Rapid bacterial genome sequencing: methods and applications in clinical microbiology.

The recent advances in sequencing technologies have given all microbiology laboratories access to whole genome sequencing. Providing that tools for the automated analysis of sequence data and databases for associated meta-data are developed, whole genome sequencing will become a routine tool for large clinical microbiology laboratories. Indeed, the continuing reduction in sequencing costs and the shortening of the 'time to result' makes it an attractive strategy in both research and diagnostics. Here, we review how high-throughput sequencing is revolutionizing clinical microbiology and the promise that it still holds. We discuss major applications, which include: (i) identification of target DNA sequences and antigens to rapidly develop diagnostic tools; (ii) precise strain identification for epidemiological typing and pathogen monitoring during outbreaks; and (iii) investigation of strain properties, such as the presence of antibiotic resistance or virulence factors. In addition, recent developments in comparative metagenomics and single-cell sequencing offer the prospect of a better understanding of complex microbial communities at the global and individual levels, providing a new perspective for understanding host-pathogen interactions. Being a high-resolution tool, high-throughput sequencing will increasingly influence diagnostics, epidemiology, risk management, and patient care.

Factor models, VARMA processes and parameter instability with applications in macroeconomics

Avec les avancements de la technologie de l'information, les données temporelles économiques et financières sont de plus en plus disponibles. Par contre, si les techniques standard de l'analyse des séries temporelles sont utilisées, une grande quantité d'information est accompagnée du problème de dimensionnalité. Puisque la majorité des séries d'intérêt sont hautement corrélées, leur dimension peut être réduite en utilisant l'analyse factorielle. Cette technique est de plus en plus populaire en sciences économiques depuis les années 90. Étant donnée la disponibilité des données et des avancements computationnels, plusieurs nouvelles questions se posent. Quels sont les effets et la transmission des chocs structurels dans un environnement riche en données? Est-ce que l'information contenue dans un grand ensemble d'indicateurs économiques peut aider à mieux identifier les chocs de politique monétaire, à l'égard des problèmes rencontrés dans les applications utilisant des modèles standards? Peut-on identifier les chocs financiers et mesurer leurs effets sur l'économie réelle? Peut-on améliorer la méthode factorielle existante et y incorporer une autre technique de réduction de dimension comme l'analyse VARMA? Est-ce que cela produit de meilleures prévisions des grands agrégats macroéconomiques et aide au niveau de l'analyse par fonctions de réponse impulsionnelles? Finalement, est-ce qu'on peut appliquer l'analyse factorielle au niveau des paramètres aléatoires? Par exemple, est-ce qu'il existe seulement un petit nombre de sources de l'instabilité temporelle des coefficients dans les modèles macroéconomiques empiriques? Ma thèse, en utilisant l'analyse factorielle structurelle et la modélisation VARMA, répond à ces questions à travers cinq articles. Les deux premiers chapitres étudient les effets des chocs monétaire et financier dans un environnement riche en données. Le troisième article propose une nouvelle méthode en combinant les modèles à facteurs et VARMA. Cette approche est appliquée dans le quatrième article pour mesurer les effets des chocs de crédit au Canada. La contribution du dernier chapitre est d'imposer la structure à facteurs sur les paramètres variant dans le temps et de montrer qu'il existe un petit nombre de sources de cette instabilité. Le premier article analyse la transmission de la politique monétaire au Canada en utilisant le modèle vectoriel autorégressif augmenté par facteurs (FAVAR). Les études antérieures basées sur les modèles VAR ont trouvé plusieurs anomalies empiriques suite à un choc de la politique monétaire. Nous estimons le modèle FAVAR en utilisant un grand nombre de séries macroéconomiques mensuelles et trimestrielles. Nous trouvons que l'information contenue dans les facteurs est importante pour bien identifier la transmission de la politique monétaire et elle aide à corriger les anomalies empiriques standards. Finalement, le cadre d'analyse FAVAR permet d'obtenir les fonctions de réponse impulsionnelles pour tous les indicateurs dans l'ensemble de données, produisant ainsi l'analyse la plus complète à ce jour des effets de la politique monétaire au Canada. Motivée par la dernière crise économique, la recherche sur le rôle du secteur financier a repris de l'importance. Dans le deuxième article nous examinons les effets et la propagation des chocs de crédit sur l'économie réelle en utilisant un grand ensemble d'indicateurs économiques et financiers dans le cadre d'un modèle à facteurs structurel. Nous trouvons qu'un choc de crédit augmente immédiatement les diffusions de crédit (credit spreads), diminue la valeur des bons de Trésor et cause une récession. Ces chocs ont un effet important sur des mesures d'activité réelle, indices de prix, indicateurs avancés et financiers. Contrairement aux autres études, notre procédure d'identification du choc structurel ne requiert pas de restrictions temporelles entre facteurs financiers et macroéconomiques. De plus, elle donne une interprétation des facteurs sans restreindre l'estimation de ceux-ci. Dans le troisième article nous étudions la relation entre les représentations VARMA et factorielle des processus vectoriels stochastiques, et proposons une nouvelle classe de modèles VARMA augmentés par facteurs (FAVARMA). Notre point de départ est de constater qu'en général les séries multivariées et facteurs associés ne peuvent simultanément suivre un processus VAR d'ordre fini. Nous montrons que le processus dynamique des facteurs, extraits comme combinaison linéaire des variables observées, est en général un VARMA et non pas un VAR comme c'est supposé ailleurs dans la littérature. Deuxièmement, nous montrons que même si les facteurs suivent un VAR d'ordre fini, cela implique une représentation VARMA pour les séries observées. Alors, nous proposons le cadre d'analyse FAVARMA combinant ces deux méthodes de réduction du nombre de paramètres. Le modèle est appliqué dans deux exercices de prévision en utilisant des données américaines et canadiennes de Boivin, Giannoni et Stevanovic (2010, 2009) respectivement. Les résultats montrent que la partie VARMA aide à mieux prévoir les importants agrégats macroéconomiques relativement aux modèles standards. Finalement, nous estimons les effets de choc monétaire en utilisant les données et le schéma d'identification de Bernanke, Boivin et Eliasz (2005). Notre modèle FAVARMA(2,1) avec six facteurs donne les résultats cohérents et précis des effets et de la transmission monétaire aux États-Unis. Contrairement au modèle FAVAR employé dans l'étude ultérieure où 510 coefficients VAR devaient être estimés, nous produisons les résultats semblables avec seulement 84 paramètres du processus dynamique des facteurs. L'objectif du quatrième article est d'identifier et mesurer les effets des chocs de crédit au Canada dans un environnement riche en données et en utilisant le modèle FAVARMA structurel. Dans le cadre théorique de l'accélérateur financier développé par Bernanke, Gertler et Gilchrist (1999), nous approximons la prime de financement extérieur par les credit spreads. D'un côté, nous trouvons qu'une augmentation non-anticipée de la prime de financement extérieur aux États-Unis génère une récession significative et persistante au Canada, accompagnée d'une hausse immédiate des credit spreads et taux d'intérêt canadiens. La composante commune semble capturer les dimensions importantes des fluctuations cycliques de l'économie canadienne. L'analyse par décomposition de la variance révèle que ce choc de crédit a un effet important sur différents secteurs d'activité réelle, indices de prix, indicateurs avancés et credit spreads. De l'autre côté, une hausse inattendue de la prime canadienne de financement extérieur ne cause pas d'effet significatif au Canada. Nous montrons que les effets des chocs de crédit au Canada sont essentiellement causés par les conditions globales, approximées ici par le marché américain. Finalement, étant donnée la procédure d'identification des chocs structurels, nous trouvons des facteurs interprétables économiquement. Le comportement des agents et de l'environnement économiques peut varier à travers le temps (ex. changements de stratégies de la politique monétaire, volatilité de chocs) induisant de l'instabilité des paramètres dans les modèles en forme réduite. Les modèles à paramètres variant dans le temps (TVP) standards supposent traditionnellement les processus stochastiques indépendants pour tous les TVPs. Dans cet article nous montrons que le nombre de sources de variabilité temporelle des coefficients est probablement très petit, et nous produisons la première évidence empirique connue dans les modèles macroéconomiques empiriques. L'approche Factor-TVP, proposée dans Stevanovic (2010), est appliquée dans le cadre d'un modèle VAR standard avec coefficients aléatoires (TVP-VAR). Nous trouvons qu'un seul facteur explique la majorité de la variabilité des coefficients VAR, tandis que les paramètres de la volatilité des chocs varient d'une façon indépendante. Le facteur commun est positivement corrélé avec le taux de chômage. La même analyse est faite avec les données incluant la récente crise financière. La procédure suggère maintenant deux facteurs et le comportement des coefficients présente un changement important depuis 2007. Finalement, la méthode est appliquée à un modèle TVP-FAVAR. Nous trouvons que seulement 5 facteurs dynamiques gouvernent l'instabilité temporelle dans presque 700 coefficients.

Integrating socio-economics and ecology: a taxonomy of quantitative methods and a review of their use in agro-ecology

Answering many of the critical questions in conservation, development and environmental management requires integrating the social and natural sciences. However, understanding the array of available quantitative methods and their associated terminology presents a major barrier to successful collaboration. We provide an overview of quantitative socio-economic methods that distils their complexity into a simple taxonomy. We outline how each has been used in conjunction with ecological models to address questions relating to the management of socio-ecological systems. We review the application of social and ecological quantitative concepts to agro-ecology and classify the approaches used to integrate the two disciplines. Our review included all published integrated models from 2003 to 2008 in 27 journals that publish agricultural modelling research. Although our focus is on agro-ecology, many of the results are broadly applicable to other fields involving an interaction between human activities and ecology. We found 36 papers that integrated social and ecological concepts in a quantitative model. Four different approaches to integration were used, depending on the scale at which human welfare was quantified. Most models viewed humans as pure profit maximizers, both when calculating welfare and predicting behaviour. Synthesis and applications. We reached two main conclusions based on our taxonomy and review. The first is that quantitative methods that extend predictions of behaviour and measurements of welfare beyond a simple market value basis are underutilized by integrated models. The second is that the accuracy of prediction for integrated models remains largely unquantified. Addressing both problems requires researchers to reach a common understanding of modelling goals and data requirements during the early stages of a project.

NaOH and KOH for preparing activated carbons used in energy and environmental applications

Alkaline hydroxides, especially sodium and potassium hydroxides, are multi-million-ton per annum commodities and strong chemical bases that have large scale applications. Some of them are related with their consequent ability to degrade most materials, depending on the temperature used. As an example, these chemicals are involved in the manufacture of pulp and paper, textiles, biodiesels, soaps and detergents, acid gases removal (e.g., SO2) and others, as well as in many organic synthesis processes. Sodium and potassium hydroxides are strong and corrosive bases, but they are also very stable chemicals that can melt without decomposition, NaOH at 318ºC, and KOH at 360ºC. Hence, they can react with most materials, even with relatively inert ones such as carbon materials. Thus, at temperatures higher than 360ºC these melted hydroxides easily react with most types of carbon-containing raw materials (coals, lignocellulosic materials, pitches, etc.), as well as with most pure carbon materials (carbon fibers, carbon nanofibers and carbon nanotubes). This reaction occurs via a solid-liquid redox reaction in which both hydroxides (NaOH or KOH) are converted to the following main products: hydrogen, alkaline metals and alkaline carbonates, as a result of the carbon precursor oxidation. By controlling this reaction, and after a suitable washing process, good quality activated carbons (ACs), a classical type of porous materials, can be prepared. Such carbon activation by hydroxides, known since long time ago, continues to be under research due to the unique properties of the resulting activated carbons. They have promising high porosity developments and interesting pore size distributions. These two properties are important for new applications such as gas storage (e.g., natural gas or hydrogen), capture, storage and transport of carbon dioxide, electricity storage demands (EDLC-supercapacitors-) or pollution control. Because these applications require new and superior quality activated carbons, there is no doubt that among the different existing activating processes, the one based on the chemical reaction between the carbon precursor and the alkaline hydroxide (NaOH or KOH) gives the best activation results. The present article covers different aspects of the activation by hydroxides, including the characteristics of the resulting activated carbons and their performance in some environment-related applications. The following topics are discussed: i) variables of the preparation method, such as the nature of the hydroxide, the type of carbon precursor, the hydroxide/carbon precursor ratio, the mixing procedure of carbon precursor and hydroxide (impregnation of the precursor with a hydroxide solution or mixing both, hydroxide and carbon precursor, as solids), or the temperature and time of the reaction are discussed, analyzing their effect on the resulting porosity; ii) analysis of the main reactions occurring during the activation process, iii) comparative analysis of the porosity development obtained from different activation processes (e.g., CO2, steam, phosphoric acid and hydroxides activation); and iv) performance of the prepared activated carbon materials on a few applications, such as VOC removal, electricity and gas storages.

Zero-non-zero patterned vector error correction modeling for I(2) cointegrated time series with applications in testing PPP and stock market relationships

Vector error-correction models (VECMs) have become increasingly important in their application to financial markets. Standard full-order VECM models assume non-zero entries in all their coefficient matrices. However, applications of VECM models to financial market data have revealed that zero entries are often a necessary part of efficient modelling. In such cases, the use of full-order VECM models may lead to incorrect inferences. Specifically, if indirect causality or Granger non-causality exists among the variables, the use of over-parameterised full-order VECM models may weaken the power of statistical inference. In this paper, it is argued that the zero–non-zero (ZNZ) patterned VECM is a more straightforward and effective means of testing for both indirect causality and Granger non-causality. For a ZNZ patterned VECM framework for time series of integrated order two, we provide a new algorithm to select cointegrating and loading vectors that can contain zero entries. Two case studies are used to demonstrate the usefulness of the algorithm in tests of purchasing power parity and a three-variable system involving the stock market.

RFID in the warehouse:a literature analysis (1995-2010) of its applications, benefits, challenges and future trends

Radio Frequency Identification (RFID) has been identified as a crucial technology for the modern 21st century knowledge-based economy. Some businesses have realised benefits of RFID adoption through improvements in operational efficiency, additional cost savings, and opportunities for higher revenues. RFID research in warehousing operations has been less prominent than in other application domains. To investigate how RFID technology has had an impact in warehousing, a comprehensive analysis of research findings available from articles through leading scientific article databases has been conducted. Articles from years 1995 to 2010 have been reviewed and analysed with respect to warehouse operations, RFID application domains, benefits achieved and obstacles encountered. Four discussion topics are presented covering RFID in warehousing focusing on its applications, perceived benefits, obstacles to its adoption and future trends. This is aimed at elucidating the current state of RFID in the warehouse and providing insights for researchers to establish new research agendas and for practitioners to consider and assess the adoption of RFID in warehousing functions. © 2013 Elsevier B.V.

It's all very well, in theory: Theoretical perspectives and their applications in contemporary pedagogical research

Current debates about educational theory are concerned with the relationship between knowledge and power and thereby issues such as who possesses a truth and how have they arrived at it, what questions are important to ask, and how should they best be answered. As such, these debates revolve around questions of preferred, appropriate, and useful theoretical perspectives. This paper overviews the key theoretical perspectives that are currently used in physical education pedagogy research and considers how these inform the questions we ask and shapes the conduct of research. It also addresses what is contested with respect to these perspectives. The paper concludes with some cautions about allegiances to and use of theories in line with concerns for the applicability of educational research to pressing social issues.

EEG-based Brain-Computer Interfaces: An Overview of Basic Concepts and Clinical Applications in Neurorehabilitation

Some patients are no longer able to communicate effectively or even interact with the outside world in ways that most of us take for granted. In the most severe cases, tetraplegic or post-stroke patients are literally `locked in` their bodies, unable to exert any motor control after, for example, a spinal cord injury or a brainstem stroke, requiring alternative methods of communication and control. But we suggest that, in the near future, their brains may offer them a way out. Non-invasive electroencephalogram (EEG)-based brain-computer interfaces (BCD can be characterized by the technique used to measure brain activity and by the way that different brain signals are translated into commands that control an effector (e.g., controlling a computer cursor for word processing and accessing the internet). This review focuses on the basic concepts of EEG-based BC!, the main advances in communication, motor control restoration and the down-regulation of cortical activity, and the mirror neuron system (MNS) in the context of BCI. The latter appears to be relevant for clinical applications in the coming years, particularly for severely limited patients. Hypothetically, MNS could provide a robust way to map neural activity to behavior, representing the high-level information about goals and intentions of these patients. Non-invasive EEG-based BCIs allow brain-derived communication in patients with amyotrophic lateral sclerosis and motor control restoration in patients after spinal cord injury and stroke. Epilepsy and attention deficit and hyperactive disorder patients were able to down-regulate their cortical activity. Given the rapid progression of EEG-based BCI research over the last few years and the swift ascent of computer processing speeds and signal analysis techniques, we suggest that emerging ideas (e.g., MNS in the context of BC!) related to clinical neuro-rehabilitation of severely limited patients will generate viable clinical applications in the near future.

Protein crystallography and examples of its applications in medicinal chemistry

The field of protein crystallography inspires and enthrals, whether it be for the beauty and symmetry of a perfectly formed protein crystal, the unlocked secrets of a novel protein fold, or the precise atomic-level detail yielded from a protein-ligand complex. Since 1958, when the first protein structure was solved, there have been tremendous advances in all aspects of protein crystallography, from protein preparation and crystallisation through to diffraction data measurement and structure refinement. These advances have significantly reduced the time required to solve protein crystal structures, while at the same time substantially improving the quality and resolution of the resulting structures. Moreover, the technological developments have induced researchers to tackle ever more complex systems, including ribosomes and intact membrane-bound proteins, with a reasonable expectation of success. In this review, the steps involved in determining a protein crystal structure are described and the impact of recent methodological advances identified. Protein crystal structures have proved to be extraordinarily useful in medicinal chemistry research, particularly with respect to inhibitor design. The precise interaction between a drug and its receptor can be visualised at the molecular level using protein crystal structures, and this information then used to improve the complementarity and thus increase the potency and selectivity of an inhibitor. The use of protein crystal structures in receptor-based drug design is highlighted by (i) HIV protease, (ii) influenza virus neuraminidase and (iii) prostaglandin H-2-synthetase. These represent, respectively, examples of protein crystal structures that (i) influenced the design of drugs currently approved for use in the treatment of HIV infection, (ii) led to the design of compounds currently in clinical trials for the treatment of influenza infection and (iii) could enable the design of highly specific non-steroidal anti-inflammatory drugs that lack the common side-effects of this drug class.

Comparative epidemiology of chronic fatigue syndrome in Brazilian and British primary care: prevalence and recognition

Background Although fatigue is a ubiquitous symptom across countries, clinical descriptions of chronic fatigue syndrome have arisen from a limited number of high-income countries. This might reflect differences in true prevalence or clinical recognition influenced by sociocultural factors. Aims To compare the prevalence, physician recognition and diagnosis of chronic fatigue syndrome in London and Sao Paulo. Method Primary care patients in London (n=2459) and Sao Paulo n=3914) were surveyed for the prevalence of chronic fatigue syndrome. Medical records were reviewed for the physician recognition and diagnosis. Results The prevalence of chronic fatigue syndrome according to Centers for Disease Control 1994 criteria was comparable in Britain and Brazil, 2.1% v. 1.6% (P=0.20). Medical records review identified 11 diagnosed cases of chronic fatigue syndrome in Britain, but none in Brazil (P<0.001). Conclusions The primary care prevalence of chronic fatigue syndrome was similar in two Culturally and economically distinct nations. However, doctors are unlikely to recognise and label chronic fatigue syndrome as a discrete disorder in Brazil. The recognition of this illness rather than the illness itself may be culturally induced.