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Staffing remote schools: Perennial failure
No full textEducational and socioeconomic disadvantage in remote communities, and the inadequacies of government action to bring about significant change needs to be addressed. This article presents a descriptive study examining the complexities of staffing remote and very remote schools in Australia with appropriately-qualified teachers. The findings of analysis of data from the Australian Bureau of Statistics (ABS) on behalf of the Australian Government through the National Schools Statistics Collection (NSSC) indicate that the majority of students in remote schools in Australia live, and are educated in, Indigenous communities in three jurisdictions. This raises concerns of unacknowledged and unacceptable discrimination. Complexity within the current approach to resourcing of remote and very remote schools in Australia, especially in relation to economies of scale are explored. The analysis of existing data was discussed, and how this may be used to address the perennial failure to develop quality decisions, particularly in areas of resourcing in remote and very remote schools
Book Review: Habitantes de la obscuridad (Fauna Ibero-Balear de las Cuevas) – Inhabitants of the darkness (Ibero-Baleric fauna of caves)
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Osprey (\u3ci\u3ePandion haliaetus\u3c/i\u3e)
No full textThe Osprey is the only member of its genus, Pandion, and family, Pandionidae
Predicting TF Proteins by Incorporating Evolution Information Through PSSM
No full textTranscription factors (TFs) are DNA binding proteins involved in the regulation of gene expression. They exist in all organisms and activate or repress transcription by binding to specific DNA sequences. Traditionally, TFs have been identified by experimental methods that are time-consuming and costly. In recent years, various computational methods have been developed to identify TF to overcome these limitations. However, there is a room for further improvement in the predictive performance of these tools in terms of accuracy. We report here a novel computational tool, TFnet, that provides accurate and comprehensive TF predictions from protein sequences. The accuracy of these predictions is substantially better than the results of the existing TF predictors and methods. Especially, it outperforms comparable methods significantly when sequence similarity to other known sequences in the database drops below 40%. Ablation tests reveal that the high predictive performance stems from innovative ways used in TFnet to derive sequence Position-Specific Scoring Matrix (PSSM) and encode inputs
First Reported Hybridization of Female Canyon Towhee and Male Abert\u27s Towhee; First Reporte Placement of Towhee Nest in Box; First Reported Helper at Towhee Nest
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Frontmatter for the Florida BBA II
No full texthttps://digitalcommons.usf.edu/bba2_about/1000/thumbnail.jp