Integrated Segmentation of Brain Tumor Images for Radiotherapy and Neurosurgery

Image-based modeling of tumor growth combines methods from cancer simulation and medical imaging. In this context, we present a novel approach to adapt a healthy brain atlas to MR images of tumor patients. In order to establish correspondence between a healthy atlas and a pathologic patient image, tumor growth modeling in combination with registration algorithms is employed. In a first step, the tumor is grown in the atlas based on a new multi-scale, multi-physics model including growth simulation from the cellular level up to the biomechanical level, accounting for cell proliferation and tissue deformations. Large-scale deformations are handled with an Eulerian approach for finite element computations, which can operate directly on the image voxel mesh. Subsequently, dense correspondence between the modified atlas and patient image is established using nonrigid registration. The method offers opportunities in atlasbased segmentation of tumor-bearing brain images as well as for improved patient-specific simulation and prognosis of tumor progression.

Potentials and constraints of modeling for transdisciplinary co-producing strategies for sustainable water governance

Both climate change and socio-economic development will significantly modify the supply and consumption of water in future. Consequently, regional development has to face aggravation of existing or emergence of new conflicts of interest. In this context, transdisciplinary co-production of knowledge is considered as an important means for coping with these challenges. Accordingly, the MontanAqua project aims at developing strategies for more sustainable water management in the study area Crans-Montana-Sierre (Switzerland) in a transdisciplinary way. It strives for co-producing system, target and transformation knowledge among researchers, policy makers, public administration and civil society organizations. The research process basically consisted of the following steps: First, the current water situation in the study region was investigated. How much water is available? How much water is being used? How are decisions on water distribution and use taken? Second, participatory scenario workshops were conducted in order to identify the stakeholders’ visions of regional development. Third, the water situation in 2050 was simulated by modeling the evolution of water resources and water use and by reflecting on the institutional aspects. These steps laid ground for jointly assessing the consequences of the stakeholders’ visions of development in view of scientific data regarding governance, availability and use of water in the region as well as developing necessary transformation knowledge. During all of these steps researchers have collaborated with stakeholders in the support group RegiEau. The RegiEau group consists of key representatives of owners, managers, users, and pressure groups related to water and landscape: representatives of the communes (mostly the presidents), the canton (administration and parliament), water management associations, agriculture, viticulture, hydropower, tourism, and landscape protection. The aim of the talk is to explore potentials and constraints of scientific modeling of water availability and use within the process of transdisciplinary co-producing strategies for more sustainable water governance.

APPLICATIONS OF EPHB4 RECEPTOR SPECIFIC PEPTIDES IN TARGETED CANCER IMAGING AND THERAPY

EphB4 receptors, a member of the largest family of receptor tyrosine kinases, are found over-expressed in a variety of tumors cells including glioma cells as well as angiogenic blood vessels. Noninvasive imaging of EphB4 could potentially increase early detection rates, monitor response to therapy directed against EphB4, and improve patient outcomes. Targeted delivery of EphB4 receptor specific peptide conjugated hollow gold nanoshells (HAuNS) into tumors has great potential in cancer imaging and photothermal therapy. In this study, we developed an EphB4 specific peptide named TNYL-RAW and labeled with radioisotope 64Cu and Cy5.5 dye. We also conjugate this specific peptide with hollow gold nanoshells (HAuNS) to evaluate targeted photothermal therapy of cancers. In vitro, 64Cu-DOTA-TNYL- RAW specifically bind to CT26 and PC-3M cells but not to A549 cells. In vivo, Small-animal PET/CT clearly showed the significant uptake of 64Cu-DOTA-TNYL-RAW in CT26 and PC-3M tumors but not in A549 tumors. Furthermore, µPET/CT and near-infrared optical imaging clearly showed the uptake of the dual labeled TNYL-RAW peptide in both U251 and U87 tumors in the brains of nude mice. In U251 tumors, Cy5.5-labeled peptide can bind to EphB4-expressing tumor blood vessels and tumors cells. But in U87 models, dual labeled peptide only could bind to tumor associated blood vessels. Also, Irradiation of PC-3M and CT-26 cell treated with TNYL-PEG-HAuNS nanopatilces with near-infrared (NIR) laser resulted in selective destruction of these cells in vitro. EphB4 targeted TNYL-PEG-HAuNS showed more photothermal killing effect on CT26 tumor model than PEG-HAuNS did. In summary, tumors with overexpression of EphB4 receptors can be noninvasively visualized by micro PET/CT with 64Cu labeled or dual labeled TNYL-RAW peptide. Targeted delivery of TNYL-RAW conjugated HAuNS into tumors can greatly improve the treatment effect of photothermal therapy. The information acquired with this study should be advantageous in improving diagnostics and future applications in photothermal ablation therapy in clinical.

Potential desiccation cracks on Mars: A synthesis from modeling, analogue-field studies, and global observations

Potential desiccation polygons (PDPs) are polygonal surface patterns that are a common feature in Noachian-to-Hesperian-aged phyllosilicate- and chloride-bearing terrains and have been observed with size scales that range from cm-wide (by current rovers) to 10s of meters-wide. The global distribution of PDPs shows that they share certain traits in terms of morphology and geologic setting that can aid identification and distinction from fracturing patterns caused by other processes. They are mostly associated with sedimentary deposits that display spectral evidence for the presence of Fe/Mg smectites, Al-rich smectites or less commonly kaolinites, carbonates, and sulfates. In addition, PDPs may indicate paleolacustrine environments, which are of high interest for planetary exploration, and their presence implies that the fractured units are rich in smectite minerals that may have been deposited in a standing body of water. A collective synthesis with new data, particularly from the HiRISE camera suggests that desiccation cracks may be more common on the surface of Mars than previously thought. A review of terrestrial research on desiccation processes with emphasis on the theoretical background, field studies, and modeling constraints is presented here as well and shown to be consistent with and relevant to certain polygonal patterns on Mars.

Mineralogical and isotopic record of diagenesis from the Opalinus Clay formation at Benken, Switzerland: Implications for the modeling of pore-water chemistry in a clay formation

Argillaceous rocks are considered to be a suitable geological barrier for the long-term containment of wastes. Their efficiency at retarding contaminant migration is assessed using reactive-transport experiments and modeling, the latter requiring a sound understanding of pore-water chemistry. The building of a pore-water model, which is mandatory for laboratory experiments mimicking in situ conditions, requires a detailed knowledge of the rock mineralogy and of minerals at equilibrium with present-day pore waters. Using a combination of petrological, mineralogical, and isotopic studies, the present study focused on the reduced Opalinus Clay formation (Fm) of the Benken borehole (30 km north of Zurich) which is intended for nuclear-waste disposal in Switzerland. A diagenetic sequence is proposed, which serves as a basis for determining the minerals stable in the formation and their textural relationships. Early cementation of dominant calcite, rare dolomite, and pyrite formed by bacterial sulfate reduction, was followed by formation of iron-rich calcite, ankerite, siderite, glauconite, (Ba, Sr) sulfates, and traces of sphalerite and galena. The distribution and abundance of siderite depends heavily on the depositional environment (and consequently on the water column). Benken sediment deposition during Aalenian times corresponds to an offshore environment with the early formation of siderite concretions at the water/sediment interface at the fluctuating boundary between the suboxic iron reduction and the sulfate reduction zones. Diagenetic minerals (carbonates except dolomite, sulfates, silicates) remained stable from their formation to the present. Based on these mineralogical and geochemical data, the mineral assemblage previously used for the geochemical model of the pore waters at Mont Terri may be applied to Benken without significant changes. These further investigations demonstrate the need for detailed mineralogical and geochemical study to refine the model of pore-water chemistry in a clay formation.

Similarity Mapplet: Interactive Visualization of the Directory of Useful Decoys and ChEMBL in High Dimensional Chemical Spaces

An Internet portal accessible at www.gdb.unibe.ch has been set up to automatically generate color-coded similarity maps of the ChEMBL database in relation to up to two sets of active compounds taken from the enhanced Directory of Useful Decoys (eDUD), a random set of molecules, or up to two sets of user-defined reference molecules. These maps visualize the relationships between the selected compounds and ChEMBL in six different high dimensional chemical spaces, namely MQN (42-D molecular quantum numbers), SMIfp (34-D SMILES fingerprint), APfp (20-D shape fingerprint), Xfp (55-D pharmacophore fingerprint), Sfp (1024-bit substructure fingerprint), and ECfp4 (1024-bit extended connectivity fingerprint). The maps are supplied in form of Java based desktop applications called “similarity mapplets” allowing interactive content browsing and linked to a “Multifingerprint Browser for ChEMBL” (also accessible directly at www.gdb.unibe.ch) to perform nearest neighbor searches. One can obtain six similarity mapplets of ChEMBL relative to random reference compounds, 606 similarity mapplets relative to single eDUD active sets, 30 300 similarity mapplets relative to pairs of eDUD active sets, and any number of similarity mapplets relative to user-defined reference sets to help visualize the structural diversity of compound series in drug optimization projects and their relationship to other known bioactive compounds.

THE NATURAL AND ORTHOGONAL INTERACTION (NOIA) MODELS FOR QUANTITATIVE TRAITS (QTs) AND COMPLEX DISEASES

My dissertation focuses on developing methods for gene-gene/environment interactions and imprinting effect detections for human complex diseases and quantitative traits. It includes three sections: (1) generalizing the Natural and Orthogonal interaction (NOIA) model for the coding technique originally developed for gene-gene (GxG) interaction and also to reduced models; (2) developing a novel statistical approach that allows for modeling gene-environment (GxE) interactions influencing disease risk, and (3) developing a statistical approach for modeling genetic variants displaying parent-of-origin effects (POEs), such as imprinting. In the past decade, genetic researchers have identified a large number of causal variants for human genetic diseases and traits by single-locus analysis, and interaction has now become a hot topic in the effort to search for the complex network between multiple genes or environmental exposures contributing to the outcome. Epistasis, also known as gene-gene interaction is the departure from additive genetic effects from several genes to a trait, which means that the same alleles of one gene could display different genetic effects under different genetic backgrounds. In this study, we propose to implement the NOIA model for association studies along with interaction for human complex traits and diseases. We compare the performance of the new statistical models we developed and the usual functional model by both simulation study and real data analysis. Both simulation and real data analysis revealed higher power of the NOIA GxG interaction model for detecting both main genetic effects and interaction effects. Through application on a melanoma dataset, we confirmed the previously identified significant regions for melanoma risk at 15q13.1, 16q24.3 and 9p21.3. We also identified potential interactions with these significant regions that contribute to melanoma risk. Based on the NOIA model, we developed a novel statistical approach that allows us to model effects from a genetic factor and binary environmental exposure that are jointly influencing disease risk. Both simulation and real data analyses revealed higher power of the NOIA model for detecting both main genetic effects and interaction effects for both quantitative and binary traits. We also found that estimates of the parameters from logistic regression for binary traits are no longer statistically uncorrelated under the alternative model when there is an association. Applying our novel approach to a lung cancer dataset, we confirmed four SNPs in 5p15 and 15q25 region to be significantly associated with lung cancer risk in Caucasians population: rs2736100, rs402710, rs16969968 and rs8034191. We also validated that rs16969968 and rs8034191 in 15q25 region are significantly interacting with smoking in Caucasian population. Our approach identified the potential interactions of SNP rs2256543 in 6p21 with smoking on contributing to lung cancer risk. Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting affects several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we propose a NOIA framework for a single locus association study that estimates both main allelic effects and POEs. We develop statistical (Stat-POE) and functional (Func-POE) models, and demonstrate conditions for orthogonality of the Stat-POE model. We conducted simulations for both quantitative and qualitative traits to evaluate the performance of the statistical and functional models with different levels of POEs. Our results showed that the newly proposed Stat-POE model, which ensures orthogonality of variance components if Hardy-Weinberg Equilibrium (HWE) or equal minor and major allele frequencies is satisfied, had greater power for detecting the main allelic additive effect than a Func-POE model, which codes according to allelic substitutions, for both quantitative and qualitative traits. The power for detecting the POE was the same for the Stat-POE and Func-POE models under HWE for quantitative traits.

Planktic foraminiferal Mg/Ca and oxygen isotopes, plus estimated d18Oseawater and ice volume corrected d18Oseawater for the past 35000 years of sediment core GeoB10069-3

Evidence from geologic archives suggests that there were large changes in the tropical hydrologic cycle associated with the two prominent northern hemisphere deglacial cooling events, Heinrich Stadial 1 (HS1; ~19 to 15 kyr BP; kyr BP = 1000 yr before present) and the Younger Dryas (~12.9 to 11.7 kyr BP). These hydrologic shifts have been alternatively attributed to high and low latitude origin. Here, we present a new record of hydrologic variability based on planktic foraminifera-derived d18O of seawater (d18Osw) estimates from a sediment core from the tropical Eastern Indian Ocean, and using 12 additional d18Osw records, construct a single record of the dominant mode of tropical Eastern Equatorial Pacific and Indo-Pacific Warm Pool (IPWP) hydrologic variability. We show that deglacial hydrologic shifts parallel variations in the reconstructed interhemispheric temperature gradient, suggesting a strong response to variations in the Atlantic Meridional Overturning Circulation and the attendant heat redistribution. A transient model simulation of the last deglaciation suggests that hydrologic changes, including a southward shift in the Intertropical Convergence Zone (ITCZ) which likely occurred during these northern hemisphere cold events, coupled with oceanic advection and mixing, resulted in increased salinity in the Indonesian region of the IPWP and the eastern tropical Pacific, which is recorded by the d18Osw proxy. Based on our observations and modeling results we suggest the interhemispheric temperature gradient directly controls the tropical hydrologic cycle on these time scales, which in turn mediates poleward atmospheric heat transport.

Uso de DES y RANS no estacionario para la simulación del flujo alrededor de una carena Wigley - Use of Unsteady RANS and DES to simulate flows around a Wigley Hull)

Computer Fluid Dynamics tools have already become a valuable instrument for Naval Architects during the ship design process, thanks to their accuracy and the available computer power. Unfortunately, the development of RANSE codes, generally used when viscous effects play a major role in the flow, has not reached a mature stage, being the accuracy of the turbulence models and the free surface representation the most important sources of uncertainty. Another level of uncertainty is added when the simulations are carried out for unsteady flows, as those generally studied in seakeeping and maneuvering analysis and URANS equations solvers are used. Present work shows the applicability and the benefits derived from the use of new approaches for the turbulence modeling (Detached Eddy Simulation) and the free surface representation (Level Set) on the URANS equations solver CFDSHIP-Iowa. Compared to URANS, DES is expected to predict much broader frequency contents and behave better in flows where boundary layer separation plays a major role. Level Set methods are able to capture very complex free surface geometries, including breaking and overturning waves. The performance of these improvements is tested in set of fairly complex flows, generated by a Wigley hull at pure drift motion, with drift angle ranging from 10 to 60 degrees and at several Froude numbers to study the impact of its variation. Quantitative verification and validation are performed with the obtained results to guarantee their accuracy. The results show the capability of the CFDSHIP-Iowa code to carry out time-accurate simulations of complex flows of extreme unsteady ship maneuvers. The Level Set method is able to capture very complex geometries of the free surface and the use of DES in unsteady simulations highly improves the results obtained. Vortical structures and instabilities as a function of the drift angle and Fr are qualitatively identified. Overall analysis of the flow pattern shows a strong correlation between the vortical structures and free surface wave pattern. Karman-like vortex shedding is identified and the scaled St agrees well with the universal St value. Tip vortices are identified and the associated helical instabilities are analyzed. St using the hull length decreases with the increase of the distance along the vortex core (x), which is similar to results from other simulations. However, St scaled using distance along the vortex cores shows strong oscillations compared to almost constants for those previous simulations. The difference may be caused by the effect of the free-surface, grid resolution, and interaction between the tip vortex and other vortical structures, which needs further investigations. This study is exploratory in the sense that finer grids are desirable and experimental data is lacking for large α, especially for the local flow. More recently, high performance computational capability of CFDSHIP-Iowa V4 has been improved such that large scale computations are possible. DES for DTMB 5415 with bilge keels at α = 20º were conducted using three grids with 10M, 48M and 250M points. DES analysis for flows around KVLCC2 at α = 30º is analyzed using a 13M grid and compared with the results of DES on the 1.6M grid by. Both studies are consistent with what was concluded on grid resolution herein since dominant frequencies for shear-layer, Karman-like, horse-shoe and helical instabilities only show marginal variation on grid refinement. The penalties of using coarse grids are smaller frequency amplitude and less resolved TKE. Therefore finer grids should be used to improve V&V for resolving most of the active turbulent scales for all different Fr and α, which hopefully can be compared with additional EFD data for large α when it becomes available.

Applications for wireless sensor networks : tracking with binary proximity sensors

El interés cada vez mayor por las redes de sensores inalámbricos pueden ser entendido simplemente pensando en lo que esencialmente son: un gran número de pequeños nodos sensores autoalimentados que recogen información o detectan eventos especiales y se comunican de manera inalámbrica, con el objetivo final de entregar sus datos procesados a una estación base. Los nodos sensores están densamente desplegados dentro del área de interés, se pueden desplegar al azar y tienen capacidad de cooperación. Por lo general, estos dispositivos son pequeños y de bajo costo, de modo que pueden ser producidos y desplegados en gran numero aunque sus recursos en términos de energía, memoria, velocidad de cálculo y ancho de banda están enormemente limitados. Detección, tratamiento y comunicación son tres elementos clave cuya combinación en un pequeño dispositivo permite lograr un gran número de aplicaciones. Las redes de sensores proporcionan oportunidades sin fin, pero al mismo tiempo plantean retos formidables, tales como lograr el máximo rendimiento de una energía que es escasa y por lo general un recurso no renovable. Sin embargo, los recientes avances en la integración a gran escala, integrado de hardware de computación, comunicaciones, y en general, la convergencia de la informática y las comunicaciones, están haciendo de esta tecnología emergente una realidad. Del mismo modo, los avances en la nanotecnología están empezando a hacer que todo gire entorno a las redes de pequeños sensores y actuadores distribuidos. Hay diferentes tipos de sensores tales como sensores de presión, acelerómetros, cámaras, sensores térmicos o un simple micrófono. Supervisan las condiciones presentes en diferentes lugares tales como la temperatura, humedad, el movimiento, la luminosidad, presión, composición del suelo, los niveles de ruido, la presencia o ausencia de ciertos tipos de objetos, los niveles de tensión mecánica sobre objetos adheridos y las características momentáneas tales como la velocidad , la dirección y el tamaño de un objeto, etc. Se comprobara el estado de las Redes Inalámbricas de Sensores y se revisaran los protocolos más famosos. Así mismo, se examinara la identificación por radiofrecuencia (RFID) ya que se está convirtiendo en algo actual y su presencia importante. La RFID tiene un papel crucial que desempeñar en el futuro en el mundo de los negocios y los individuos por igual. El impacto mundial que ha tenido la identificación sin cables está ejerciendo fuertes presiones en la tecnología RFID, los servicios de investigación y desarrollo, desarrollo de normas, el cumplimiento de la seguridad y la privacidad y muchos más. Su potencial económico se ha demostrado en algunos países mientras que otros están simplemente en etapas de planificación o en etapas piloto, pero aun tiene que afianzarse o desarrollarse a través de la modernización de los modelos de negocio y aplicaciones para poder tener un mayor impacto en la sociedad. Las posibles aplicaciones de redes de sensores son de interés para la mayoría de campos. La monitorización ambiental, la guerra, la educación infantil, la vigilancia, la micro-cirugía y la agricultura son solo unos pocos ejemplos de los muchísimos campos en los que tienen cabida las redes mencionadas anteriormente. Estados Unidos de América es probablemente el país que más ha investigado en esta área por lo que veremos muchas soluciones propuestas provenientes de ese país. Universidades como Berkeley, UCLA (Universidad de California, Los Ángeles) Harvard y empresas como Intel lideran dichas investigaciones. Pero no solo EE.UU. usa e investiga las redes de sensores inalámbricos. La Universidad de Southampton, por ejemplo, está desarrollando una tecnología para monitorear el comportamiento de los glaciares mediante redes de sensores que contribuyen a la investigación fundamental en glaciología y de las redes de sensores inalámbricos. Así mismo, Coalesenses GmbH (Alemania) y Zurich ETH están trabajando en diversas aplicaciones para redes de sensores inalámbricos en numerosas áreas. Una solución española será la elegida para ser examinada más a fondo por ser innovadora, adaptable y polivalente. Este estudio del sensor se ha centrado principalmente en aplicaciones de tráfico, pero no se puede olvidar la lista de más de 50 aplicaciones diferentes que ha sido publicada por la firma creadora de este sensor específico. En la actualidad hay muchas tecnologías de vigilancia de vehículos, incluidos los sensores de bucle, cámaras de video, sensores de imagen, sensores infrarrojos, radares de microondas, GPS, etc. El rendimiento es aceptable, pero no suficiente, debido a su limitada cobertura y caros costos de implementación y mantenimiento, especialmente este ultimo. Tienen defectos tales como: línea de visión, baja exactitud, dependen mucho del ambiente y del clima, no se puede realizar trabajos de mantenimiento sin interrumpir las mediciones, la noche puede condicionar muchos de ellos, tienen altos costos de instalación y mantenimiento, etc. Por consiguiente, en las aplicaciones reales de circulación, los datos recibidos son insuficientes o malos en términos de tiempo real debido al escaso número de detectores y su costo. Con el aumento de vehículos en las redes viales urbanas las tecnologías de detección de vehículos se enfrentan a nuevas exigencias. Las redes de sensores inalámbricos son actualmente una de las tecnologías más avanzadas y una revolución en la detección de información remota y en las aplicaciones de recogida. Las perspectivas de aplicación en el sistema inteligente de transporte son muy amplias. Con este fin se ha desarrollado un programa de localización de objetivos y recuento utilizando una red de sensores binarios. Esto permite que el sensor necesite mucha menos energía durante la transmisión de información y que los dispositivos sean más independientes con el fin de tener un mejor control de tráfico. La aplicación se centra en la eficacia de la colaboración de los sensores en el seguimiento más que en los protocolos de comunicación utilizados por los nodos sensores. Las operaciones de salida y retorno en las vacaciones son un buen ejemplo de por qué es necesario llevar la cuenta de los coches en las carreteras. Para ello se ha desarrollado una simulación en Matlab con el objetivo localizar objetivos y contarlos con una red de sensores binarios. Dicho programa se podría implementar en el sensor que Libelium, la empresa creadora del sensor que se examinara concienzudamente, ha desarrollado. Esto permitiría que el aparato necesitase mucha menos energía durante la transmisión de información y los dispositivos sean más independientes. Los prometedores resultados obtenidos indican que los sensores de proximidad binarios pueden formar la base de una arquitectura robusta para la vigilancia de áreas amplias y para el seguimiento de objetivos. Cuando el movimiento de dichos objetivos es suficientemente suave, no tiene cambios bruscos de trayectoria, el algoritmo ClusterTrack proporciona un rendimiento excelente en términos de identificación y seguimiento de trayectorias los objetos designados como blancos. Este algoritmo podría, por supuesto, ser utilizado para numerosas aplicaciones y se podría seguir esta línea de trabajo para futuras investigaciones. No es sorprendente que las redes de sensores de binarios de proximidad hayan atraído mucha atención últimamente ya que, a pesar de la información mínima de un sensor de proximidad binario proporciona, las redes de este tipo pueden realizar un seguimiento de todo tipo de objetivos con la precisión suficiente. Abstract The increasing interest in wireless sensor networks can be promptly understood simply by thinking about what they essentially are: a large number of small sensing self-powered nodes which gather information or detect special events and communicate in a wireless fashion, with the end goal of handing their processed data to a base station. The sensor nodes are densely deployed inside the phenomenon, they deploy random and have cooperative capabilities. Usually these devices are small and inexpensive, so that they can be produced and deployed in large numbers, and so their resources in terms of energy, memory, computational speed and bandwidth are severely constrained. Sensing, processing and communication are three key elements whose combination in one tiny device gives rise to a vast number of applications. Sensor networks provide endless opportunities, but at the same time pose formidable challenges, such as the fact that energy is a scarce and usually non-renewable resource. However, recent advances in low power Very Large Scale Integration, embedded computing, communication hardware, and in general, the convergence of computing and communications, are making this emerging technology a reality. Likewise, advances in nanotechnology and Micro Electro-Mechanical Systems are pushing toward networks of tiny distributed sensors and actuators. There are different sensors such as pressure, accelerometer, camera, thermal, and microphone. They monitor conditions at different locations, such as temperature, humidity, vehicular movement, lightning condition, pressure, soil makeup, noise levels, the presence or absence of certain kinds of objects, mechanical stress levels on attached objects, the current characteristics such as speed, direction and size of an object, etc. The state of Wireless Sensor Networks will be checked and the most famous protocols reviewed. As Radio Frequency Identification (RFID) is becoming extremely present and important nowadays, it will be examined as well. RFID has a crucial role to play in business and for individuals alike going forward. The impact of ‘wireless’ identification is exerting strong pressures in RFID technology and services research and development, standards development, security compliance and privacy, and many more. The economic value is proven in some countries while others are just on the verge of planning or in pilot stages, but the wider spread of usage has yet to take hold or unfold through the modernisation of business models and applications. Possible applications of sensor networks are of interest to the most diverse fields. Environmental monitoring, warfare, child education, surveillance, micro-surgery, and agriculture are only a few examples. Some real hardware applications in the United States of America will be checked as it is probably the country that has investigated most in this area. Universities like Berkeley, UCLA (University of California, Los Angeles) Harvard and enterprises such as Intel are leading those investigations. But not just USA has been using and investigating wireless sensor networks. University of Southampton e.g. is to develop technology to monitor glacier behaviour using sensor networks contributing to fundamental research in glaciology and wireless sensor networks. Coalesenses GmbH (Germany) and ETH Zurich are working in applying wireless sensor networks in many different areas too. A Spanish solution will be the one examined more thoroughly for being innovative, adaptable and multipurpose. This study of the sensor has been focused mainly to traffic applications but it cannot be forgotten the more than 50 different application compilation that has been published by this specific sensor’s firm. Currently there are many vehicle surveillance technologies including loop sensors, video cameras, image sensors, infrared sensors, microwave radar, GPS, etc. The performance is acceptable but not sufficient because of their limited coverage and expensive costs of implementation and maintenance, specially the last one. They have defects such as: line-ofsight, low exactness, depending on environment and weather, cannot perform no-stop work whether daytime or night, high costs for installation and maintenance, etc. Consequently, in actual traffic applications the received data is insufficient or bad in terms of real-time owed to detector quantity and cost. With the increase of vehicle in urban road networks, the vehicle detection technologies are confronted with new requirements. Wireless sensor network is the state of the art technology and a revolution in remote information sensing and collection applications. It has broad prospect of application in intelligent transportation system. An application for target tracking and counting using a network of binary sensors has been developed. This would allow the appliance to spend much less energy when transmitting information and to make more independent devices in order to have a better traffic control. The application is focused on the efficacy of collaborative tracking rather than on the communication protocols used by the sensor nodes. Holiday crowds are a good case in which it is necessary to keep count of the cars on the roads. To this end a Matlab simulation has been produced for target tracking and counting using a network of binary sensors that e.g. could be implemented in Libelium’s solution. Libelium is the enterprise that has developed the sensor that will be deeply examined. This would allow the appliance to spend much less energy when transmitting information and to make more independent devices. The promising results obtained indicate that binary proximity sensors can form the basis for a robust architecture for wide area surveillance and tracking. When the target paths are smooth enough ClusterTrack particle filter algorithm gives excellent performance in terms of identifying and tracking different target trajectories. This algorithm could, of course, be used for different applications and that could be done in future researches. It is not surprising that binary proximity sensor networks have attracted a lot of attention lately. Despite the minimal information a binary proximity sensor provides, networks of these sensing modalities can track all kinds of different targets classes accurate enough.

Flow and fracture behaviour of high performance alloys

Based on our needs, that is to say, through precise simulation of the impact phenomena that may occur inside a jet engine turbine with an explicit non-linear finite element code, four new material models are postulated. Each one of is calibrated for four high-performance alloys that can be encountered in a modern jet engine. A new uncoupled material model for high strain and ballistic is proposed. Based on a Johnson-Cook type model, the proposed formulation introduces the effect of the third deviatoric invariant by means of three different Lode angle dependent functions. The Lode dependent functions are added to both plasticity and failure models. The postulated model is calibrated for a 6061-T651 aluminium alloy with data taken from the literature. The fracture pattern predictability of the JCX material model is shown performing numerical simulations of various quasi-static and dynamic tests. As an extension of the above-mentioned model, a modification in the thermal softening behaviour due to phase transformation temperatures is developed (JCXt). Additionally, a Lode angle dependent flow stress is defined. Analysing the phase diagram and high temperature tests performed, phase transformation temperatures of the FV535 stainless steel are determined. The postulated material model constants for the FV535 stainless steel are calibrated. A coupled elastoplastic-damage material model for high strain and ballistic applications is presented (JCXd). A Lode angle dependent function is added to the equivalent plastic strain to failure definition of the Johnson-Cook failure criterion. The weakening in the elastic law and in the Johnson-Cook type constitutive relation implicitly introduces the Lode angle dependency in the elastoplastic behaviour. The material model is calibrated for precipitation hardened Inconel 718 nickel-base superalloy. The combination of a Lode angle dependent failure criterion with weakened constitutive equations is proven to predict fracture patterns of the mechanical tests performed and provide reliable results. A transversely isotropic material model for directionally solidified alloys is presented. The proposed yield function is based a single linear transformation of the stress tensor. The linear operator weighs the degree of anisotropy of the yield function. The elastic behaviour, as well as the hardening, are considered isotropic. To model the hardening, a Johnson-Cook type relation is adopted. A material vector is included in the model implementation. The failure is modelled with the Cockroft-Latham failure criterion. The material vector allows orienting the reference orientation in any other that the user may need. The model is calibrated for the MAR-M 247 directionally solidified nickel-base superalloy.

Regularization for sparsity in statistical analysis and machine learning

Pragmatism is the leading motivation of regularization. We can understand regularization as a modification of the maximum-likelihood estimator so that a reasonable answer could be given in an unstable or ill-posed situation. To mention some typical examples, this happens when fitting parametric or non-parametric models with more parameters than data or when estimating large covariance matrices. Regularization is usually used, in addition, to improve the bias-variance tradeoff of an estimation. Then, the definition of regularization is quite general, and, although the introduction of a penalty is probably the most popular type, it is just one out of multiple forms of regularization. In this dissertation, we focus on the applications of regularization for obtaining sparse or parsimonious representations, where only a subset of the inputs is used. A particular form of regularization, L1-regularization, plays a key role for reaching sparsity. Most of the contributions presented here revolve around L1-regularization, although other forms of regularization are explored (also pursuing sparsity in some sense). In addition to present a compact review of L1-regularization and its applications in statistical and machine learning, we devise methodology for regression, supervised classification and structure induction of graphical models. Within the regression paradigm, we focus on kernel smoothing learning, proposing techniques for kernel design that are suitable for high dimensional settings and sparse regression functions. We also present an application of regularized regression techniques for modeling the response of biological neurons. Supervised classification advances deal, on the one hand, with the application of regularization for obtaining a na¨ıve Bayes classifier and, on the other hand, with a novel algorithm for brain-computer interface design that uses group regularization in an efficient manner. Finally, we present a heuristic for inducing structures of Gaussian Bayesian networks using L1-regularization as a filter. El pragmatismo es la principal motivación de la regularización. Podemos entender la regularización como una modificación del estimador de máxima verosimilitud, de tal manera que se pueda dar una respuesta cuando la configuración del problema es inestable. A modo de ejemplo, podemos mencionar el ajuste de modelos paramétricos o no paramétricos cuando hay más parámetros que casos en el conjunto de datos, o la estimación de grandes matrices de covarianzas. Se suele recurrir a la regularización, además, para mejorar el compromiso sesgo-varianza en una estimación. Por tanto, la definición de regularización es muy general y, aunque la introducción de una función de penalización es probablemente el método más popular, éste es sólo uno de entre varias posibilidades. En esta tesis se ha trabajado en aplicaciones de regularización para obtener representaciones dispersas, donde sólo se usa un subconjunto de las entradas. En particular, la regularización L1 juega un papel clave en la búsqueda de dicha dispersión. La mayor parte de las contribuciones presentadas en la tesis giran alrededor de la regularización L1, aunque también se exploran otras formas de regularización (que igualmente persiguen un modelo disperso). Además de presentar una revisión de la regularización L1 y sus aplicaciones en estadística y aprendizaje de máquina, se ha desarrollado metodología para regresión, clasificación supervisada y aprendizaje de estructura en modelos gráficos. Dentro de la regresión, se ha trabajado principalmente en métodos de regresión local, proponiendo técnicas de diseño del kernel que sean adecuadas a configuraciones de alta dimensionalidad y funciones de regresión dispersas. También se presenta una aplicación de las técnicas de regresión regularizada para modelar la respuesta de neuronas reales. Los avances en clasificación supervisada tratan, por una parte, con el uso de regularización para obtener un clasificador naive Bayes y, por otra parte, con el desarrollo de un algoritmo que usa regularización por grupos de una manera eficiente y que se ha aplicado al diseño de interfaces cerebromáquina. Finalmente, se presenta una heurística para inducir la estructura de redes Bayesianas Gaussianas usando regularización L1 a modo de filtro.

LiDAR simulation in modelled orchards to optimise the use of terretrial laser scanners and derived vegetative measures

Light detection and ranging (LiDAR) technology is beginning to have an impact on agriculture. Canopy volume and/or fruit tree leaf area can be estimated using terrestrial laser sensors based on this technology. However, the use of these devices may have different options depending on the resolution and scanning mode. As a consequence, data accuracy and LiDAR derived parameters are affected by sensor configuration, and may vary according to vegetative characteristics of tree crops. Given this scenario, users and suppliers of these devices need to know how to use the sensor in each case. This paper presents a computer program to determine the best configuration, allowing simulation and evaluation of different LiDAR configurations in various tree structures (or training systems). The ultimate goal is to optimise the use of laser scanners in field operations. The software presented generates a virtual orchard, and then allows the scanning simulation with a laser sensor. Trees are created using a hidden Markov tree (HMT) model. Varying the foliar structure of the orchard the LiDAR simulation was applied to twenty different artificially created orchards with or without leaves from two positions (lateral and zenith). To validate the laser sensor configuration, leaf surface of simulated trees was compared with the parameters obtained by LiDAR measurements: the impacted leaf area, the impacted total area (leaves and wood), and th impacted area in the three outer layers of leaves.

Laser Driven Neutron Sources: Characteristics, Applications and Prospects

The basics of laser driven neutron sources, properties and possible applications are discussed. We describe the laser driven nuclear processes which trigger neutron generation, namely, nuclear reactions induced by laser driven ion beam (ion n), thermonuclear fusion by implosion and photo-induced nuclear (gamma n) reactions. Based on their main properties, i.e. point source (<100 μm) and short durations (< ns), different applications are described, such as radiography, time-resolved spectroscopy and pump-probe experiments. Prospects on the development of laser technology suggest that, as higher intensities and higher repetition rate lasers become available (for example, using DPSSL technology), laser driven methodologies may provide neutron fluxes comparable to that achieved by accelerator driven neutron sources in the near future.