<p> This work was started to investigate new methods of synthesizing certain fulvenes. It was hoped that nucleophilic aromatic substitution of chlorine on 6,6-bis-(p-chlorophenyl) fulvene would provide an alternate route for the preparation of para-substituted 6,6-diphenyl fulvenes which had previously been prepared through the appropriately para-substituted benzophenone and cyclo-pentadienide (1,2). Attempts to prepare these substituted 6,6-diphenylfulvenes were unsuccessful.</p> <p> Secondly, a method of alkylating certain fulvenes in the cyclopentadiene ring was studied. With this in mind, 6,6-diphenylfulvene was treated with various nucleophiles which should give the relatively stable cyclopentadienide intermediate if the base adds to the exocyclic carbon atom. Alkylation of this anion, followed by expulsion of the nucleophilic group and a proton should then generate a new fulvene alkylated in the cyclopentadiene ring. In no case was any alkylated fulvene isolated. The major reaction products were two isomers of benzhydryl cyclopentadiene, rather than the expected alkylated fulvenes. The benzhydryl cyclopentadiene (mixture of two isomers) appears to have resulted from a reduction reaction.</p> <p> Since fulvenes of the type under study are generally unstable, an attempt was made to trap these alkylated fulvenes, if these were present, as their Diels-Alder adducts with tetracyanoethylene (TCNE). This attempt gave the adduct from one of the isomers of benzhydryl cyclopentadiene. The adducts from the other two possible isomers of benzhydryl cyclopentadiene were not detected. This result is an indication of the different reactivities of these isomers to TCNE.</p> <p> From the absence of TCNE adducts of the expected alkylated fulvenes, it was concluded that these fulvenes had not materialized in the attempted alkylation.</p> / Thesis / Master of Science (MSc)

<p>Synthesizing the realistic motion of a humanoid is a very sophisticated task, studied in different research areas. This work addresses the problem to synthetize realistic animations of 3D biped characters in a simulated environment, using genetic algorithms. Characters are represented as a structure of rigid bodies linked each other by 1DOF joints. Such joints are controlled by sinusoidal functions whose parameters are calculated by the genetic algorithm. Results, obtained by testing and comparing several different genetic operators, are presented. The system we have created allows the non-skilled user, to automatically create animations by setting only few key-poses of the characters.</p>

Background: Computerization and the automation of nursing practice have evolved discretely and concurrently in this local health authority. During the early years when computers were first introduced into the clinical areas, computer technology was deployed with lilLIe or no consideration of the relationship between nurses and their requirements for access to information. With limited education and training, computer adoption rates among nurses have varied and havc not yct achieved the desired level of uptake to optimize the use ofcomputer technology in nursing practice. Aim: The purposc of this grounded theory research study was to gain a theoretical understanding about how nurses' understand and manage computer integration in their clinical practice. Method: Grounded Theory methods were used to examine the data acquired through semistructured interviews of 12 RN participants, currently practicing in two acute care, tertiary hospitals. Using the constant-comparative method of analysis, all data wcre collected and analyzed concurrently. Memo-writing was used extensively throughout the data collection and analysis process to further analyze and engage with the data. Findings: The findings demonstrate that nurses experience the integration of computers in their practice with varying spccds and degrees of adoption. They all engaged in the social process identified in this thesis as "Developing a Relationship with the Computer in Nursing Practice". Conditions and contingencies such as Prior Experiences contribute 10 the nurses' ability to Synthesize Values in their practice. Synthesizing Values is a process that requires nurses to identify and acknowledge their practice values in relation to the integration of computer technology in the context of patient care. The extent to which the nurse is able to synthesize values, detcnnincs herlhis ability to realize the benefits of integrating computer technology and subsequently manage the barriers. The extent to which nurses realize benefits and manage the barriers further defines whether they, "adopt", "adapt" or "ignore" the computer technology. This process is continuous and dynamic. As the nurses engage in new experiences associated with computerization, their acknowledgment of and ability to synthesize values and thus to realize benefits and/or manage the barriers becomes that much more infonned. Ln the end, the nurse may transition from a stale of"ignoring" to a stale of ,'adopting" depending on the outcome of her or his ability 10 realize benefits and manage the barriers. Conclusions: The participants in this study illuminated the importance of the organization attending to a diverse nursing community whcn introducing computer technology in their respective practice environments. Consideration of nurses' prior experiences particularly in the areas of computer experiences, bio-medical technology experiences, leaming, organizational discourses and professional discourses, will better inform future computerization initiatives requiring computer adoption and the inclusion of related clinical information systems. The participants in this study reveal the basic social process of DEVELOPING A RELATIONSHJP WITH THE COMPUTER IN NURSING PRACTICE when confronted with computerization in their practice. / Graduate

Synthesizing the realistic motion of a humanoid is a very sophisticated task, studied in different research areas. This work addresses the problem to synthetize realistic animations of 3D biped characters in a simulated environment, using genetic algorithms. Characters are represented as a structure of rigid bodies linked each other by 1DOF joints. Such joints are controlled by sinusoidal functions whose parameters are calculated by the genetic algorithm. Results, obtained by testing and comparing several different genetic operators, are presented. The system we have created allows the non-skilled user, to automatically create animations by setting only few key-poses of the characters.

Robot motion can be described in several alternative representations, including joint configuration or end-effector spaces. These representations are often used for manipulation or navigation tasks but they are not suitable for tasks that involve close interaction with the environment. In these scenarios, collisions and relative poses of the robot and its surroundings create a complex planning space. To deal with this complexity, we exploit several representations that capture the state of the interaction, rather than the state of the robot. Borrowing notions of topology invariances and homotopy classes, we design task spaces based on winding numbers and writhe for synthesizing winding motion, and electro-static fields for planning reaching and grasping motion. Our experiments show that these representations capture the motion, preserving its qualitative properties, while generalising over finer geometrical detail. Based on the same motivation, we utilise a scale and rotation invariant representation for locally preserving distances, called interaction mesh. The interaction mesh allows for transferring motion between robots of different scales (motion re-targeting), between humans and robots (teleoperation) and between different environments (motion adaptation). To estimate the state of the environment we employ real-time sensing techniques utilizing dense stereo tracking, magnetic tracking sensors and inertia measurements units. We combine and exploit these representations for synthesis and generalization of motion in dynamic environments. The benefit of this method is on problems where direct planning in joint space is extremely hard whereas local optimal control exploiting topology and metric of these novel representations can efficiently compute optimal trajectories. We formulate this approach in the framework of optimal control as an approximate inference problem. This allows for consistent combination of multiple task spaces (e.g. end-effector, joint space and the abstract task spaces we investigate in this thesis). Motion generalization to novel situations and kinematics is similarly performed by projecting motion from abstract representations to joint configuration space. This technique, based on operational space control, allows us to adapt the motion in real time. This process of real-time re-mapping generates robust motion, thus reducing the amount of re-planning. We have implemented our approach as a part of an open source project called the Extensible Optimisation library (EXOTica). This software allows for defining motion synthesis problems by combining task representations and presenting this problem to various motion planners using a common interface. Using EXOTica, we perform comparisons between different representations and different planners to validate that these representations truly improve the motion planning.

L’architecture et la régulation de la traduction eucaryote fut pendant longtemps un mystère pour les biologistes. Je présente ici un protocole détaillé pour purifier de manière homogène des ribosomes à partir de cellules HeLa, pour des études biochimiques mais également structurales. En utilisant ces ribosomes, j’ai obtenu des cristaux diffractant à faible résolution, pouvant être utilisés pour de futurs travaux. Une analyse par cryo-microscopie électronique (CME) a abouti à une structure à 5 A de résolution, permettant la construction d’un modèle. De plus, les facteurs eRF1 et eRF3 ont permis des premières études de la terminaison de la traduction par CME. Ces protéines en complexe ont également été étudiées par cristallographie aux rayons-X, montrant des interactions jusqu’alors jamais observées. L’ensemble de ce travail fournit des résultats importants pour la préparation et la description de la structure du ribosome humain, pavant la voie vers l’analyse de complexes fonctionnels. / Ribosomes comprise the translational machinery engaged in synthesizing proteins. The architecture and translation regulation of eukaryotic especially, human ribosomes, has been an enigma for a long time. I established a protocol for purifying homogenous ribosomes from HeLa cells which can be used for structural as well as biochemical analysis. Using these ribosomes, I obtained plate-like crystals of 80S diffracting to low resolution. A cryo electron microscopy analysis of these ribosomes yielded 5 Å resolution structure with secondary structures of rRNA and protein clearly visible. Furthermore, these ribosomes, along with the eukaryotic release factors (eRF1 and eRF3) purified by over-expression in bacteria, formed the basis for translation termination studies using cryo electron microscopy. Simultaneously, eRF1-eRF3 protein complex was explored by X-ray crystallography revealing new interactions. Together, this work paves the way for the analysis of functional ribosome complexes.

An evidence synthesis group has worked under the auspices of the DEC Recommended Practices Commission with assistance from ECTA to develop systematic and replicable procedures and guidelines for synthesizing research evidence supporting the DEC recommended practices. This session presents the guidelines, illustrations, and impacts of syntheses completed to date.

The mission statements of Utah State University and the Department of Biology, as well as the requirements of funding agencies like the National Science Foundation encourage an integration of teaching and research. I have attempted to achieve that in my dissertation work by using tools I originally created to support and inform my biological research projects to teach science content and inquiry to middle school and undergraduate students. Chapter 2 of this dissertation reports the results of surveys for Hymenophyllum wrightii, a fern with independent gametophyte populations in the Pacific Northwest, which improved our understanding of the range, distribution, and habitat requirements of this species that was previously thought to be rare. The result of these surveys led to the removal of the species from the Forest Service's Alaska Region Sensitive Species List and provided a first report of the species in the contiguous United States. A preliminary genetic data analyses of gametophyte populations found during the surveys sets the stage for future work to determine the relationships between the independent gametophyte populations and sporophytes growing in Haidi Gwaii, British Columbia and East Asia, which is important for understanding their evolutionary and conservation potential. Chapter 3 describes an attempt to explore the population genetics of another fern with independent gametophyte populations, Crepidomanes intricatum in the Appalachian mountains of Eastern North America. This species apparently exists only as gametophytes, which raises interesting questions about how and when it was established, and its conservation and evolutionary potential. This population genetics analysis was not able to be completed, but led to an analysis of potential sources of error in genotyping-by-sequencing datasets and to the development of a set of software tools for evaluating the quality of these datasets. To help better visualize the evolutionary processes at work in populations of ferns with independent gametophytes, I developed an interactive software tool to simulate populations of ferns in a virtual 3-dimensional space. Chapter 4 describes that tool, an educational activity using it to teach population genetics and science inquiry to undergraduates, and the results of a study demonstrating its effects on student content learning and confidence in their ability to perform inquiry. This tool and the activity built around it have been used in undergraduate genetic laboratories at Utah State University since 2011. The apparent benefits of this simulation tool led to a collaboration with educators and the development of another 3-dimensional simulation tool to teach eight grade students about the effects of the environment and human impacts on living organisms. Chapter 4 presents an educational activity using this tool that has been used as part of a larger National Science Foundation funded project to train teachers to use technology in the classroom. The simulations are publicly available and have been used by hundreds of students in two Utah school districts. Together, these projects demonstrate on way that research to expand knowledge can lead to tools to impart knowledge to students.

Research on biosynthesis of tobacco mosaic virus (TMV) ribonucleic acid (RNA) in vitro has been reported by Cochran, et al; Karasek and Schramm; Kim and Wildman; Cornuet and Astier; and Tongur and Baland in. It has been postulated that the replication of a number of viruses containing single-stranded RNA is accompanied by the formation of a virus-specific double-stranded helical RNA, the replicative form. This has been demonstrated both for animal and bacterial viruses including MS2. The double helical structure of purified replicative form of MS2 was established by X-ray diffraction studies. One of the strands was shown to be a viral RNA strand of the parental type ("plus" strand), the other being complementary to it ("minus" strand). Studies on Escherichia coli infected with RNA phages suggest that a structure containing both a "plus 11 and a "minus " strand is an obligatory intermediate in viral reproduction.

The field of Artificial Intelligence (AI) has experienced unprecedented growth in recent years, thanks to the numerous applications related to speech recognition, natural language processing, and computer vision. However, one of the challenges facing AI is the requirement for large amounts of energy, time, and data to be effective and accurate. As a result, many researchers are focusing on finding ways to minimize these challenges and make AI more accessible to everyone. One solution that has gained popularity in recent years is the generation of data artificially, either through synthetic or augmented means. Synthetic data is created by first learning how to recreate the structure or knowledge behind real-world data, while augmentation involves artificially changing the original data, such as flipping, rotating, cropping, or scaling. By generating data in this way, researchers can overcome the challenge of acquiring large amounts of real-world data and provide a more cost-effective way of training machine learning models. The lack of direct qualitative comparisons between synthetic and augmented data prompts the goal of this thesis, which aims to investigate the differences between the two approaches in generating data for an analytical tool that analyzes microorganisms. The thesis seeks to explore the effectiveness of each data type by training a segmentation model with the aim of generating accurate and realistic segmentations of microorganisms. The organism's growth rate and size is provided by a segmentation mask used as the base for the image generation. Which, in order to  generate realistic images that accurately depict their behavior it needs to be able to recreate imaging noise, halo effect, and relational dependencies. Additionally, a training process is being conducted with an augmentation model to compare the performance of the segmentation model based on different data types, offering valuable insights into their respective advantages and effectiveness in maximizing the limited data count. To achieve this goal, the thesis used three main components: the Albumentations augmentation library, the Taming transformer synthesizer built on a VQ-GAN, and the Omnipose segmentation model for evaluation. With the help of a microorganism dataset, the thesis aimed to train Omnipose to generate realistic and accurate segmentations based on different training sets. However, this is limited to testing on a restricted set of models among the wide range that exists. The findings of the thesis suggest that a better method for qualitative comparison is needed, which could involve a less elaborate setup or novel evaluation methods. Nonetheless, the results indicate that the choice between synthetic and augmented input data does not have significant effects on the initial outcomes when training the segementation model. This is supported by the Structural similarity index (SSIM) and Peak signal-to-noise ratio (PSNR) averages and curves between the two methods, despite the differences in data generation. A more considerable difference is observed with the quality of data, as indicated by the poor performance of the synthetic model and further testing of specific data distributions. Therefore, the efficiency of training a segmentation model on micro-organisms data is determined more by the quality and distribution of data rather than the dataset generation methods. This finding is of significance to researchers in the field as it adds further information on the how to better training on a segmentation model with a limited dataset of microbial images. Which can have significant implications in various fields, such as medicine, environmental science, and biotechnology, where accurate analysis of microorganisms can help diagnose diseases, monitor the health of ecosystems, and develop new biotechnological products. Moving forward, it is recommended that future research should aim to establish clear definitions for synthetic and augmented data, and evaluate their inherent characteristics in order to better understand their differences. This should include specific studies that generate synthetic and augmented data for micro-organisms, as well as direct comparisons between the two data types. Furthermore, additional research should be conducted on well-established datasets, such as ImageNet , with a focus on image-to-image processing and examining the impact on various computer vision models. Following a less established dataset on other microbial organisms to compare the results. Ultimately, this thesis contributes to the ongoing efforts to overcome the challenges faced in the field of AI by providing valuable insights into the effectiveness of generating data artificially.