1,127 research outputs found
Curriculum Restructuring at Lynchburg College: Effects of Realignment to State-Mandated Competencies and Implications for K-6 Math and Science Teacher Preparation
Because Lynchburg College offers a four-year program to attain teacher licensure, current restructuring efforts have been aimed at targeting the professional studies requirements across a program of courses that are efficiently integrated. Math and science methods courses will be combined into a workshop course. A new general studies program has been approved which requires eight hours of lab sciences and three hours of math. A General Science course has been approved which will be geared towards pre-service teachers. The professional core requires an additional eight hours of lab sciences, totaling 16 hours in science, and six hours of math, geared towards the needs of pre-service teachers. While recommended teaching practices are stressed, these may be de-emphasized by the student teaching capstone experience. This is due to the current pressure in public schools to address content-loaded Standards of Learning. From this perspective, standards-based education may prove to be an impediment to reform efforts in science education that stress process skills and the messy, time-consuming nature of learning
Equivalence after extension for compact operators on Banach spaces
In recent years the coincidence of the operator relations equivalence after
extension and Schur coupling was settled for the Hilbert space case, by showing
that equivalence after extension implies equivalence after one-sided extension.
In this paper we investigate consequences of equivalence after extension for
compact Banach space operators. We show that generating the same operator ideal
is necessary but not sufficient for two compact operators to be equivalent
after extension. In analogy with the necessary and sufficient conditions on the
singular values for compact Hilbert space operators that are equivalent after
extension, we prove the necessity of similar relationships between the
-numbers of two compact Banach space operators that are equivalent after
extension, for arbitrary -functions.
We investigate equivalence after extension for operators on
-spaces. We show that two operators that act on different
-spaces cannot be equivalent after one-sided extension. Such
operators can still be equivalent after extension, for instance all invertible
operators are equivalent after extension, however, if one of the two operators
is compact, then they cannot be equivalent after extension. This contrasts the
Hilbert space case where equivalence after one-sided extension and equivalence
after extension are, in fact, identical relations.
Finally, for general Banach spaces and , we investigate consequences
of an operator on being equivalent after extension to a compact operator on
. We show that, in this case, a closed finite codimensional subspace of
must embed into , and that certain general Banach space properties must
transfer from to . We also show that no operator on can be
equivalent after extension to an operator on , if and are
essentially incomparable Banach spaces
Digestiflow: from BCL to FASTQ with ease
Management of raw-sequencing data and its pre-processing (conversion into sequences and demultiplexing) remains a challenging topic for groups running sequencing devices. They face many challenges in such efforts and solutions ranging from manual management of spreadsheets to very complex and customized laboratory information management systems handling much more than just sequencing raw data. In this article, we describe the software package DigestiFlow that focuses on the management of Illumina flow cell sample sheets and raw data. It allows for automated extraction of information from flow cell data and management of sample sheets. Furthermore, it allows for the automated and reproducible conversion of Illumina base calls to sequences and the demultiplexing thereof using bcl2fastq and Picard Tools, followed by quality control report generation. Availability and implementation: The software is available under the MIT license at https://github.com/bihealth/digestiflow-server. The client software components are available via Bioconda
Asymmetric root distributions reveal press–pulse responses in retreating coastal forests
The impacts of climate change on ecosystems are manifested in how organisms respond to episodic and continuous stressors. The conversion of coastal forests to salt marshes represents a prominent example of ecosystem state change, driven by the continuous stress of sea-level rise (press), and episodic storms (pulse). Here, we measured the rooting dimension and fall direction of 143 windthrown eastern red cedar (Juniperus virginiana) trees in a rapidly retreating coastal forest in Chesapeake Bay (USA). We found that tree roots were distributed asymmetrically away from the leading edge of soil salinization and towards freshwater sources. The length, number, and circumference of roots were consistently higher in the upslope direction than downslope direction, suggesting an active morphological adaptation to sea-level rise and salinity stress. Windthrown trees consistently fell in the upslope direction regardless of aspect and prevailing wind direction, suggesting that asymmetric rooting destabilized standing trees, and reduced their ability to withstand high winds. Together, these observations help explain curious observations of coastal forest resilience, and highlight an interesting nonadditive response to climate change, where adaptation to press stressors increases vulnerability to pulse stressors
Biophysical controls of marsh soil shear strength along an estuarine salinity gradient
Sea-level rise, saltwater intrusion, and wave erosion threaten coastal marshes, but the influence of salinity on marsh erodibility remains poorly understood. We measured the shear strength of marsh soils along a salinity and biodiversity gradient in the York River estuary in Virginia to assess the direct and indirect im-pacts of salinity on potential marsh erodibility. We found that soil shear strength was higher in monospecific salt marshes (5–36 kPa) than in biodiverse freshwater marshes (4–8 kPa), likely driven by differences in below ground biomass. However, we also found that shear strength at the marsh edge was controlled by sediment characteristics, rather than vegetation or salinity, suggesting that inherent relationships may be obscured in more dynamic environments. Our results indicate that York River freshwater marsh soils are weaker than salt marsh soils, and suggest that salinization of these freshwater marshes may lead to simultaneous losses in biodiversity and erodibility
SCelVis: Powerful explorative single cell data analysis on the desktop and in the cloud
Background: Single cell omics technologies present unique opportunities for biomedical and life sciences from lab to clinic, but the high dimensional nature of such data poses challenges for computational analysis and interpretation. Furthermore, FAIR data management as well as data privacy and security become crucial when working with clinical data, especially in cross-institutional and translational settings. Existing solutions are either bound to the desktop of one researcher or come with dependencies on vendor-specific technology for cloud storage or user authentication. Results: To facilitate analysis and interpretation of single-cell data by users without bioinformatics expertise, we present SCelVis, a flexible, interactive and user-friendly app for web-based visualization of pre-processed single-cell data. Users can survey multiple interactive visualizations of their single cell expression data and cell annotation, and download raw or processed data for further offline analysis. SCelVis can be run both on the desktop and cloud systems, accepts input from local and various remote sources using standard and open protocols, and allows for hosting data in the cloud and locally. Methods: SCelVis is implemented in Python using Dash by Plotly. It is available as a standalone application as a Python package, via Conda/Bioconda and as a Docker image. All components are available as open source under the permissive MIT license and are based on open standards and interfaces, enabling further development and integration with third party pipelines and analysis components. The GitHub repository is https://github.com/bihealth/scelvis
SCelVis: exploratory single cell data analysis on the desktop and in the cloud
BACKGROUND: Single cell omics technologies present unique opportunities for biomedical and life sciences from lab to clinic, but the high dimensional nature of such data poses challenges for computational analysis and interpretation. Furthermore, FAIR data management as well as data privacy and security become crucial when working with clinical data, especially in cross-institutional and translational settings. Existing solutions are either bound to the desktop of one researcher or come with dependencies on vendor-specific technology for cloud storage or user authentication. RESULTS: To facilitate analysis and interpretation of single-cell data by users without bioinformatics expertise, we present SCelVis, a flexible, interactive and user-friendly app for web-based visualization of pre-processed single-cell data. Users can survey multiple interactive visualizations of their single cell expression data and cell annotation, define cell groups by filtering or manual selection and perform differential gene expression, and download raw or processed data for further offline analysis. SCelVis can be run both on the desktop and cloud systems, accepts input from local and various remote sources using standard and open protocols, and allows for hosting data in the cloud and locally. We test and validate our visualization using publicly available scRNA-seq data. METHODS: SCelVis is implemented in Python using Dash by Plotly. It is available as a standalone application as a Python package, via Conda/Bioconda and as a Docker image. All components are available as open source under the permissive MIT license and are based on open standards and interfaces, enabling further development and integration with third party pipelines and analysis components. The GitHub repository is https://github.com/bihealth/scelvis
SigsPack, a package for cancer mutational signatures
BACKGROUND: Mutational signatures are specific patterns of somatic mutations introduced into the genome by oncogenic processes. Several mutational signatures have been identified and quantified from multiple cancer studies, and some of them have been linked to known oncogenic processes. Identification of the processes contributing to mutations observed in a sample is potentially informative to understand the cancer etiology. RESULTS: We present here SigsPack, a Bioconductor package to estimate a sample's exposure to mutational processes described by a set of mutational signatures. The package also provides functions to estimate stability of these exposures, using bootstrapping. The performance of exposure and exposure stability estimations have been validated using synthetic and real data. Finally, the package provides tools to normalize the mutation frequencies with respect to the tri-nucleotide contents of the regions probed in the experiment. The importance of this effect is illustrated in an example. CONCLUSION: SigsPack provides a complete set of tools for individual sample exposure estimation, and for mutation catalogue & mutational signatures normalization
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