Different approaches to grounding resistance. Calculation for thin wire structures at low frequency energization

The present paper deals with the calculation of grounding resistance of an electrode composed of thin wires, that we consider here as perfect electric conductors (PEC) e.g. with null internal resistance, when buried in a soil of uniform resistivity. The potential profile at the ground surface is also calculated when the electrode is energized with low frequency current. The classic treatment by using leakage currents, called Charge Simulated Method (CSM), is compared with that using a set of steady currents along the axis of the wires, here called the Longitudinal Currents Method (LCM), to solve the Maxwell equations. The method of moments is applied to obtain a numerical approximation of the solution by using rectangular basis functions. Both methods are applied to two types of electrodes and the results are also compared with those obtained using a thirth approach, the Average Potential Method (APM), later described in the text. From the analysis performed, we can estimate a value of the error in the determination of grounding resistance as a function of the number of segments in which the electrodes are divided.

The impact of institutional environment and cultural context in the four different approaches to social enterprise

This article analyzes the characteristics of four different social enterprise schools of though (social economy, earned-income school in developed countries, earned-income in emerging countries, and social innovation) and the influence of the contextual elements (cultural, political, economic and social) on their configuration. This article draws on the qualitative discussions of social enterprise in different regions of the world. This paper is intended to contribute to the field of social enterprise by broadening the understanding of the influence of environment and institutions on the emergence of social enterprise.

Proposal of a trust and reputation model to provide recommendation in open quality oriented environments

El auge y penetración de las nuevas tecnologías junto con la llamada Web Social están cambiando la forma en la que accedemos a la medicina. Cada vez más pacientes y profesionales de la medicina están creando y consumiendo recursos digitales de contenido clínico a través de Internet, surgiendo el problema de cómo asegurar la fiabilidad de estos recursos. Además, un nuevo concepto está apareciendo, el de pervasive healthcare o sanidad ubicua, motivado por pacientes que demandan un acceso a los servicios sanitarios en todo momento y en todo lugar. Este nuevo escenario lleva aparejado un problema de confianza en los proveedores de servicios sanitarios. Las plataformas de eLearning se están erigiendo como paradigma de esta nueva Medicina 2.0 ya que proveen un servicio abierto a la vez que controlado/supervisado a recursos digitales, y facilitan las interacciones y consultas entre usuarios, suponiendo una buena aproximación para esta sanidad ubicua. En estos entornos los problemas de fiabilidad y confianza pueden ser solventados mediante la implementación de mecanismos de recomendación de recursos y personas de manera confiable. Tradicionalmente las plataformas de eLearning ya cuentan con mecanismos de recomendación, si bien están más enfocados a la recomendación de recursos. Para la recomendación de usuarios es necesario acudir a mecanismos más elaborados como son los sistemas de confianza y reputación (trust and reputation) En ambos casos, tanto la recomendación de recursos como el cálculo de la reputación de los usuarios se realiza teniendo en cuenta criterios principalmente subjetivos como son las opiniones de los usuarios. En esta tesis doctoral proponemos un nuevo modelo de confianza y reputación que combina evaluaciones automáticas de los recursos digitales en una plataforma de eLearning, con las opiniones vertidas por los usuarios como resultado de las interacciones con otros usuarios o después de consumir un recurso. El enfoque seguido presenta la novedad de la combinación de una parte objetiva con otra subjetiva, persiguiendo mitigar el efecto de posibles castigos subjetivos por parte de usuarios malintencionados, a la vez que enriquecer las evaluaciones objetivas con información adicional acerca de la capacidad pedagógica del recurso o de la persona. El resultado son recomendaciones siempre adaptadas a los requisitos de los usuarios, y de la máxima calidad tanto técnica como educativa. Esta nueva aproximación requiere una nueva herramienta para su validación in-silico, al no existir ninguna aplicación que permita la simulación de plataformas de eLearning con mecanismos de recomendación de recursos y personas, donde además los recursos sean evaluados objetivamente. Este trabajo de investigación propone pues una nueva herramienta, basada en el paradigma de programación orientada a agentes inteligentes para el modelado de comportamientos complejos de usuarios en plataformas de eLearning. Además, la herramienta permite también la simulación del funcionamiento de este tipo de entornos dedicados al intercambio de conocimiento. La evaluación del trabajo propuesto en este documento de tesis se ha realizado de manera iterativa a lo largo de diferentes escenarios en los que se ha situado al sistema frente a una amplia gama de comportamientos de usuarios. Se ha comparado el rendimiento del modelo de confianza y reputación propuesto frente a dos modos de recomendación tradicionales: a) utilizando sólo las opiniones subjetivas de los usuarios para el cálculo de la reputación y por extensión la recomendación; y b) teniendo en cuenta sólo la calidad objetiva del recurso sin hacer ningún cálculo de reputación. Los resultados obtenidos nos permiten afirmar que el modelo desarrollado mejora la recomendación ofrecida por las aproximaciones tradicionales, mostrando una mayor flexibilidad y capacidad de adaptación a diferentes situaciones. Además, el modelo propuesto es capaz de asegurar la recomendación de nuevos usuarios entrando al sistema frente a la nula recomendación para estos usuarios presentada por el modo de recomendación predominante en otras plataformas que basan la recomendación sólo en las opiniones de otros usuarios. Por último, el paradigma de agentes inteligentes ha probado su valía a la hora de modelar plataformas virtuales complejas orientadas al intercambio de conocimiento, especialmente a la hora de modelar y simular el comportamiento de los usuarios de estos entornos. La herramienta de simulación desarrollada ha permitido la evaluación del modelo de confianza y reputación propuesto en esta tesis en una amplia gama de situaciones diferentes. ABSTRACT Internet is changing everything, and this revolution is especially present in traditionally offline spaces such as medicine. In recent years health consumers and health service providers are actively creating and consuming Web contents stimulated by the emergence of the Social Web. Reliability stands out as the main concern when accessing the overwhelming amount of information available online. Along with this new way of accessing the medicine, new concepts like ubiquitous or pervasive healthcare are appearing. Trustworthiness assessment is gaining relevance: open health provisioning systems require mechanisms that help evaluating individuals’ reputation in pursuit of introducing safety to these open and dynamic environments. Technical Enhanced Learning (TEL) -commonly known as eLearning- platforms arise as a paradigm of this Medicine 2.0. They provide an open while controlled/supervised access to resources generated and shared by users, enhancing what it is being called informal learning. TEL systems also facilitate direct interactions amongst users for consultation, resulting in a good approach to ubiquitous healthcare. The aforementioned reliability and trustworthiness problems can be faced by the implementation of mechanisms for the trusted recommendation of both resources and healthcare services providers. Traditionally, eLearning platforms already integrate recommendation mechanisms, although this recommendations are basically focused on providing an ordered classifications of resources. For users’ recommendation, the implementation of trust and reputation systems appears as the best solution. Nevertheless, both approaches base the recommendation on the information from the subjective opinions of other users of the platform regarding the resources or the users. In this PhD work a novel approach is presented for the recommendation of both resources and users within open environments focused on knowledge exchange, as it is the case of TEL systems for ubiquitous healthcare. The proposed solution adds the objective evaluation of the resources to the traditional subjective personal opinions to estimate the reputation of the resources and of the users of the system. This combined measure, along with the reliability of that calculation, is used to provide trusted recommendations. The integration of opinions and evaluations, subjective and objective, allows the model to defend itself against misbehaviours. Furthermore, it also allows ‘colouring’ cold evaluation values by providing additional quality information such as the educational capacities of a digital resource in an eLearning system. As a result, the recommendations are always adapted to user requirements, and of the maximum technical and educational quality. To our knowledge, the combination of objective assessments and subjective opinions to provide recommendation has not been considered before in the literature. Therefore, for the evaluation of the trust and reputation model defined in this PhD thesis, a new simulation tool will be developed following the agent-oriented programming paradigm. The multi-agent approach allows an easy modelling of independent and proactive behaviours for the simulation of users of the system, conforming a faithful resemblance of real users of TEL platforms. For the evaluation of the proposed work, an iterative approach have been followed, testing the performance of the trust and reputation model while providing recommendation in a varied range of scenarios. A comparison with two traditional recommendation mechanisms was performed: a) using only users’ past opinions about a resource and/or other users; and b) not using any reputation assessment and providing the recommendation considering directly the objective quality of the resources. The results show that the developed model improves traditional approaches at providing recommendations in Technology Enhanced Learning (TEL) platforms, presenting a higher adaptability to different situations, whereas traditional approaches only have good results under favourable conditions. Furthermore the promotion period mechanism implemented successfully helps new users in the system to be recommended for direct interactions as well as the resources created by them. On the contrary OnlyOpinions fails completely and new users are never recommended, while traditional approaches only work partially. Finally, the agent-oriented programming (AOP) paradigm has proven its validity at modelling users’ behaviours in TEL platforms. Intelligent software agents’ characteristics matched the main requirements of the simulation tool. The proactivity, sociability and adaptability of the developed agents allowed reproducing real users’ actions and attitudes through the diverse situations defined in the evaluation framework. The result were independent users, accessing to different resources and communicating amongst them to fulfil their needs, basing these interactions on the recommendations provided by the reputation engine.

Costimulatory protein B7-1 enhances the cytotoxic T cell response and antibody response to hepatitis B surface antigen.

There is a need for more effective therapy for chronic virus infections. A principle natural mechanism for elimination of virus-infected host cells is activation of viral antigen-specific cytotoxic T lymphocytes (CTL). In an effort to develop methods of inducing virus-specific CTL responses that might be utilized in therapy of virus infections, we have investigated the effect of B7, a costimulatory factor for T-cell activation. In this study we show that delivery of genes encoding human B7-1 and a viral antigen in the same recombinant viral vector to cells of mice induces a greater viral antigen-specific CTL response than does similar delivery of the viral antigen gene alone. Two recombinant adenovirus vectors were constructed with the foreign genes inserted in the early region 3. One of them (Ad1312) directed expression of the surface antigen gene of hepatitis B virus (HBS); the other (Ad1310) directed coexpression of HBS and human B7-1 (CD80) by means of an internal ribosomal entry site placed between the two coding sequences. When inoculated into BALB/c mice, both vectors induced a viral surface antigen-specific CTL response. The response induced by Ad1310 was stronger than that by Adl312 as measured by a chromium release assay for CTL activity and limiting dilution analysis for CTL precursor frequency, indicating that the B7-1 gene co-delivered with the HBS gene had an enhancing effect on the CTL response against surface antigen. Ad1310 also induced a higher titer of antibody against surface antigen than did Ad1312. This result suggests that expression of a costimulatory protein and a viral antigen in the same cells in vivo induces stronger immune responses than expression of the antigen alone. This could be a novel strategy for development of both preventive and therapeutic vaccines against infectious agents.

Gene targeting approaches to complex genetic diseases: atherosclerosis and essential hypertension.

Gene targeting allows precise, predetermined changes to be made in a chosen gene in the mouse genome. To date, targeting has been used most often for generation of animals completely lacking the product of a gene of interest. The resulting "knockout" mice have confirmed some hypotheses, have upset others, but have rarely been uninformative. Models of several human genetic diseases have been produced by targeting--including Gaucher disease, cystic fibrosis, and the fragile X syndrome. These diseases are primarily determined by defects in single genes, and their modes of inheritance are well understood. When the disease under study has a complex etiology with multiple genetic and environmental components, the generation of animal models becomes more difficult but no less valuable. The problems associated with dissecting out the individual genetic factors also increases substantially and the distinction between causation and correlation is often difficult. To prove causation in a complex system requires rigorous adherence to the principle that the experiments must allow detection of the effects of changing only a single variable at one time. Gene targeting experiments, when properly designed, can test the effects of a precise genetic change completely free from the effects of differences in any other genes (linked or unlinked to the test gene). They therefore allow proofs of causation.

Evaluating knowledge-based approaches to the multilingual extension of a temporal expression normalizer

The extension to new languages is a well known bottleneck for rule-based systems. Considerable human effort, which typically consists in re-writing from scratch huge amounts of rules, is in fact required to transfer the knowledge available to the system from one language to a new one. Provided sufficient annotated data, machine learning algorithms allow to minimize the costs of such knowledge transfer but, up to date, proved to be ineffective for some specific tasks. Among these, the recognition and normalization of temporal expressions still remains out of their reach. Focusing on this task, and still adhering to the rule-based framework, this paper presents a bunch of experiments on the automatic porting to Italian of a system originally developed for Spanish. Different automatic rule translation strategies are evaluated and discussed, providing a comprehensive overview of the challenge.

Computational approaches to subjectivity and sentiment analysis: Present and envisaged methods and applications

Recent years have witnessed a surge of interest in computational methods for affect, ranging from opinion mining, to subjectivity detection, to sentiment and emotion analysis. This article presents a brief overview of the latest trends in the field and describes the manner in which the articles contained in the special issue contribute to the advancement of the area. Finally, we comment on the current challenges and envisaged developments of the subjectivity and sentiment analysis fields, as well as their application to other Natural Language Processing tasks and related domains.

Computer Networks Virtualization with GNS3: Evaluating a solution to optimize resources and achieve a distance learning

Designing educational resources allow students to modify their learning process. In particular, on-line and downloadable educational resources have been successfully used in engineering education the last years [1]. Usually, these resources are free and accessible from web. In addition, they are designed and developed by lecturers and used by their students. But, they are rarely developed by students in order to be used by other students. In this work-in-progress, lecturers and students are working together to implement educational resources, which can be used by students to improve the learning process of computer networks subject in engineering studies. In particular, network topologies to model LAN (Local Area Network) and MAN (Metropolitan Area Network) are virtualized in order to simulate the behavior of the links and nodes when they are interconnected with different physical and logical design.

Using new scanning electron microscopy (SEM) approaches to elucidate bacterial biofilm architecture

Healthcare-associated infections (HAI) are a major public health problem being Klebsiella pneumoniae and nontuberculous mycobacteria, both with high antibiotic resistance rates, among their etiological agent. Since biofilme assembly is pointed as one of the mechanisms involved in emergence of antibiotic resistance understanding bacteria organization within the biofilm and the identification of differences between planktonic and sessile forms of bacteria will be a step forward to fight HAI. In the present work we used SEM as a tool to characterize the internal structure of biofilm assembled on different surfaces. For SEM analysis, biofilms were allowed to form either on six-well cell culture plates, silicon or metallic disks placed inside the wells for different incubation periods at 37 °C. The biofilm assembled on the cell culture dish was for both secondary and backscattered electron analysis as described before. Biofilms assembled on silicon disks instead of being sectioned were prepared as metallographic samples, by grinding with grit SIC paper and polishing with diamond particles. Samples were cleaned (70% ethanol), dried with hot air, further coated and analysed. A preliminary study using FIB-SEM has been performed to access the ultrastructure of biofilms assembled on metallic surfaces. The results obtained showed that the same bacteria assembled biofilms with different ratios of biomass and extracellular matrix depending on the surface. SEM performed on thin sections of biofilms is a powerful tool to elucidate biofilm structure allowing the quantification of the major components. FIB-SEM is also a promising tool in this field.

Morphology and surface texture of quartz grains from ODP Site 105-645

The shapes and surface textures of sand-sized quartz grains from the sediments cored at Site 645 in southern Baffin Bay during ODP Leg 105 were studied to characterize the terrigenous materials and the settling processes involved in the deposition of these sediments. Here, we show a homogeneous sand fraction that results from mixing grains from various provenances. The characteristics inherited from terrestrial processes (varying degrees of wear; fluviatile, aeolian, and diagenetic features) dominate the characteristics that result from evolution in a high-energy marine environment. Thus, the influence of the last stage of sedimentation in a deep-marine environment was difficult to distinguish. However, fluctuations in the relative proportions of particular features reveal that the terrigenous material derived from sedimentary formations of Baffin Island and East Greenland or from direct abrasion of the crystalline shield, which changed through time as the dominant settling processes evolved. In particular, this study confirms the onset of major ice rafting as old as late Miocene.

Techniques for needs assessment : state experiences and suggested approaches in response to Title XX of the Social security act /

Companion vol. to the author's State experiences in social services planning.

The sea and its living wonders; a popular account of the marvels of the deep and of the progress of maritime discovery from the earliest ages to the present time,

Mode of access: Internet.

1995 status of the nation's surface transportation system: condition and performance. Report to Congress.

Mode of access: Internet.