The application of artificial neural networks to the interpretation and classification of freshwater benthic invertebrate communities

This thesis presents a thorough and principled investigation into the application of artificial neural networks to the biological monitoring of freshwater. It contains original ideas on the classification and interpretation of benthic macroinvertebrates, and aims to demonstrate their superiority over the biotic systems currently used in the UK to report river water quality. The conceptual basis of a new biological classification system is described, and a full review and analysis of a number of river data sets is presented. The biological classification is compared to the common biotic systems using data from the Upper Trent catchment. This data contained 292 expertly classified invertebrate samples identified to mixed taxonomic levels. The neural network experimental work concentrates on the classification of the invertebrate samples into biological class, where only a subset of the sample is used to form the classification. Other experimentation is conducted into the identification of novel input samples, the classification of samples from different biotopes and the use of prior information in the neural network models. The biological classification is shown to provide an intuitive interpretation of a graphical representation, generated without reference to the class labels, of the Upper Trent data. The selection of key indicator taxa is considered using three different approaches; one novel, one from information theory and one from classical statistical methods. Good indicators of quality class based on these analyses are found to be in good agreement with those chosen by a domain expert. The change in information associated with different levels of identification and enumeration of taxa is quantified. The feasibility of using neural network classifiers and predictors to develop numeric criteria for the biological assessment of sediment contamination in the Great Lakes is also investigated.

Induction of placental heme oxygenase-1 is protective against TNFα-induced cytotoxicity and promotes vessel relaxation

Background: Pregnancy is characterized by an inflammatory-like process and this may be exacerbated in preeclampsia. The heme oxygenase (HO) enzymes generate carbon monoxide (CO) that induces blood vessel relaxation and biliverdin that acts as an endogenous antioxidant. Materials and Methods: We examined the expression and localization of HO-1 and HO-2 in normal and preeclamptic placenta using reverse transcription polymerase chain reaction (RT-PCR), RNase protection assay, immunoblotting and immunohistochemistry. In addition, the effect of HO activation on tumor necrosis factor-alpha (TNF) induced placental damage and on feto-placental circulation was studied. Results: We provide the first evidence for the role of HO as an endogenous placental factor involved with cytoprotection and placental blood vessel relaxation. HO-1 was significantly higher at term, compared with first trimester placentae indicating its role in placental vascular development and regulation. HO-1 predominantly localized in the extravascular connective tissue that forms the perivascular contractile sheath around the developing blood vessels. HO-2 was localized in the capillaries, as well as the villous stroma, with weak staining of trophoblast. Induction of HO-1 caused a significant attenuation of TNF-mediated cellular damage in placental villous explants, as assessed by lactate dehydrogenase leakage (p 0.01). HO-1 protein was significantly reduced in placentae from pregnancies complicated with preeclampsia, compared with gestationally matched normal pregnancies. This suggests that the impairment of HO-1 activation may compromise the compensatory mechanism and predispose the placenta to cellular injury and subsequent maternal endothelial cell activation. Isometric contractility studies showed that hemin reduced vascular tension by 61% in U46619-preconstricted placental arteries. Hemininduced vessel relaxation and CO production was inhibited by HO inhibitor, tin protoporphyrin IX. Conclusions: Our findings establish HO-1 as an endogenous system that offers protection against cytotoxic damage in the placenta, identifies the HO-CO pathway to regulate feto-placental circulation and provides a new approach to study the disease of preeclampsia.

The MIMIC model and formative variables:problems and solutions

The use of the multiple indicators, multiple causes model to operationalize formative variables (the formative MIMIC model) is advocated in the methodological literature. Yet, contrary to popular belief, the formative MIMIC model does not provide a valid method of integrating formative variables into empirical studies and we recommend discarding it from formative models. Our arguments rest on the following observations. First, much formative variable literature appears to conceptualize a causal structure between the formative variable and its indicators which can be tested or estimated. We demonstrate that this assumption is illogical, that a formative variable is simply a researcher-defined composite of sub-dimensions, and that such tests and estimates are unnecessary. Second, despite this, researchers often use the formative MIMIC model as a means to include formative variables in their models and to estimate the magnitude of linkages between formative variables and their indicators. However, the formative MIMIC model cannot provide this information since it is simply a model in which a common factor is predicted by some exogenous variables—the model does not integrate within it a formative variable. Empirical results from such studies need reassessing, since their interpretation may lead to inaccurate theoretical insights and the development of untested recommendations to managers. Finally, the use of the formative MIMIC model can foster fuzzy conceptualizations of variables, particularly since it can erroneously encourage the view that a single focal variable is measured with formative and reflective indicators. We explain these interlinked arguments in more detail and provide a set of recommendations for researchers to consider when dealing with formative variables.

Using Community Outreach to Build Children’s Resiliency and Critical Literacy through Digital Tools

Grade three students used tablet computers with a pre-selected series of applications over a seven-month period at school and through a community afterschool program. The study determined that these students benefited from differentiated learning in the school environment and online collaborative play in the afterschool centre. Benefits of the exposure to digital tools included: intergenerational learning as children assisted both parents and teachers with digital applications; problem-solving; and enhanced collaborative play for students across environments. Although this study makes a contribution to the field of digital literacy and young learners, the researchers conclude further investigation is warranted, in regards to the inter-relationships between home, school and community as spaces for the learning and teaching of digital technologies.