395 research outputs found
A Study of the Perspective of Superintendents of How Policies and Practices of Pennsylvania School Boards Affect Student Achievement in High- and Low-Achieving Districts
The intent of this study was to identify and examine the policies and practices of Pennsylvania School Boards, and identify what relationship these might have to patterns of district-level student performance. This study utilized a sequential mixed-methods approach in collecting data. First, quantitative data were secured using surveys sent to a large group of superintendents from similar-sized school districts across Pennsylvania. Then, for the qualitative aspect, a select few superintendents were interviewed in order to more closely analyze the policies and practices of school boards that were identified from the survey. The two research questions developed to guide the study were 1) What policies and practices does a school board engage in that influences student achievement? 2) How do those policies and practices of school boards compare in lower- and higher-achieving school districts?Even though school boards do not directly instruct students, their actions can have a profound effect on the quality of education they receive. Indicative of the study, school boards want their students to be academically successful; however, not all of the policies and practices they partake are beneficial in reaching that goal. The survey and interview data from the study indicates there are both similarities and significant differences between boards from lower- and higher-achieving districts in regards to the policies and practices they participate in, which ultimately influences student achievement. The findings from this study can help both school boards and superintendents utilize the most successful policies and practices to enhance board governance as well as provide the best opportunity to allow their students to be academically successful
Observation of a Strong Atom-Dimer Attraction in a Mass-Imbalanced Fermi-Fermi Mixture
We investigate a mixture of ultracold fermionic K atoms and weakly
bound LiK dimers on the repulsive side of a heteronuclear atomic
Feshbach resonance. By radio-frequency spectroscopy we demonstrate that the
normally repulsive atom-dimer interaction is turned into a strong attraction.
The phenomenon can be understood as a three-body effect in which two heavy
K fermions exchange the light Li atom, leading to attraction in
odd partial-wave channels (mainly p-wave). Our observations show that mass
imbalance in a fermionic system can profoundly change the character of
interactions as compared to the well-established mass-balanced case
From estimation to prediction of genomic variances : allowing for linkage disequilibrium and unbiasedness
In Chapter 1 of this thesis, we briefly summarize the theory about the genetic
variance from quantitative genetics, the genomic variance in
linear regression models, and relate these quantities to the ``Missing
Heritability''.
In Chapter 2, we introduce novel concepts of estimating the genomic variance
in accordance to quantitative genetics theory, i.e. the source of the genetic
variability stems from the variability in marker-genotypes and not from the
randomness of the marker effects.
We distinguish the analysis between Fixed Effect Models, Bayesian Regression
Models and Random Regression Models.
We adapt the estimators for the genomic variance to the specific model
set-ups and show that the resulting quantities explicitly include the
contribution of linkage disequilibrium.
We substantiate our theoretical findings in simulations studies in Chapter 3
by showing that our approach enables a reduction of the ``Missing
Heritability''
ORD-Xplore: Bridging Open Research Data Collections through Modality Abstractions
We present ORD-Xplore, an approach to bridge gaps between digital editions, which represent valuable collections of multiple digitized research artifacts. However, digital editions often co-exist isolated, making it difficult for researchers to access, find, and re-use open research data from multiple digital editions. An ultimate goal is to unify library services across editions, even for editions with heterogeneity. In ORD-Xplore, we utilize abstraction methods from visualization research to help digital librarians identify unifying data modalities, as one important step towards standardization of heterogeneous digital editions
A revised core-seismic integration in the Molloy Basin (ODP Site 909): Implications for the history of ice rafting and ocean circulation in the Atlantic-Arctic gateway
Today's cryosphere reflects an extreme climate state that developed through stepwise global Cenozoic cooling. In this context the opening of the Fram Strait, the Atlantic-Arctic Gateway (AAG), enabled deep-water exchange between the northern North Atlantic and the Arctic Ocean and thereby influenced global ocean circulation and climate. Here we present a new age model for Ocean Drilling Program Site 909 located in the Molloy Basin, a key site to investigate the late opening phase of the central Fram Strait and the early history of oceanic circulation in the AAG. Our results are based on a revised magnetostratigraphy calibrated by new palynomorph bioevents, which shifts previously used stratigraphies for Site 909 to significantly younger ages in the time interval from c. 15 Ma to 3 Ma. The revised late Miocene to present chronology combined with an improved core-log-seismic integration leads to a new high-resolution seismic stratigraphy for the central Fram Strait that allows a more comprehensive correlation with seismic markers from the western Barents Sea margin and also the adjacent Yermak Plateau. The new stratigraphy implies that prominent maxima in coarse sand particles and kaolinite, often interpreted as evidence for ice rafting in the Fram Strait occur at c. 10.8 Ma, c. 3 Myr later as previously inferred and thus well after the Middle Miocene Climate Transition (c. 15–13 Ma). In the late Tortonian (<7.5 Ma), sediment transport became current controlled, mainly through a western, recirculating branch of the West Spitsbergen Current. This transport was strongly enhanced between c. 6.4 and 4.6 Ma and likely linked to the subsiding Hovgaard (Hovgård) Ridge and the widening of the AAG. Late Pliocene to Pleistocene seismic reflectors correlate with episodes of elevated ice-rafted detritus input related to major steps in Northern Hemisphere ice sheet growth such as the prominent glacial inception MIS M2 that predates the mid-Piacenzian Warm Period and the intensification of Northern Hemisphere glaciation starting at c. 2.7 Ma. At the beginning of the Mid Pleistocene Transition (c. 1.2–0.8 Ma), sediment accumulation in the Fram Strait significantly decreased
PROCESS MODELING AND SCENARIO SIMULATION IN CONSTRUCTION USING ENTERPRISE DYNAMICS SIMULATION SOFTWARE
Modeling and simulation of organizational processes are established methodologies and tools in most industries. In civil engineering, however, this is not the case. One of the reasons for this is the lack of special tools, specifically computer programs used primarily for modeling and simulating characteristic processes of construction. In this paper the authors look for analogies between processes typical for construction and those in other industries in which Enterprise Dynamics software has been successfully applied. In order to perform a valid software analysis, the authors tested this software in a case study that represents universal problems at construction sites: queuing and sequencing. In this study, authors modeled and simulated the production, transport, and laying of a hot asphalt mixture. Results show that this software is suitable for modeling and scenario simulation in this case and that the software shows promise for other uses in the construction industry
FDive: Learning Relevance Models using Pattern-based Similarity Measures
The detection of interesting patterns in large high-dimensional datasets is
difficult because of their dimensionality and pattern complexity. Therefore,
analysts require automated support for the extraction of relevant patterns. In
this paper, we present FDive, a visual active learning system that helps to
create visually explorable relevance models, assisted by learning a
pattern-based similarity. We use a small set of user-provided labels to rank
similarity measures, consisting of feature descriptor and distance function
combinations, by their ability to distinguish relevant from irrelevant data.
Based on the best-ranked similarity measure, the system calculates an
interactive Self-Organizing Map-based relevance model, which classifies data
according to the cluster affiliation. It also automatically prompts further
relevance feedback to improve its accuracy. Uncertain areas, especially near
the decision boundaries, are highlighted and can be refined by the user. We
evaluate our approach by comparison to state-of-the-art feature selection
techniques and demonstrate the usefulness of our approach by a case study
classifying electron microscopy images of brain cells. The results show that
FDive enhances both the quality and understanding of relevance models and can
thus lead to new insights for brain research.Comment: 12 pages, 7 figures, 2 tables, LaTeX; corrected typo; added DO
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