1,459 research outputs found
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
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
Dynamic environmental control mechanisms for pneumatic foil constructions
Membrane and foil structures have become over the last decades an attractive alternative to conventional materials and building systems with increasing implementation in different typologies and scale. The development of transparent, light, flexible and resistant materials like Ethylene Tetrafluoroethylene (ETFE) has triggered a rethinking of the building envelope in the building industry towards lightweight systems. ETFE foil cushions have proven to fulfil the design requirements in terms of structural efficiency and aesthetic values. But the strategies to satisfy increasing demands of energy efficiency and comfort conditions are still under development. The prediction and manipulation of the thermo-optical behaviour of ETFE foil cushion structures currently remain as one of the main challenges for designers and manufacturers. This paper reviews ongoing research regarding the control of the thermo-optical performance of ETFE cushion structures and highlights challenges and possible improvements. An overview of different dynamic and responsive environmental control mechanisms for multilayer foil constructions is provided and the state of the art in building application outlined by the discussion of case studie
Is "the theory of everything'' merely the ultimate ensemble theory?
We discuss some physical consequences of what might be called ``the ultimate
ensemble theory'', where not only worlds corresponding to say different sets of
initial data or different physical constants are considered equally real, but
also worlds ruled by altogether different equations. The only postulate in this
theory is that all structures that exist mathematically exist also physically,
by which we mean that in those complex enough to contain self-aware
substructures (SASs), these SASs will subjectively perceive themselves as
existing in a physically ``real'' world. We find that it is far from clear that
this simple theory, which has no free parameters whatsoever, is observationally
ruled out. The predictions of the theory take the form of probability
distributions for the outcome of experiments, which makes it testable. In
addition, it may be possible to rule it out by comparing its a priori
predictions for the observable attributes of nature (the particle masses, the
dimensionality of spacetime, etc) with what is observed.Comment: 29 pages, revised to match version published in Annals of Physics.
The New Scientist article and color figures are available at
http://www.sns.ias.edu/~max/toe_frames.html or from [email protected]
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
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