No description available.

No description available.

No description available.

No description available.

No description available.

No description available.

Fluorescence microscopy is an essential tool for imaging subcellular structures in tissue. Two-photon microscopy enables imaging deeper into tissue using near-infrared light. The use of image analysis and computer vision tools to detect and extract information from the images is still challenging due to the degraded microscopy volumes by blurring and noise during the image acquisition and the complexity of subcellular structures presented in the volumes. In this thesis we describe methods for segmentation and detection of fluorescence microscopy images in 3D. We segment tubule boundaries by distinguishing them from other structures using three dimensional steerable filters. These filters can capture strong directional tendencies of the voxels on a tubule boundary. We also describe multiple three dimensional convolutional neural networks (CNNs) to segment nuclei. Training the CNNs usually require a large set of labeled images which is extremely difficult to obtain in biomedical images. We describe methods to generate synthetic microscopy volumes and to train our 3D CNNs using these synthetic volumes without using any real ground truth volumes. The locations and sizes of the nuclei are detected using of our CNNs, known as the Sphere Estimation Network. Our methods are evaluated using real ground truth volumes and are shown to outperform other techniques.

The steady downscaling of CMOS technology has led to the development of devices with nanometer dimensions. Contemporaneously, maturity in technologies such as chemical self-assembly and DNA scaffolding has influenced the rapid development of non-CMOS nanodevices including vertical carbon nanotube (CNT) transistors and molecular switches. One main problem in manufacturing defect-free nanodevices, both CMOS and non-CMOS, is the inherent variability in nanoscale fabrication processes. Compared to current CMOS devices, nanodevices are also more susceptible to signal noise and thermal perturbations. One approach for developing robust digital systems from such unreliable nanodevices is to introduce defect- and fault-tolerance at the architecture level. Structurally redundant architectures, reconfigurable architectures and architectures that are a hybrid of the previous two have been proposed as potential defect- and fault-tolerant nanoscale architectures. Hence, the design of reliable nanoscale digital systems will require detailed architectural exploration. In this dissertation, we develop probabilistic methodologies and CAD tools to expedite the exploration of defect- and fault-tolerant architectures. These methodologies and tools will provide nanoscale system designers with the capability to carry out trade-off analysis in terms of area, delay, redundancy and reliability. During execution, the next state of a digital system is only dependent on the present state and the digital signals propagate in discrete time. Hence, we have used Markov processes to analyze the reliability of nanoscale digital architectures. Discrete Time Markov Chains (DTMCs) have been used to analyze logic architectures and Markov Decision processes (MDPs) have been used to analyze memory architectures. Since structurally redundant and reconfigurable nanoarchitectures may consist of millions of nanodevices, we have applied state space partitioning techniques and Belief propagation to scale these techniques. We have developed three toolsets based on these Markovian techniques. One of these toolsets has been specifically developed for the architectural exploration of molecular logic systems. The toolset can generate defect maps for isolating defective nanodevices and provide capabilities to organize structurally redundant fault-tolerant architectures with the non-defective devices. Design trade-offs for each of these architectures can be computed in terms of signal delay, area, redundancy and reliability. Another tool called HMAN (Hybrid Memory Analyzer) has been developed for analyzing molecular memory systems. Besides analyzing reliability-redundancy trade-offs using MDPs, HMAN provides a very accurate redundancy-delay trade-off analysis using HSPICE. SETRA (Scalable, Extensible Tool for Reliability Analysis) has been specifically designed for analyzing nanoscale CMOS logic architectures with DTMCs. SETRA also integrates well with current industry-standard CAD tools. It has been shown that multimodal computational models capture the operation of emerging nanoscale devices such as vertical CNT transistors, instead of the bimodal Boolean computational model that has been used to understand the operation of current electronic devices. We have extended an existing multimodal computational model based on Markov Random Fields (MRFs) for analyzing structurally redundant and reconfigurable architectures. Hence, this dissertation develops multiple probabilistic methodologies and tools for performing nanoscale architectural exploration. It also looks at different defect- and fault-tolerant architectures and explores different nanotechnologies. / Ph. D.

Hydrogen causes defects, for which aluminiurn alloy products are rejected. The behaviour of hydrogen in aluminium-magnesium-silicon alloy extrusion ingots, has been studied throughout the course of manufacture from freshly reduced aluminium. It is shown that hydrogen in the liquid metal is produced by temperature-dependent reaction between the metal and water vapour in the atmosphere. As the metal is received from the reduction cells, its temperature is -850 'C and its hydrogen content, >0.4 cm3/100 g, is too high for casting sound ingots. The metal is transferred first to a so-called melting furnace, where it is alloyed and stirred, thence to a holding furnace, where the composition is adjusted, the metal is degassed by gas sparging and allowed to settle before casting. The metal cools throughout these operations and as the temperature falls, the calculated value for the hydrogen content in equilibrium with the atmosphere falls in response to the reduced hydrogen solubility. The actual hydrogen content of the metal exhibited marked hysteresis in following the equilibrium value. Significant reduction of the hydrogen content occurred only when the metal was agitated. The hydrogen content never fell below the equilibrium value even during the nominal degassing operation, leading to the conclusion that gas sparging in a furnace does not positively remove hydrogen but only assists the equilibration. The hot-top DC casting process yielded a 8 m x 0.18 m diameter ingot with a virtually uniform hydrogen content. When this ingot was homogenised by heating it to 590˚C in a 7h cycle, a significant proportion of the hydrogen content was lost from the surface zone. By matching the loss to a theoretical model assuming diffusion control, it was shown that the loss of hydrogen is attenuated by trapping in micropores. The effects of simulated industrial atmospheres on the loss or absorption of hydrogen by the solid alloy were investigated in an extended series of laboratory heat-treatments. The interaction of the metal with these atmospheres was found to be determined by the nature of the oxide films formed and therefore the films were investigated by XPS and SIMS surface analysis techniques. In clean atmospheres the absorption or loss of hydrogen was determined by the balance between inward migration of protons and outward diffusion of hydrogen atoms through the oxide. Pollution of the air by chlorine or especially sulphur stimulated hydrogen absorption to a degree which seriously damaged the metal by pore growth. These effects are explained by modified compositions and structures in the surface oxide.

Cette étude, après avoir souligné l’évolution complexe de l’enseignement de la littérature au secondaire, et les difficultés actuelles face à ce que les instructions officielles nomment la lecture analytique, montre les intérêts didactiques du texte poétique résistant. Une mise en œuvre auprès d’élèves de 3e dans le cadre de cet apprentissage, et l’analyse de leurs textes de lecteurs, permettent ainsi de vérifier l’intérêt didactique du texte poétique résistant. En effet, les zones d’indéterminations spécifiques qui le caractérisent créent une dynamique motivationnelle et stimulent l’effort interprétatif de l’élève. Les contraintes fécondes de ce type de texte favorisent ainsi une lecture littéraire « dialectique », plurielle, contribuant à la compréhension de la notion d’interprétation littéraire. La rencontre avec les textes poétiques résistants apparait donc comme une expérience précieuse, porteuse de progrès pour l’apprentissage de l’élève et pour son autonomisation. / After underlining the complex evolution of teaching literature at Secondary school level, and the current difficulties faced when teaching the official syllabus, particularily as far as analytical reading is concerned, this study reveals the educational benefits of teaching Resistance poetry. An experiment carried out with Year 10 pupils, and the analysis of their reader's texts enables us to assess the educational importance of the study of Resistance poetry. Indeed, the characteristic indetermination zones create a motivational dynamic and stimulate interpretational efforts amongst the pupils. The prolific constraints of this type of text encourage a « dialectic » and plural literary reading of the text, contributing to the understanding of the notion of literary interpretation. The encounter with Resistance poetry appears then to be a valuable experience, encouraging pupils to progress and become more independent.