931 resultados para Capture-recapture Data


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In this position paper, we claim that the need for time consuming data preparation and result interpretation tasks in knowledge discovery, as well as for costly expert consultation and consensus building activities required for ontology building can be reduced through exploiting the interplay of data mining and ontology engineering. The aim is to obtain in a semi-automatic way new knowledge from distributed data sources that can be used for inference and reasoning, as well as to guide the extraction of further knowledge from these data sources. The proposed approach is based on the creation of a novel knowledge discovery method relying on the combination, through an iterative ?feedbackloop?, of (a) data mining techniques to make emerge implicit models from data and (b) pattern-based ontology engineering to capture these models in reusable, conceptual and inferable artefacts.

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Versatile and accurate motion capture systems, with the required properties to be integrated within both clinical and domiciliary environments, would represent a significant advance in following the progress of the patients as well as in allowing the incorporation of new data exploitation and analysis methods to enhance the functional neurorehabilitation therapeutic processes. Besides, these systems would permit the later development of new applications focused on the automatization of the therapeutic tasks in order to increase the therapist/patient ratio, thus decreasing the costs [1]. However, current motion capture systems are not still ready to work within uncontrolled environments.

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A series of numerical simulations of the flow over a forest stand have been conducted using two different turbulence closure models along with various levels of canopy morphology data. Simulations have been validated against Stereoscopic Particle Image Velocimetry measurements from a wind tunnel study using one hundred architectural model trees, the porosities of which have been assessed using a photographic technique. It has been found that an accurate assessment of the porosity of the canopy, and specifically the variability with height, improves simulation quality regardless of the turbulence closure model used or the level of canopy geometry included. The observed flow field and recovery of the wake is in line with characteristic canopy flows published in the literature and it was found that the shear stress transport turbulence model was best able to capture this detail numerically.

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La diabetes mellitus es un trastorno en la metabolización de los carbohidratos, caracterizado por la nula o insuficiente segregación de insulina (hormona producida por el páncreas), como resultado del mal funcionamiento de la parte endocrina del páncreas, o de una creciente resistencia del organismo a esta hormona. Esto implica, que tras el proceso digestivo, los alimentos que ingerimos se transforman en otros compuestos químicos más pequeños mediante los tejidos exocrinos. La ausencia o poca efectividad de esta hormona polipéptida, no permite metabolizar los carbohidratos ingeridos provocando dos consecuencias: Aumento de la concentración de glucosa en sangre, ya que las células no pueden metabolizarla; consumo de ácidos grasos mediante el hígado, liberando cuerpos cetónicos para aportar la energía a las células. Esta situación expone al enfermo crónico, a una concentración de glucosa en sangre muy elevada, denominado hiperglucemia, la cual puede producir a medio o largo múltiples problemas médicos: oftalmológicos, renales, cardiovasculares, cerebrovasculares, neurológicos… La diabetes representa un gran problema de salud pública y es la enfermedad más común en los países desarrollados por varios factores como la obesidad, la vida sedentaria, que facilitan la aparición de esta enfermedad. Mediante el presente proyecto trabajaremos con los datos de experimentación clínica de pacientes con diabetes de tipo 1, enfermedad autoinmune en la que son destruidas las células beta del páncreas (productoras de insulina) resultando necesaria la administración de insulina exógena. Dicho esto, el paciente con diabetes tipo 1 deberá seguir un tratamiento con insulina administrada por la vía subcutánea, adaptado a sus necesidades metabólicas y a sus hábitos de vida. Para abordar esta situación de regulación del control metabólico del enfermo, mediante una terapia de insulina, no serviremos del proyecto “Páncreas Endocrino Artificial” (PEA), el cual consta de una bomba de infusión de insulina, un sensor continuo de glucosa, y un algoritmo de control en lazo cerrado. El objetivo principal del PEA es aportar al paciente precisión, eficacia y seguridad en cuanto a la normalización del control glucémico y reducción del riesgo de hipoglucemias. El PEA se instala mediante vía subcutánea, por lo que, el retardo introducido por la acción de la insulina, el retardo de la medida de glucosa, así como los errores introducidos por los sensores continuos de glucosa cuando, se descalibran dificultando el empleo de un algoritmo de control. Llegados a este punto debemos modelar la glucosa del paciente mediante sistemas predictivos. Un modelo, es todo aquel elemento que nos permita predecir el comportamiento de un sistema mediante la introducción de variables de entrada. De este modo lo que conseguimos, es una predicción de los estados futuros en los que se puede encontrar la glucosa del paciente, sirviéndonos de variables de entrada de insulina, ingesta y glucosa ya conocidas, por ser las sucedidas con anterioridad en el tiempo. Cuando empleamos el predictor de glucosa, utilizando parámetros obtenidos en tiempo real, el controlador es capaz de indicar el nivel futuro de la glucosa para la toma de decisones del controlador CL. Los predictores que se están empleando actualmente en el PEA no están funcionando correctamente por la cantidad de información y variables que debe de manejar. Data Mining, también referenciado como Descubrimiento del Conocimiento en Bases de Datos (Knowledge Discovery in Databases o KDD), ha sido definida como el proceso de extracción no trivial de información implícita, previamente desconocida y potencialmente útil. Todo ello, sirviéndonos las siguientes fases del proceso de extracción del conocimiento: selección de datos, pre-procesado, transformación, minería de datos, interpretación de los resultados, evaluación y obtención del conocimiento. Con todo este proceso buscamos generar un único modelo insulina glucosa que se ajuste de forma individual a cada paciente y sea capaz, al mismo tiempo, de predecir los estados futuros glucosa con cálculos en tiempo real, a través de unos parámetros introducidos. Este trabajo busca extraer la información contenida en una base de datos de pacientes diabéticos tipo 1 obtenidos a partir de la experimentación clínica. Para ello emplearemos técnicas de Data Mining. Para la consecución del objetivo implícito a este proyecto hemos procedido a implementar una interfaz gráfica que nos guía a través del proceso del KDD (con información gráfica y estadística) de cada punto del proceso. En lo que respecta a la parte de la minería de datos, nos hemos servido de la denominada herramienta de WEKA, en la que a través de Java controlamos todas sus funciones, para implementarlas por medio del programa creado. Otorgando finalmente, una mayor potencialidad al proyecto con la posibilidad de implementar el servicio de los dispositivos Android por la potencial capacidad de portar el código. Mediante estos dispositivos y lo expuesto en el proyecto se podrían implementar o incluso crear nuevas aplicaciones novedosas y muy útiles para este campo. Como conclusión del proyecto, y tras un exhaustivo análisis de los resultados obtenidos, podemos apreciar como logramos obtener el modelo insulina-glucosa de cada paciente. ABSTRACT. The diabetes mellitus is a metabolic disorder, characterized by the low or none insulin production (a hormone produced by the pancreas), as a result of the malfunctioning of the endocrine pancreas part or by an increasing resistance of the organism to this hormone. This implies that, after the digestive process, the food we consume is transformed into smaller chemical compounds, through the exocrine tissues. The absence or limited effectiveness of this polypeptide hormone, does not allow to metabolize the ingested carbohydrates provoking two consequences: Increase of the glucose concentration in blood, as the cells are unable to metabolize it; fatty acid intake through the liver, releasing ketone bodies to provide energy to the cells. This situation exposes the chronic patient to high blood glucose levels, named hyperglycemia, which may cause in the medium or long term multiple medical problems: ophthalmological, renal, cardiovascular, cerebrum-vascular, neurological … The diabetes represents a great public health problem and is the most common disease in the developed countries, by several factors such as the obesity or sedentary life, which facilitate the appearance of this disease. Through this project we will work with clinical experimentation data of patients with diabetes of type 1, autoimmune disease in which beta cells of the pancreas (producers of insulin) are destroyed resulting necessary the exogenous insulin administration. That said, the patient with diabetes type 1 will have to follow a treatment with insulin, administered by the subcutaneous route, adapted to his metabolic needs and to his life habits. To deal with this situation of metabolic control regulation of the patient, through an insulin therapy, we shall be using the “Endocrine Artificial Pancreas " (PEA), which consists of a bomb of insulin infusion, a constant glucose sensor, and a control algorithm in closed bow. The principal aim of the PEA is providing the patient precision, efficiency and safety regarding the normalization of the glycemic control and hypoglycemia risk reduction". The PEA establishes through subcutaneous route, consequently, the delay introduced by the insulin action, the delay of the glucose measure, as well as the mistakes introduced by the constant glucose sensors when, decalibrate, impede the employment of an algorithm of control. At this stage we must shape the patient glucose levels through predictive systems. A model is all that element or set of elements which will allow us to predict the behavior of a system by introducing input variables. Thus what we obtain, is a prediction of the future stages in which it is possible to find the patient glucose level, being served of input insulin, ingestion and glucose variables already known, for being the ones happened previously in the time. When we use the glucose predictor, using obtained real time parameters, the controller is capable of indicating the future level of the glucose for the decision capture CL controller. The predictors that are being used nowadays in the PEA are not working correctly for the amount of information and variables that it need to handle. Data Mining, also indexed as Knowledge Discovery in Databases or KDD, has been defined as the not trivial extraction process of implicit information, previously unknown and potentially useful. All this, using the following phases of the knowledge extraction process: selection of information, pre- processing, transformation, data mining, results interpretation, evaluation and knowledge acquisition. With all this process we seek to generate the unique insulin glucose model that adjusts individually and in a personalized way for each patient form and being capable, at the same time, of predicting the future conditions with real time calculations, across few input parameters. This project of end of grade seeks to extract the information contained in a database of type 1 diabetics patients, obtained from clinical experimentation. For it, we will use technologies of Data Mining. For the attainment of the aim implicit to this project we have proceeded to implement a graphical interface that will guide us across the process of the KDD (with graphical and statistical information) of every point of the process. Regarding the data mining part, we have been served by a tool called WEKA's tool called, in which across Java, we control all of its functions to implement them by means of the created program. Finally granting a higher potential to the project with the possibility of implementing the service for Android devices, porting the code. Through these devices and what has been exposed in the project they might help or even create new and very useful applications for this field. As a conclusion of the project, and after an exhaustive analysis of the obtained results, we can show how we achieve to obtain the insulin–glucose model for each patient.

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Determinar con buena precisión la posición en la que se encuentra un terminal móvil, cuando éste se halla inmerso en un entorno de interior (centros comerciales, edificios de oficinas, aeropuertos, estaciones, túneles, etc), es el pilar básico sobre el que se sustentan un gran número de aplicaciones y servicios. Muchos de esos servicios se encuentran ya disponibles en entornos de exterior, aunque los entornos de interior se prestan a otros servicios específicos para ellos. Ese número, sin embargo, podría ser significativamente mayor de lo que actualmente es, si no fuera necesaria una costosa infraestructura para llevar a cabo el posicionamiento con la precisión adecuada a cada uno de los hipotéticos servicios. O, igualmente, si la citada infraestructura pudiera tener otros usos distintos, además del relacionado con el posicionamiento. La usabilidad de la misma infraestructura para otros fines distintos ofrecería la oportunidad de que la misma estuviera ya presente en las diferentes localizaciones, porque ha sido previamente desplegada para esos otros usos; o bien facilitaría su despliegue, porque el coste de esa operación ofreciera un mayor retorno de usabilidad para quien lo realiza. Las tecnologías inalámbricas de comunicaciones basadas en radiofrecuencia, ya en uso para las comunicaciones de voz y datos (móviles, WLAN, etc), cumplen el requisito anteriormente indicado y, por tanto, facilitarían el crecimiento de las aplicaciones y servicios basados en el posicionamiento, en el caso de poderse emplear para ello. Sin embargo, determinar la posición con el nivel de precisión adecuado mediante el uso de estas tecnologías, es un importante reto hoy en día. El presente trabajo pretende aportar avances significativos en este campo. A lo largo del mismo se llevará a cabo, en primer lugar, un estudio de los principales algoritmos y técnicas auxiliares de posicionamiento aplicables en entornos de interior. La revisión se centrará en aquellos que sean aptos tanto para tecnologías móviles de última generación como para entornos WLAN. Con ello, se pretende poner de relieve las ventajas e inconvenientes de cada uno de estos algoritmos, teniendo como motivación final su aplicabilidad tanto al mundo de las redes móviles 3G y 4G (en especial a las femtoceldas y small-cells LTE) como al indicado entorno WLAN; y teniendo siempre presente que el objetivo último es que vayan a ser usados en interiores. La principal conclusión de esa revisión es que las técnicas de triangulación, comúnmente empleadas para realizar la localización en entornos de exterior, se muestran inútiles en los entornos de interior, debido a efectos adversos propios de este tipo de entornos como la pérdida de visión directa o los caminos múltiples en el recorrido de la señal. Los métodos de huella radioeléctrica, más conocidos bajo el término inglés “fingerprinting”, que se basan en la comparación de los valores de potencia de señal que se están recibiendo en el momento de llevar a cabo el posicionamiento por un terminal móvil, frente a los valores registrados en un mapa radio de potencias, elaborado durante una fase inicial de calibración, aparecen como los mejores de entre los posibles para los escenarios de interior. Sin embargo, estos sistemas se ven también afectados por otros problemas, como por ejemplo los importantes trabajos a realizar para ponerlos en marcha, y la variabilidad del canal. Frente a ellos, en el presente trabajo se presentan dos contribuciones originales para mejorar los sistemas basados en los métodos fingerprinting. La primera de esas contribuciones describe un método para determinar, de manera sencilla, las características básicas del sistema a nivel del número de muestras necesarias para crear el mapa radio de la huella radioeléctrica de referencia, junto al número mínimo de emisores de radiofrecuencia que habrá que desplegar; todo ello, a partir de unos requerimientos iniciales relacionados con el error y la precisión buscados en el posicionamiento a realizar, a los que uniremos los datos correspondientes a las dimensiones y realidad física del entorno. De esa forma, se establecen unas pautas iniciales a la hora de dimensionar el sistema, y se combaten los efectos negativos que, sobre el coste o el rendimiento del sistema en su conjunto, son debidos a un despliegue ineficiente de los emisores de radiofrecuencia y de los puntos de captura de su huella. La segunda contribución incrementa la precisión resultante del sistema en tiempo real, gracias a una técnica de recalibración automática del mapa radio de potencias. Esta técnica tiene en cuenta las medidas reportadas continuamente por unos pocos puntos de referencia estáticos, estratégicamente distribuidos en el entorno, para recalcular y actualizar las potencias registradas en el mapa radio. Un beneficio adicional a nivel operativo de la citada técnica, es la prolongación del tiempo de usabilidad fiable del sistema, bajando la frecuencia en la que se requiere volver a capturar el mapa radio de potencias completo. Las mejoras anteriormente citadas serán de aplicación directa en la mejora de los mecanismos de posicionamiento en interiores basados en la infraestructura inalámbrica de comunicaciones de voz y datos. A partir de ahí, esa mejora será extensible y de aplicabilidad sobre los servicios de localización (conocimiento personal del lugar donde uno mismo se encuentra), monitorización (conocimiento por terceros del citado lugar) y seguimiento (monitorización prolongada en el tiempo), ya que todos ellas toman como base un correcto posicionamiento para un adecuado desempeño. ABSTRACT To find the position where a mobile is located with good accuracy, when it is immersed in an indoor environment (shopping centers, office buildings, airports, stations, tunnels, etc.), is the cornerstone on which a large number of applications and services are supported. Many of these services are already available in outdoor environments, although the indoor environments are suitable for other services that are specific for it. That number, however, could be significantly higher than now, if an expensive infrastructure were not required to perform the positioning service with adequate precision, for each one of the hypothetical services. Or, equally, whether that infrastructure may have other different uses beyond the ones associated with positioning. The usability of the same infrastructure for purposes other than positioning could give the opportunity of having it already available in the different locations, because it was previously deployed for these other uses; or facilitate its deployment, because the cost of that operation would offer a higher return on usability for the deployer. Wireless technologies based on radio communications, already in use for voice and data communications (mobile, WLAN, etc), meet the requirement of additional usability and, therefore, could facilitate the growth of applications and services based on positioning, in the case of being able to use it. However, determining the position with the appropriate degree of accuracy using these technologies is a major challenge today. This paper provides significant advances in this field. Along this work, a study about the main algorithms and auxiliar techniques related with indoor positioning will be initially carried out. The review will be focused in those that are suitable to be used with both last generation mobile technologies and WLAN environments. By doing this, it is tried to highlight the advantages and disadvantages of each one of these algorithms, having as final motivation their applicability both in the world of 3G and 4G mobile networks (especially in femtocells and small-cells of LTE) and in the WLAN world; and having always in mind that the final aim is to use it in indoor environments. The main conclusion of that review is that triangulation techniques, commonly used for localization in outdoor environments, are useless in indoor environments due to adverse effects of such environments as loss of sight or multipaths. Triangulation techniques used for external locations are useless due to adverse effects like the lack of line of sight or multipath. Fingerprinting methods, based on the comparison of Received Signal Strength values measured by the mobile phone with a radio map of RSSI Recorded during the calibration phase, arise as the best methods for indoor scenarios. However, these systems are also affected by other problems, for example the important load of tasks to be done to have the system ready to work, and the variability of the channel. In front of them, in this paper we present two original contributions to improve the fingerprinting methods based systems. The first one of these contributions describes a method for find, in a simple way, the basic characteristics of the system at the level of the number of samples needed to create the radio map inside the referenced fingerprint, and also by the minimum number of radio frequency emitters that are needed to be deployed; and both of them coming from some initial requirements for the system related to the error and accuracy in positioning wanted to have, which it will be joined the data corresponding to the dimensions and physical reality of the environment. Thus, some initial guidelines when dimensioning the system will be in place, and the negative effects into the cost or into the performance of the whole system, due to an inefficient deployment of the radio frequency emitters and of the radio map capture points, will be minimized. The second contribution increases the resulting accuracy of the system when working in real time, thanks to a technique of automatic recalibration of the power measurements stored in the radio map. This technique takes into account the continuous measures reported by a few static reference points, strategically distributed in the environment, to recalculate and update the measurements stored into the map radio. An additional benefit at operational level of such technique, is the extension of the reliable time of the system, decreasing the periodicity required to recapture the radio map within full measurements. The above mentioned improvements are directly applicable to improve indoor positioning mechanisms based on voice and data wireless communications infrastructure. From there, that improvement will be also extensible and applicable to location services (personal knowledge of the location where oneself is), monitoring (knowledge by other people of your location) and monitoring (prolonged monitoring over time) as all of them are based in a correct positioning for proper performance.

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Humans' desire for knowledge regarding animal species and their interactions with the natural world have spurred centuries of studies. The relatively new development of remote sensing systems using satellite or aircraft-borne sensors has opened up a wide field of research, which unfortunately largely remains dependent on coarse-scale image spatial resolution, particularly for habitat modeling. For habitat-specialized species, such data may not be sufficient to successfully capture the nuances of their preferred areas. Of particular concern are those species for which topographic feature attributes are a main limiting factor for habitat use. Coarse spatial resolution data can smooth over details that may be essential for habitat characterization. Three studies focusing on sea turtle nesting beaches were completed to serve as an example of how topography can be a main deciding factor for certain species. Light Detection and Ranging (LiDAR) data were used to illustrate that fine spatial scale data can provide information not readily captured by either field work or coarser spatial scale sources. The variables extracted from the LiDAR data could successfully model nesting density for loggerhead (Caretta caretta), green (Chelonia mydas), and leatherback (Dermochelys coriacea) sea turtle species using morphological beach characteristics, highlight beach changes over time and their correlations with nesting success, and provide comparisons for nesting density models across large geographic areas. Comparisons between the LiDAR dataset and other digital elevation models (DEMs) confirmed that fine spatial scale data sources provide more similar habitat information than those with coarser spatial scales. Although these studies focused solely on sea turtles, the underlying principles are applicable for many other wildlife species whose range and behavior may be influenced by topographic features.

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A hydrological–economic model is introduced to describe the dynamics of groundwater-dependent economics (agriculture and tourism) for sustainable use in sparse-data drylands. The Amtoudi Oasis, a remote area in southern Morocco, in the northern Sahara attractive for tourism and with evidence of groundwater degradation, was chosen to show the model operation. Governing system variables were identified and put into action through System Dynamics (SD) modeling causal diagrams to program basic formulations into a model having two modules coupled by the nexus ‘pumping’: (1) the hydrological module represents the net groundwater balance (G) dynamics; and (2) the economic module reproduces the variation in the consumers of water, both the population and tourists. The model was operated under similar influx of tourists and different scenarios of water availability, such as the wet 2009–2010 and the average 2010–2011 hydrological years. The rise in international tourism is identified as the main driving force reducing emigration and introducing new social habits in the population, in particular concerning water consumption. Urban water allotment (PU) was doubled for less than a 100-inhabitant net increase in recent decades. The water allocation for agriculture (PI), the largest consumer of water, had remained constant for decades. Despite that the 2-year monitoring period is not long enough to draw long-term conclusions, groundwater imbalance was reflected by net aquifer recharge (R) less than PI + PU (G < 0) in the average year 2010–2011, with net lateral inflow from adjacent Cambrian formations being the largest recharge component. R is expected to be much less than PI + PU in recurrent dry spells. Some low-technology actions are tentatively proposed to mitigate groundwater degradation, such as: wastewater capture, treatment, and reuse for irrigation; storm-water harvesting for irrigation; and active maintenance of the irrigation system to improve its efficiency.

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Jellyfishes have functionally replaced several overexploited commercial stocks of planktivorous fishes. This is paradoxical, because they use a primitive prey capture mechanism requiring direct contact with the prey, whereas fishes use more efficient visual detection. We have compiled published data to show that, in spite of their primitive life-style, jellyfishes exhibit similar instantaneous prey clearance and respiration rates as their fish competitors and similar potential for growth and reproduction. To achieve this production, they have evolved large, water-laden bodies that increase prey contact rates. Although larger bodies are less efficient for swimming, optimization analysis reveals that large collectors are advantageous if they move through the water sufficiently slowly.

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The leatherback turtle Dermochelys coriacea is considered to be at serious risk of global extinction, despite ongoing conservation efforts. Intensive long-term monitoring of a leatherback nesting population on Sandy Point (St. Croix, US Virgin Islands) offers a unique opportunity to quantify basic population parameters and evaluate effectiveness of nesting beach conservation practices. We report a significant increase in the number of females nesting annually from ca. 18-30 in the 1980s to 186 in 2001, with a corresponding increase in annual hatchling production from ca. 2000 to over 49,000. We then analyzed resighting data from 1991 to 2001 with an open robust-design capture-mark-recapture model to estimate annual nester survival and adult abundance for this population. The expected annual survival probability was estimated at ca. 0.893 (95% CL 0.87-0.92) and the population was estimated to be increasing ca. 13% pa since the early 1990s. Taken together with DNA fingerprinting that identify mother-daughter relations, our findings suggest that the increase in the size of the nesting population since 1991 was probably due to an aggressive program of beach protection and egg relocation initiated more than 20 years ago. Beach protection and egg relocation provide a simple and effective conservation strategy for this Northern Caribbean nesting population as long as adult survival at sea remains relatively high. (c) 2005 Elsevier Ltd. All rights reserved.

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The Australian energy market is in the final stages of deregulation. These changes have created a dynamic environment which is highly volatile and competitive with respect to both demand and price. Our current research seeks to visualise aspects of the National Energy Market with a view to developing techniques which may be useful in identifying significant characteristics and/or drivers of these characteristics. In order to capture the complexity of the problem we explore a suite of different visualisation techniques, which, when combined into a unified package, highlight aspects of the problem. The particular problem visualised here is "Does the date exhibit characteristics which suggest that the time of day, day of the week, or the season, aflect the variation in demand and/or price?" © Austral. Mathematical Soc. 2005.

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A longitudinal capture-mark-recapture study was conducted to determine the temporal dynamics of rabbit haemorrhagic disease (RHD) in a European rabbit (Oryctolagus cuniculus) population of low to moderate density on sand-hill country in the lower North Island of New Zealand. A combination of sampling ( trapping and radio-tracking) and diagnostic (cELISA, PCR and isotype ELISA) methods was employed to obtain data weekly from May 1998 until June 2001. Although rabbit haemorrhagic disease virus ( RHDV) infection was detected in the study population in all 3 years, disease epidemics were evident only in the late summer or autumn months in 1999 and 2001. Overall, 20% of 385 samples obtained from adult animals older than 11 weeks were seropositive. An RHD outbreak in 1999 contributed to an estimated population decline of 26%. A second RHD epidemic in February 2001 was associated with a population decline of 52% over the subsequent month. Following the outbreaks, the seroprevalence in adult survivors was between 40% and 50%. During 2000, no deaths from RHDV were confirmed and mortalities were predominantly attributed to predation. Influx of seronegative immigrants was greatest in the 1999 and 2001 breeding seasons, and preceded the RHD epidemics in those years. Our data suggest that RHD epidemics require the population immunity level to fall below a threshold where propagation of infection can be maintained through the population.

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We developed a method to rapidly and safely live capture wild dugongs based on the “rodeo method” employed to catch marine turtles. This method entails close pursuit of a dugong by boat until it is fatigued. The dugong is then caught around the peduncle region by a catcher leaping off the boat, and the dugong is restrained at the water surface by several people while data are collected. Our sampling protocol involves a short restraint time, typically < 5 min. No ropes or nets were attached to the dugong to avoid the risk of entanglement and subsequent drowning. This method is suitable for shallow, open-water captures when weather and water conditions are fair, and may be adapted for deeper waters.

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Hierarchical visualization systems are desirable because a single two-dimensional visualization plot may not be sufficient to capture all of the interesting aspects of complex high-dimensional data sets. We extend an existing locally linear hierarchical visualization system PhiVis [1] in several directions: bf(1) we allow for em non-linear projection manifolds (the basic building block is the Generative Topographic Mapping -- GTM), bf(2) we introduce a general formulation of hierarchical probabilistic models consisting of local probabilistic models organized in a hierarchical tree, bf(3) we describe folding patterns of low-dimensional projection manifold in high-dimensional data space by computing and visualizing the manifold's local directional curvatures. Quantities such as magnification factors [3] and directional curvatures are helpful for understanding the layout of the nonlinear projection manifold in the data space and for further refinement of the hierarchical visualization plot. Like PhiVis, our system is statistically principled and is built interactively in a top-down fashion using the EM algorithm. We demonstrate the visualization system principle of the approach on a complex 12-dimensional data set and mention possible applications in the pharmaceutical industry.

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Exploratory analysis of data in all sciences seeks to find common patterns to gain insights into the structure and distribution of the data. Typically visualisation methods like principal components analysis are used but these methods are not easily able to deal with missing data nor can they capture non-linear structure in the data. One approach to discovering complex, non-linear structure in the data is through the use of linked plots, or brushing, while ignoring the missing data. In this technical report we discuss a complementary approach based on a non-linear probabilistic model. The generative topographic mapping enables the visualisation of the effects of very many variables on a single plot, which is able to incorporate far more structure than a two dimensional principal components plot could, and deal at the same time with missing data. We show that using the generative topographic mapping provides us with an optimal method to explore the data while being able to replace missing values in a dataset, particularly where a large proportion of the data is missing.

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In this paper we propose a data envelopment analysis (DEA) based method for assessing the comparative efficiencies of units operating production processes where input-output levels are inter-temporally dependent. One cause of inter-temporal dependence between input and output levels is capital stock which influences output levels over many production periods. Such units cannot be assessed by traditional or 'static' DEA which assumes input-output correspondences are contemporaneous in the sense that the output levels observed in a time period are the product solely of the input levels observed during that same period. The method developed in the paper overcomes the problem of inter-temporal input-output dependence by using input-output 'paths' mapped out by operating units over time as the basis of assessing them. As an application we compare the results of the dynamic and static model for a set of UK universities. The paper is suggested that dynamic model capture the efficiency better than static model. © 2003 Elsevier Inc. All rights reserved.