An edition of Svipdagsmál

Section I of this thesis establishes a text of the two Old Norse poems Gróugaldr and Fjǫlsvinnsmál, known collectively as Svipdagsmál (Sv). Previous editions are surveyed, discussing their use of the two MSS upon which the emended text offered by this edition is based, Stockholm Papp. 15 8vo and Rask 21 a (I.1). Reasons are given for the choice of these two MSS (out of the forty six MSS known to the editor) and the two MSS are described (I.2). The emended and normalised text is accompanied by a translation and summary apparatus (I.3), followed by a Commentary (I.4). A reconstruction is attempted of the history of the MS tradition (I.5). This reconstruction is based on computer collation of the MSS and database analysis of the collation, together with external evidence where available. The reconstruction confirms the choice of Stockholm Papp. 15 8vo and Rask 21 a: most of the other MSS appear descended from one of these two. Section II gathers together analogues to the poems in Celtic, Icelandic and Scandinavian ballad tradition. The story was earlier an Irish mythical tale, itself an adaptation of an international popular tale of the "giant's daughter" type (II.2). Traces of this original tale are to be found in Icelandic popular tradition (II.3). The Scandinavian Ungen Svendal ballads seem derived from Sv itself (II.4). Section III analyses the poet's use of Old Norse poetic and mythological materials. The poems are skilful studies in Eddic style (III.2) and the poet shows a deliberate creativity in the adaptation and invention of mythological material (III.3-5). Evidence is presented for a date of composition in the early thirteenth century (IV.1). A study of the art of the poems shows a poet of rare skill (IV.2)

Scale-Invariant Geometric Data Analysis (SIGDA)

The purpose of this research is to introduce a new data analysis method called Scale Invariant Geometric Data Analysis (SIGDA). SIGDA has been shown to be more informative than more common data analysis methods, such as Principal Component Analysis (PCA). SIGDA is used to visualize complex data sets in a way that accurately preserves data patterns and behavior. SIGDA is designed to preserve relative ratios in a numerical matrix, and the number of entries has to be more than the total number of rows and columns. Our research involved providing a simple explanation of SIGDA\u27s mathematical process—simple enough for the public to understand—and constructing educational materials to promote the use of SIGDA. I worked with my mentor, Max Robinson, to create posters and presentations to illustrate how SIGDA works. We used feedback from fellow scientists to continue to update and simplify the material to a level that a high school student could understand

Community Preparatory School: 2013-2014 Public Relations Plan

Community Prep sends out seasonal newsletters during fall, winter, spring, and summer of each year that promote recent activities in school, discuss recent events, profile important donors, and give updates on alumni’s successes. These newsletters are sent out in the mail, and are also accessible on Community Prep’s website. Each newsletter comes in one color, with black and white photographs, and has a readable and attractive layout. Email updates have similar information, but sometimes have embedded videos, and provide links to a site where donations can be made or tickets can be bought for future events

CHEMICAL COMPOSITIONS AND AMINO ACIDS OF DOLPHIN FISH (Coryphaena hippurus) ROES

Fish processing industry produces more than 60% of byproducts include the head, bones, fins, skin, viscera and roes. Only 40% of the total body of fish that can be consumed by humans. Byproduct of the fishing industry is a source of nutrition and functional food ingredients, such as roes have a high protein content and amino acids. The aim of this study was determine the chemical composition and amino acid profile of dolphin fish roe. The proximate composition of dolphin fish roe is protein 19.16%, fat 2.05%, moisture 72.94%, ash 1.12% and 4.72 carbohydrates. There are 17 amino acids in dolphin fish roe including proline (3.32%), arginine (3.01%), serine (2.85%) and phenilalanine (2.65 %) while the smallest amino acid is cystine (0.43%), histidine (1.22%) valine (1.34%) and methionine (1.36%).&nbsp

The impact of maternal gestational stress on motor development in late childhood and adolescence: a longitudinal study

The number and timing of stressors experienced during pregnancy were investigated using longitudinal data from the Western Australian Pregnancy (Raine) Study cohort (N = 2,900). Motor development data were collected at 10 (n = 1,622), 14 (n = 1,584), and 17 (n = 1,222) years using the McCarron Assessment of Neuromuscular Development. Linear mixed models were used to examine the effect of stress on motor development, accounting for repeated measures. Number of stressful events and mean Neuromuscular Development Index were negatively related (β = −1.197, p = .001). Stressful events experienced in late pregnancy were negatively related with offspring motor development (β = −0.0541, p = .050), while earlier stressful events had no significant impact

Prediction of Human Phenotype Ontology terms by means of hierarchical ensemble methods

Background The prediction of human gene–abnormal phenotype associations is a fundamental step toward the discovery of novel genes associated with human disorders, especially when no genes are known to be associated with a specific disease. In this context the Human Phenotype Ontology (HPO) provides a standard categorization of the abnormalities associated with human diseases. While the problem of the prediction of gene–disease associations has been widely investigated, the related problem of gene–phenotypic feature (i.e., HPO term) associations has been largely overlooked, even if for most human genes no HPO term associations are known and despite the increasing application of the HPO to relevant medical problems. Moreover most of the methods proposed in literature are not able to capture the hierarchical relationships between HPO terms, thus resulting in inconsistent and relatively inaccurate predictions. Results We present two hierarchical ensemble methods that we formally prove to provide biologically consistent predictions according to the hierarchical structure of the HPO. The modular structure of the proposed methods, that consists in a “flat” learning first step and a hierarchical combination of the predictions in the second step, allows the predictions of virtually any flat learning method to be enhanced. The experimental results show that hierarchical ensemble methods are able to predict novel associations between genes and abnormal phenotypes with results that are competitive with state-of- the-art algorithms and with a significant reduction of the computational complexity. Conclusions Hierarchical ensembles are efficient computational methods that guarantee biologically meaningful predictions that obey the true path rule, and can be used as a tool to improve and make consistent the HPO terms predictions starting from virtually any flat learning method. The implementation of the proposed methods is available as an R package from the CRAN repository