Non-Classical Nucleation Phenomena Study And Following Process Monitoring and Optimization in Solution Crystallization Process

Nucleation is a crucial step in the solution crystallization process. Despite their good development, classical nucleation theory and two-step nucleation theory cannot explain all the nucleation phenomena, especially for the non-classical nucleation phenomena which include oiling out, gelation and non-monotonic nucleation. Accordingly, for the non-classical nucleation systems, the crystallization processes are seldom designed based on the nucleation monitoring and supervision. In this thesis, crystallization process optimization was conducted to study the mechanism of non-classical nucleation phenomena and in-line process monitoring technology development. Two kinds of non-classical nucleation phenomena with non-monotonic nucleation rate and gel formation were investigated, and accordingly, two nucleation pathways that self-induced nucleation and jellylike phase mediated nucleation were proposed based on the analysis of in-line spectral monitoring and off-line sample characterizations. Results indicated the agitation level would affect the pre-nucleation clusters’ existence in the non-monotonic nucleation system, and the properties of solvent determined the formation of jellylike phase and the transformation to crystals. Motion-based objects tracking model and the state-of-the-art neural network Mask R-CNN were introduced to monitor the onset of nucleation and following the crystallization process. Combined with a cost-effective camera probe, the developed real-time tracking system can detect the nucleation onset accurately even with ultrasonic irradiation and can extract much more information during the whole crystallization process. Subsequently, ultrasonic irradiation and seeding were used to optimize a non-classical nucleation system that accompanied oiling out phenomenon. Different frequencies and intensities of ultrasonic irradiation and seeds addition time were screened to optimize the nucleation step, which proved their effectiveness of promoting nucleation and narrowing the metastable zone widths of oiling out and nucleation. A fine-tuning of nucleation step was carried out in a mixed suspension mixed product removal (MSMPR)-tubular crystallizer series. The nucleation step was optimized in the MSMPR stage with the aid of principal component analysis, which enabled the growth of crystals in the tubular crystallizer with preferred polymorphism, shape, and size. The study in this thesis provides insights into non-classical nucleation mechanism and nucleation based crystallization process design and optimization

Measurements, Models, Systems and Design

531 s.

IMPROVED IMAGE QUALITY IN CONE-BEAM COMPUTED TOMOGRAPHY FOR IMAGE-GUIDED INTERVENTIONS

In the past few decades, cone-beam computed tomography (CBCT) emerged as a rapidly developing imaging modality that provides single rotation 3D volumetric reconstruction with sub-millimeter spatial resolution. Compared to the conventional multi-detector CT (MDCT), CBCT exhibited a number of characteristics that are well suited to applications in image-guided interventions, including improved mechanical simplicity, higher portability, and lower cost. Although the current generation of CBCT has shown strong promise for high-resolution and high-contrast imaging (e.g., visualization of bone structures and surgical instrumentation), it is often believed that CBCT yields inferior contrast resolution compared to MDCT and is not suitable for soft-tissue imaging. Aiming at expanding the utility of CBCT in image-guided interventions, this dissertation concerns the development of advanced imaging systems and algorithms to tackle the challenges of soft-tissue contrast resolution. The presented material includes work encompassing: (i) a comprehensive simulation platform to generate realistic CBCT projections (e.g., as training data for deep learning approaches); (ii) a new projection domain statistical noise model to improve the noise-resolution tradeoff in model-based iterative reconstruction (MBIR); (iii) a novel method to avoid CBCT metal artifacts by optimization of the source-detector orbit; (iv) an integrated software pipeline to correct various forms of CBCT artifacts (i.e., lag, glare, scatter, beam hardening, patient motion, and truncation); (v) a new 3D reconstruction method that only reconstructs the difference image from the image prior for use in CBCT neuro-angiography; and (vi) a novel method for 3D image reconstruction (DL-Recon) that combines deep learning (DL)-based image synthesis network with physics-based models based on Bayesian estimation of the statical uncertainty of the neural network. Specific clinical challenges were investigated in monitoring patients in the neurological critical care unit (NCCU) and advancing intraoperative soft-tissue imaging capability in image-guided spinal and intracranial neurosurgery. The results show that the methods proposed in this work substantially improved soft-tissue contrast in CBCT. The thesis demonstrates that advanced imaging approaches based on accurate system models, novel artifact reduction methods, and emerging 3D image reconstruction algorithms can effectively tackle current challenges in soft-tissue contrast resolution and expand the application of CBCT in image-guided interventions

Biomimetic bone grafts: from the lab to the clinic

Aplicat embargament des de la data de defensa fins el dia 17/6/2022Bone grafting is a common medical practice in today’s society, being bone the second most transplanted tissue worldwide after blood. Therefore, it represents a field of major interest for both, biomedical research and the biomedical industry. Despite the ability of bone to self-heal, in some scenarios where defects are large or complex, bone grafts are essential for a successfully regeneration. Although autografting is still today the gold standard in terms of biological performance, the limited availability and morbidity associated with this practice drive to search for alternatives. Synthetic grafts arise as a promising option due to their unlimited availability and the possibility to tune their structure and composition for optimal performance. The present thesis explores biomimetic calcium deficient hydroxyapatite (CDHA), a promising material for synthetic bone grafts, in a translational-oriented perspective. Two product presentations are studied: A more conventional granulated conformation and a 3D printed personalised format. Chapter 1 offers a brief overview of bone biology, as well as a state of the art of the currently available bone grafting strategies found in the literature. Chapter 2 focuses on the validation of the in vivo performance of CDHA granules compared to the well- established bovine xenograft particulate grafts in a dental indication in miniature swine. It is concluded that both biomaterials meet the requirements for bone grafting, (i.e., biocompatibility, osseointegration, and osteoconduction). Moreover, it is revealed that granule morphology is a key factor to ensure the preservation of the grafted volume. In the following chapters, the focus is moved to the 3D printed personalised CDHA bone grafts. Chapter 3 investigates different approaches to accelerate the consolidation process of the 3D printed grafts in order to make the technology more suitable for industrial applications, and develops a hydrothermal treatment that reduces the reaction time to 30 minutes instead of the 7 days needed in the biomimetic approach. Despite the slight differences in physicochemical properties associated to this approach (e.g., microstructure, crystalline phase, microporosity, specific surface area), the resulting scaffolds support adhesion and proliferation of rat mesenchymal stem cells, suggesting its potential as bone graft substitutes. In Chapter 4 the hydrothermal route introduced in the previous chapter is compared to the long-established biomimetic treatment in terms of the in vivo performance of the 3D-printed scaffolds through orthotopic implantation in rabbit condyle monocortical defects. The samples treated with this new process, in addition to the excellent biocompatibility, osseointegrative and osteoconductive properties characteristic of biomimetic CDHA, exhibit a significantly higher amount of newly formed bone than the biomimetic counterpart. This enhanced performance is attributed to the higher permeability of the microstructure, as demonstrated with a protein adsorption test. Chapter 5 explores a strategy to enhance the degree of concavity and specific surface area of 3D printed structures obtained by microextrusion, by using nozzles with non-circular cross-sections. Besides achieving the intended purpose and characterising the 3D-printed structures, different technical constraints for the printing process associated to the use of non-circular nozzles are identified. In a further step, this developed technology is applied to the fabrication of 3D-printed bone grafts with concave filament surfaces and tested in vivo in a rabbit condyle orthotopic model in Chapter 6. It is found that using strands with star-shaped cross-sections helps to guide bone, enhancing the osteoconductive properties of the scaffolds. Finally, Chapter 7 summarises all the work carried out in this thesis to transfer the 3D printing technology of synthetic bone grafts to the market, turning it into a commercially available product.L'ús d'empelts ossis és cada vegada més freqüent: l'os és el segon teixit més trasplantat del món, després de la sang. Per això, aquesta pràctica atreu un gran interès tant a nivell de recerca com per a la indústria biomèdica. En casos en què els defectes són massa grossos o complexos, l'ús d'empelts ossis és essencial per aconseguir una bona regeneració. Malgrat que els autoempelts segueixen sent el tractament de primera elecció, la seva disponibilitat limitada així com la morbiditat associada fan necessari buscar altres solucions. Els empelts sintètics sorgeixen com una alternativa prometedora, donada la seva àmplia disponibilitat i la possibilitat de modificar-ne l'estructura i la composició per obtenir un rendiment òptim. En aquesta tesi s'estudia la hidroxiapatita biomimètica deficient en calci (CDHA) per a la fabricació d'empelts ossis sintètics, des d'una perspectiva orientada a la recerca translacional. S'estudien dues presentacions diferents del producte: una configuració en forma de grànuls i un format personalitzat obtingut per impressió 3D. El Capítol 1 recull una descripció general de la biologia de l'os, juntament amb l'estat de l'art de les diferents estratègies d'empelts ossis que es poden trobar a la literatura. El Capítol 2 se centra en l'estudi de la resposta in vivo de grànuls de CDHA, en comparació amb el xenoempelt boví amb més reconeixement mèdic, en una indicació dental en porcs en miniatura. L'estudi conclou que ambdós biomaterials compleixen els requisits d'un empelt ossi, i.e., biocompatibilitat, osteointegració i osteoconducció. A més, es demostra que la morfologia dels grànuls és un factor clau per assegurar la preservació del volum empeltat. En el Capítol 3 s'investiguen diferents processos per accelerar la consolidació dels empelts impresos en 3D per tal d'aconseguir una tecnologia més adient per a aplicacions industrials, i es desenvolupa un tractament hidrotèrmic que redueix el temps de reacció dels 7 dies necessaris per mètodes biomimètics a només 30 minuts. Amb el nou tractament s'observen petites diferències en les propietats fisicoquímiques (per exemple, en la microestructura, en la fase cristal·lina, la microporositat o la superfície específica), però els empelts obtinguts permeten l'adhesió i la proliferació de cèl·lules mare de rata, que indica que són una solució viable com a substituts ossis. En el Capítol 4 el procés hidrotèrmic introduït al capítol anterior es compara amb el tractament biomimètic in vivo mitjançant la implantació ortotòpica d'empelts 3D en defectes monocorticals en còndils de conills. Les mostres tractades amb aquest nou procediment, a més de presentar l'excel·lent biocompatibilitat i les propietats osteointegratives i osteoconductives pròpies de la CDHA biomimètica, també mostren una quantitat significativament més gran de teixit ossi neoformat que la seva contrapart. Aquestes diferències s'atribueixen a la major permeabilitat de la microestructura, tal com es demostra en un assaig d'absorció de proteïnes. En el Capítol 5 s'estudia una estratègia per millorar tant el grau de concavitat com la superfície específica d'estructures impreses en 3D obtingudes per microextrusió. Per això, s'utilitzen broquets d'extrusió amb seccions transversals no circulars. A més d'aconseguir-ho i caracteritzar les propietats de les estructures impreses, s'identifiquen un conjunt de restriccions tècniques associades a l'ús de broquets no circulars. En un pas més, aquesta estratègia s'aplica a la fabricació d'empelts ossis amb superfícies de filament còncaves i, en el Capítol 6, s'assaja in vivo en un model ortotòpic de còndil de conill. S'observa que utilitzar filaments amb una secció transversal en forma d'estrella ajuda a guiar l'os i millora les propietats osteoconductives dels empelts. Finalment, el Capítol 7 resumeix la feina duta a terme al llarg de la tesi per transferir la tecnologia d'impressió 3D d'empelts ossis sintètics, convertint-lo en un producte disponible comercialment.Postprint (published version

Automated deep phenotyping of the cardiovascular system using magnetic resonance imaging

Across a lifetime, the cardiovascular system must adapt to a great range of demands from the body. The individual changes in the cardiovascular system that occur in response to loading conditions are influenced by genetic susceptibility, and the pattern and extent of these changes have prognostic value. Brachial blood pressure (BP) and left ventricular ejection fraction (LVEF) are important biomarkers that capture this response, and their measurements are made at high resolution. Relatively, clinical analysis is crude, and may result in lost information and the introduction of noise. Digital information storage enables efficient extraction of information from a dataset, and this strategy may provide more precise and deeper measures to breakdown current phenotypes into their component parts. The aim of this thesis was to develop automated analysis of cardiovascular magnetic resonance (CMR) imaging for more detailed phenotyping, and apply these techniques for new biological insights into the cardiovascular response to different loading conditions. I therefore tested the feasibility and clinical utility of computational approaches for image and waveform analysis, recruiting and acquiring additional patient cohorts where necessary, and then applied these approaches prospectively to participants before and after six-months of exercise training for a first-time marathon. First, a multi-centre, multi-vendor, multi-field strength, multi-disease CMR resource of 110 patients undergoing repeat imaging in a short time-frame was assembled. The resource was used to assess whether automated analysis of LV structure and function is feasible on real-world data, and if it can improve upon human precision. This showed that clinicians can be confident in detecting a 9% change in EF or a 20g change in LV mass. This will be difficult to improve by clinicians because the greatest source of human error was attributable to the observer rather than modifiable factors. Having understood these errors, a convolutional neural network was trained on separate multi-centre data for automated analysis and was successfully generalizable to the real-world CMR data. Precision was similar to human analysis, and performance was 186 times faster. This real-world benchmarking resource has been made freely available (thevolumesresource.com). Precise automated segmentations were then used as a platform to delve further into the LV phenotype. Global LVEFs measured from CMR imaging in 116 patients with severe aortic stenosis were broken down into ~10 million regional measurements of structure and function, represented by computational three-dimensional LV models for each individual. A cardiac atlas approach was used to compile, label, segment and represent these data. Models were compared with healthy matched controls, and co-registered with follow-up one year after aortic valve replacement (AVR). This showed that there is a tendency to asymmetric septal hypertrophy in all patients with severe aortic stenosis (AS), rather than a characteristic specific to predisposed patients. This response to AS was more unfavourable in males than females (associated with higher NT-proBNP, and lower blood pressure), but was more modifiable with AVR. This was not detected using conventional analysis. Because cardiac function is coupled with the vasculature, a novel integrated assessment of the cardiovascular system was developed. Wave intensity theory was used to combine central blood pressure and CMR aortic blood flow-velocity waveforms to represent the interaction of the heart with the vessels in terms of traveling energy waves. This was performed and then validated in 206 individuals (the largest cohort to date), demonstrating inefficient ventriculo-arterial coupling in female sex and healthy ageing. CMR imaging was performed in 236 individuals before training for a first-time marathon and 138 individuals were followed-up after marathon completion. After training, systolic/diastolic blood pressure reduced by 4/3mmHg, descending aortic stiffness decreased by 16%, and ventriculo-arterial coupling improved by 14%. LV mass increased slightly, with a tendency to more symmetrical hypertrophy. The reduction in aortic stiffness was equivalent to a 4-year reduction in estimated biological aortic age, and the benefit was greater in older, male, and slower individuals. In conclusion, this thesis demonstrates that automating analysis of clinical cardiovascular phenotypes is precise with significant time-saving. Complex data that is usually discarded can be used efficiently to identify new biology. Deeper phenotypes developed in this work inform risk reduction behaviour in healthy individuals, and demonstrably deliver a more sensitive marker of LV remodelling, potentially enhancing risk prediction in severe aortic stenosis

Semi-automatic liquid filling system using NodeMCU as an integrated Iot Learning tool

Computer programming and IoT are the key skills required in Industrial Revolution 4.0 (IR4.0). The industry demand is very high and therefore related students in this field should grasp adequate knowledge and skill in college or university prior to employment. However, learning technology related subject without applying it to an actual hardware can pose difficulty to relate the theoretical knowledge to problems in real application. It is proven that learning through hands-on activities is more effective and promotes deeper understanding of the subject matter (He et al. in Integrating Internet of Things (IoT) into STEM undergraduate education: Case study of a modern technology infused courseware for embedded system course. Erie, PA, USA, pp 1–9 (2016)). Thus, to fulfill the learning requirement, an integrated learning tool that combines learning of computer programming and IoT control for an industrial liquid filling system model is developed and tested. The integrated learning tool uses NodeMCU, Blynk app and smartphone to enable the IoT application. The system set-up is pre-designed for semi-automation liquid filling process to enhance hands-on learning experience but can be easily programmed for full automation. Overall, it is a user and cost friendly learning tool that can be developed by academic staff to aid learning of IoT and computer programming in related education levels and field

Background Investigations of the KATRIN Pre-Spectrometer

Measurements and analysis methods of this thesis have revealed that an electrostatic retarding spectrometer (MAC-E filter) with a rather large magnetic shielding is essentially a background-free device, if both the effects from Penning traps and Radon emanation processes are controlled by careful design and appropriate counter measures (e.g. LN2 baffles)

Design, development and application of an automated framework for cell growth and laboratory evolution

Precise control over microbial cell growth conditions could enable detection of minute phenotypic changes, which would improve our understanding of how genotypes are shaped by adaptive selection. Although automated cell- culture systems such as bioreactors offer strict control over liquid culture conditions, they often do not scale to high-throughput or require cumbersome redesign to alter growth conditions. I report the design and validation of eVOLVER, a scalable DIY framework that can be configured to carry out high- throughput growth experiments in molecular evolution, systems biology, and microbiology. I perform high-throughput evolution of yeast across systematically varied population density niches to show how eVOLVER can precisely characterize adaptive niches. I describe growth selection using time-varying temperature programs on a genome-wide yeast knockout library to identify strains with altered sensitivity to changes in temperature magnitude or frequency. Inspired by large-scale integration of electronics and microfluidics, I also demonstrate millifluidic multiplexing modules that enable multiplexed media routing, cleaning, vial-to-vial transfers and automated yeast mating

Proceedings of the 2011 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory

This book is a collection of 15 reviewed technical reports summarizing the presentations at the 2011 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory. The covered topics include image processing, optical signal processing, visual inspection, pattern recognition and classification, human-machine interaction, world and situation modeling, autonomous system localization and mapping, information fusion, and trust propagation in sensor networks