The performance of interferon-gamma release assays in tuberculosis patients with type II diabetes

The sensitivity of Interferon-γ release assays for detection of Mycobacterium tuberculosis (MTB) infection or disease is affected by conditions that depress host immunity (such as HIV). It is critical to determine whether these assays are affected by diabetes and related conditions (i.e. hyperglycemia, chronic hyperglycemia, or being overweight/obese) given that immune impairment is thought to underline susceptibility to tuberculosis (TB) in people with diabetes. This is important for tuberculosis control due to the millions of type 2 diabetes patients at risk for tuberculosis worldwide.^ The objective of this study was to identify host characteristics, including diabetes, that may affect the sensitivity of two commercially available Interferon-γ (IFN-γ) release assays (IGRA), the QuantiFERON®-TB Gold (QFT-G) and the T-SPOT®.TB in active TB patients. We further explored whether IFN-γ secretion in response to MTB antigens (ESAT-6 and CFP-10) is associated with diabetes and its defining characteristics (high blood glucose, high HbA1c, high BMI). To achieve these objectives, the sensitivity of QFT-G and T-SPOT. TB assays were evaluated in newly diagnosed, tuberculosis confirmed (by positive smear for acid fast bacilli and/or positive culture for MTB) adults enrolled at Texas and Mexico study sites between March 2006 and April 2009. Univariate and multivariate models were constructed to identify host characteristics associated with IGRA result and level of IFN-γ secretion.^ QFT-G was positive in 68% of tuberculosis patients. Those with diabetes, chronic hyperglycemia or obesity were more likely to have a positive QFT-G result, and to secrete higher levels of IFN-γ in response to the mycobacterial antigens (p<0.05). Previous history of BCG vaccination was the only other host characteristic associated with QFT-G result, whereby a higher proportion of non-BCG vaccinated persons were QFT-G positive, in comparison to vaccinated persons. In a separate group of patients, the T-SPOT.TB was 94% sensitive, with similar performance in all tuberculosis patients, regardless of host characteristics.^ In summary, we have demonstrated the validity of QFT-G and T-SPOT. TB to support the diagnosis of TB in patients with a range of host characteristics, but most notably in patients with diabetes. We also confirmed that TB patients with diabetes and associated characteristics (chronic hyperglycemia or BMI) secreted higher titers of IFN-γ when stimulated with MTB specific antigens, in comparison to patients without these characteristics. Together, these findings suggest that the mechanism by which diabetes increases risk to TB may not be explained by the inability to secrete IFN-γ, a key cytokine for TB control.^

The effects of ethnicity and ethnic composition of schools on physical activity and nutrition behaviors of 8th and 11th graders in Texas

With rates of obesity and overweight continuing to increase in the US, the attention of public health researchers has focused on nutrition and physical activity behaviors. However, attempts to explain the disparate rates of obesity and overweight between whites and Hispanics have often proven inadequate. Indeed, the nebulous term ‘ethnicity’ provides little important detail in addressing potential biological, behavioral, and environmental factors that may affect rates of obesity and overweight. In response to this, the present research seeks to test the explanatory powers of ethnicity by situating the nutrition and physical activity behaviors of whites and Hispanic into their broader social contexts. It is hypothesized that a student's gender and grade level, as well as the socioeconomic status and ethnic composition of their school, will have more predictive power for these behaviors than will self-reported ethnicity. ^ Analyses revealed that while ethnicity did not seem to impact nutrition behaviors among the wealthier schools and those with fewer Hispanics, ethnicity was relevant in explaining these behaviors in the poorest tertile of schools and those with the highest number of Hispanics. With respect to physical activity behaviors, the results were mixed. The variables representing regular physical activity, participation in extracurricular physical activities, and performance of strengthening and toning exercises were more likely to be determined by SES and ethnic composition than ethnicity, especially among 8th grade males. However, school sports team and physical education participation continued to vary by ethnicity, even after controlling for SES and ethnic composition of schools. In conclusion then, it is important to understand the intersecting demographic and social variables that define and surround the individual in order to understand nutrition and physical activity behaviors and thus overweight and obesity.^

The CoastColour Round Robin datasets: a database to evaluate the performance of algorithms for the retrieval of water quality parameters in coastal waters

The CoastColour project Round Robin (CCRR) project (http://www.coastcolour.org) funded by the European Space Agency (ESA) was designed to bring together a variety of reference datasets and to use these to test algorithms and assess their accuracy for retrieving water quality parameters. This information was then developed to help end-users of remote sensing products to select the most accurate algorithms for their coastal region. To facilitate this, an inter-comparison of the performance of algorithms for the retrieval of in-water properties over coastal waters was carried out. The comparison used three types of datasets on which ocean colour algorithms were tested. The description and comparison of the three datasets are the focus of this paper, and include the Medium Resolution Imaging Spectrometer (MERIS) Level 2 match-ups, in situ reflectance measurements and data generated by a radiative transfer model (HydroLight). The datasets mainly consisted of 6,484 marine reflectance associated with various geometrical (sensor viewing and solar angles) and sky conditions and water constituents: Total Suspended Matter (TSM) and Chlorophyll-a (CHL) concentrations, and the absorption of Coloured Dissolved Organic Matter (CDOM). Inherent optical properties were also provided in the simulated datasets (5,000 simulations) and from 3,054 match-up locations. The distributions of reflectance at selected MERIS bands and band ratios, CHL and TSM as a function of reflectance, from the three datasets are compared. Match-up and in situ sites where deviations occur are identified. The distribution of the three reflectance datasets are also compared to the simulated and in situ reflectances used previously by the International Ocean Colour Coordinating Group (IOCCG, 2006) for algorithm testing, showing a clear extension of the CCRR data which covers more turbid waters.

Effects of RoHs and REACH regulations on firm-level production and export, and the role of global value chains : the cases of Malaysia and Vietnam

This paper uses firm-level data to examine the impact of foreign chemical safety regulations such as RoHS and REACH on the production costs and export performance of firms in Malaysia and Vietnam. This paper also investigates the role of global value chains in enhancing the likelihood that a firm complies with RoHS and REACH. We find that in addition to the initial setup costs for compliance, EU RoHS (REACH) implementation imposes on firms additional variable production costs by requiring additional labor and capital expenditures of around 57% (73%) of variable costs. We also find that compliance with RoHS and REACH significantly increases the probability of export and that compliance with EU RoHS and REACH helps firms enter a greater variety of countries. Furthermore, firms participating in global value chains have higher compliance with RoHS and REACH regulations, regardless of whether the firm is directly exporting, when the firm operates in upstream or downstream industries of the countries' supply chain.

A Bayesian strategy to enhance the performance of indoor localization systems

This work describes the probabilistic modelling af a Bayesian-based mechanism to improve location estimates of an already deployed location system by fusing its outputs with low-cost binary sensors. This mechanism takes advantege of the localization captabilities of different technologies usually present in smart environments deployments. The performance of the proposed algorithm over a real sensor deployment is evaluated using simulated and real experimental data.

Review of the Performance of Residential PV systems in Belgium

The main objective of this paper is to review the state of the art of residential PV systems in Belgium by the analysis of the operational data of 993 installations. For that, three main questions are posed: how much energy do they produce? What level of performance is associated to their production? Which are the key parameters that most influence their quality? This work brings answers to these questions. A middling commercial PV system, optimally oriented, produces a mean annual energy of 892 kWh/kWp. As a whole, the orientation of PV generators causes energy productions to be some 6% inferior to optimally oriented PV systems. The mean performance ratio is 78% and the mean performance index is 85%. That is to say, the energy produced by a typical PV system in Belgium is 15% inferior to the energy produced by a very high quality PV system. Finally, on average, the real power of the PV modules falls 5% below its corresponding nominal power announced on the manufacturer's datasheet. Differences between real and nominal power of up to 16% have been detected.

Review of the Performance of Residential PV systems in France

The main objective of this paper is to review the state of the art of residential PV systems in France. This is done analyzing the operational data of 6868 installations. Three main questions are posed. How much energy do they produce? What level of performance is associated to their production? Which are the key parameters that most influence their quality? During the year 2010, the PV systems in France have produced a mean annual energy of 1163 kWh/kWp. As a whole, the orientation of PV generators causes energy productions to be some 7% inferior to optimally oriented PV systems. The mean Performance Ratio is 76% and the mean Performance Index is 85%. That is to say, the energy produced by a typical PV system in France is 15% inferior to the energy produced by a very high quality PV system. On average, the real power of the PV modules falls 4.9% below its corresponding nominal power announced on the manufacturer's datasheet. A brief analysis by PV modules technology has led to relevant observations about two technologies in particular. On the one hand, the PV systems equipped with heterojunction with intrinsic thin layer (HIT) modules show performances higher than average. On the other hand, the systems equipped with the copper indium (di)selenide (CIS) modules show a real power that is 16% lower than their nominal value.

An investigation of the performance of a new Mechanical thrombectomy device using Bond Graph modelling: application to the extraction of blood clots in the middle cerebral artery

A number of thrombectomy devices using a variety of methods have now been developed to facilitate clot removal. We present research involving one such experimental device recently developed in the UK, called a ‘GP’ Thrombus Aspiration Device (GPTAD). This device has the potential to bring about the extraction of a thrombus. Although the device is at a relatively early stage of development, the results look encouraging. In this work, we present an analysis and modeling of the GPTAD by means of the bond graph technique; it seems to be a highly effective method of simulating the device under a variety of conditions. Such modeling is useful in optimizing the GPTAD and predicting the result of clot extraction. The aim of this simulation model is to obtain the minimum pressure necessary to extract the clot and to verify that both the pressure and the time required to complete the clot extraction are realistic for use in clinical situations, and are consistent with any experimentally obtained data. We therefore consider aspects of rheology and mechanics in our modeling.

Combining statistical and semantic approaches to the translation of ontologies and taxonomies

Ontologies and taxonomies are widely used to organize concepts providing the basis for activities such as indexing, and as background knowledge for NLP tasks. As such, translation of these resources would prove useful to adapt these systems to new languages. However, we show that the nature of these resources is significantly different from the "free-text" paradigm used to train most statistical machine translation systems. In particular, we see significant differences in the linguistic nature of these resources and such resources have rich additional semantics. We demonstrate that as a result of these linguistic differences, standard SMT methods, in particular evaluation metrics, can produce poor performance. We then look to the task of leveraging these semantics for translation, which we approach in three ways: by adapting the translation system to the domain of the resource; by examining if semantics can help to predict the syntactic structure used in translation; and by evaluating if we can use existing translated taxonomies to disambiguate translations. We present some early results from these experiments, which shed light on the degree of success we may have with each approach

Localization and activity detection Based on the fusion of environment And inertial sensors = Localización y detección de actividad Basadas en integración de sensores y dispositivos inerciales

Los sensores inerciales (acelerómetros y giróscopos) se han ido introduciendo poco a poco en dispositivos que usamos en nuestra vida diaria gracias a su minituarización. Hoy en día todos los smartphones contienen como mínimo un acelerómetro y un magnetómetro, siendo complementados en losmás modernos por giróscopos y barómetros. Esto, unido a la proliferación de los smartphones ha hecho viable el diseño de sistemas basados en las medidas de sensores que el usuario lleva colocados en alguna parte del cuerpo (que en un futuro estarán contenidos en tejidos inteligentes) o los integrados en su móvil. El papel de estos sensores se ha convertido en fundamental para el desarrollo de aplicaciones contextuales y de inteligencia ambiental. Algunos ejemplos son el control de los ejercicios de rehabilitación o la oferta de información referente al sitio turístico que se está visitando. El trabajo de esta tesis contribuye a explorar las posibilidades que ofrecen los sensores inerciales para el apoyo a la detección de actividad y la mejora de la precisión de servicios de localización para peatones. En lo referente al reconocimiento de la actividad que desarrolla un usuario, se ha explorado el uso de los sensores integrados en los dispositivos móviles de última generación (luz y proximidad, acelerómetro, giróscopo y magnetómetro). Las actividades objetivo son conocidas como ‘atómicas’ (andar a distintas velocidades, estar de pie, correr, estar sentado), esto es, actividades que constituyen unidades de actividades más complejas como pueden ser lavar los platos o ir al trabajo. De este modo, se usan algoritmos de clasificación sencillos que puedan ser integrados en un móvil como el Naïve Bayes, Tablas y Árboles de Decisión. Además, se pretende igualmente detectar la posición en la que el usuario lleva el móvil, no sólo con el objetivo de utilizar esa información para elegir un clasificador entrenado sólo con datos recogidos en la posición correspondiente (estrategia que mejora los resultados de estimación de la actividad), sino también para la generación de un evento que puede producir la ejecución de una acción. Finalmente, el trabajo incluye un análisis de las prestaciones de la clasificación variando el tipo de parámetros y el número de sensores usados y teniendo en cuenta no sólo la precisión de la clasificación sino también la carga computacional. Por otra parte, se ha propuesto un algoritmo basado en la cuenta de pasos utilizando informaiii ción proveniente de un acelerómetro colocado en el pie del usuario. El objetivo final es detectar la actividad que el usuario está haciendo junto con la estimación aproximada de la distancia recorrida. El algoritmo de cuenta pasos se basa en la detección de máximos y mínimos usando ventanas temporales y umbrales sin requerir información específica del usuario. El ámbito de seguimiento de peatones en interiores es interesante por la falta de un estándar de localización en este tipo de entornos. Se ha diseñado un filtro extendido de Kalman centralizado y ligeramente acoplado para fusionar la información medida por un acelerómetro colocado en el pie del usuario con medidas de posición. Se han aplicado también diferentes técnicas de corrección de errores como las de velocidad cero que se basan en la detección de los instantes en los que el pie está apoyado en el suelo. Los resultados han sido obtenidos en entornos interiores usando las posiciones estimadas por un sistema de triangulación basado en la medida de la potencia recibida (RSS) y GPS en exteriores. Finalmente, se han implementado algunas aplicaciones que prueban la utilidad del trabajo desarrollado. En primer lugar se ha considerado una aplicación de monitorización de actividad que proporciona al usuario información sobre el nivel de actividad que realiza durante un período de tiempo. El objetivo final es favorecer el cambio de comportamientos sedentarios, consiguiendo hábitos saludables. Se han desarrollado dos versiones de esta aplicación. En el primer caso se ha integrado el algoritmo de cuenta pasos en una plataforma OSGi móvil adquiriendo los datos de un acelerómetro Bluetooth colocado en el pie. En el segundo caso se ha creado la misma aplicación utilizando las implementaciones de los clasificadores en un dispositivo Android. Por otro lado, se ha planteado el diseño de una aplicación para la creación automática de un diario de viaje a partir de la detección de eventos importantes. Esta aplicación toma como entrada la información procedente de la estimación de actividad y de localización además de información almacenada en bases de datos abiertas (fotos, información sobre sitios) e información sobre sensores reales y virtuales (agenda, cámara, etc.) del móvil. Abstract Inertial sensors (accelerometers and gyroscopes) have been gradually embedded in the devices that people use in their daily lives thanks to their miniaturization. Nowadays all smartphones have at least one embedded magnetometer and accelerometer, containing the most upto- date ones gyroscopes and barometers. This issue, together with the fact that the penetration of smartphones is growing steadily, has made possible the design of systems that rely on the information gathered by wearable sensors (in the future contained in smart textiles) or inertial sensors embedded in a smartphone. The role of these sensors has become key to the development of context-aware and ambient intelligent applications. Some examples are the performance of rehabilitation exercises, the provision of information related to the place that the user is visiting or the interaction with objects by gesture recognition. The work of this thesis contributes to explore to which extent this kind of sensors can be useful to support activity recognition and pedestrian tracking, which have been proven to be essential for these applications. Regarding the recognition of the activity that a user performs, the use of sensors embedded in a smartphone (proximity and light sensors, gyroscopes, magnetometers and accelerometers) has been explored. The activities that are detected belong to the group of the ones known as ‘atomic’ activities (e.g. walking at different paces, running, standing), that is, activities or movements that are part of more complex activities such as doing the dishes or commuting. Simple, wellknown classifiers that can run embedded in a smartphone have been tested, such as Naïve Bayes, Decision Tables and Trees. In addition to this, another aim is to estimate the on-body position in which the user is carrying the mobile phone. The objective is not only to choose a classifier that has been trained with the corresponding data in order to enhance the classification but also to start actions. Finally, the performance of the different classifiers is analysed, taking into consideration different features and number of sensors. The computational and memory load of the classifiers is also measured. On the other hand, an algorithm based on step counting has been proposed. The acceleration information is provided by an accelerometer placed on the foot. The aim is to detect the activity that the user is performing together with the estimation of the distance covered. The step counting strategy is based on detecting minima and its corresponding maxima. Although the counting strategy is not innovative (it includes time windows and amplitude thresholds to prevent under or overestimation) no user-specific information is required. The field of pedestrian tracking is crucial due to the lack of a localization standard for this kind of environments. A loosely-coupled centralized Extended Kalman Filter has been proposed to perform the fusion of inertial and position measurements. Zero velocity updates have been applied whenever the foot is detected to be placed on the ground. The results have been obtained in indoor environments using a triangulation algorithm based on RSS measurements and GPS outdoors. Finally, some applications have been designed to test the usefulness of the work. The first one is called the ‘Activity Monitor’ whose aim is to prevent sedentary behaviours and to modify habits to achieve desired objectives of activity level. Two different versions of the application have been implemented. The first one uses the activity estimation based on the step counting algorithm, which has been integrated in an OSGi mobile framework acquiring the data from a Bluetooth accelerometer placed on the foot of the individual. The second one uses activity classifiers embedded in an Android smartphone. On the other hand, the design of a ‘Travel Logbook’ has been planned. The input of this application is the information provided by the activity and localization modules, external databases (e.g. pictures, points of interest, weather) and mobile embedded and virtual sensors (agenda, camera, etc.). The aim is to detect important events in the journey and gather the information necessary to store it as a journal page.

Riding out of the storm: How to deal with the complexity of grid and cloud management

Over the last decade, Grid computing paved the way for a new level of large scale distributed systems. This infrastructure made it possible to securely and reliably take advantage of widely separated computational resources that are part of several different organizations. Resources can be incorporated to the Grid, building a theoretical virtual supercomputer. In time, cloud computing emerged as a new type of large scale distributed system, inheriting and expanding the expertise and knowledge that have been obtained so far. Some of the main characteristics of Grids naturally evolved into clouds, others were modified and adapted and others were simply discarded or postponed. Regardless of these technical specifics, both Grids and clouds together can be considered as one of the most important advances in large scale distributed computing of the past ten years; however, this step in distributed computing has came along with a completely new level of complexity. Grid and cloud management mechanisms play a key role, and correct analysis and understanding of the system behavior are needed. Large scale distributed systems must be able to self-manage, incorporating autonomic features capable of controlling and optimizing all resources and services. Traditional distributed computing management mechanisms analyze each resource separately and adjust specific parameters of each one of them. When trying to adapt the same procedures to Grid and cloud computing, the vast complexity of these systems can make this task extremely complicated. But large scale distributed systems complexity could only be a matter of perspective. It could be possible to understand the Grid or cloud behavior as a single entity, instead of a set of resources. This abstraction could provide a different understanding of the system, describing large scale behavior and global events that probably would not be detected analyzing each resource separately. In this work we define a theoretical framework that combines both ideas, multiple resources and single entity, to develop large scale distributed systems management techniques aimed at system performance optimization, increased dependability and Quality of Service (QoS). The resulting synergy could be the key 350 J. Montes et al. to address the most important difficulties of Grid and cloud management.

Ballistic performance of nanocrystalline and nanotwinned ultrafine crystal steel

Because of their remarkable mechanical properties, nanocrystalline metals have been the focus of much research in recent years. Refining their grain size to the nanometer range (<100 nm) effectively reduces their dislocation mobility, thus achieving very high yield strength and surface hardness—as predicted by the Hall–Petch relation—as well as higher strain-rate sensitivity. Recent works have additionally suggested that nanocrystalline metals exhibit an even higher compressive strength under shock loading. However, the increase in strength of these materials is generally accompanied by an important reduction in ductility. As an alternative, efforts have been focused on ultrafine crystals, i.e. polycrystals with a grain size in the range of 500 nm to 1 μm, in which “growth twins” (twins introduced inside the grain before deformation) act as barriers against dislocation movement, thus increasing the strength in a similar way as nanocrystals but without significant loss of ductility. Due to their outstanding mechanical properties, both nanocrystalline and nanotwinned ultrafine crystalline steels appear to be relevant candidates for ballistic protection. The aim of the present work is to compare their ballistic performance against coarse-grained steel, as well as to identify the effect of the hybridization with a carbon fiber–epoxy composite layer. Hybridization is proposed as a way to improve the nanocrystalline brittle properties in a similar way as is done with ceramics in other protection systems. The experimental campaign is finally complemented by numerical simulations to help identify some of the intrinsic deformation mechanisms not observable experimentally. As a conclusion, nanocrystalline and nanotwinned ultrafine crystals show a lower energy absorption than coarse-grained steel under ballistic loading, but under equal impact conditions with no penetration, deformation in the impact direction is smaller by nearly 40%. This a priori surprising difference in the energy absorption is rationalized by the more important local contribution of the deviatoric stress vs. volumetric stress under impact than under uniaxial deformation. Ultimately, the deformation advantage could be exploited in the future for personal protection systems where a small deformation under impact is of key importance.

Citizens Interactive Behaviour in the Performance of the Urban Space of Cohabitacion. Interactive Atlas of Urban Habitability

The article shows a range of contemporary phenomena linked with urban space and the increasing citizens? interactivity in the network. The sources for theory and reflection are related to the ongoing research project ?Interactive Atlas of urban habitability" which is based on citizen participation in the sensitive description of the urban environment. It addresses a classification of variables related to the desires of urban habitability.

Effect of concentration on the performance of quantum dot intermediate-band solar cells

Implementation of a high-efficiency quantum dot intermediate-band solar cell (QD-IBSC) must accompany a sufficient photocurrent generation via IB states. The demonstration of a QD-IBSC is presently undergoing two stages. The first is to develop a technology to fabricate high-density QD stacks or a superlattice of low defect density placed within the active region of a p-i-n SC, and the second is to realize half-filled IB states to maximize the photocurrent generation by two-step absorption of sub-bandgap photons. For this, we have investigated the effect of light concentration on the characteristics of QDSCs comprised of multi-layer stacks of self-organized InAs/GaNAs QDs grown with and without impurity doping in molecular beam epitaxy.

Using a causal smoothing to improve the performance of an on-line neural network glucose prediction algorithm

This work evaluates a spline-based smoothing method applied to the output of a glucose predictor. Methods:Our on-line prediction algorithm is based on a neural network model (NNM). We trained/validated the NNM with a prediction horizon of 30 minutes using 39/54 profiles of patients monitored with the Guardian® Real-Time continuous glucose monitoring system The NNM output is smoothed by fitting a causal cubic spline. The assessment parameters are the error (RMSE), mean delay (MD) and the high-frequency noise (HFCrms). The HFCrms is the root-mean-square values of the high-frequency components isolated with a zero-delay non-causal filter. HFCrms is 2.90±1.37 (mg/dl) for the original profiles.