661 research outputs found

    New chemistry of sterically-crowded carboranes

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    Chapter one gives an introduction into heteroborane chemistry focussing on the areas of icosahedral and supraicosahedral (metalla)carboranes and their isomerisation mechanisms. Chapter two describes attempts at placing bulky substituents onto a 1,7-closo-C2B10 species so that upon reduction and subsequent oxidation the carbon atoms are unable to connect thus potentially preventing oxidation and allowing for easier capitation to form a supraicosahedral carborane. Initial efforts to synthesise such 1,7- bulky species, using tertiary alcohol substituents, did not lead to polyhedral expansion due to undesired reactivity. Compounds with bulky substituents incorporating cobaltacarborane clusters were successfully prepared but in insufficient yield for further expansion chemistry. Chapter three discusses the synthesis and characterisation of 1,7-closo-C2B10 species which incorporate a ferrocenyl unit on each substituent. Polyhedral expansion to form a 13-vertex carborane was unsuccessful, instead upon oxidation forming significantly sterically deformed 1,2 species with unprecedentedly elongated C-C connectivities. Chapter four investigates the redox chemistry of the ferrocenyl 1,2 and 1,7 species. The electronic spectrum of the 1,2 species were compared to that given by TD DFT calculations which suggest a degree of charge transfer. Associated electrochemistry suggests this may be a sterically-induced charge transfer within the 1,2 species. The steric deformation of the bis-ferrocenyl 1,2 species leads to a relatively lowtemperature isomerisation to the 1,7 species. This has renewed interest in the elucidation of the isomerisation mechanism of icosahedral carboranes. Chapter five details the synthesis and characterisation of labelled species with labels which can be reliably tracked upon isomerisation. A comparison of the experimental findings to the results of theoretical studies on the subject is examined. Chapter six contains experimental procedures and characterisation details for all the new compounds reported herein. Crystallographic data is listed in Appendices A and B (CD) along with structure solution and refinement details

    A question of trust: can we build an evidence base to gain trust in systematic review automation technologies?

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    Background Although many aspects of systematic reviews use computational tools, systematic reviewers have been reluctant to adopt machine learning tools. Discussion We discuss that the potential reason for the slow adoption of machine learning tools into systematic reviews is multifactorial. We focus on the current absence of trust in automation and set-up challenges as major barriers to adoption. It is important that reviews produced using automation tools are considered non-inferior or superior to current practice. However, this standard will likely not be sufficient to lead to widespread adoption. As with many technologies, it is important that reviewers see “others” in the review community using automation tools. Adoption will also be slow if the automation tools are not compatible with workflows and tasks currently used to produce reviews. Many automation tools being developed for systematic reviews mimic classification problems. Therefore, the evidence that these automation tools are non-inferior or superior can be presented using methods similar to diagnostic test evaluations, i.e., precision and recall compared to a human reviewer. However, the assessment of automation tools does present unique challenges for investigators and systematic reviewers, including the need to clarify which metrics are of interest to the systematic review community and the unique documentation challenges for reproducible software experiments. Conclusion We discuss adoption barriers with the goal of providing tool developers with guidance as to how to design and report such evaluations and for end users to assess their validity. Further, we discuss approaches to formatting and announcing publicly available datasets suitable for assessment of automation technologies and tools. Making these resources available will increase trust that tools are non-inferior or superior to current practice. Finally, we identify that, even with evidence that automation tools are non-inferior or superior to current practice, substantial set-up challenges remain for main stream integration of automation into the systematic review process

    Soccer Marketing in the United States

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    Soccer is continuing to grow in popularity in the United States. According to the U.S. Soccer Federation, there are more than 4 million players in the US, more than double the number in 1990 (Belson, 2010). The Sports and Fitness Industry Association (formerly SGMA) has found that total participation in soccer had increased nearly 3% annually in 2011 (Physical Activity Council, 2011). According to another SFIA study, however, a shortage of facilities and emphasis on tournament and showcase events may result in potential future downturn in participation (Athletic Business, 2012). There is also a shifting emphasis from tournament and showcase events (winning trophies) to player development, as evidenced by the formation of U.S. Soccer’s Development Academy and US Club Soccer’s National Premier Leagues. In addition, there is an increasing proliferation of the club-centric model. Marketing efforts have primarily focused on two main areas: increased participation, particularly at the youth level (Physical Activity Council, 2011; Hopkins, 2010, Wangerin, 2008) and increased revenue, spectatorship, and competitive success at the Olympic, World Cup, and professional levels (Kuper & Szymanski, 2012; Bondy, 2010; Dure, 2010; Wangerin, 2008; Pons & Standifird, 2007; Southall & Nagel, 2007). The results of these efforts have been mixed (Hopkins, 2010). There are many organizations in the United States whose main goal is to positively impact, market, and manage the growth of soccer at various levels of participation. The present study will summarize the historical, current, and future marketing efforts (including successes and failures) of the following organizations: • U.S. Soccer Foundation • U.S. Club Soccer • U.S. Soccer Federation • Major League Soccer • United Soccer Leagues • American Youth Soccer Organization • United States Adult Soccer Association • National Soccer Coaches Association of Americ

    Characterization of Prepreg Tack for Composite Manufacturing by Automated Fiber Placement

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    Automated fiber placement (AFP) has become the industry standard for large-scale production of carbon fiber reinforced plastics (CFRP) to improve rate and reduce defects associated with manual layup. Still, defects generated during AFP processes require manual, painstaking inspection by technicians and rework of the part when substantial defects are found. Prepreg (carbon fiber infused with uncured epoxy resin) tack is one of the primary factors that influences the generation of defects that arise during auto-mated fiber placement (AFP). Tack, as it relates to AFP processes and defect formation, can be understood as a combination of two stages, cohesion and decohesion. During the cohesion phase, two pieces of prepreg are brought into contact under elevated temperature and pressure. Compaction of the resin within the contact area will result in a degree of intimate contact, I, between the mating prepreg surfaces. Defect formation, as a result of decohesion between prepreg surfaces, occurs after the cohesion phase and arises due to stress from events such as fiber placement over an existing defect, on a contoured path, etc. (Figure 1). Tack strength resists the displacement of prepreg on a surface due to stresses developed during deposition

    Deep Boosted Regression for MR to CT Synthesis

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    Attenuation correction is an essential requirement of positron emission tomography (PET) image reconstruction to allow for accurate quantification. However, attenuation correction is particularly challenging for PET-MRI as neither PET nor magnetic resonance imaging (MRI) can directly image tissue attenuation properties. MRI-based computed tomography (CT) synthesis has been proposed as an alternative to physics based and segmentation-based approaches that assign a population-based tissue density value in order to generate an attenuation map. We propose a novel deep fully convolutional neural network that generates synthetic CTs in a recursive manner by gradually reducing the residuals of the previous network, increasing the overall accuracy and generalisability, while keeping the number of trainable parameters within reasonable limits. The model is trained on a database of 20 pre-acquired MRI/CT pairs and a four-fold random bootstrapped validation with a 80:20 split is performed. Quantitative results show that the proposed framework outperforms a state-of-the-art atlas-based approach decreasing the Mean Absolute Error (MAE) from 131HU to 68HU for the synthetic CTs and reducing the PET reconstruction error from 14.3% to 7.2%.Comment: Accepted at SASHIMI201
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