510 research outputs found

    Beam scanning by liquid-crystal biasing in a modified SIW structure

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    A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium

    Advancing clinical evaluation and diagnostics with artificial intelligence technologies

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    Machine Learning (ML) is extensively used in diverse healthcare applications to aid physicians in diagnosing and identifying associations, sometimes hidden, between dif- ferent biomedical parameters. This PhD thesis investigates the interplay of medical images and biosignals to study the mechanisms of aging, knee cartilage degeneration, and Motion Sickness (MS). The first study shows the predictive power of soft tissue radiodensitometric parameters from mid-thigh CT scans. We used data from the AGES-Reykjavik study, correlating soft tissue numerical profiles from 3,000 subjects with cardiac pathophysiologies, hy- pertension, and diabetes. The results show the role of fat, muscle, and connective tissue in the evaluation of healthy aging. Moreover, we classify patients experiencing gait symptoms, neurological deficits, and a history of stroke in a Korean population, reveal- ing the significant impact of cognitive dual-gait analysis when coupled with single-gait. The second study establishes new paradigms for knee cartilage assessment, correlating 2D and 3D medical image features obtained from CT and MRI scans. In the frame of the EU-project RESTORE we were able to classify degenerative, traumatic, and healthy cartilages based on their bone and cartilage features, as well as we determine the basis for the development of a patient-specific cartilage profile. Finally, in the MS study, based on a virtual reality simulation synchronized with a moving platform and EEG, heart rate, and EMG, we extracted over 3,000 features and analyzed their importance in predicting MS symptoms, concussion in female ath- letes, and lifestyle influence. The MS features are extracted from the brain, muscle, heart, and from the movement of the center of pressure during the experiment and demonstrate their potential value to advance quantitative evaluation of postural con- trol response. This work demonstrates, through various studies, the importance of ML technologies in improving clinical evaluation and diagnosis contributing to advance our understanding of the mechanisms associated with pathological conditions.Tölvulærdómur (Machine Learning eða ML) er algjörlega viðurkennt og nýtt í ýmsum heilbrigðisþjónustuviðskiptum til að hjálpa læknunum við að greina og finna tengsl milli mismunandi líffærafræðilegra gilda, stundum dulinna. Þessi doktorsritgerð fjallar um samspil læknisfræðilegra mynda og lífsmerkja til að skoða eðli aldrunar, niðurbrot hnéhringjar og hreyfikerfissjúkdóms (Motion Sickness eða MS). Fyrsta rannsóknin sýnir spárkraft midjubeins-CT-skanna í því að fullyrða staðfest- ar meðalþyngdarlíkön, þar sem gögn úr AGES-Reykjavik-rannsókninni eru tengd við hjarta- og æðafræðilega sjúkdóma, blóðþrýstingsveikindi og sykursýki hjá 3.000 þátt- takendum. Niðurstöðurnar sýna hlutverk fitu, vöðva og tengikjarna í mati á heilbrigð- um öldrun. Þar að auki flokkum við sjúklinga sem upplifa gangvandamál, taugaein- kenni og sögu af heilablóðfalli í kóreanskri þjóð, þar sem einstök gangtaksskoðun er tengd saman við tvískoðun. Önnur rannsóknin setur upp ný tölfræðisfræðileg umhverfisviðmið til matar á hnéhringju með samhengi 2D og 3D mynda sem aflað er úr CT og MRI-skömmtum. Í rauninni höfum við getuð flokkað niðurbrots-, slys- og heilbrigðar hnéhringjur á grundvelli bein- og brjóskmerkja með raun að sækja niðurstöður í umfjöllun um sjúklingar eftir réttu einkasniði. Að lokum, í MS-rannsókninni, notum við myndræn tilraun samþættaða með hreyfan- legan grundvöll og EEG, hjartslátt, EMG þar sem yfir 3.000 aðgerðir eru útfránn og greindir til að átta sig á áhrifum MS, höfuðárás hjá konum sem eru íþróttamenn, lífs- stíl og fleira. Einkenni MS eru aflöguð úr heilanum, vöðvum, hjarta og frá hreyfingum þyngdupunktsins á meðan tilraunin stendur og sýna mög

    Development of polarization-resolved optical scanning microscopy imaging techniques to study biomolecular organizations

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    Light, as electromagnetic radiation, conveys energy through space and time via fluctuations in electric and magnetic fields. This thesis explores the interaction of light and biological structures through polarization-resolved imaging techniques. Light microscopy, and polarization analysis enable the examination of biological entities. Biological function often centers on chromatin, the genetic material composed of DNA wrapped around histone proteins within cell nuclei. This structure's chiral nature gives rise to interactions with polarized light. This research encompasses three main aspects. Firstly, an existing multimodal Circular Intensity Differential Scattering (CIDS) and fluorescence microscopy are upgraded into an open configuration to be integrated with other modalities. Secondly, a novel cell classification method employing CIDS and a phasor representation is introduced. Thirdly, polarization analysis of fluorescence emission is employed for pathological investigations. Accordingly, the thesis is organized into three chapters. Chapter 1 lays the theoretical foundation for light propagation and polarization, outlining the Jones and Stokes-Mueller formalisms. The interaction between light and optical elements, transmission, and reflection processes are discussed. Polarized light's ability to reveal image contrast in polarizing microscopes, linear and nonlinear polarization-resolved microscopy, and Mueller matrix microscopy as a comprehensive technique for studying biological structures are detailed. Chapter 2 focuses on CIDS, a label-free light scattering method, including a single point angular spectroscopy mode and scanning microscopy imaging. A significant upgrade of the setup is achieved, incorporating automation, calibration, and statistical analysis routines. An intuitive phasor approach is proposed, enabling image segmentation, cell discrimination, and enhanced interpretation of polarimetric contrast. As a result, image processing programs have been developed to provide automated measurements using polarization-resolved laser scanning microscopy imaging integrated with confocal fluorescence microscopy of cells and chromatin inside cell nuclei, including the use of new types of samples such as progeria cells. Chapter 3 applies a polarization-resolved two-photon excitation fluorescence (2PEF) microscopy to study multicellular cancerous cells. A homemade 2PEF microscope is developed for colon cancer cell analysis. The integration of polarization and fluorescence techniques leads to a comprehensive understanding of the molecular orientation within samples, particularly useful for cancer diagnosis. Overall, this thesis presents an exploration of polarization-resolved imaging techniques for studying biological structures, encompassing theory, experimental enhancements, innovative methodologies, and practical applications

    Analysis and Visualization of Higher-Order Tensors: Using the Multipole Representation

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    Materialien wie Kristalle, biologisches Gewebe oder elektroaktive Polymere kommen häufig in verschiedenen Anwendung, wie dem Prothesenbau oder der Simulation von künstlicher Muskulatur vor. Diese und viele weitere Materialien haben gemeinsam, dass sie unter gewissen Umständen ihre Form und andere Materialeigenschaften ändern. Um diese Veränderung beschreiben zu können, werden, abhängig von der Anwendung, verschiedene Tensoren unterschiedlicher Ordnung benutzt. Durch die Komplexität und die starke Abhängigkeit der Tensorbedeutung von der Anwendung, gibt es bisher kein Verfahren Tensoren höherer Ordnung darzustellen, welches standardmäßig benutzt wird. Auch bezogen auf einzelne Anwendungen gibt es nur sehr wenig Arbeiten, die sich mit der visuellen Darstellung dieser Tensoren auseinandersetzt. Diese Arbeit beschäftigt sich mit diesem Problem. Es werden drei verschiedene Methoden präsentiert, Tensoren höherer Ordnung zu analysieren und zu visualisieren. Alle drei Methoden basieren auf der sogenannte deviatorischen Zerlegung und der Multipoldarstellung. Mit Hilfe der Multipole können die Symmetrien des Tensors und damit des beschriebenen Materials bestimmt werden. Diese Eigenschaft wird in für die Visualisierung des Steifigkeitstensors benutzt. Die zweite Methode basiert direkt auf den Multipolen und kann damit beliebige Tensoren in drei Dimensionen darstellen. Dieses Verfahren wird anhand des Kopplungs Tensors, ein Tensor dritter Ordnung, vorgestellt. Die ersten zwei Verfahren sind lokale Glyph-basierte Verfahren. Das dritte Verfahren ist ein erstes globales Tensorvisualisierungsverfahren, welches Tensoren beliebiger Ordnung und Symmetry in drei Dimensionen mit Hilfe eines linienbasierten Verfahrens darstellt.Materials like crystals, biological tissue or electroactive polymers are frequently used in applications like prosthesis construction or the simulation of artificial musculature. These and many other materials have in common that they change their shape and other material properties under certain circumstances. To describe these changes, different tensors of different order, dependent of the application, are used. Due to the complexity and the strong dependency of the tensor meaning of the application, there is, by now, no visualization method that is used by default. Also for specific applications there are only a few methods that address the visual analysis of higher-order tensors. This work adresses this problem. Three different methods to analyse and visualize tensors of higher order will be provided. All three methods are based on the so called deviatoric decomposition and the multipole representation. Using the multipoles the symmetries of a tensor and, therefore, of the described material, can be calculated. This property is used to visualize the stiffness tensor. The second method uses the multipoles directly and can be used for each tensor of any order in three dimensions. This method is presented by analysing the third-order coupling tensor. These two techniques are glyph-based visualization methods. The third one, a line-based method, is, according to our knowledge, a first global visualization method that can be used for an arbitrary tensor in three dimensions

    Serial sectioning block-face imaging of post-mortem human brain

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    No current imaging technology can directly and without significant distortion visualize the defining microscopic features of the human brain. Ex vivo histological techniques yield exquisite planar images, but the cutting, mounting and staining they require induce slice-specific distortions, introducing cross-slice differences that prohibit true 3D analysis. Clearing techniques have proven difficult to apply to large blocks of human tissue and cause dramatic distortions as well. Thus, we have only a poor understanding of human brain structures that occur at a scale of 1–100 μm, in which neurons are organized into functional cohorts. To date, mesoscopic features which are critical components of this spatial context, have only been quantified in studies of 2D histologic images acquired in a small number of subjects and/or over a small region of the brain, typically in the coronal orientation, implying that features that are oblique or orthogonal to the coronal plane are difficult to properly analyze. A serial sectioning optical coherence tomography (OCT) imaging infrastructure will be developed and utilized to obtain images of cyto- and myelo-architectural features and microvasculature network of post-mortem human brain tissue. Our imaging infrastructure integrates vibratome with imaging head along with pre and post processing algorithms to construct volumetric OCT images of cubic centimeters of brain tissue blocks. Imaging is performed on tissue block-face prior to sectioning, which preserves the 3D information. Serial sections cut from the block can be subsequently treated with multiplexed histological staining of multiple molecular markers that will facilitate cellular classification or imaged with high-resolution transmission birefringence microscope. The successful completion of this imaging infrastructure enables the automated reconstruction of undistorted volume of human tissue brain blocks and permits studying the pathological alternations arising from diseases. Specifically, the mesoscopic and microscopic pathological alternations, as well as the optical properties and cortical morphological alternations of the dorsolateral prefrontal cortical region of two difference neurodegeneration diseases, Chronic Traumatic Encephalopathy (CTE) and Alzheimer’s Disease (AD), were evaluated using this imaging infrastructure

    Impact of Temporal Order Selection on Clustering Intensive Longitudinal Data Based on VAR Models

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    In real-world research, intensive longitudinal data (ILDs) are typically collected from a group of individuals of interest, which enables researchers to model not only the within-individual dynamics of the studied processes but also the between-individual differences on the within-individual dynamics. Among the statistical techniques proposed for modeling ILDs of multiple individuals, clustering of intensive longitudinal data provides a meaningful way to quantify sample heterogeneity in dynamic processes, assuming that such heterogeneity reflects the distinct nature of the studied processes. The aims of this dissertation are threefold: (a) to introduce a VAR-based clustering technique, (b) to examine the impact of temporal order selection on clustering accuracy and parameter estimation by a simulation study, and (c) to demonstrate the application of the clustering technique through an empirical analysis. Specially, I investigated the influence of two temporal order selection strategies: (1) using the most complex structure or highest order (HO) for all individual processes, and (2) using the most parsimonious structure or the lowest order (LO) for all individuals on the performance of two-step model-based clustering procedure. This procedure extracted dynamic coefficients from vector autoregressive (VAR) models and employed the Gaussian mixture model (GMM) and K-means clustering algorithms on the coefficients for cluster identification. Additionally, I also examined whether the influence varied across two clustering algorithms. The simulation study showed that, regardless of the clustering algorithms used, LO strategy consistently outperformed HO strategy in terms of recovering the number of clusters, cluster membership, and cluster-specific AR and CR effects. GMM performed better than K-means when LO strategy was applied; however, the performance of GMM decreased while the temporal orders increased. Additionally, GMM showed more vulnerability with smaller numbers of participants. The application of the two-step VAR-based method to affect data yielded a meaningful and informative clustering solution, which provided further insights of the uses of the model-based clustering approach Lastly, suggestions and recommendations were offered based on the results of the simulation and empirical analyses

    1-D broadside-radiating leaky-wave antenna based on a numerically synthesized impedance surface

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    A newly-developed deterministic numerical technique for the automated design of metasurface antennas is applied here for the first time to the design of a 1-D printed Leaky-Wave Antenna (LWA) for broadside radiation. The surface impedance synthesis process does not require any a priori knowledge on the impedance pattern, and starts from a mask constraint on the desired far-field and practical bounds on the unit cell impedance values. The designed reactance surface for broadside radiation exhibits a non conventional patterning; this highlights the merit of using an automated design process for a design well known to be challenging for analytical methods. The antenna is physically implemented with an array of metal strips with varying gap widths and simulation results show very good agreement with the predicted performance

    Imaging fascicular organisation in mammalian vagus nerve for selective VNS

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    Nerves contain a large number of nerve fibres, or axons, organised into bundles known as fascicles. Despite the somatic nervous system being well understood, the organisation of the fascicles within the nerves of the autonomic nervous system remains almost completely unknown. The new field of bioelectronics medicine, Electroceuticals, involves the electrical stimulation of nerves to treat diseases instead of administering drugs or performing complex surgical procedures. Of particular interest is the vagus nerve, a prime target for intervention due to its afferent and efferent innervation to the heart, lungs and majority of the visceral organs. Vagus nerve stimulation (VNS) is a promising therapy for treatment of various conditions resistant to standard therapeutics. However, due to the unknown anatomy, the whole nerve is stimulated which leads to unwanted off-target effects. Electrical Impedance Tomography (EIT) is a non-invasive medical imaging technique in which the impedance of a part of the body is inferred from electrode measurements and used to form a tomographic image of that part. Micro-computed tomography (microCT) is an ex vivo method that has the potential to allow for imaging and tracing of fascicles within experimental models and facilitate the development of a fascicular map. Additionally, it could validate the in vivo technique of EIT. The aim of this thesis was to develop and optimise the microCT imaging method for imaging the fascicles within the nerve and to determine the fascicular organisation of the vagus nerve, ultimately allowing for selective VNS. Understanding and imaging the fascicular anatomy of nerves will not only allow for selective VNS and the improvement of its therapeutic efficacy but could also be integrated into the study on all peripheral nerves for peripheral nerve repair, microsurgery and improving the implementation of nerve guidance conduits. Chapter 1 provides an introduction to vagus nerve anatomy and the principles of microCT, neuronal tracing and EIT. Chapter 2 describes the optimisation of microCT for imaging the fascicular anatomy of peripheral nerves in the experimental rat sciatic and pig vagus nerve models, including the development of pre-processing methods and scanning parameters. Cross-validation of this optimised microCT method, neuronal tracing and EIT in the rat sciatic nerve was detailed in Chapter 3. Chapter 4 describes the study with microCT with tracing, EIT and selective stimulation in pigs, a model for human nerves. The microCT tracing approach was then extended into the subdiaphragmatic branches of the vagus nerves, detailed in Chapter 5. The ultimate goal of human vagus nerve tracing was preliminarily performed and described in Chapter 6. Chapter 7 concludes the work and describes future work. Lastly, Appendix 1 (Chapter 8) is a mini review on the application of selective vagus nerve stimulation to treat acute respiratory distress syndrome and Appendix 2 is morphological data corresponding to Chapter 4

    Exercise and Proximal Femur Bone Strength to Reduce Fall-Induced Hip Fracture

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    Bone mass and structure, constituting its strength, adapt to prevalent mechanical environment. Physical activity and exercise provide natural ways to apply the mechanical loading to bone. Finding effective osteogenic exercise types to improve proximal femur bone strength is of great importance to reduce hip fracture incidence and consequent substantial socioeconomic burden. Importantly, almost all hip fractures are caused by falls. Therefore, the primary objective of the present doctoral research was to find such effective exercise types by exploring the effect of long-term specific exercise loading on proximal femur bone strength in the fall situation using a finite element (FE) method. The secondary objective was to analyze 3D morphological adaptation of proximal femur cortical bone to the specific exercise loading. The results from this secondary objective were anticipated to help understanding the findings pertinent to the primary objective. To achieve these objectives, proximal femur MRI data were obtained from 91 young adult female athletes (aged 24.7 ± 6.1 years, > 8 years competing career) and 20 nonathletic but physically active controls (aged 23.7 ± 3.8 years). The athletes were classified into five distinct exercise loading groups based on the typical loading patterns of their sports: high-impact (H-I: triple- and high-jumpers), odd-impact (O-I: soccer/football and squash players), high-magnitude (H-M: powerlifters), repetitive-impact (R-I: endurance runners), and repetitive non-impact (R-NI: swimmers). Based on their MRI data, proximal femur FE models were first created in a single fall configuration (direction) to compare 1) cortical stresses in eight anatomical octants of femoral neck cross-sections in the proximal, middle, and distal femoral neck regions and 2) fracture behavior (load, location, and mode) between each exercise loading and control groups. The athletic bones are adapted to the long- term specific exercise loading characterized by not only the loading magnitude, rate, and frequency but also direction. Given this, the study was extended to simulate the FE models in multiple fall directions to examine whether potentially identified higher proximal femur bone strength to reduce fall-induced hip fracture risk, attributed to the long-term specific exercise loading, depends on the direction of the fall onto the greater trochanter or hip. For the secondary objective, a new computational anatomy method called Ricci-flow conformal mapping (RCM) was implemented to obtain 3D distribution of the cortical thickness within the proximal femur and to perform its spatial between-group statistical comparisons. Key results from the present research demonstrated that young adult females with the exercise loading history of high ground impacts (H-I), ground impacts from unusual/odd directions (O-I), or a great number of repetitive ground impacts (R-I) had 10-22%, 12-16%, and 14-23% lower fall-induced cortical stress at the fracture-prone superolateral femoral neck and 11-17%, 10-11%, and 22-28% higher fracture loads (higher proximal femur bone strength) in the fall situations compared to the controls, respectively. These results indicate that the long-term H-I, O-I, and R-I exercise loadings may reduce the fall-induced hip fracture risk. Furthermore, the present results showed that the higher proximal femur bone strength to reduce hip fracture risk in athletes engaged in the high-impact or repetitive-impact sports are robust and independent of the direction of fall. In contrast, the higher strength attributed to the odd-impact exercise loading appears more modest and specific to the fall direction. The analysis of the minimum fall strength spanning the multiple fall directions also supported the higher proximal femur bone strength in the athletes engaged in these impact exercises. In concordance with the literature, the present results also confirmed in these young adult females that 1) the fall-induced hip fracture most likely initiates from the superolateral femoral neck’s cortical bone, particularly at its posterior aspect (superoposterior cortex) in the distal femoral neck region, and 2) the most dangerous fracture-causing fall direction is the one where the impact is imposed to the posterolateral aspect of the greater trochanter. It would be ideal if impact exercise loading could induce beneficial cortical bone adaptation in the fracture-prone posterior aspect of superolateral femoral neck cortex. However, such apparently beneficial cortical adaptation was not observed in any of the impact or nonimpact exercise loading types examined in the present research based on the supplementary RCM-based 3D morphological analyses of proximal femur cortical bone. This analysis importantly showed that the higher proximal femur bone strengths to reduce fall-induced hip fracture risk in athletes engaged in the high- or odd-impact exercise types are likely due to thicker cortical layers in other femoral neck regions including the inferior, posterior, and/or superior-to-superoanterior regions. Interestingly, the higher proximal femur strength in the athletes with the repetitive-impact exercise loading was not supported by such cortical adaptation. This suggests that other structural/geometrical adaptation contributes to their higher strength. This calls for further studies to elucidate the source of the higher proximal femur bone strength in this type of athletes. In contrast to the impact exercise loading histories, the exercise loading history of the high-magnitude (e.g., powerlifting) or repetitive, non-impact (e.g., swimming) was not associated with higher proximal femur bone strength to reduce fall-induced hip fracture risk. This most likely reflects the lack of any beneficial structural adaptations of cortical bone around the femoral neck in the athletes with these exercise loading histories. Considering the loading characteristics of the exercise types examined in the present doctoral research, the moderate-to-high loading magnitude alone appears insufficient but needs to be generated at the high loading rate and/or frequency to induce the beneficial adaptation in the proximal femur cortical bone. Therefore, in addition to aforementioned three impact exercise loading types, other exercise or sport types satisfying this condition may also be effective to increase or maintain the proximal femur bone strength to reduce fall- induced hip fracture risk. As a clinical prospect, the present findings highlight the importance of impact exercise in combating fall-induced hip fracture. Compared to the high-impact loading exercises (e.g., triple/long and high jumping exercise), the odd-impact [ball or invasion games (e.g., football/soccer, tennis)] and/or repetitive-impact loading exercises (e.g., endurance running, jogging, and perhaps vigorous walking) likely provide a safer and more feasible choice for the populations covering the sedentary adults to old people. This is due to the relatively more moderate ground impact involved in the odd- and repetitive-impact loading exercises than in the high-impact exercises. For young, physically active, and/or fit people, the above-mentioned or similar jumping exercises and any other exercise types consisting of the high ground impact (e.g., volleyball, basketball, gymnastics) can also be incorporated into their habitual exercise routines. Lastly, the present results were observed in the young adult females who had engaged in sport-specific training from their childhood/adolescence to early adulthood. Therefore, this calls for the prospective and/or retrospective observational studies to investigate whether the higher proximal femur bone strength to reduce fall-induced hip fracture risk obtained from the long-term specific impact exercise loading during these early phases of life can sustain into the later stages, especially after age of 65 years when the hip fracture is generally more common
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