Improved Techniques for Acquisition and Analysis of Dynamic Contrast-Enhanced Magnetic Resonance Imaging for Detecting Vascular Permeability in the Central Nervous System

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a noninvasive technique for quantitative assessment of the integrity of blood-brain barrier and blood-spinal cord barrier (BSCB) in the presence of central nervous system pathologies. However, the results of DCE-MRI show substantial variability. The high variability can be caused by a number of factors including inaccurate T1 estimation, insufficient temporal resolution and poor contrast-to-noise ratio. My thesis work is to develop improved methods to reduce the variability of DCE-MRI results. To obtain fast and accurate T1 map, the Look-Locker acquisition technique was implemented with a novel and truly centric k-space segmentation scheme. In addition, an original multi-step curve fitting procedure was developed to increase the accuracy of T1 estimation. A view sharing acquisition method was implemented to increase temporal resolution, and a novel normalization method was introduced to reduce image artifacts. Finally, a new clustering algorithm was developed to reduce apparent noise in the DCE-MRI data. The performance of these proposed methods was verified by simulations and phantom studies. As part of this work, the proposed techniques were applied to an in vivo DCE-MRI study of experimental spinal cord injury (SCI). These methods have shown robust results and allow quantitative assessment of regions with very low vascular permeability. In conclusion, applications of the improved DCE-MRI acquisition and analysis methods developed in this thesis work can improve the accuracy of the DCE-MRI results.

Current and potential water erosion estimation with RUSLE3D in Castellon province (Spain)

The purpose of this study was the estimation of current and potential water erosion rates in Castellon Province (Spain) using RUSLE3D (Revised Universal Soil Loss Equation-3D) model with Geographical Information System (GIS) support. RUSLE3D uses a new methodology for topographic factor estimation (LS factor) based on the impact of flow convergence allowing better assessment of sediment distribution detached by water erosion. In RUSLE3D equation, the effect that vegetation cover has on soil erosion rate is reflected by the C factor. Potential erosion indicates soil erosion rate without considering C factor in RUSLE3D equation. The results showed that 57% of estimated current erosion does not exceed 10 t/ha.year (low erosion). In the case of potential erosion rates, 5% of the area of Castellon Province does not exceed 10 t/ha.year but 55% exceed 200 t/ha.year. Based on these results, the current vegetation cover of Castellon Province is adequate but needs to be conserved to avoid an increase in the current soil erosion rates as shown by potential erosion rates.

Respiration and ingestion rates of calanoid copepod in the northern Benguela Current System measured ex situ during the RSS Discovery D356 cruise in 2010

Respiration rates of 16 calanoid copepod species from the northern Benguela upwelling system were measured on board RRS Discovery in September/October 2010 to determine their energy requirements and assess their significance in the carbon cycle. Copepod species were sampled by different net types. Immediately after the hauls, samples were sorted to species and stages (16 species; females, males and C5 copepodids) according to Bradford-Grieve et al. (1999). Specimens were kept in temperature-controlled refrigerators for at least 12 h before they were used in experiments. Respiration rates of different copepod species were measured onboard by optode respirometry (for details see Köster et al., 2008) with a 10-channel optode respirometer (PreSens Precision Sensing Oxy-10 Mini, Regensburg, Germany) under simulated in situ conditions in temperature-controlled refrigerators. Experiments were run in gas-tight glass bottles (12-13 ml). For each set of experiments, two controls without animals were measured under exactly the same conditions to compensate for potential bias. The number of animals per bottle depended on the copepods size, stage and metabolic activity. Animals were not fed during the experiments but they showed natural species-specific movements. Immediately after the experiments, all specimens were deep-frozen at - 80 °C for later dry mass determination (after lyophilisation for 48 h) in the home lab. The carbon content (% of dry mass) of each species was measured by mass-spectrometry in association with stable isotope analysis and body dry mass was converted to units of carbon. For species without available carbon data, the mean value of all copepod species (44% dry mass) was applied. For the estimation of carbon requirements of copepod species, individual oxygen consumption rates were converted to carbon units, assuming that the expiration of 1 ml oxygen mobilises 0.44 mg of organic carbon by using a respiratory quotient (RQ) of 0.82 for a mixed diet consisting of proteins (RQ = 0.8-1.0), lipids (RQ = 0.7) and carbohydrates (RQ = 1.0) (Auel and Werner, 2003). The carbon ingestion rates were calculated using the energy budget and the potential maximum ingestion rate approach. To allow for physiological comparisons of respiration rates of deep- and shallow-living copepod species without the effects of ambient temperature and different individual body mass, individual respiration rates were temperature- (15°C, Q10=2) and size-adjusted. The scaling coefficient of 0.76 (R2=0.556) is used for the standardisation of body dry mass to 0.3 mg (mean dry mass of all analysed copepods), applying the allometric equation R= (R15°C/M0.76)×0.30.76, where R is respiration and M is individual dry mass in mg.

Integrated program debugging, verification, and optimization using abstract interpretation (and the Ciao system preprocessor)

The technique of Abstract Interpretation has allowed the development of very sophisticated global program analyses which are at the same time provably correct and practical. We present in a tutorial fashion a novel program development framework which uses abstract interpretation as a fundamental tool. The framework uses modular, incremental abstract interpretation to obtain information about the program. This information is used to validate programs, to detect bugs with respect to partial specifications written using assertions (in the program itself and/or in system libraries), to generate and simplify run-time tests, and to perform high-level program transformations such as multiple abstract specialization, parallelization, and resource usage control, all in a provably correct way. In the case of validation and debugging, the assertions can refer to a variety of program points such as procedure entry, procedure exit, points within procedures, or global computations. The system can reason with much richer information than, for example, traditional types. This includes data structure shape (including pointer sharing), bounds on data structure sizes, and other operational variable instantiation properties, as well as procedure-level properties such as determinacy, termination, nonfailure, and bounds on resource consumption (time or space cost). CiaoPP, the preprocessor of the Ciao multi-paradigm programming system, which implements the described functionality, will be used to illustrate the fundamental ideas.

Simultaneous 3D object tracking and camera parameter estimation by Bayesian methods and transdimensional MCMC sampling

Multi-camera 3D tracking systems with overlapping cameras represent a powerful mean for scene analysis, as they potentially allow greater robustness than monocular systems and provide useful 3D information about object location and movement. However, their performance relies on accurately calibrated camera networks, which is not a realistic assumption in real surveillance environments. Here, we introduce a multi-camera system for tracking the 3D position of a varying number of objects and simultaneously refin-ing the calibration of the network of overlapping cameras. Therefore, we introduce a Bayesian framework that combines Particle Filtering for tracking with recursive Bayesian estimation methods by means of adapted transdimensional MCMC sampling. Addi-tionally, the system has been designed to work on simple motion detection masks, making it suitable for camera networks with low transmission capabilities. Tests show that our approach allows a successful performance even when starting from clearly inaccurate camera calibrations, which would ruin conventional approaches.

Rapid sizing tool for a low cost university microsatellite structure subsystem

In recent decays university class small satellites are creating many opportunities for space research and professional trainings while at the same time responding to constrained budgets. In this work the main focus is on developing a simple and rapid structural sizing tool considering the main objectives of a low cost university class microsatellite project. In satellite projects, structure subsystem is one of the influential subsystems as a driver of the cost and acceptance of the final design. At the first steps of such projects there is no confirmed data regarding the launch vehicle or even in some cases there is no data for the satellite payload. Due to these facts, developing simple sizing tools at conceptual design phase for obtaining an over view of the effect of different variables is useful before entering complex calculations in detailed design phases. In this study, after developing a simple analytical model of satellite structure subsystem, a design space is evaluated with practical boundaries considering mass and dimensions constraints of such projects. The results are useful to give initial insight to establish the system level structural sizing

Cost and energy efficient reconfigurable embedded platform using Spartan-6 FPGAs

Modern FPGAs with run-time reconfiguration allow the implementation of complex systems offering both the flexibility of software-based solutions combined with the performance of hardware. This combination of characteristics, together with the development of new specific methodologies, make feasible to reach new points of the system design space, and make embedded systems built on these platforms acquire more and more importance. However, the practical exploitation of this technique in fields that traditionally have relied on resource restricted embedded systems, is mainly limited by strict power consumption requirements, the cost and the high dependence of DPR techniques with the specific features of the device technology underneath. In this work, we tackle the previously reported problems, designing a reconfigurable platform based on the low-cost and low-power consuming Spartan-6 FPGA family. The full process to develop the platform will be detailed in the paper from scratch. In addition, the implementation of the reconfiguration mechanism, including two profiles, is reported. The first profile is a low-area and low-speed reconfiguration engine based mainly on software functions running on the embedded processor, while the other one is a hardware version of the same engine, implemented in the FPGA logic. This reconfiguration hardware block has been originally designed to the Virtex-5 family, and its porting process will be also described in this work, facing the interoperability problem among different families.

On-board and Ground Visual Pose Estimation Techniques for UAV Control

In this paper, two techniques to control UAVs (Unmanned Aerial Vehicles), based on visual information are presented. The first one is based on the detection and tracking of planar structures from an on-board camera, while the second one is based on the detection and 3D reconstruction of the position of the UAV based on an external camera system. Both strategies are tested with a VTOL (Vertical take-off and landing) UAV, and results show good behavior of the visual systems (precision in the estimation and frame rate) when estimating the helicopter¿s position and using the extracted information to control the UAV.

Development of low cost photovoltaic sensor for over-tree radiation assessment

The crop diseases sometimes are related to the irradiance that the crop receives. When an experiment requires the measurement of the irradiance, usually it results in an expensive data acquisition system. If it is necessary to check many test points, the use of traditional sensors will increase the cost of the experiment. By using low cost sensors based in the photovoltaic effect, it is possible to perform a precise test of irradiance with a reduced price. This work presents an experiment performed in Ademuz (Valencia, Spain) during September of 2011 to check the validity of low cost sensors based on solar cells.

Using combined static analysis and profiling for logic program execution time estimation

Predicting statically the running time of programs has many applications ranging from task scheduling in parallel execution to proving the ability of a program to meet strict time constraints. A starting point in order to attack this problem is to infer the computational complexity of such programs (or fragments thereof). This is one of the reasons why the development of static analysis techniques for inferring cost-related properties of programs (usually upper and/or lower bounds of actual costs) has received considerable attention.

Some techniques for automated, resource-aware distributed and mobile computing in a multi-paradigm programming system

Distributed parallel execution systems speed up applications by splitting tasks into processes whose execution is assigned to different receiving nodes in a high-bandwidth network. On the distributing side, a fundamental problem is grouping and scheduling such tasks such that each one involves sufñcient computational cost when compared to the task creation and communication costs and other such practical overheads. On the receiving side, an important issue is to have some assurance of the correctness and characteristics of the code received and also of the kind of load the particular task is going to pose, which can be specified by means of certificates. In this paper we present in a tutorial way a number of general solutions to these problems, and illustrate them through their implementation in the Ciao multi-paradigm language and program development environment. This system includes facilities for parallel and distributed execution, an assertion language for specifying complex programs properties (including safety and resource-related properties), and compile-time and run-time tools for performing automated parallelization and resource control, as well as certification of programs with resource consumption assurances and efñcient checking of such certificates.

Program development using abstract interpretation (and the ciao system preprocessor)

The technique of Abstract Interpretation has allowed the development of very sophisticated global program analyses which are at the same time provably correct and practical. We present in a tutorial fashion a novel program development framework which uses abstract interpretation as a fundamental tool. The framework uses modular, incremental abstract interpretation to obtain information about the program. This information is used to validate programs, to detect bugs with respect to partial specifications written using assertions (in the program itself and/or in system librarles), to genérate and simplify run-time tests, and to perform high-level program transformations such as múltiple abstract specialization, parallelization, and resource usage control, all in a provably correct way. In the case of validation and debugging, the assertions can refer to a variety of program points such as procedure entry, procedure exit, points within procedures, or global computations. The system can reason with much richer information than, for example, traditional types. This includes data structure shape (including pointer sharing), bounds on data structure sizes, and other operational variable instantiation properties, as well as procedure-level properties such as determinacy, termination, non-failure, and bounds on resource consumption (time or space cost). CiaoPP, the preprocessor of the Ciao multi-paradigm programming system, which implements the described functionality, will be used to illustrate the fundamental ideas.

Program analysis, debugging and optimization using the ciao system preprocessor

We present a tutorial overview of Ciaopp, the Ciao system preprocessor. Ciao is a public-domain, next-generation logic programming system, which subsumes ISO-Prolog and is specifically designed to a) be highly extensible via librarles and b) support modular program analysis, debugging, and optimization. The latter tasks are performed in an integrated fashion by Ciaopp. Ciaopp uses modular, incremental abstract interpretation to infer properties of program predicates and literals, including types, variable instantiation properties (including modes), non-failure, determinacy, bounds on computational cost, bounds on sizes of terms in the program, etc. Using such analysis information, Ciaopp can find errors at compile-time in programs and/or perform partial verification. Ciaopp checks how programs cali system librarles and also any assertions present in the program or in other modules used by the program. These assertions are also used to genérate documentation automatically. Ciaopp also uses analysis information to perform program transformations and optimizations such as múltiple abstract specialization, parallelization (including granularity control), and optimization of run-time tests for properties which cannot be checked completely at compile-time. We illustrate "hands-on" the use of Ciaopp in all these tasks. By design, Ciaopp is a generic tool, which can be easily tailored to perform these and other tasks for different LP and CLP dialects.