Using appreciative inquiry to explore the professional practice of a lecturer in higher education: moving towards life-centric practice

This paper reports on a strategy for exploring the life-centric practice of a lecturer in Higher Education. The initiative for this inquiry arose out of the realisation that there did not appear to be positive, heart-lifting stories in a lecturer’s current teaching experiences. Using an appreciative eye and supported by a critical friend, life-giving experiences were ‘stalked’ from the past. The hope in this endeavour was to find greater meaning in the lecturer’s best professional practice. Using an Appreciative Inquiry approach, this endeavour rejuvenated the lecturer’s professional practice. As life-centric stories were recalled, provocative propositions were constructed that became the basis of a personalised action plan for future professional practice. This paper outlines the nature of the journey and the heartfelt discoveries

Terminal deoxynucleotidyltransferase. Serological studies and radioimmunoassay

Mouse antisera against calf terminal deoxynucleotidyltransferase (terminal transferase) have been prepared. The sera have been used to characterize terminal transferase both by studying inhibition of enzyme activity and by developing a competition radioimmunoassay using highly purified 125I-labeled terminal transferase. By either assay, anti-terminal transferase serum did not cross-react significantly with calf DNA polymerases alpha and beta, Escherichia coli DNA polymerase I, or the reverse transcriptase of Moloney mouse leukemia virus. The calf terminal transferase did, however, share cross-reactive but not identical determinants with human and murine terminal transferase. The radioimmunoassay could detect as little as 2 ng of terminal transferase/mg of soluble protein in a tissue extract. Thymocytes were found to contain 280 ng of terminal transferase/mg of cell protein or about 1 X 10^(5) molecules/cell; bone marrow had about 1% of the level of enzyme found in thymus. Extracts of spleen, peripheral white blood cells, lymph nodes, liver, muscle, and kidney all lacked detectable antigenicity of terminal transferase. These data indicate that terminal transferase is a tissue-specific enzyme and is not related to other DNA polymerases

Improved Computer Detection and Mapping of Cerebral Oxygenation

Near-infrared (NIR) optical image reconstruction that incorporates blood oxygen level dependant (BOLD) magnetic resonance imaging has the potential to improve both quantifiable measurement of oxygenation and the spatial resolution involved in such mapping. My thesis continues some preliminary work in this area through development of an analytic diffusion parameter estimation algorithm for use with a NIR imaging array and development of a finite element mesh utility to read a priori BOLD images and tag them with property elements for NIR image resolution improvement

Murine terminal deoxynucleotidyl transferase: cellular distribution and response to cortisone

The mouse thymus contains two forms of terminal deoxynucleotidyl transferase (TdT) which are distinguishable by the salt concentration necessary to elute them from a phosphocellulose column, by their distrubtion among the thymocyte subpopulations, and by their sensitivity to cortisone treatment. In the whole thymus the later eluting peak (peak II) is the predominant one with about 3-10% of the total activity appearing in peak I. Both peak I and peak II activities are most sensitively assayed by the polymerization of dGMP onto an oligo(dA) primer. The minor population of thymocytes which is less dense and cortisone-resistant contains a higher specific activity of peak I TdT. The majority of TdT activity is, however, found in the major population of thymocytes which occurs in the center region of a bovine serum albumin gradient and is cortisone-sensitive. A very low level of an activity indistinguishable from peak II TdT activity is also detected in the mouse bone marrow. Other tissues, such as spleen, liver, heart, and brain lack detectable amounts of TdT activity

Corporate Compliance Issues in Managing Supply Chains in the Environmental-Friendly 21 st Century

Recent economic crisis has alerted citizens around the world about the behavioral patterns of corporations that were not in lined with the expectations of the local citizens. These events has re-emerged the global conversations of the responsibilities of corporations that are beyond the conventional wisdom of financial accomplishments. Traditionally, corporations have been in tuned with financial goals and awareness of necessity of Corporate Compliance efforts operationally along their Supply Chains. The recent addition of Social Responsibilities has certainly complicated corporate strategies in varied magnitude. At times, it introduced un- welcomed uncertainty in terms of expectations. The focus of this research is to investigate the first-step for corporations, the understanding of Corporate Social Responsibility expectations so as to allow corporations to refine their strategies so as to be in compliance along their supply chains with minimal additional resources. An empirical model for data collection from corporate practitioners will also be introduced

Map Generation from Large Scale Incomplete and Inaccurate Data Labels

Accurately and globally mapping human infrastructure is an important and challenging task with applications in routing, regulation compliance monitoring, and natural disaster response management etc.. In this paper we present progress in developing an algorithmic pipeline and distributed compute system that automates the process of map creation using high resolution aerial images. Unlike previous studies, most of which use datasets that are available only in a few cities across the world, we utilizes publicly available imagery and map data, both of which cover the contiguous United States (CONUS). We approach the technical challenge of inaccurate and incomplete training data adopting state-of-the-art convolutional neural network architectures such as the U-Net and the CycleGAN to incrementally generate maps with increasingly more accurate and more complete labels of man-made infrastructure such as roads and houses. Since scaling the mapping task to CONUS calls for parallelization, we then adopted an asynchronous distributed stochastic parallel gradient descent training scheme to distribute the computational workload onto a cluster of GPUs with nearly linear speed-up.Comment: This paper is accepted by KDD 202