14,818 research outputs found
Structural and lithologic study of northern California Coast Range and Sacramento Valley, California
The author has identified the following significant results. Photgeologic examination of repetitive multispectral ERTS-1 imagery of Northern California has disclosed several systems of linear features which may be important for the interpretation of the structural history of California. They are separated from an orthogonal system of linears in the Klamath Mts. by a set of discontinuous southeast-trending linear features (the Mendocino system) which is traceable from the Pacific Coast, at Cape Mendocino, into the eastern foothills of the Sierra Nevada. Within the Sierra Nevada, the Mendocino system separates the north-trending Sierran system from a set of linears characteristic of the Modoc Plateau. With minor exception, little overlap exists among the systems which suggests a decipherable chronology and evolutionary history for the region. The San Andres system of linears appears to truncate or co-exist with most of the other systems in the northern Coast Ranges. The Mendocino system truncates the Klamath, Sierran, and Modoc systems. The Sierran system may represent fundamental and long-persisting pre-late Paleozoic zones of crustal weakness which have been reactivated from time to time. The Mendocino system was possibly developed in early Mesozoic and is important to the structural framework of Northern California
Literature-based priors for gene regulatory networks
Motivation: The use of prior knowledge to improve gene regulatory network modelling has often been proposed. In this paper we present the first research on the massive incorporation of prior knowledge from literature for Bayesian network learning of gene networks. As the publication rate of scientific papers grows, updating online databases, which have been proposed as potential prior knowledge in past rese-arch, becomes increasingly challenging. The novelty of our approach lies in the use of gene-pair association scores that describe the over-lap in the contexts in which the genes are mentioned, generated from a large database of scientific literature, harnessing the information contained in a huge number of documents into a simple, clear format. Results: We present a method to transform such literature-based gene association scores to network prior probabilities, and apply it to learn gene sub-networks for yeast, E. coli and Human organisms. We also investigate the effect of weighting the influence of the prior know-ledge. Our findings show that literature-based priors can improve both the number of true regulatory interactions present in the network and the accuracy of expression value prediction on genes, in comparison to a network learnt solely from expression data. Networks learnt with priors also show an improved biological interpretation, with identified subnetworks that coincide with known biological pathways. Contact
Performance of the cross-product steering law for the transearth injection phase
Steering law for transearth injection between circular lunar orbit and vector
Mechanotransduction of mitochondrial AMPK and its distinct role in flow-induced breast cancer cell migration
The biophysical microenvironment of the tumor site has significant impact on breast cancer progression and metastasis. The importance of altered mechanotransduction in cancerous tissue has been documented, yet its role in the regulation of cellular metabolism and the potential link between cellular energy and cell migration remain poorly understood. In this study, we investigated the role of mechanotransduction in AMP-activated protein kinase (AMPK) activation in breast cancer cells in response to interstitial fluid flow (IFF). Additionally, we explored the involvement of AMPK in breast cancer cell migration. IFF was applied to the 3D cell-matrix construct. The subcellular signaling activity of Src, FAK, and AMPK was visualized in real-time using fluorescent resonance energy transfer (FRET). We observed that breast cancer cells (MDA-MB-231) are more sensitive to IFF than normal epithelial cells (MCF-10A). AMPK was activated at the mitochondria of MDA-MB-231 cells by IFF, but not in other subcellular compartments (i.e., cytosol, plasma membrane, and nucleus). The inhibition of FAK or Src abolished flow-induced AMPK activation in the mitochondria of MDA-MB-231 cells. We also observed that global AMPK activation reduced MDA-MB-231 cell migration. Interestingly, specific AMPK inhibition in the mitochondria reduced cell migration and blocked flow-induced cell migration. Our results suggest the linkage of FAK/Src and mitochondria-specific AMPK in mechanotransduction and the differential role of AMPK in breast cancer cell migration depending on its subcellular compartment-specific activation
Extracting predictive models from marked-p free-text documents at the Royal Botanic Gardens, Kew, London
In this paper we explore the combination of text-mining, un-supervised and supervised learning to extract predictive models from a corpus of digitised historical floras. These documents deal with the nomenclature, geographical distribution, ecology and comparative morphology of the species of a region. Here we exploit the fact that portions of text in the floras are marked up as different types of trait and habitat. We infer models from these different texts that can predict different habitat-types based upon the traits of plant species. We also integrate plant taxonomy data in order to assist in the validation of our models. We have shown that by clustering text describing the habitat of different floras we can identify a number of important and distinct habitats that are associated with particular families of species along with statistical significance scores. We have also shown that by using these discovered habitat-types as labels for supervised learning we can predict them based upon a subset of traits, identified using wrapper feature selection
An investigation of computer coupled automatic activation analysis and remote lunar analysis Quarterly progress report, 1 Nov. 1962 - 1 Feb. 1963
Mark II automatic activation analysis system, influence of radiation on silver ion migration in mice, selenium determination in submicrogram quantities, and remote lunar analysi
Small woodland owners in Sequatchie County, Tennessee : problem A: Characteristics of Sequatchie County small woodland owners and their farms : problem B: Management practices of Sequatchie County small woodland owners : problem C: Factors influencing woodland management adoption by Sequatchie County small woodland owners : three related problems in lieu of thesis /
This study was the first of three related problems regarding small woodland owners in Sequatchie County, Tennessee. It was conducted for the purpose of determining the characteristics of small woodland owners in the county. A random sample of 50 owners were selected; and the farmers were classified by the SCS technician, Extension Leader and Associate Extension Agent into high (20) or low (30) adopters depending upon whether they were inclined to be among the first to adopt recommended practices or not. The findings revealed that the average small woodland owner in Sequatchie County had the following characteristics: (1) was 51. 3 years of age; (2) had completed 12. 0 grade; (3) reported a median gross family income of $9,143.00; (4) was very well or fairly well known by the interviewer; and the owner was friendly or somewhat friendly toward the survey
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