Measurement of tissue optical properties in a wide spectral range: a review

A distinctive feature of this review is a critical analysis of methods and results of measurements of the optical properties of tissues in a wide spectral range from deep UV to terahertz waves. Much attention is paid to measurements of the refractive index of biological tissues and liquids, the knowledge of which is necessary for the effective application of many methods of optical imaging and diagnostics. The optical parameters of healthy and pathological tissues are presented, and the reasons for their differences are discussed, which is important for the discrimination of pathologies and the demarcation of their boundaries. When considering the interaction of terahertz radiation with tissues, the concept of an effective medium is discussed, and relaxation models of the effective optical properties of tissues are presented. Attention is drawn to the manifestation of the scattering properties of tissues in the THz range and the problems of measuring the optical properties of tissues in this range are discussed. In conclusion, a method for the dynamic analysis of the optical properties of tissues under optical clearing using an application of immersion agents is presented. The main mechanisms and technologies of optical clearing, as well as examples of the successful application for differentiation of healthy and pathological tissues, are analyzed

Simulation and Design of an UWB Imaging System for Breast Cancer Detection

Breast cancer is the most frequently diagnosed cancer among women. In recent years, the mortality rate due to this disease is greatly decreased thanks to both enormous progress in cancer research, and screening campaigns which have allowed the increase in the number of early diagnoses of the disease. In fact, if the tumor is identied in its early stage, e.g. when it has a diameter of less than one centimeter, the possibility of a cure can reach 93%. However, statistics show that more young aged women are suered breast cancer. The goal of screening exams for early breast cancer detection is to nd cancers before they start to cause symptoms. Regular mass screening of all women at risk is a good option to achieve that. Instead of meeting very high diagnostic standards, it is expected to yield an early warning, not a denitive diagnosis. In the last decades, X-ray mammography is the most ecient screening technique. However, it uses ionizing radiation and, therefore, should not be used for frequent check-ups. Besides, it requires signicant breast compression, which is often painful. In this scenario many alternative technologies were developed to overcome the limitations of mammography. Among these possibilities, Magnetic Resonance Imaging (MRI) is too expensive and time-consuming, Ultrasound is considered to be too operatordependent and low specicity, which are not suitable for mass screening. Microwave imaging techniques, especially Ultra WideBand (UWB) radar imaging, is the most interesting one. The reason of this interest relies on the fact that microwaves are non-ionizing thus permitting frequent examinations. Moreover, it is potentially lowcost and more ecient for young women. Since it has been demonstrated in the literatures that the dielectric constants between cancerous and healthy tissues are quite dierent, the technique consists in illuminating these biological tissues with microwave radiations by one or more antennas and analyzing the re ected signals. An UWB imaging system consists of transmitters, receivers and antennas for the RF part, the transmission channel and of a digital backend imaging unit for processing the received signals. When an UWB pulse strikes the breast, the pulse is re ected due to the dielectric discontinuity in tissues, the bigger the dierence, the bigger the backscatter. The re ected signals are acquired and processed to create the energy maps. This thesis aims to develop an UWB system at high resolution for the detection of carcinoma breast already in its initial phase. To favor the adoption of this method in screening campaigns, it is necessary to replace the expensive and bulky RF instrumentation used so far with ad-hoc designed circuits and systems. In order to realize that, at the very beginning, the overall system environment must be built and veried, which mainly consists of the transmission channel{the breast model and the imaging unit. The used transmission channel data come from MRI of the prone patient. In order to correctly use this numerical model, a simulator was built, which was implemented in Matlab, according to the Finite-Dierence-Time- Domain (FDTD) method. FDTD algorithm solves the electric and magnetic eld both in time and in space, thus, simulates the propagation of electromagnetic waves in the breast model. To better understand the eect of the system non-idealities, two 2D breast models are investigated, one is homogeneous, the other is heterogeneous. Moreover, the modeling takes into account all critical aspects, including stability and medium dispersion. Given the types of tissues under examination, the frequency dependence of tissue dielectric properties is incorporated into wideband FDTD simulations using Debye dispersion parameters. A performed further study is in the implementation of the boundary conditions. The Convolution Perfectly Matched Layer (CPML) is used to implement the absorbing boundaries. The objective of the imaging unit is to obtain an energy map representing the amount of energy re ected from each point of the breast, by recombining the sampled backscattered signals. For this purpose, the study has been carried out on various beamforming in the literature. The basic idea is called as "delay and sum", which is to align the received signals in such a way as to focus a given point in space and then add up all the contributions, so as to obtain a constructive interference at that point if this is a diseased tissue. In this work, Microwave Imaging via Space Time (MIST) Beamforming algorithm is applied, which is based on the above principle and add more elaborations of the signals in order to make the algorithm less sensitive to propagation phenomena in the medium and to the non-idealities of the system. It is divided into two distinct steps: the rst step, called SKin Artifact Removal (SKAR), takes care of removing the contributions from the signal caused by the direct path between the transmitter and receiver, the re ection of skin, as they are orders of magnitude higher compared to the re ections caused by cancers; the second step, which is BEAmForming (BEAF), performs the algorithm of reconstruction by forming a weighted combination of time delayed version of the calibrated re ected signals. As discussed above, more attention must be paid on the implementation of the ad-hoc integration circuits. In this scenario, due to the strict requirements on the RF receiver component, two dierent approaches of the implementation of the RF front-end, Direct Conversion (DC) receiver and Coherent Equivalent Time Sampling (CETS) receiver are compared. They are modeled behaviorally and the eects of various impairments, such as thermal, jitter, and phase noise, as well as phase inaccuracies, non-linearity, ADC quantization noise and distortion, on energy maps and on quantitative metrics such as SCR and SMR are evaluated. Dierential Gaussian pulse is chosen as the exciting source. Results show that DC receiver performs higher sensitivity to phase inaccuracies, which makes it less robust than the CETS receiver. Another advantage of the CETS receiver is that it can work in time domain with UWB pulses, other than in frequency domain with stepped frequency continuous waves like the DC one, which reduces the acquisition time without impacting the performance. Based on the results of the behavioral simulations, low noise amplier (LNA) and Track and Hold Amplier (THA) can be regarded as the most critical parts for the proposed CETS receiver, as well as the UWB antenna. This work therefore focuses on their hardware implementations. The LNA, which shows critical performance limitation at bandwidth and noise gure of receiver, has been developed based on common-gate conguration. And the THA based on Switched Source Follower (SSF) scheme has been presented and improved to obtain high input bandwidth, high sampling rate, high linearity and low power consumption. LNA and THA are implemented in CMOS 130nm technology and the circuit performance evaluation has been taken place separately and together. The small size UWB wide-slot antenna is designed and simulated in HFSS. Finally, in order to evaluate the eect of the implemented transistor level components on system performance, a multi-resolution top-down system methodology is applied. Therfore, the entire ow is analyzed for dierent levels of the RF frontend. Initially the system components are described behaviorally as ideal elements. The main activity consists in the analysis and development of the entire frontend system, observing and complementing each other blocks in a single ow simulation, clear and well-dened in its various interfaces. To achieve that the receiver is modeled and analyzed using VHDL-AMS language block by block, moreover, the impact of quantization, noise, jitter, and non-linearity is also evaluated. At last, the behavioral description of antenna, LNA and THA is replaced with a circuit-level one without changing the rest of the system, which permits a system-level assessment of low-level issues

Investigation of Heat Therapies using Multi-Scale Models and Statistical Methods

Ph.DDOCTOR OF PHILOSOPH

MICROELECTRODE ARRAY FOR CAPACITIVE TRANSDUCTION OF RETINAL RESPONSES

Neural degenerative diseases and traumatic injuries to the eye affect millions of people worldwide, motivating the development of neural prosthetic interfaces to restore sensory or motor function in affected individuals. Advances in neural sensing and stimulation interface technology will allow a more comprehensive understanding of neural function while leading to the development of hybrid biological-electronic sensor devices for robust, functioning neural prosthetic systems. Current techniques of neural activity sensing employ multi-electrode arrays (MEAs) that typically incorporate metal electrodes and measure currents via an electrochemical junction, leading to corrosion and charge transfer across the electrode-tissue interface. High-density neural interface technology will require active circuitry within the implant; the device must withstand corrosion and induce minimal damage at the electrode/tissue interface. The work shown here demonstrates a prototype neural interface device based on capacitive coupling through hafnium oxide encapsulation of a novel 3D device architecture, advancing neural sensing technology toward long-term implantable neural interfaces. The functionalization of biosensors interfaced with neural tissue is important to ensure that the active components of the sensor are fully protected from the surrounding biological environment. Self-assembled monolayers (SAMs) have been extensively studied as coatings for implantable devices due to their ability to tailor surface properties and relative ease of film formation. We report a series of studies aimed at investigating the stability of phosphonate self-assembled monolayers, octdecylphosphonic acid (ODPA) or perfluorophosphonic acid (PFPA) on various oxide surfaces (SiO2, TiO2, Al2O3 and HfO2) to serve as the biotic-abiotic interface of the prototype neural device developed here. The monolayers were deposited by a series of techniques including self-assembly from solution, tethering by aggregation and growth and Langmuir-Blodgett (LB). SAMs prepared by LB were primarily used in our stability investigations because they were found to be the most uniform and reproducible. All films deposited on oxide-coated substrates were characterized by means of water contact angle measurements, spectroscopic ellipsometry, X-ray photoelectron spectroscopy (XPS) and atomic force microscopy (AFM). XPS data conclusively showed covalent phosphonate formation on all substrates except SiO2, which had background spectra that interfered with the data analysis. AFM images of SAMs formed on SiO2 and TiO2 showed significant surface reorganization upon exposure to water within 30 minutes. SAMs formed on Al2O3 and HfO2 were much more stable upon exposure to water. PFPA SAMs on HfO2 were found to be the most stable SAMs studied here in either water or phosphate buffer at room temperature. This is the first report of a SAM-oxide system showing stability for an extended period of time, greater than 20 days. These data suggest that phosphonate SAMs should be considered for implantable neural devices that require longer-term stability under aqueous conditions. To examine the encoding and processing of information by networks of neurons, microelectrode arrays (MEAs) have been developed and applied, but evolving scientific questions and biomedical applications require higher density sampling and wider spatial coverage. The integration of 3D electrodes can provide closer contact with neurons to facilitate detection and resolution of single cell action potentials. The fabrication methods implemented here allows reliable fabrication of a novel MEA consisting of probes with dimensions of a few microns, unlike most other approaches to 3D electrode arrays, which produce structures on the scale of tens of microns or more. The device incorporates over 3,800 micro pillar electrodes, grouped into 60 independent sensors for compatibility with existing electronics, spread over an area of 750 μm2; each sensor site consists of an 8x8 array of micropillars, interconnected by a lead to an output pad of the device. Individual 3D pillars are 3 μm in diameter with a height of 8 μm. Our experience has suggested that such microstructured probes can achieve more intimate contact with the surface of neural tissue, and enhance the quality of neuronal recordings. Electrochemical impedance spectroscopy (EIS) at 1 kHz measured average magnitude and phase shift of 710 W and 17°, respectively, for a single sensor site. These values confirm the robustness of our fabrication process for developing highly conductive 3D microelectrodes. The results shown here demonstrate high-density, three-dimensional microfabrication technology that was applied to the development of an advanced capacitive sensor array for neural tissue. Applications in sensing technology now require electro-neural interface devices to withstand corrosion and induce minimal damage at the electrode/tissue interface. We have developed a platform suitable for hermetic sealing and have shown encapsulation through atomic layer deposition of hafnium oxide over the active components of the device to overcome the direct current limitations of existing MEA technology. EIS was used to study the oxide deposition on the 3D micro pillar sensor array to ensure a pinhole-free dielectric coating. The characteristic impedance magnitudes increase up to 3 orders of magnitude upon oxide deposition and the phase indicates fully capacitive sensor sites. The fabrication process and electrochemical impedance study shown here, demonstrates the usefulness of such techniques for building high-density 3D arrays that can be fully encapsulated with a protective dielectric coating. This work advances the technology towards capacitive sensing of retinal neurons with a robust, non-invasive sensing device. Sensing retinal neurons with the 3D micropillar array developed here was performed for direct current and capacitive configurations of the device. Electroretinograms (ERGs) were recorded and the overall performance of the device was analyzed. The devices showed good consistency across all 60 Pt electrode clusters during characterization and when interfaced with retinal tissue. ERGs were recorded by more than 80% of the direct current electrode sites and the performance was evenly distributed around the mean response. This performance surpasses previous reports of 3D electrode arrays interfaced with retinal tissue, where typically 1-6 electrode signals are recorded successfully. Encapsulation of the device platform was achieved and successful recordings of ERG signals were shown. This work is the first report of sensing the overall electrical behavior of retinal tissue with a coupled capacitive MEA

Computational studies of drug-binding kinetics

The drug-receptor binding kinetics are defined by the rate at which a given drug associates with and dissociates from its binding site on its macromolecular receptor. The lead optimization stage of drug discovery programs usually emphasizes optimizing the affinity (as described by the equilibrium dissociation constant, Kd) of a drug which depends on the strength of its binding to a specific target. Since affinity is optimized under equilibrium conditions, it does not always ensures higher potency in vivo. There has been a growing consensus that, in addition to Kd, kinetic parameters (kon and koff ) should be optimized to improve the chances of a good clinical outcome. However, current understanding of the physicochemical features that contribute to differences in binding kinetics is limited. Experimental methods that are used to determine kinetic parameters for drug binding and unbinding are often time consuming and labor-intensive. Therefore, robust, high-throughput in silico methods are needed to predict binding kinetic parameters and to explore the mechanistic determinants of drug-protein binding. As the experimental data on drug-binding kinetics is continuously growing and the number of crystallographic structures of ligand-receptor complexes is also increasing, methods to compute three dimensional (3D) Quantitative-Structure-Kinetics relationships (QSKRs) offer great potential for predicting kinetic rate constants for new compounds. COMparative BINding Energy(COMBINE) analysis is one example of such approach that was developed to derive target-specific scoring functions based on molecular mechanics calculations. It has been used extensively to predict properties such as binding affinity, target selectivity, and substrate specificity. In this thesis, I made the first application of COMBINE analysis to derive Quantitative Structure-Kinetics Relationships (QSKRs) for the dissociation rates. I obtained models for koff of inhibitors of HIV-1 protease and heat shock protein 90 (HSP90) with very good predictive power and identified the key ligand-receptor interactions that contribute to the variance in binding kinetics. With technological and methodological advances, the use of all-atom unbiased Molecular Dynamics (MD) simulations can allow sampling upto the millisecond timescale and investigation of the kinetic profile of drug binding and unbinding to a receptor. However, the residence times of drug-receptor complexes are usually longer than the timescales that are feasible to simulate using conventional molecular dynamics techniques. Enhanced sampling methods can allow faster sampling of protein and ligand dynamics, thereby resulting in application of MD techniques to study longer timescale processes. I have evaluated the application of Tau-Random Acceleration Molecular Dynamics (Tau-RAMD), an enhanced sampling method based on MD, to compute the relative residence times of a series of compounds binding to Haspin kinase. A good correlation (R2 = 0.86) was observed between the computed residence times and the experimental residence times of these compounds. I also performed interaction energy calculations, both at the quantum chemical level and at the molecular mechanics level, to explain the experimental observation that the residence times of kinase inhibitors can be prolonged by introducing halogen-aromatic pi interactions between halogen atoms of inhibitors and aromatic residues at the binding site of kinases. I determined different energetic contributions to this highly polar and directional halogen-bonding interaction by partitioning the total interaction energy calculated at the quantum-chemical level into its constituent energy components. It was observed that the major contribution to this interaction energy comes from the correlation energy which describes second-order intermolecular dispersion interactions and the correlation corrections to the Hartree-Fock energy. In addition, a protocol to determine diffusional kon rates of low molecular weight compounds from Brownian Dynamics (BD) simulations of protein-ligand association was established using SDA 7 software. The widely studied test case of benzamidine binding to trypsin was used to evaluate a set of parameters and a robust set of optimal parameters was determined that should be generally applicable for computing the diffusional association rate constants of a wide range of protein-ligand binding pairs. I validated this protocol on inhibitors of several targets with varying complexity such as Human Coagulation Factor Xa, Haspin kinase and N1 Neuraminidase, and the computed diffusional association rate constants were compared with the experiments. I contributed to the development of a toolbox of computational methods: KBbox (http://kbbox.h-its.org/toolbox/), which provides information about various computational methods to study molecular binding kinetics, and different computational tools that employ them. It was developed to guide researchers on the use of the different computational and simulation approaches available to compute the kinetic parameters of drug-protein binding

Nonlinear Dynamic Modeling, Simulation And Characterization Of The Mesoscale Neuron-electrode Interface

Extracellular neuroelectronic interfacing has important applications in the fields of neural prosthetics, biological computation and whole-cell biosensing for drug screening and toxin detection. While the field of neuroelectronic interfacing holds great promise, the recording of high-fidelity signals from extracellular devices has long suffered from the problem of low signal-to-noise ratios and changes in signal shapes due to the presence of highly dispersive dielectric medium in the neuron-microelectrode cleft. This has made it difficult to correlate the extracellularly recorded signals with the intracellular signals recorded using conventional patch-clamp electrophysiology. For bringing about an improvement in the signalto-noise ratio of the signals recorded on the extracellular microelectrodes and to explore strategies for engineering the neuron-electrode interface there exists a need to model, simulate and characterize the cell-sensor interface to better understand the mechanism of signal transduction across the interface. Efforts to date for modeling the neuron-electrode interface have primarily focused on the use of point or area contact linear equivalent circuit models for a description of the interface with an assumption of passive linearity for the dynamics of the interfacial medium in the cell-electrode cleft. In this dissertation, results are presented from a nonlinear dynamic characterization of the neuroelectronic junction based on Volterra-Wiener modeling which showed that the process of signal transduction at the interface may have nonlinear contributions from the interfacial medium. An optimization based study of linear equivalent circuit models for representing signals recorded at the neuron-electrode interface subsequently iv proved conclusively that the process of signal transduction across the interface is indeed nonlinear. Following this a theoretical framework for the extraction of the complex nonlinear material parameters of the interfacial medium like the dielectric permittivity, conductivity and diffusivity tensors based on dynamic nonlinear Volterra-Wiener modeling was developed. Within this framework, the use of Gaussian bandlimited white noise for nonlinear impedance spectroscopy was shown to offer considerable advantages over the use of sinusoidal inputs for nonlinear harmonic analysis currently employed in impedance characterization of nonlinear electrochemical systems. Signal transduction at the neuron-microelectrode interface is mediated by the interfacial medium confined to a thin cleft with thickness on the scale of 20-110 nm giving rise to Knudsen numbers (ratio of mean free path to characteristic system length) in the range of 0.015 and 0.003 for ionic electrodiffusion. At these Knudsen numbers, the continuum assumptions made in the use of Poisson-Nernst-Planck system of equations for modeling ionic electrodiffusion are not valid. Therefore, a lattice Boltzmann method (LBM) based multiphysics solver suitable for modeling ionic electrodiffusion at the mesoscale neuron-microelectrode interface was developed. Additionally, a molecular speed dependent relaxation time was proposed for use in the lattice Boltzmann equation. Such a relaxation time holds promise for enhancing the numerical stability of lattice Boltzmann algorithms as it helped recover a physically correct description of microscopic phenomena related to particle collisions governed by their local density on the lattice. Next, using this multiphysics solver simulations were carried out for the charge relaxation dynamics of an electrolytic nanocapacitor with the intention of ultimately employing it for a simulation of the capacitive coupling between the neuron and the v planar microelectrode on a microelectrode array (MEA). Simulations of the charge relaxation dynamics for a step potential applied at t = 0 to the capacitor electrodes were carried out for varying conditions of electric double layer (EDL) overlap, solvent viscosity, electrode spacing and ratio of cation to anion diffusivity. For a large EDL overlap, an anomalous plasma-like collective behavior of oscillating ions at a frequency much lower than the plasma frequency of the electrolyte was observed and as such it appears to be purely an effect of nanoscale confinement. Results from these simulations are then discussed in the context of the dynamics of the interfacial medium in the neuron-microelectrode cleft. In conclusion, a synergistic approach to engineering the neuron-microelectrode interface is outlined through a use of the nonlinear dynamic modeling, simulation and characterization tools developed as part of this dissertation research

Modelado de las propiedades dieléctricas del suelo. Aplicación en el diseño de sensores para sistemas de control en agricultura de precisión

[SPA] Esta tesis doctoral se presenta bajo la modalidad de compendio de publicaciones. El agua es una sustancia clave para el desarrollo de la vida en La Tierra. Es por ello que la búsqueda de oportunidad de vida en otros planetas y satélites se basa en la presencia de agua en los mismos. La gestión ecológica del agua es necesaria para la sostenibilidad de los ecosistemas. Uno de los ecosistemas más amplios y donde el agua juega un papel más importante es el suelo, que alberga multitud de variedades de microorganismos cuya actividad, en parte resultante en la generación de nutrientes para el desarrollo de las especies vegetales, es totalmente dependiente del contenido de agua en el suelo. En zonas áridas y semiáridas, como es el caso de la cuenca Mediterránea, la escasez de agua supone un grave problema a la hora de gestionar los pocos recursos hídricos disponibles. En este caso, donde las condiciones geográficas son idóneas para el desarrollo de la agricultura, las soluciones pasan por una optimización de las técnicas de riego y un mayor control sobre los recursos hídricos. En este sentido, las técnicas de riego deficitario controlado se han mostrado exitosas en la reducción de la dotación hídrica a los cultivos en fases no críticas. Sin embargo, para realizar una aplicación prudente y eficiente de las mismas, resulta necesario monitorizar el estado hídrico de los cultivos, con el objetivo de que éstos no alcancen situaciones de estrés irreversible en términos de producción o estado vegetativo. Los indicadores que mayor información aportan sobre el estado hídrico de la planta suelen estar relacionados con variables medibles a partir de la propia planta, pero que son difícilmente automatizables debido a las operaciones de manejo asociadas. Este es el caso del potencial hídrico de tallo a mediodía medido con cámara de presión, considerado hasta la fecha como el indicador más fiable del estado hídrico de los cultivos en general. Es por ello que, para lograr una monitorización continua de esta variable, se busquen otras variables del continuo suelo-planta-atmósfera que puedan estar relacionadas y a partir de las cuales obtener una estimación indirecta. El suelo es la matriz de donde la planta adquiere la mayor parte del agua y los nutrientes que necesita para realizar la fotosíntesis. La relación entre el estado hídrico del suelo y el estado hídrico de los cultivos está más que demostrada. Sin embargo, la precisión alcanzada en los modelos de correlación entre ambos estados requiere de una mejora considerable para hacer un uso realmente fiable de los mismos, y esta mejora no solo pasa por encontrar mejores métodos de correlación, sino también por mejorar la precisión de las medidas obtenidas del suelo. Para monitorizar el estado hídrico del suelo, existen diversas metodologías que ofrecen parámetros medibles como el contenido de agua. El método de medida más extendido para monitorizar el contenido de agua en el suelo es a través del uso de sensores dieléctricos. Sin embargo, la precisión de los mismos está sujeta a diversos factores, entre ellos las características propias del suelo donde se instalan y su coste, relativamente alto para el pequeño y mediano agricultor, condicionando una implantación extensiva de la Agricultura de Precisión y limitando a veces la aplicación de algunos desarrollos únicamente a trabajos de investigación. Esta tesis, elaborada bajo la modalidad de compendio de publicaciones, aborda a través de cuatro artículos científicos la propuesta de soluciones accesibles para la medida del estado hídrico del suelo, con especial enfoque en el contenido de agua; explora las limitaciones y retos asociados con la calibración de los sensores dieléctricos de suelo; participa en la generación de nuevos conocimientos y propuestas para un mejor entendimiento del comportamiento del agua en el suelo y de su interacción con las ondas electromagnéticas; y establece nuevos enfoques y modelos que mejoran la predicción del estado hídrico de los cultivos a partir de medidas indirectas y automatizables en suelo y atmósfera. [ENG] This doctoral dissertation has been presented in the form of thesis by publication. Water is a fundamental substance for the development of life on Earth. That is why the search for life on other planets and satellites is based on the presence of water on them. Ecological water management is necessary for the sustainability of ecosystems. One of the most extensive ecosystems where water plays a major role is soil, which hosts a large variety of micro-organisms whose activity, partly resulting in the generation of nutrients for the development of plant species, is totally dependent on the water content of the soil. In arid and semi-arid regions, as it is the case in the Mediterranean basin, water scarcity is a serious problem when it comes to managing the few water resources available. In this case, where the geographical conditions are ideal for the development of agriculture, the solutions involve optimization of irrigation techniques and greater control over water resources. In this sense, regulated deficit irrigation strategies have proven to be successful in reducing the water supply to crops in non-critical periods. However, in order to apply them prudently and efficiently, it is necessary to monitor the water status of the crops, so that they do not reach irreversible stress situations in terms of yield or vegetative state. The indicators that provide the highest amount of information on the water status of the plant are usually related to variables that can be measured from the plant itself, but which are difficult to automate due to the labor and time-consuming associated operations. This is the case of the midday stem water potential measured with a pressure chamber, considered to date to be the most reliable indicator of the crop's water status in general. In order to achieve a continuous monitoring of this variable, it is necessary to look for other variables of the soil-plant-atmosphere continuum that may be related and from which to obtain an indirect estimate. Soil is the matrix from which the plant acquires most of the water and nutrients it needs for photosynthesis. The relationship between soil water status and crop water status is well established. However, the accuracy achieved in the correlation models between the two requires considerable improvement to make a truly reliable use of them, and this improvement is not only to find better correlation methods, but also to improve the accuracy of the measurements obtained from the soil. To monitor soil water status, there are several methodologies that provide measurable parameters such as water content. The most widespread measurement method for monitoring soil water content is through the use of dielectric sensors. However, the accuracy of these sensors is subject to various factors, including the characteristics of the soil where they are installed, and their relatively high cost for small and medium-sized farmers, conditioning the extensive implementation of precision agriculture and sometimes limiting the application of some developments only to research work. This thesis, elaborated under the modality of a compendium of publications, addresses through four scientific articles the proposal of affordable solutions for the measurement of soil water status, with special focus on water content; it explores the limitations and challenges associated with the calibration of soil dielectric sensors; participates in the generation of new insights and proposals for a better understanding of the behavior of water in soil and its interaction with electromagnetic waves; and establishes new approaches and models that improve the prediction of crop water status from indirect and automatable measurements in soil and atmosphere.Esta tesis doctoral se presenta bajo la modalidad de compendio de publicaciones. Está formada por un total de cuatro artículos: Article I. González-Teruel, J.D., Torres-Sánchez, R., Blaya-Ros, P.J., Toledo-Moreo, A.B., Jiménez-Buendía, M., Soto-Valles, F., 2019. Design and Calibration of a Low-Cost SDI-12 Soil Moisture Sensor. Sensors, 19, 491. DOI: 10.3390/s19030491 - Article II. González-Teruel, J.D., Jones, S.B., Soto-Valles, F., Torres-Sánchez, R., Lebron, I., Friedman, S.P., Robinson, D.A., 2020. Dielectric Spectroscopy and Application of Mixing Models Describing Dielectric Dispersion in Clay Minerals and Clayey Soils. Sensors, 20, 6678. DOI: 10.3390/s20226678 Article III. González-Teruel, J.D., Jones, S.B., Robinson, D.A., Giménez-Gallego, J., Zornoza, R., Torres-Sánchez, R., 2022. Measurement of the broadband complex permittivity of soils in the frequency domain with a low-cost Vector Network Analyzer and an Open-Ended coaxial probe. Computers and Electronics in Agriculture, 195, 106847. DOI: 10.1016/J.COMPAG.2022.106847 Article IV. González-Teruel, J.D., Ruiz-Abellon, M.C., Blanco, V., Blaya-Ros, P.J., Domingo, R., Torres-Sánchez, R., 2022. Prediction of Water Stress Episodes in Fruit Trees Based on Soil and Weather Time Series Data. Agronomy, 12, 1422. DOI: 10.3390/agronomy12061422Escuela Internacional de Doctorado de la Universidad Politécnica de CartagenaUniversidad Politécnica de CartagenaPrograma de Doctorado en Tecnologías Industriale

Design of Miniaturized Antipodal Vivaldi Antennas and a Microwave Head Imaging System for the Detection of Blood Clots in the Brain

Traditional brain imaging modalities, for example, MRI, CT scan, X-ray, etc. can provide precise and high-resolution images of the brain for diagnosing lesions, tumors or clots inside the brain. However, these modalities require bulky and expensive test setups accessible only at specialized diagnostic centers, and hence may not be suitable or affordable to many patients. Furthermore, the inherent health risks limit the usability of these modalities for frequent monitoring. Microwave imaging is deemed a promising alternative due to its being cost-effective, portable, non-ionizing, non-intrusive. Therefore, this work aims to design an effective microwave head imaging system for the detection of blood clots inside the brain. Two miniaturized antipodal Vivaldi antenna designs are proposed which can provide wideband operation covering the low microwave frequency range (within 1 - 6 GHz) while having electrically small dimensions, directional radiation pattern with reasonable gain, and without requiring immersion in any matching/ coupling liquid. A head imaging system is presented which utilizes a quarter-head scanning approach, to reconstruct four images of the brain by scanning four quarters of the head, using the designed antipodal wideband Vivaldi antenna. A numerical brain model, with and without the presence of blood clot, is simulated using the proposed head-imaging system. At each quarter, the antenna is placed at nine different positions for scanning. The reflected signal at each position is processed and using confocal microwave imaging technique four images of the brain are reconstructed. A comparison is made among the four images in terms of their intensities, for the detection and approximate location of the blood clot inside the brain. The presence of higher intensity regions in any specific quarter of the head demonstrates the presence of a clot and its location and validates the feasibility of the proposed head imaging system using the low frequency wideband Vivaldi antenna