated method to classify lithological units according to their radon characteristics and to develop mapping and predictive tools in order to improve local radon prediction. METHOD: About 240 000 indoor radon concentration (IRC) measurements in about 150 000 buildings were available for our analysis. The automated classification of lithological units was based on k-medoids clustering via pair-wise Kolmogorov distances between IRC distributions of lithological units. For IRC mapping and prediction we used random forests and Bayesian additive regression trees (BART). RESULTS: The automated classification groups lithological units well in terms of their IRC characteristics. Especially the IRC differences in metamorphic rocks like gneiss are well revealed by this method. The maps produced by random forests soundly represent the regional difference of IRCs in Switzerland and improve the spatial detail compared to existing approaches. We could explain 33% of the variations in IRC data with random forests. Additionally, the influence of a variable evaluated by random forests shows that building characteristics are less important predictors for IRCs than spatial/geological influences. BART could explain 29% of IRC variability and produced maps that indicate the prediction uncertainty. CONCLUSION: Ensemble regression trees are a powerful tool to model and understand the multidimensional influences on IRCs. Automatic clustering of lithological units complements this method by facilitating the interpretation of radon properties of rock types. This study provides an important element for radon risk communication. Future approaches should consider taking into account further variables like soil gas radon measurements as well as more detailed geological information.

Multi-sensor Simultaneous Localization and Mapping

Simultaneous localization and mapping(SLAM) is a very important problem in mobile robotics. Many solutions have been proposed by different scientists during the last two decades, nevertheless few studies have considered the use of multiple sensors simultane¬ously. The solution is on combining several data sources with the aid of an Extended Kalman Filter (EKF). Two approaches are proposed. The first one is to use the ordinary EKF SLAM algorithm for each data source separately in parallel and then at the end of each step, fuse the results into one solution. Another proposed approach is the use of multiple data sources simultaneously in a single filter. The comparison of the computational com¬plexity of the two methods is also presented. The first method is almost four times faster than the second one.

Efficient image mosaicing for multi-robot visual underwater mapping

Robotic platforms have advanced greatly in terms of their remote sensing capabilities, including obtaining optical information using cameras. Alongside these advances, visual mapping has become a very active research area, which facilitates the mapping of areas inaccessible to humans. This requires the efficient processing of data to increase the final mosaic quality and computational efficiency. In this paper, we propose an efficient image mosaicing algorithm for large area visual mapping in underwater environments using multiple underwater robots. Our method identifies overlapping image pairs in the trajectories carried out by the different robots during the topology estimation process, being this a cornerstone for efficiently mapping large areas of the seafloor. We present comparative results based on challenging real underwater datasets, which simulated multi-robot mapping

Mapping of summer crops in the State of Paraná, Brazil, through the 10-day spot vegetation NDVI composites

The search for low subjectivity area estimates has increased the use of remote sensing for agricultural monitoring and crop yield prediction, leading to more flexibility in data acquisition and lower costs comparing to traditional methods such as census and surveys. Low spatial resolution satellite images with higher frequency in image acquisition have shown to be adequate for cropland mapping and monitoring in large areas. The main goal of this study was to map the Summer crops in the State of Paraná, Brazil, using 10-day composition of NDVI SPOT Vegetation data for 2005/2006, 2006/2007 and 2007/2008 cropping seasons. For this, a supervised digital classification method with Parallelepiped algorithm in multitemporal RGB image composites was used, in order to generate masks of Summer cultures for each 10-day composition. Accuracy assessment was performed using Kappa index, overall accuracy and Willmott's concordance index, resulting in good levels of accuracy. This methodology allowed the accomplishment, with free and low resolution data, of the mapping of Summer cultures at State level.

A systematic mapping study of web services discovery mechanisms

Context: Web services have been gaining popularity due to the success of service oriented architecture and cloud computing. Web services offer tremendous opportunity for service developers to publish their services and applications over the boundaries of the organization or company. However, to fully exploit these opportunities it is necessary to find efficient discovery mechanism thus, Web services discovering mechanism has attracted a considerable attention in Semantic Web research, however, there have been no literature surveys that systematically map the present research result thus overall impact of these research efforts and level of maturity of their results are still unclear. This thesis aims at providing an overview of the current state of research into Web services discovering mechanism using systematic mapping. The work is based on the papers published 2004 to 2013, and attempts to elaborate various aspects of the analyzed literature including classifying them in terms of the architecture, frameworks and methods used for web services discovery mechanism. Objective: The objective if this work is to summarize the current knowledge that is available as regards to Web service discovery mechanisms as well as to systematically identify and analyze the current published research works in order to identify different approaches presented. Method: A systematic mapping study has been employed to assess the various Web Services discovery approaches presented in the literature. Systematic mapping studies are useful for categorizing and summarizing the level of maturity research area. Results: The result indicates that there are numerous approaches that are consistently being researched and published in this field. In terms of where these researches are published, conferences are major contributing publishing arena as 48% of the selected papers were conference published papers illustrating the level of maturity of the research topic. Additionally selected 52 papers are categorized into two broad segments namely functional and non-functional based approaches taking into consideration architectural aspects and information retrieval approaches, semantic matching, syntactic matching, behavior based matching as well as QOS and other constraints.

Spatial modeling techniques for mapping and characterization of acid sulfate soils

Acid sulfate (a.s.) soils constitute a major environmental issue. Severe ecological damage results from the considerable amounts of acidity and metals leached by these soils in the recipient watercourses. As even small hot spots may affect large areas of coastal waters, mapping represents a fundamental step in the management and mitigation of a.s. soil environmental risks (i.e. to target strategic areas). Traditional mapping in the field is time-consuming and therefore expensive. Additional more cost-effective techniques have, thus, to be developed in order to narrow down and define in detail the areas of interest. The primary aim of this thesis was to assess different spatial modeling techniques for a.s. soil mapping, and the characterization of soil properties relevant for a.s. soil environmental risk management, using all available data: soil and water samples, as well as datalayers (e.g. geological and geophysical). Different spatial modeling techniques were applied at catchment or regional scale. Two artificial neural networks were assessed on the Sirppujoki River catchment (c. 440 km2) located in southwestern Finland, while fuzzy logic was assessed on several areas along the Finnish coast. Quaternary geology, aerogeophysics and slope data (derived from a digital elevation model) were utilized as evidential datalayers. The methods also required the use of point datasets (i.e. soil profiles corresponding to known a.s. or non-a.s. soil occurrences) for training and/or validation within the modeling processes. Applying these methods, various maps were generated: probability maps for a.s. soil occurrence, as well as predictive maps for different soil properties (sulfur content, organic matter content and critical sulfide depth). The two assessed artificial neural networks (ANNs) demonstrated good classification abilities for a.s. soil probability mapping at catchment scale. Slightly better results were achieved using a Radial Basis Function (RBF) -based ANN than a Radial Basis Functional Link Net (RBFLN) method, narrowing down more accurately the most probable areas for a.s. soil occurrence and defining more properly the least probable areas. The RBF-based ANN also demonstrated promising results for the characterization of different soil properties in the most probable a.s. soil areas at catchment scale. Since a.s. soil areas constitute highly productive lands for agricultural purpose, the combination of a probability map with more specific soil property predictive maps offers a valuable toolset to more precisely target strategic areas for subsequent environmental risk management. Notably, the use of laser scanning (i.e. Light Detection And Ranging, LiDAR) data enabled a more precise definition of a.s. soil probability areas, as well as the soil property modeling classes for sulfur content and the critical sulfide depth. Given suitable training/validation points, ANNs can be trained to yield a more precise modeling of the occurrence of a.s. soils and their properties. By contrast, fuzzy logic represents a simple, fast and objective alternative to carry out preliminary surveys, at catchment or regional scale, in areas offering a limited amount of data. This method enables delimiting and prioritizing the most probable areas for a.s soil occurrence, which can be particularly useful in the field. Being easily transferable from area to area, fuzzy logic modeling can be carried out at regional scale. Mapping at this scale would be extremely time-consuming through manual assessment. The use of spatial modeling techniques enables the creation of valid and comparable maps, which represents an important development within the a.s. soil mapping process. The a.s. soil mapping was also assessed using water chemistry data for 24 different catchments along the Finnish coast (in all, covering c. 21,300 km2) which were mapped with different methods (i.e. conventional mapping, fuzzy logic and an artificial neural network). Two a.s. soil related indicators measured in the river water (sulfate content and sulfate/chloride ratio) were compared to the extent of the most probable areas for a.s. soils in the surveyed catchments. High sulfate contents and sulfate/chloride ratios measured in most of the rivers demonstrated the presence of a.s. soils in the corresponding catchments. The calculated extent of the most probable a.s. soil areas is supported by independent data on water chemistry, suggesting that the a.s. soil probability maps created with different methods are reliable and comparable.

Recombinant antigen-based immuno-slot blot method for serodiagnosis of syphilis

Three recombinant antigens of Treponema pallidum Nichols strain were fused with GST, cloned and expressed in Escherichia coli, resulting in high levels of GST-rTp47 and GST-rTp17 expression, and supplementation with arginine tRNA for the AGR codon was needed to obtain GST-rTp15 overexpression. Purified fusion protein yields were 1.9, 1.7 and 5.3 mg/l of cell culture for GST-rTp47, GST-rTp17 and GST-rTp15, respectively. The identities of the antigens obtained were confirmed by automated DNA sequencing using ABI Prism 310 and peptide mapping by Finningan LC/MS. These recombinant antigens were evaluated by immuno-slot blot techniques applied to 137 serum samples from patients with a clinical and laboratory diagnosis of syphilis (61 samples), from healthy blood donors (50 samples), individuals with sexually transmitted disease other than syphilis (3 samples), and from individuals with other spirochetal diseases such as Lyme disease (20 samples) and leptospirosis (3 samples). The assay had sensitivity of 95.1% (95% CI, 86.1 to 98.7%) and a specificity of 94.7% (95% CI, 87.0 to 98.7%); a stronger reactivity was observed with fraction rTp17. The immunoreactivity results showed that fusion recombinant antigens based-immuno-slot blot techniques are suitable for use in diagnostic assays for syphilis.

A systematic mapping study on open data

This thesis presented the overview of Open Data research area, quantity of evidence and establishes the research evidence based on the Systematic Mapping Study (SMS). There are 621 such publications were identified published between years 2005 and 2014, but only 243 were selected in the review process. This thesis highlights the implications of Open Data principals’ proliferation in the emerging era of the accessibility, reusability and sustainability of data transparency. The findings of mapping study are described in quantitative and qualitative measurement based on the organization affiliation, countries, year of publications, research method, star rating and units of analysis identified. Furthermore, units of analysis were categorized by development lifecycle, linked open data, type of data, technical platforms, organizations, ontology and semantic, adoption and awareness, intermediaries, security and privacy and supply of data which are important component to provide a quality open data applications and services. The results of the mapping study help the organizations (such as academia, government and industries), re-searchers and software developers to understand the existing trend of open data, latest research development and the demand of future research. In addition, the proposed conceptual framework of Open Data research can be adopted and expanded to strengthen and improved current open data applications.

A study of chymotrypsin immobilization conditions for improved peptide mapping

La cartographie peptidique est une technique de grande importance utilisée lors de l’identification des protéines et la caractérisation des modifications post-traductionnelles des protéines. Deux méthodes sont utilisées afin de couper les protéines en peptides pour la cartographie : les méthodes chimiques et les méthodes enzymatiques. Dans ce projet, l’enzyme chymotrypsine a été utilisée pour l’hydrolyse (la digestion) des liens peptidiques. Cependant, l’autoprotéolyse des enzymes peut augmenter la complexité des échantillons, rendant ainsi ardue l’obtention de pics résolus suite à l’apparition de pics non-désirés dans la carte peptidique. Par conséquent, nous avons utilisé la réticulation des enzymes protéolytiques par réaction avec le glutaraldéhyde (GA) donnant une enzyme insoluble afin de réduire l’autoprotéolyse. L’immobilisation de la chymotrypsine par GA a été effectuée selon une méthode rapportée précédemment par le groupe Waldron. L’électrophorèse capillaire (CE) couplée à l’absorption UV-visible a été utilisée pour la séparation et la détection de peptides et pour obtenir ainsi une cartographie peptidique. Deux tampons différents ont été évalués afin d’obtenir les meilleures conditions pour la digestion de substrats protéiques par la chymotrypsine libre (soluble) ou la GAchymotrypsine et l’analyse par CE. Les cartes des peptides autoprotéolytiques ont été comparées entre les deux formats de chymotrypsine. Afin d’améliorer la cartographie peptidique, nous avons évalué trois méthodes de conditionnement du capillaire CE et deux méthodes pour stopper la digestion. Le bicarbonate d’ammonium s’est avéré être le tampon optimal pour la digestion en solution et l’utilisation d’un bain d’acétone et de glace sèche s’est avérée être la méthode optimale pour stopper la digestion. Une solution de SDS, 25 mM, dans l’étape de rinçage a été utilisée après chaque analyse CE et a permis d’améliorer la résolution des cartes peptidiques. La comparaison entre l’autoprotéolyse de la chymotrypsine libre et de celle immobilisé par GA a été effectuée par des tests utilisant une gamme de six différentes combinaisons de conditions afin d’évaluer le temps (30 et 240 min) et la température de digestion (4, 24 et 37°C). Dans ces conditions, nos résultats ont confirmé que le GA-chymotrypsine réduit l’autoprotéolyse par rapport à l’enzyme libre. La digestion (à 37°C/240 min) de deux substrats modèles par la chymotrypsine libre et immobilisée en fonction de la température de dénaturation du substrat a été étudiée. iii Avant la digestion, les substrats (l’albumine de sérum bovine, BSA, et la myoglobine) ont été dénaturés par chauffage pendant 45 min à trois températures différentes (60, 75 et 90°C). Les résultats ont démontré que la dénaturation par chauffage du BSA et de la myoglobine n’a pas amélioré la cartographie peptidique pour la GA-chymotrypsine, tandis que la digestion de ceux-ci en présence de la chymotrypsine libre a amélioré de façon quantifiable à des températures élevées. Ainsi, le chauffage du substrat à 90°C avec l’enzyme soluble facilite le dépliement partiel du substrat et sa digestion limitée, ce qui a été mieux pour la myoglobine que pour la BSA.