1,026 research outputs found

    La traduzione specializzata all’opera per una piccola impresa in espansione: la mia esperienza di internazionalizzazione in cinese di Bioretics© S.r.l.

    Get PDF
    Global markets are currently immersed in two all-encompassing and unstoppable processes: internationalization and globalization. While the former pushes companies to look beyond the borders of their country of origin to forge relationships with foreign trading partners, the latter fosters the standardization in all countries, by reducing spatiotemporal distances and breaking down geographical, political, economic and socio-cultural barriers. In recent decades, another domain has appeared to propel these unifying drives: Artificial Intelligence, together with its high technologies aiming to implement human cognitive abilities in machinery. The “Language Toolkit – Le lingue straniere al servizio dell’internazionalizzazione dell’impresa” project, promoted by the Department of Interpreting and Translation (Forlì Campus) in collaboration with the Romagna Chamber of Commerce (Forlì-Cesena and Rimini), seeks to help Italian SMEs make their way into the global market. It is precisely within this project that this dissertation has been conceived. Indeed, its purpose is to present the translation and localization project from English into Chinese of a series of texts produced by Bioretics© S.r.l.: an investor deck, the company website and part of the installation and use manual of the Aliquis© framework software, its flagship product. This dissertation is structured as follows: Chapter 1 presents the project and the company in detail; Chapter 2 outlines the internationalization and globalization processes and the Artificial Intelligence market both in Italy and in China; Chapter 3 provides the theoretical foundations for every aspect related to Specialized Translation, including website localization; Chapter 4 describes the resources and tools used to perform the translations; Chapter 5 proposes an analysis of the source texts; Chapter 6 is a commentary on translation strategies and choices

    Interaction of elastomechanics and fluid dynamics in the human heart : Opportunities and challenges of light coupling strategies

    Get PDF
    Das menschliche Herz ist das hochkomplexe Herzstück des kardiovaskulären Systems, das permanent, zuverlässig und autonom den Blutfluss im Körper aufrechterhält. In Computermodellen wird die Funktionalität des Herzens nachgebildet, um Simulationsstudien durchzuführen, die tiefere Einblicke in die zugrundeliegenden Phänomene ermöglichen oder die Möglichkeit bieten, relevante Parameter unter vollständig kontrollierten Bedingungen zu variieren. Angesichts der Tatsache, dass Herz-Kreislauf-Erkrankungen die häufigste Todesursache in den Ländern der westlichen Hemisphäre sind, ist ein Beitrag zur frühzeit- igen Diagnose derselben von großer klinischer Bedeutung. In diesem Zusammenhang können computergestützte Strömungssimulationen wertvolle Einblicke in die Blutflussdynamik liefern und bieten somit die Möglichkeit, einen zentralen Bereich der Physik dieses multiphysikalischen Organs zu untersuchen. Da die Verformung der Endokardoberfläche den Blutfluss antreibt, müssen die Effekte der Elastomechanik als Randbedingungen für solche Strömungssimulationen berücksichtigt werden. Um im klinischen Kontext relevant zu sein, muss jedoch ein Mittelweg zwischen dem Rechenaufwand und der erforderlichen Genauigkeit gefunden werden, und die Modelle müssen sowohl robust als auch zuverlässig sein. Daher werden in dieser Arbeit die Möglichkeiten und Herausforderungen leichter und daher weniger komplexer Kopplungsstrategien mit Schwerpunkt auf drei Schlüsselaspekten bewertet: Erstens wird ein auf dem Immersed Boundary-Ansatz basierender Fluiddynamik-Löser implementiert, da diese Methode mit einer sehr robusten Darstellung von bewegten Netzen besticht. Die grundlegende Funktionalität wurde für verschiedene vereinfachte Geometrien verifiziert und zeigte eine hohe Übereinstimmung mit der jeweiligen analytischen Lösung. Vergleicht man die 3D-Simulation einer realistischen Geometrie des linken Teils des Herzens mit einem körperangepassten Netzbeschreibung, so wurden grundlegende globale Größen korrekt reproduziert. Allerdings zeigten Variationen der Randbedingungen einen großen Einfluss auf die Simulationsergebnisse. Die Anwendung des Lösers zur Simulation des Einflusses von Pathologien auf die Blutströmungsmuster ergab Ergebnisse in guter Übereinstimmung mit Literaturwerten. Bei Simulationen der Mitralklappeninsuffizienz wurde der rückströmende Anteil mit Hilfe einer Partikelverfolgungsmethode visualisiert. Bei hypertropher Kardiomyopathie wurden die Strömungsmuster im linken Ventrikel mit Hilfe eines passiven Skalartransports bewertet, um die lokale Konzentration des ursprünglichen Blutvolumens zu visualisieren. Da in den vorgenannten Studien nur ein unidirektionaler Informationsfluss vom elas- tomechanischen Modell zum Strömungslöser berücksichtigt wurde, wird die Rückwirkung des räumlich aufgelösten Druckfeldes aus den Strömungssimulationen auf die Elastomechanik quantifiziert. Es wird ein sequenzieller Kopplungsansatz eingeführt, um fluiddynamische Einflüsse in einer Schlag-für-Schlag-Kopplungsstruktur zu berücksichtigen. Die geringen Abweichungen im mechanischen Solver von 2 mm verschwanden bereits nach einer Iteration, was darauf schließen lässt, dass die Rückwirkungen der Fluiddynamik im gesunden Herzen begrenzt ist. Zusammenfassend lässt sich sagen, dass insbesondere bei Strömungsdynamiksimula- tionen die Randbedingungen mit Vorsicht gewählt werden müssen, da sie aufgrund ihres großen Einflusses die Anfälligkeit der Modelle erhöhen. Nichtsdestotrotz zeigten verein- fachte Kopplungsstrategien vielversprechende Ergebnisse bei der Reproduktion globaler fluiddynamischer Größen, während die Abhängigkeit zwischen den Lösern reduziert und Rechenaufwand eingespart wird

    Biomaterials for Bone Tissue Engineering 2020

    Get PDF
    This book presents recent advances in the field of bone tissue engineering, including molecular insights, innovative biomaterials with regenerative properties (e.g., osteoinduction and osteoconduction), and physical stimuli to enhance bone regeneration

    Automatic breach detection during spine pedicle drilling based on vibroacoustic sensing

    Full text link
    Pedicle drilling is a complex and critical spinal surgery task. Detecting breach or penetration of the surgical tool to the cortical wall during pilot-hole drilling is essential to avoid damage to vital anatomical structures adjacent to the pedicle, such as the spinal cord, blood vessels, and nerves. Currently, the guidance of pedicle drilling is done using image-guided methods that are radiation intensive and limited to the preoperative information. This work proposes a new radiation-free breach detection algorithm leveraging a non-visual sensor setup in combination with deep learning approach. Multiple vibroacoustic sensors, such as a contact microphone, a free-field microphone, a tri-axial accelerometer, a uni-axial accelerometer, and an optical tracking system were integrated into the setup. Data were collected on four cadaveric human spines, ranging from L5 to T10. An experienced spine surgeon drilled the pedicles relying on optical navigation. A new automatic labeling method based on the tracking data was introduced. Labeled data was subsequently fed to the network in mel-spectrograms, classifying the data into breach and non-breach. Different sensor types, sensor positioning, and their combinations were evaluated. The best results in breach recall for individual sensors could be achieved using contact microphones attached to the dorsal skin (85.8\%) and uni-axial accelerometers clamped to the spinous process of the drilled vertebra (81.0\%). The best-performing data fusion model combined the latter two sensors with a breach recall of 98\%. The proposed method shows the great potential of non-visual sensor fusion for avoiding screw misplacement and accidental bone breaches during pedicle drilling and could be extended to further surgical applications

    Surface-Based tools for Characterizing the Human Brain Cortical Morphology

    Get PDF
    Tesis por compendio de publicacionesThe cortex of the human brain is highly convoluted. These characteristic convolutions present advantages over lissencephalic brains. For instance, gyrification allows an expansion of cortical surface area without significantly increasing the cranial volume, thus facilitating the pass of the head through the birth channel. Studying the human brain’s cortical morphology and the processes leading to the cortical folds has been critical for an increased understanding of the pathological processes driving psychiatric disorders such as schizophrenia, bipolar disorders, autism, or major depression. Furthermore, charting the normal developmental changes in cortical morphology during adolescence or aging can be of great importance for detecting deviances that may be precursors for pathology. However, the exact mechanisms that push cortical folding remain largely unknown. The accurate characterization of the neurodevelopment processes is challenging. Multiple mechanisms co-occur at a molecular or cellular level and can only be studied through the analysis of ex-vivo samples, usually of animal models. Magnetic Resonance Imaging can partially fill the breach, allowing the portrayal of the macroscopic processes surfacing on in-vivo samples. Different metrics have been defined to measure cortical structure to describe the brain’s morphological changes and infer the associated microstructural events. Metrics such as cortical thickness, surface area, or cortical volume help establish a relation between the measured voxels on a magnetic resonance image and the underlying biological processes. However, the existing methods present limitations or room for improvement. Methods extracting the lines representing the gyral and sulcal morphology tend to over- or underestimate the total length. These lines can provide important information about how sulcal and gyral regions function differently due to their distinctive ontogenesis. Nevertheless, some methods label every small fold on the cortical surface as a sulcal fundus, thus losing the perspective of lines that travel through the deeper zones of a sulcal basin. On the other hand, some methods are too restrictive, labeling sulcal fundi only for a bunch of primary folds. To overcome this issue, we have proposed a Laplacian-collapse-based algorithm that can delineate the lines traversing the top regions of the gyri and the fundi of the sulci avoiding anastomotic sulci. For this, the cortex, represented as a 3D surface, is segmented into gyral and sulcal surfaces attending to the curvature and depth at every point of the mesh. Each resulting surface is spatially filtered, smoothing the boundaries. Then, a Laplacian-collapse-based algorithm is applied to obtain a thinned representation of the morphology of each structure. These thin curves are processed to detect where the extremities or endpoints lie. Finally, sulcal fundi and gyral crown lines are obtained by eroding the surfaces while preserving the structure topology and connectivity between the endpoints. The assessment of the presented algorithm showed that the labeled sulcal lines were close to the proposed ground truth length values while crossing through the deeper (and more curved) regions. The tool also obtained reproducibility scores better or similar to those of previous algorithms. A second limitation of the existing metrics concerns the measurement of sulcal width. This metric, understood as the physical distance between the points on opposite sulcal banks, can come in handy in detecting cortical flattening or complementing the information provided by cortical thickness, gyrification index, or such features. Nevertheless, existing methods only provided averaged measurements for different predefined sulcal regions, greatly restricting the possibilities of sulcal width and ignoring the intra-region variability. Regarding this, we developed a method that estimates the distance from each sulcal point in the cortex to its corresponding opposite, thus providing a per-vertex map of the physical sulcal distances. For this, the cortical surface is sampled at different depth levels, detecting the points where the sulcal banks change. The points corresponding to each sulcal wall are matched with the closest point on a different one. The distance between those points is the sulcal width. The algorithm was validated against a simulated sulcus that resembles a simple fold. Then the tool was used on a real dataset and compared against two widely-used sulcal width estimation methods, averaging the proposed algorithm’s values into the same region definition those reference tools use. The resulting values were similar for the proposed and the reference methods, thus demonstrating the algorithm’s accuracy. Finally, both algorithms were tested on a real aging population dataset to prove the methods’ potential in a use-case scenario. The main idea was to elucidate fine-grained morphological changes in the human cortex with aging by conducting three analyses: a comparison of the age-dependencies of cortical thickness in gyral and sulcal lines, an analysis of how the sulcal and gyral length changes with age, and a vertex-wise study of sulcal width and cortical thickness. These analyses showed a general flattening of the cortex with aging, with interesting findings such as a differential age-dependency of thickness thinning in the sulcal and gyral regions. By demonstrating that our method can detect this difference, our results can pave the way for future in vivo studies focusing on macro- and microscopic changes specific to gyri or sulci. Our method can generate new brain-based biomarkers specific to sulci and gyri, and these can be used on large samples to establish normative models to which patients can be compared. In parallel, the vertex-wise analyses show that sulcal width is very sensitive to changes during aging, independent of cortical thickness. This corroborates the concept of sulcal width as a metric that explains, in the least, the unique variance of morphology not fully captured by existing metrics. Our method allows for sulcal width vertex-wise analyses that were not possible previously, potentially changing our understanding of how changes in sulcal width shape cortical morphology. In conclusion, this thesis presents two new tools, open source and publicly available, for estimating cortical surface-based morphometrics. The methods have been validated and assessed against existing algorithms. They have also been tested on a real dataset, providing new, exciting insights into cortical morphology and showing their potential for defining innovative biomarkers.Programa de Doctorado en Ciencia y Tecnología Biomédica por la Universidad Carlos III de MadridPresidente: Juan Domingo Gispert López.- Secretario: Norberto Malpica González de Vega.- Vocal: Gemma Cristina Monté Rubi

    Elastic shape analysis of geometric objects with complex structures and partial correspondences

    Get PDF
    In this dissertation, we address the development of elastic shape analysis frameworks for the registration, comparison and statistical shape analysis of geometric objects with complex topological structures and partial correspondences. In particular, we introduce a variational framework and several numerical algorithms for the estimation of geodesics and distances induced by higher-order elastic Sobolev metrics on the space of parametrized and unparametrized curves and surfaces. We extend our framework to the setting of shape graphs (i.e., geometric objects with branching structures where each branch is a curve) and surfaces with complex topological structures and partial correspondences. To do so, we leverage the flexibility of varifold fidelity metrics in order to augment our geometric objects with a spatially-varying weight function, which in turn enables us to indirectly model topological changes and handle partial matching constraints via the estimation of vanishing weights within the registration process. In the setting of shape graphs, we prove the existence of solutions to the relaxed registration problem with weights, which is the main theoretical contribution of this thesis. In the setting of surfaces, we leverage our surface matching algorithms to develop a comprehensive collection of numerical routines for the statistical shape analysis of sets of 3D surfaces, which includes algorithms to compute Karcher means, perform dimensionality reduction via multidimensional scaling and tangent principal component analysis, and estimate parallel transport across surfaces (possibly with partial matching constraints). Moreover, we also address the development of numerical shape analysis pipelines for large-scale data-driven applications with geometric objects. Towards this end, we introduce a supervised deep learning framework to compute the square-root velocity (SRV) distance for curves. Our trained network provides fast and accurate estimates of the SRV distance between pairs of geometric curves, without the need to find optimal reparametrizations. As a proof of concept for the suitability of such approaches in practical contexts, we use it to perform optical character recognition (OCR), achieving comparable performance in terms of computational speed and accuracy to other existing OCR methods. Lastly, we address the difficulty of extracting high quality shape structures from imaging data in the field of astronomy. To do so, we present a state-of-the-art expectation-maximization approach for the challenging task of multi-frame astronomical image deconvolution and super-resolution. We leverage our approach to obtain a high-fidelity reconstruction of the night sky, from which high quality shape data can be extracted using appropriate segmentation and photometric techniques

    Stretch sensors for measuring knee kinematics in sports

    Get PDF
    The popularity of wearable technology in sport has increased, due to its ability to provide unobtrusive monitoring of athletes. This technology has been used to objectively measure kinetic and kinematic variables, with the aim of preventing injury, maximising athletic performance and classifying the skill level of athletes, all of which can influence training and coaching practices. Wearable technologies overcome the limitations of motion capture systems which are limited in their capture volume, enabling the collection of data in-field, during training and competition. Inertial sensors are a common form of technology used in these environments however, their high-cost and complex calibration due to multiple sensor integration can make them prohibitive for widespread use. This thesis focuses on the development of a strain sensor that can be used to measure knee range of motion in sports, specifically rowing and cycling, as a potential low-cost, lightweight alternative to inertial sensors which can also be integrated into clothing, making them more discreet. A systematic review highlighted the lack of alternate technologies to inertial sensors such as strain sensors, as well as the limited use of wearable technologies in both rowing and cycling. Strain sensors were fabricated from a carbon nanotube-natural rubber composite using solvent exchange techniques and employed a piezoresistive sensing mechanism. These were then characterised using mechanical testing, to determine their electrical properties under cyclical strain. The strain sensors displayed hysteretic behaviour, but were durable, withstanding over 4500 strain cycles. Statistical analysis indicated that over 60% of the tests conducted had good intra-test variability with regards to the resistance response range in each strain cycle and sensor response deviating by less than 10% at strain rates below 100 mm/min and less than 20% at a strain rate of 350 mm/min. These sensors were integrated into a wearable sensor system and tested on rowing and cycling cohorts consisting of ten athletes each, to assess the translational use of the strain sensor. This preliminary testing indicated that strain sensors were able to track the motion of the knee during the rowing stroke and cycling pedalling motion, when compared to the output of a motion capture system. Perspectives of participants on the wearable system were collected, which indicated their desire for a system that they could use in their sport, and they considered the translation of this system for real-life use with further development to improve comfort of the system and consistency of the sensor response. The strain sensors developed in this project, when integrated into a wearable sensor system, have the potential to provide an unobtrusive method of measuring knee kinematics, helping athletes, coaches and other support staff make technical changes that can reduce injury risk and improve performance.Open Acces

    Diffusion MRI tractography for oncological neurosurgery planning:Clinical research prototype

    Get PDF

    Imaging fascicular organisation in mammalian vagus nerve for selective VNS

    Get PDF
    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
    • …
    corecore