Exploring the effects of outdoor activities and connectedness with nature on cognitive styles and creativity : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Psychology at Massey University, Wellington, New Zealand

Listed in 2017 Dean's List of Exceptional ThesesThe natural environment’s potential to improve education, work, and lifestyles is receiving increasing attention by policy makers and practitioners. Psychological research has demonstrated that stress reduction, attention restoration, and increased creativity can result from exposure to nature. Such evidence notwithstanding, the precise psychological mechanisms explaining these effects remain unclear. This thesis provides a systematic examination of how contact with nature might affect humans. Four studies were conducted. Study 1 reports two meta-analyses (N = 10701, k = 100) involving: (i) 66 studies using preand post-test designs, and (ii) 32 experimental studies that include a control group. Although outdoor activities have been found overall to affect personal and social outcomes positively, there has been limited research into the effects on cognitive variables of exposure to outdoor environments. To address this gap in the literature, I aim to investigate whether contact with nature (in two dimensions–the psychological attachment to nature and the physical exposure to it) is associated with processes related to creativity (i.e., cognitive styles and divergent thinking creativity). Study 2 (N = 138) tests the relationship between connectedness with nature and cognitive styles and reports a significant positive association between connectedness with nature and both innovative and holistic thinking styles. Building on this finding, Study 3 (N = 185) not only replicates the results of Study 2 by controlling for wellbeing processes, but includes a new creativity test to examine the link between connectedness with nature and creative processes (connectedness with nature is found to be positively linked with divergent-thinking creativity). As these three studies employ cross-sectional data where causality cannot be inferred, the last study involves an experimental design. Study 4 (N = 93) manipulates active versus passive engagement with nature and examines the mediating impact of connectedness with nature on the link between outdoor activities and divergentthinking creativity. Some theoretical explanations as to how nature might affect our creativity are proposed. Potential limitations and suggestions for future research are discussed. The findings are intended to provide supporting evidence for the relationship between nature and creativity, and hopefully inform educational pedagogy and lifestyle choices likely to enhance creativity

Reactivating Fetal Hemoglobin Expression in Human Adult Erythroblasts Through BCL11A Knockdown Using Targeted Endonucleases.

We examined the efficiency, specificity, and mutational signatures of zinc finger nucleases (ZFNs), transcriptional activator-like effector nucleases (TALENs), and clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9 systems designed to target the gene encoding the transcriptional repressor BCL11A, in human K562 cells and human CD34+ progenitor cells. ZFNs and TALENs were delivered as in vitro transcribed mRNA through electroporation; CRISPR/Cas9 was codelivered by Cas9 mRNA with plasmid-encoded guideRNA (gRNA) (pU6.g1) or in vitro transcribed gRNA (gR.1). Analyses of efficacy revealed that for these specific reagents and the delivery methods used, the ZFNs gave rise to more allelic disruption in the targeted locus compared to the TALENs and CRISPR/Cas9, which was associated with increased levels of fetal hemoglobin in erythroid cells produced in vitro from nuclease-treated CD34+ cells. Genome-wide analysis to evaluate the specificity of the nucleases revealed high specificity of this specific ZFN to the target site, while specific TALENs and CRISPRs evaluated showed off-target cleavage activity. ZFN gene-edited CD34+ cells had the capacity to engraft in NOD-PrkdcSCID-IL2Rγnull mice, while retaining multi-lineage potential, in contrast to TALEN gene-edited CD34+ cells. CRISPR engraftment levels mirrored the increased relative plasmid-mediated toxicity of pU6.g1/Cas9 in hematopoietic stem/progenitor cells (HSPCs), highlighting the value for the further improvements of CRISPR/Cas9 delivery in primary human HSPCs

A comparison of univariate and multivariate gene selection techniques for classification of cancer datasets

BACKGROUND: Gene selection is an important step when building predictors of disease state based on gene expression data. Gene selection generally improves performance and identifies a relevant subset of genes. Many univariate and multivariate gene selection approaches have been proposed. Frequently the claim is made that genes are co-regulated (due to pathway dependencies) and that multivariate approaches are therefore per definition more desirable than univariate selection approaches. Based on the published performances of all these approaches a fair comparison of the available results can not be made. This mainly stems from two factors. First, the results are often biased, since the validation set is in one way or another involved in training the predictor, resulting in optimistically biased performance estimates. Second, the published results are often based on a small number of relatively simple datasets. Consequently no generally applicable conclusions can be drawn. RESULTS: In this study we adopted an unbiased protocol to perform a fair comparison of frequently used multivariate and univariate gene selection techniques, in combination with a ränge of classifiers. Our conclusions are based on seven gene expression datasets, across several cancer types. CONCLUSION: Our experiments illustrate that, contrary to several previous studies, in five of the seven datasets univariate selection approaches yield consistently better results than multivariate approaches. The simplest multivariate selection approach, the Top Scoring method, achieves the best results on the remaining two datasets. We conclude that the correlation structures, if present, are difficult to extract due to the small number of samples, and that consequently, overly-complex gene selection algorithms that attempt to extract these structures are prone to overtraining

Magnetic Fields and Massive Star Formation

Massive stars ($M > 8$ \msun) typically form in parsec-scale molecular clumps that collapse and fragment, leading to the birth of a cluster of stellar objects. We investigate the role of magnetic fields in this process through dust polarization at 870 $\mu$m obtained with the Submillimeter Array (SMA). The SMA observations reveal polarization at scales of \lsim 0.1 pc. The polarization pattern in these objects ranges from ordered hour-glass configurations to more chaotic distributions. By comparing the SMA data with the single dish data at parsec scales, we found that magnetic fields at dense core scales are either aligned within $40^\circ$ of or perpendicular to the parsec-scale magnetic fields. This finding indicates that magnetic fields play an important role during the collapse and fragmentation of massive molecular clumps and the formation of dense cores. We further compare magnetic fields in dense cores with the major axis of molecular outflows. Despite a limited number of outflows, we found that the outflow axis appears to be randomly oriented with respect to the magnetic field in the core. This result suggests that at the scale of accretion disks (\lsim 10^3 AU), angular momentum and dynamic interactions possibly due to close binary or multiple systems dominate over magnetic fields. With this unprecedentedly large sample massive clumps, we argue on a statistical basis that magnetic fields play an important role during the formation of dense cores at spatial scale of 0.01 - 0.1 pc in the context of massive star and cluster star formation.Comment: Accepted for publication in Astrophysical Journa

A Market Framework for Energy Bidding Decision Making Strategy to provide a Competitive Mechanism in the Context of Deregulated Electricity Market

In the modern power grid operation, the regulatory goal of the market is to provide continuous electricity supply to the customers with reasonable energy prices. The current structure of energy market in Malaysia follows the single buyer market model, where the generation is procured solely by a single utility with a limited competition, which is not effective in lowering the electricity prices. This paper proposes a market framework for competitive strategies to achieve maximum benefits of the power grid in Sarawak, Malaysia while the optimal bidding in the day-ahead market is assessed. Game theory with the non-cooperative scheme is applied for the electricity market comprising various participants. The performance of the proposed approach is evaluated using a practical power grid with data of the electricity market obtained from available sources. The feasibility of electricity market deregulation in Sarawak is proven to be effective, as the proposed framework can provide insight into the generated revenue of energy producers in a fair and competitive market environment

A Market Framework for Energy Bidding Decision- Making Strategy to provide a Competitive Mechanism in the Context of Deregulated Electricity Market

In the modern power grid operation, the regulatory goal of the market is to provide continuous electricity supply to the customers with reasonable energy prices. The current structure of the energy market in Malaysia follows the single buyer market model, where the generation is procured solely by a single utility with limited competition, which is not effective in lowering electricity prices. This paper proposes a market framework for competitive strategies to achieve maximum benefits of the power grid in Sarawak, Malaysia while the optimal bidding in the day-ahead market is assessed. Game theory with the non-cooperative scheme is applied for the electricity market comprising various participants. The performance of the proposed approach is evaluated using a practical power grid with data of the electricity market obtained from available sources. The feasibility of electricity market deregulation in Sarawak is proven to be effective, as the proposed framework can provide insight into the generated revenue of energy producers in a fair and competitive market environment

Nanorobotic investigation identifies novel visual, structural and functional correlates of autoimmune pathology in a blistering skin disease model

Copyright © 2014 Seiffert-Sinha et al. There remain major gaps in our knowledge regarding the detailed mechanisms by which autoantibodies mediate damage at the tissue level. We have undertaken novel strategies at the interface of engineering and clinical medicine to integrate nanoscale visual and structural data using nanorobotic atomic force microscopy with cell functional analyses to reveal previously unattainable details of autoimmune processes in real-time. Pemphigus vulgaris is a life-threatening autoimmune blistering skin condition in which there is disruption of desmosomal cell-cell adhesion structures that are associated with the presence of antibodies directed against specific epithelial proteins including Desmoglein (Dsg) 3. We demonstrate that pathogenic (blister-forming) anti-Dsg3 antibodies, distinct from non-pathogenic (non-blister forming) anti-Dsg3 antibodies, alter the structural and functional properties of keratinocytes in two sequential steps - an initial loss of cell adhesion and a later induction of apoptosis-related signaling pathways, but not full apoptotic cell death. We propose a ''2-Hit'' model for autoimmune disruption associated with skin-specific pathogenic autoantibodies. These data provide unprecedented details of autoimmune processes at the tissue level and offer a novel conceptual framework for understanding the action of selfreactive antibodies.published_or_final_versio

SIRAC: Supervised Identification of Regions of Aberration in aCGH datasets

<p>Abstract</p> <p>Background</p> <p>Array comparative genome hybridization (aCGH) provides information about genomic aberrations. Alterations in the DNA copy number may cause the cell to malfunction, leading to cancer. Therefore, the identification of DNA amplifications or deletions across tumors may reveal key genes involved in cancer and improve our understanding of the underlying biological processes associated with the disease.</p> <p>Results</p> <p>We propose a supervised algorithm for the analysis of aCGH data and the identification of regions of chromosomal alteration (SIRAC). We first determine the DNA-probes that are important to distinguish the classes of interest, and then evaluate in a systematic and robust scheme if these relevant DNA-probes are closely located, i.e. form a region of amplification/deletion. SIRAC does not need any preprocessing of the aCGH datasets, and requires only few, intuitive parameters.</p> <p>Conclusion</p> <p>We illustrate the features of the algorithm with the use of a simple artificial dataset. The results on two breast cancer datasets show promising outcomes that are in agreement with previous findings, but SIRAC better pinpoints the dissimilarities between the classes of interest.</p