Paper One: An opportunity sample from three primary schools participated, split between two age categories with 37 children from year groups three and four (mean age of 8 years) and 48 from year groups five and six (mean age of 9 years 11 months). Children’s perspectives of self-talk were explored through focus groups that were transcribed and then studied through thematic analysis (Braun & Clarke, 2006). Additional quantitative data was generated from the children’s self-reported experiences of self-talk, which they also rated along constructs relating to positivity. A sample of the children’s self-talk statements that were judged to be self-evaluative, were additionally rated by an opportunity sample of four adult participants to allow a comparison between adult and child perspectives. In line with previous research, themes arose concerning children’s perspectives of the role of self-talk in enabling them to negotiate cognitive and social situations. New themes arose including the children’s concerns about the privacy of their thoughts and the prominence of self-evaluative forms of self-talk. More similarities than differences were found between the two age ranges and there was considerable overlap between adult and child ratings of the evaluative self-talk statements. The implications of these findings and suggestions for future research are discussed, including links to Paper Two of this study. Paper Two: This is a feasibility study. An opportunity sample of 79 children, aged between seven and eleven years old (mean age of 9 years 7 months), took part in a series of six group intervention sessions run by the researcher. These aimed to encourage self-talk that is self-compassionate, using elements of compassion focused approaches (Gilbert, 2009). A mixed methods design led to analysis of qualitative data from post-intervention group interviews using thematic analysis (Braun & Clarke, 2006). Quantitative data comprised the children’s pre-intervention and post-intervention responses to three questionnaires seeking to explore wellbeing, behaviour and self-compassion. Several key themes were identified, including the children’s ability to engage with the concepts of self-talk, self-kindness and the three system model of emotions (Gilbert, 2009). The concept of self-compassion itself was found to have some aspects that were harder for the children to comprehend. There were no significant differences between the children’s responses on the pre-intervention and post-intervention questionnaires, however, there were interesting qualitative responses concerning the use of these. The implications of these findings will be discussed with consideration to current educational psychologist practice and the need for future research.

Hold Me Tight: Conversations for Connection is a relationship education program based on Emotionally Focused Therapy (EFT; Johnson 2004), an empirically supported model of couple therapy with roots in attachment theory. Currently, relationship education is mostly provided through skills-based programs with a focus on teaching communication, problem-solving and conflict resolution skills from the social-learning perspective. The HMT program is different; it targets attachment and emotional connection – aspects central to relationship functioning as identified in the literature. The present study is the first outcome study of the HMT program. The purpose of the study was to examine the trajectory of change for relationship satisfaction, trust, attachment, intimacy, depressive symptoms and anxiety symptoms. Couples who participated in this study were from several cities across Canada and the United States. The trajectory for the outcome variables were modeled across baseline, pre-program, post-program and follow-up in a sample of 95 couples participating in 16 HMT program groups. Results of a four-level Hierarchical Linear Modeling (HLM: Raudenbush & Bryk, 2002) analysis demonstrated a significant cubic growth pattern for relationship satisfaction, trust, attachment avoidance, depressive and anxiety symptoms demonstrating no change from baseline to pre-program and improvements from pre-program to post-program. Scores returned to pre-program levels at follow-up. Follow-up analyses demonstrated that the changes from pre- to post-program were significant with a large effect size. We also looked at couples’ reported ability to engage in the conversations from the program and found that mean scores declined from post-program to follow-up. The results of this initial pilot study suggest that the HMT program is a promising alternative to existing relationship education programs with results comparable to skills-based relationship education programs. The decrease in scores from post-program to follow-up suggests that booster sessions following the completion of the program could be necessary to help couples maintain gains. Limitations and areas for further study are discussed.

Cost-focused innovation is perceived as the primary approach that Western companies should adopt when entering emerging markets, as their standard approaches are usually unsuitable for these environments. Although many of the principles of cost-focused innovation are relevant to these markets, companies should be weary of blindly copying previous entrants with regard to how they develop products for these markets. Each industry and product set will need to deal with a different set of factors, especially in developing environments that are constantly evolving. The aim of this research study is to gage the prevalence of a cost-focused innovation approach in developing products for emerging markets. A quantitative approach was used in order to determine if there is statistical evidence that confirms that a cost-focused innovation methodology is prevalent in designing products for low income markets. The mobile phone industry was selected for investigation as handset manufacturers have successfully created mobile phones for both developed and developing markets. The major findings were that cost-focused innovation is not significantly prevalent in developing mobile phones for low income markets. Furthermore, there is evidence that suggests that a combination of innovation approaches may be used to counter the traditional trade-offs between price and functionality in order to create low cost, high value products for both developing and developed markets. / Dissertation (MBA)--University of Pretoria, 2012. / Gordon Institute of Business Science (GIBS) / unrestricted

The use of micro- and nanotechnologies is necessary in the development of advanced sensor systems. In this thesis few selected technologies were studied and tested on fabrication of creating two different systems for bioelectrical and electrochemical applications. For biolelectrical applications a chip with a pair of gold nanoelectrodes was designed and implemented. For electrochemical analysis a novel two electrode system was designed and realized, which should contribute by greater sensitivity and accuracy in amperometric detection compared with three-electrode systems in voltammetric analysis. The fabricated systems were tested and the results were discussed.

No description available.

Histotripsy is a non-thermal, non-invasive, focused ultrasound ablation method that uses acoustic cavitation to mechanically break down tissues [1-8]. Histotripsy is heavily dependent on the mechanical properties of the tissue, allowing it to mechanically ablate tissues of lower mechanical stiffness while preserving the stiffer critical structures [15]. However, the mechanical properties of clinically relevant abdominal tissues and critical structures have not yet been adequately quantified under uniform testing parameters. Previous studies have tested and modeled the tissue selectivity of histotripsy, but these studies have been limited by the lack of mechanical property data available for these tissue types. In addition, there remains a need for additional experimental studies directly comparing the differential treatment doses required to induce histotripsy tissue damage in intra-abdominal tissue types. This thesis investigates the mechanical properties of intra-abdominal tissues under uniaxial tension, the effect of histotripsy treatment dose on intra-abdominal soft tissues and critical structures, and the potential of inducing damage to critical structures along the acoustic path pre-focal to the targeted histotripsy treatment. Results show that there are significant differences between the parenchymal tissues (liver, kidney) and the critical structure (stomach, gallbladder, small intestine, ducts, and vessels) elastic modulus, yield stress, yield strain, post-yield strain, energy to yield, and maximum stress and strain at yield. In general, histology analysis from the histotripsy experiments showed that there was an increase in tissue damage with increasing histotripsy pulses/point for all tissues. Critical structures with higher mechanical strength were more resistant to ablation compared to tissues with lower mechanical strength. Pre-focal studies showed damage to gallbladder and small intestine only in cases in which pre-focal cavitation was observed, while no damage occurred in skin and stomach for any samples treated at varying distances from the bubble cloud. Overall, this work improves our understanding of tissue selectivity of histotripsy and provides mechanical properties measurements for clinically relevant tissues that can be used to improve predictive models of tissue-selective histotripsy treatments. This work can be used in the planning of histotripsy treatments to establish proper margins of safety for treating intra-abdominal tumors. / Master of Science / Histotripsy is a non-invasive cancer treatment that mechanically breaks down tissues by rapidly forming and bursting bubbles within the tumor [1-8]. Histotripsy is heavily dependent on the mechanical properties of the tissue, allowing it to destroy weaker tissues while preserving the stiffer tissues in the surrounding area [15]. The mechanical properties of clinically relevant intra-abdominal tissues have not been quantified under uniform testing parameters. Previous studies have tested and modeled the tissue selectivity of histotripsy, but these studies have been limited by the mechanical property data available. This thesis investigates the mechanical properties of intra-abdominal tissues under tension, the effect of histotripsy treatment dose on intra-abdominal tissue damage, and the damage to critical structures from histotripsy treatment at varying distances from the tissue. Results show that there are significant differences between the liver and kidney mechanical stiffness and strength compared to the other tissues. In general, histology analysis showed that there is an increase in tissue damage with increasing histotripsy dose. Tissues with higher mechanical strength were more resistant to damage at lower doses compared to tissues with lower mechanical strength. Histotripsy damage to critical structures that are along the beam path, set distances in front of the focal point of the cavitation bubble cloud was studied. This study showed damage to gallbladder and small intestine only in cases in which pre-focal cavitation, cavitation bubbles that are not within the focal point of the cloud but are in contact with the tissue, was observed, while no damage occurred in skin and stomach for any samples treated at varying distances from the bubble cloud. Overall, this work improves our understanding of tissue selectivity of histotripsy and provides mechanical properties for clinically relevant tissues that can be used to improve predictive models of tissue-selective histotripsy treatments. This work can be used in the planning of histotripsy treatments to establish proper margins of safety for treating intra-abdominal tumors.

<p>Convolutional Neural Networks (CNNs) are machine learning models that are commonly used for computer vision tasks like image classification and object detection. State-of-the-art CNNs achieve high accuracy by using many convolutional filters to extract features from the input images for correct predictions. This high accuracy is achieved at the cost of high computational intensity. Large, accurate CNNs typically require powerful Graphics Processing Units (GPUs) to train and deploy, while attempts at creating smaller, less computationally-intense CNNs lose accuracy. In fact, maintaining consistent accuracy is a challenge for even the state-of-the-art CNNs. This presents a problem: the vast energy expenditure demanded by CNN training raises concerns about environmental impact and sustainability, while the computational intensity of CNN inference makes it challenging for low-power devices (e.g. embedded, mobile, Internet-of-Things) to deploy the CNNs on their limited hardware. Further, when reliable network is limited or when extremely low latency is required, the cloud cannot be used to offload computing from the low-power device, forcing a need to research methods to deploy CNNs on the device itself: to improve energy efficiency and mitigate consistency and accuracy losses of CNNs.</p> <p>This dissertation investigates causes of CNN accuracy inconsistency and energy consumption. We further propose methods to improve both, enabling CNN deployment on low-power devices. Our methods do not require training to avoid the high energy costs associated with training.</p> <p>To address accuracy inconsistency, we first design a new metric to properly capture such behavior. We conduct a study of modern object detectors to find that they all exhibit inconsistent behavior. That is, when two images are similar, an object detector can sometimes produce completely different predictions. Malicious actors exploit this to cause CNNs to mispredict, while  image distortions caused by camera equipment and natural phenomena can also cause mispredictions. Regardless the cause of the misprediction, we find that modern accuracy metrics do not capture this behavior, and we create a new consistency metric to measure the behavior. Finally, we demonstrate the use of image processing techniques to improve CNN consistency on modern object detection datasets.</p> <p>To improve CNN energy efficiency and reduce inference latency, we design the focused convolution operation. We observe that in a given image, many pixels are often irrelevant to the computer vision task -- if the pixels are deleted, the CNN can still give the correct prediction. We design a method to use a depth mapping neural network to identify which pixels are irrelevant in modern computer vision datasets. Next, we design the focused convolution to automatically ignore any pixels marked irrelevant outside the Area of Interest (AoI). By replacing the standard convolutional operations in CNNs with our focused convolutions, we find that ignoring those irrelevant pixels can save up to 45% energy and inference latency. </p> <p>Finally, we improve the focused convolutions, allowing for (1) energy-efficient, automated AoI generation within the CNN itself and (2) improved memory alignment and better utilization of parallel processing hardware. The original focused convolution required AoI generation in advance, using a computationally-intense depth mapping method. Our AoI generation technique automatically filters the features from the early layers of a CNN using a threshold. The threshold is determined using an Accuracy vs Latency curve search method. The remaining layers will apply focused convolutions to the AoI to reduce energy use. This will allow focused convolutions to be deployed within any pretrained CNN for various observed use cases. No training is required.</p>

Little is known about how nurses learn and use coping and adaptation skills in the workplace. Quantitative studies have identified the factors, nature, and outcomes of nursing stress. However, qualitative studies describing the human experience associated with workplace stress are lacking. The phenomenon of interest for this study using focused ethnographic method is the self-described experience of coping and adaptation associated with workplace stress of registered nurses working 12-hour shifts employed in acute care hospital facilities in east central and central Florida. Three aspects of the phenomena were examined: the self-described experiences of stress, the manner in which coping skills are acquired, and the manner in which adaptation strategies are developed by experienced bedside nursing working 12-hour shifts in acute care hospital facilities. The purposive sample included nine female bedside nurses with five or more years’ experience, working 12 hour shifts in acute care hospital facilities on bedside units, with patient ratios of 4:1 or greater. Data were collected using semi-structured, digitally recorded interviews at mutually convenient locations. The qualitative data were analyzed using inductive, constant, comparative process of coding, sorting, generalizing, and memoing to guide exploration and identify emergent themes and patterns. The predominant theme of stress emerged as the overwhelming sense of duty to the patient. Additional themes of coping and adaptation were noted. Recommendations for research, education, practice and policy are offered to support a healthy and sustainable nursing workforce.

Throughout the past 70 years, a great deal of research conducted on defining and testing problem-solving skills has led towards solution-focused practices and philosophies. As a result, some literature exists illustrating the efficacy of solution-focused practices. However, no published research exists on the factors that contribute to solution building. This study tested for components of solution building while creating a solution building inventory. Factor analysis failed to find specific factors within solution building. The results indicated that solution building is a unidimensional concept. Implications for using the solution building inventory are discussed. / Ph. D.

With its growing popularity in the field, Solution Focused Brief Therapy (SFBT) training workshops are becoming more prevalent in the family therapy training field. Because SFBT represents an innovative approach to therapy, does teaching this model demand innovative ways to train its students or are the same methods used in teaching other models of family therapy sufficient? To begin to address this question, it would be important to know how trainees experience SFBT training as it currently exists. This study qualitatively examined the process that trainees experienced when learning SFBT. Fifteen individuals responded to an email questionnaire, with 7 of those individuals participating in follow-up telephone interviews. In summary, being able to practice using a solution focused approach with clients and receiving supervision on those sessions from a supervisor who used a solution focused framework in giving feedback were factors identified as being most helpful in facilitating the learning process. The study also examined how the participants merged their existing beliefs about people and the therapeutic process with the assumptions inherent to SFBT. Finally, the study examined distinct moments, defined as moments after which the trainee knew that SFBT was a model they could use effectively with their clients. The distinct moments provided a picture of how the training and learning came together in practice for the participants. / Master of Science