Genotyping, physiological features and proteolytic activities of a potentially pathogenic Acanthamoeba sp isolated from tap water in Brazil

Acanthamoeba spp., known to cause keratitis and granulomatous encephalitis in humans, are frequently isolated from a variety of water sources. Here we report for the first time the characterization of an Acanthamoeba sp. (ACC01) isolated from tap water in Brazil. This organism is currently being maintained in an axenic growth medium. Phylogenetic analysis based on SSU rRNA gene sequences positioned the new isolate in genotype T4, closest to the keratitis-causing isolate, A. polyphaga ATCC 30461 (similar to 99% similarity). Acanthamoeba ACC01 and A. polyphaga 30461 both grew at 37 degrees C and were osmotically resistant, multiplying in hyperosmolar medium. Both isolates secreted comparable amounts of proteolytic enzymes, including serine peptidases that were optimally active at a near neutral/alkaline pH and resolved identically in gelatin gels. Incubation of gels at pH 4.0 with 2 mM DTT also indicated the secretion of similar cysteine peptidases. Altogether, the results point to the pathogenic potential of Acanthamoeba ACC01. (C) 2009 Elsevier Inc. All rights reserved.

Beyond the average: Detecting global singular nodes from local features in complex networks

Deviations from the average can provide valuable insights about the organization of natural systems. The present article extends this important principle to the systematic identification and analysis of singular motifs in complex networks. Six measurements quantifying different and complementary features of the connectivity around each node of a network were calculated, and multivariate statistical methods applied to identify singular nodes. The potential of the presented concepts and methodology was illustrated with respect to different types of complex real-world networks, namely the US air transportation network, the protein-protein interactions of the yeast Saccharomyces cerevisiae and the Roget thesaurus networks. The obtained singular motifs possessed unique functional roles in the networks. Three classic theoretical network models were also investigated, with the Barabasi-Albert model resulting in singular motifs corresponding to hubs, confirming the potential of the approach. Interestingly, the number of different types of singular node motifs as well as the number of their instances were found to be considerably higher in the real-world networks than in any of the benchmark networks. Copyright (C) EPLA, 2009

Spectroscopic features of erbium-doped CaM2O6 (M = Nb, Ta) single crystal fibers grown by the laser-heated pedestal growth technique

Erbium-doped single crystal fibers, with low phonon energy and fairly high absorption and emission cross sections are interesting laser active media, for compact, near-infrared and/or upconversion lasers. In this work, high optical quality Er3+-doped CaNb2O6 and CaTa2O6 single crystal fibers were successfully grown by the versatile laser-heated pedestal growth technique, and characterized from the structural and spectroscopic points of view. The results indicate that these crystal fiber compositions, which had not been explored so far, offer potential applications, not only as laser active media, but also in other optical devices. (c) 2007 Elsevier B.V. All rights reserved.

Intermolecular Contacts Influencing the Conformational and Geometric Features of the Pharmaceutically Preferred Mebendazole Polymorph C

Mebendazole (MBZ) is a common benzimidazole anthelmintic that exists in three different polymorphic forms, A, B, and C. Polymorph C is the pharmaceutically preferred form due to its adequated aqueous solubility. No single crystal structure determinations depicting the nature of the crystal packing and molecular conformation and geometry have been performed on this compound. The crystal structure of mebendazole form C is resolved for the first time. Mebendazole form C crystallizes in the triclinic centrosymmetric space group and this drug is practically planar, since the least-squares methyl benzimidazolylcarbamate plane is much fitted on the forming atoms. However, the benzoyl group is twisted by 31(1)degrees from the benzimidazole ring, likewise the torsional angle between the benzene and carbonyl moieties is 27(1)degrees. The formerly described bends and other interesting intramolecular geometry features were viewed as consequence of the intermolecular contacts occurring within mebendazole C structure. Among these features, a conjugation decreasing through the imine nitrogen atom of the benzimidazole core and a further resonance path crossing the carbamate one were described. At last, the X-ray powder diffractogram of a form C rich mebendazole mixture was overlaid to the calculated one with the mebendazole crystal structure. (C) 2008 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 98:2336-2344, 2009

Resilience of protein-protein interaction networks as determined by their large-scale topological features

The relationship between the structure and function of biological networks constitutes a fundamental issue in systems biology. Particularly, the structure of protein-protein interaction networks is related to important biological functions. In this work, we investigated how such a resilience is determined by the large scale features of the respective networks. Four species are taken into account, namely yeast Saccharomyces cerevisiae, worm Caenorhabditis elegans, fly Drosophila melanogaster and Homo sapiens. We adopted two entropy-related measurements (degree entropy and dynamic entropy) in order to quantify the overall degree of robustness of these networks. We verified that while they exhibit similar structural variations under random node removal, they differ significantly when subjected to intentional attacks (hub removal). As a matter of fact, more complex species tended to exhibit more robust networks. More specifically, we quantified how six important measurements of the networks topology (namely clustering coefficient, average degree of neighbors, average shortest path length, diameter, assortativity coefficient, and slope of the power law degree distribution) correlated with the two entropy measurements. Our results revealed that the fraction of hubs and the average neighbor degree contribute significantly for the resilience of networks. In addition, the topological analysis of the removed hubs indicated that the presence of alternative paths between the proteins connected to hubs tend to reinforce resilience. The performed analysis helps to understand how resilience is underlain in networks and can be applied to the development of protein network models.

Road Sign Recognition based onInvariant Features using SupportVector Machine

Since last two decades researches have been working on developing systems that can assistsdrivers in the best way possible and make driving safe. Computer vision has played a crucialpart in design of these systems. With the introduction of vision techniques variousautonomous and robust real-time traffic automation systems have been designed such asTraffic monitoring, Traffic related parameter estimation and intelligent vehicles. Among theseautomatic detection and recognition of road signs has became an interesting research topic.The system can assist drivers about signs they don’t recognize before passing them.Aim of this research project is to present an Intelligent Road Sign Recognition System basedon state-of-the-art technique, the Support Vector Machine. The project is an extension to thework done at ITS research Platform at Dalarna University [25]. Focus of this research work ison the recognition of road signs under analysis. When classifying an image its location, sizeand orientation in the image plane are its irrelevant features and one way to get rid of thisambiguity is to extract those features which are invariant under the above mentionedtransformation. These invariant features are then used in Support Vector Machine forclassification. Support Vector Machine is a supervised learning machine that solves problemin higher dimension with the help of Kernel functions and is best know for classificationproblems.

Sustainability & Consumer behavior towards Sustainability in Norway and Sweden

AimSustainability has become an important factor to consider while buying goods and services. People are being more conscious toward environmental impacts of products and services. This attitude has motivated many businesses to develop their production in contact with sustainability. The aim of this paper is to investigate different consumer behaviors toward sustainability in general and in relation to vehicles in Norway and Sweden.ApproachThe project has been embarked by dividing it into two tasks.1. Analyzing past, present and future development, growth and importance of sustainability concept. Describe the role of Government authorities in Norway and Sweden to promote sustainable consumption.2. Investigating important factors of consumer behaviors which influence their buying decision toward sustainable products in general and in relation to sustainable vehicles. Highlight the role of vehicle manufacturing companies to promote sustainable consumption.MethodA research has been conducted in order to explore consumer behavior toward sustainability in Norway and Sweden. Research is based on Document study and primary research which include questionnaire survey with consumers and interviews with vehicle dealers. In addition an expert inquiry is conducted to light up consumer intensions in Norway and Sweden toward sustainability.ResultsThe result of investigation has been revealed in shape of analyses and conclusion at the end. A comparison has been made between primary research and secondary research and findings are overlapping. Sustainable vehicles are being more popular among consumers in Norway and Sweden. Consumption trends are changing over time and environmental friendly attitudes are more developing among Swedish consumers as compared to Norwegian.

Testing common nonlinear features in vector nonlinear autoregressive models

This paper studies a special class of vector smooth-transition autoregressive (VSTAR) models that contains common nonlinear features (CNFs), for which we proposed a triangular representation and developed a procedure of testing CNFs in a VSTAR model. We first test a unit root against a stable STAR process for each individual time series and then examine whether CNFs exist in the system by Lagrange Multiplier (LM) test if unit root is rejected in the first step. The LM test has standard Chi-squared asymptotic distribution. The critical values of our unit root tests and small-sample properties of the F form of our LM test are studied by Monte Carlo simulations. We illustrate how to test and model CNFs using the monthly growth of consumption and income data of United States (1985:1 to 2011:11).

Residual-based Inference for Common Nonlinear Features

This paper investigates common nonlinear features in multivariate nonlinear autore-gressive models via testing the estimated residuals. A Wald-type test is proposed and itis asymptotically Chi-squared distributed. Simulation studies are given to examine thefinite-sample properties of the proposed test.

Factors influencing tourism sustainability : The case of the World Heritage Falun Great Copper Mountain

This thesis focuses on identifying hindrances of achieving a sustainable tourism development on a base of a World Heritage Site. Using a case study of the World Heritage Site Falun Great Copper Mountain, the thesis assesses the situational context by using qualitative methods. Five semi- structured interviews with influential stakeholders were conducted to get an inside view of the current situation and to identify site-specific issues. The thesis identifies a number of factors that determine the successful implementation of measures leading towards sustainable tourism in the long-run; the most important being the lack of clear guidelines for the whole destination and no holistic planning approach within the municipality. The thesis concludes that despite the increased pressures towards establishment of sustainable tourism, the concept remains challenging to operationalize for the World Heritage Site without frameworks and tools from UNESCO.

Common Features in Vector Nonlinear Time Series Models

This thesis consists of four manuscripts in the area of nonlinear time series econometrics on topics of testing, modeling and forecasting nonlinear common features. The aim of this thesis is to develop new econometric contributions for hypothesis testing and forecasting in these area. Both stationary and nonstationary time series are concerned. A definition of common features is proposed in an appropriate way to each class. Based on the definition, a vector nonlinear time series model with common features is set up for testing for common features. The proposed models are available for forecasting as well after being well specified. The first paper addresses a testing procedure on nonstationary time series. A class of nonlinear cointegration, smooth-transition (ST) cointegration, is examined. The ST cointegration nests the previously developed linear and threshold cointegration. An Ftypetest for examining the ST cointegration is derived when stationary transition variables are imposed rather than nonstationary variables. Later ones drive the test standard, while the former ones make the test nonstandard. This has important implications for empirical work. It is crucial to distinguish between the cases with stationary and nonstationary transition variables so that the correct test can be used. The second and the fourth papers develop testing approaches for stationary time series. In particular, the vector ST autoregressive (VSTAR) model is extended to allow for common nonlinear features (CNFs). These two papers propose a modeling procedure and derive tests for the presence of CNFs. Including model specification using the testing contributions above, the third paper considers forecasting with vector nonlinear time series models and extends the procedures available for univariate nonlinear models. The VSTAR model with CNFs and the ST cointegration model in the previous papers are exemplified in detail,and thereafter illustrated within two corresponding macroeconomic data sets.

Sustainability and research integrated in engineering courses at Dalarna University, Sweden

Högskolepedagogik, högskolepedagogisk utbildning, BHU

Benchmark Evaluation of HOG Descriptors as Features for Classification of Traffic Signs

The purpose of this paper is to analyze the performance of the Histograms of Oriented Gradients (HOG) as descriptors for traffic signs recognition. The test dataset consists of speed limit traffic signs because of their high inter-class similarities.   HOG features of speed limit signs, which were extracted from different traffic scenes, were computed and a Gentle AdaBoost classifier was invoked to evaluate the different features. The performance of HOG was tested with a dataset consisting of 1727 Swedish speed signs images. Different numbers of HOG features per descriptor, ranging from 36 features up 396 features, were computed for each traffic sign in the benchmark testing. The results show that HOG features perform high classification rate as the Gentle AdaBoost classification rate was 99.42%, and they are suitable to real time traffic sign recognition. However, it is found that changing the number of orientation bins has insignificant effect on the classification rate. In addition to this, HOG descriptors are not robust with respect to sign orientation.

Professional and Non-Professional Written Travel Texts – Do They Have Common Features? : A Comparative Investigation on Travel Texts on Trysil, Norway

This study aims to investigate possible distinctions between professional and non-professional written travel texts all treating the same destination: the Norwegian ski resort Trysil. The study will investigate to what extent the different texts correlate with the genre of travel texts, as the travel texts are treated as personal narratives, and how they conform to a given structure for narratives and with guidelines for professional writers. Furthermore, the investigation aims to explore to what extent there are similarities and differences between the texts regarding the given structure. The texts will first be analysed and organized separately by macrorules and a news schema that are constructed specifically for these sorts of texts, in order to reveal their discourse structure, and then compared to each other. As the discourse structure of the different texts is revealed, it is seen that there are certain differences between the two different text types. Finally, seen that the text types differ in their structure, this study will show that despite the fact that journalists write stories, and that non-professional written stories are narratives, they do not share the same structure, and are constructed in different ways.

Sustainability in nursing : a concept analysis

Aim. The aim of this study was to describe, explore and explain the concept of sustainability in nursing. Background. Although researchers in nursing and medicine have emphasised the issue of sustainability and health, the concept of sustainability in nursing is undefined and poorly researched. A need exists for theoretical and empirical studies of sustainability in nursing. Design. Concept analysis as developed by Walker and Avant. Method. Data were derived from dictionaries, international healthcare organisations and literature searches in the CINAHL and MEDLINE databases. Inclusive years for the search ranged from 1990 to 2012. A total of fourteen articles were found that referred to sustainability in nursing. Results. Sustainability in nursing involves six defining attributes: ecology, environment, future, globalism, holism and maintenance. Antecedents of sustainability require climate change, environmental impact and awareness, confidence in the future, responsibility and a willingness to change. Consequences of sustainability in nursing include education in the areas of ecology, environment and sustainable development as well as sustainability as a part of nursing academic programs and in the description of the academic subject of nursing. Sustainability should also be part of national and international healthcare organisations. The concept was clarified herein by giving it a definition. Conclusion. Sustainability in nursing was explored and found to contribute to sustainable development, with the ultimate goal of maintaining an environment that does not harm current and future generations' opportunities for good health. This concept analysis provides recommendations for the healthcare sector to incorporate sustainability and provides recommendations for future research.