Data fusion with artificial neural networks (ANN) for classification of earth surface from microwave satellite measurements

A data fusion system with artificial neural networks (ANN) is used for fast and accurate classification of five earth surface conditions and surface changes, based on seven SSMI multichannel microwave satellite measurements. The measurements include brightness temperatures at 19, 22, 37, and 85 GHz at both H and V polarizations (only V at 22 GHz). The seven channel measurements are processed through a convolution computation such that all measurements are located at same grid. Five surface classes including non-scattering surface, precipitation over land, over ocean, snow, and desert are identified from ground-truth observations. The system processes sensory data in three consecutive phases: (1) pre-processing to extract feature vectors and enhance separability among detected classes; (2) preliminary classification of Earth surface patterns using two separate and parallely acting classifiers: back-propagation neural network and binary decision tree classifiers; and (3) data fusion of results from preliminary classifiers to obtain the optimal performance in overall classification. Both the binary decision tree classifier and the fusion processing centers are implemented by neural network architectures. The fusion system configuration is a hierarchical neural network architecture, in which each functional neural net will handle different processing phases in a pipelined fashion. There is a total of around 13,500 samples for this analysis, of which 4 percent are used as the training set and 96 percent as the testing set. After training, this classification system is able to bring up the detection accuracy to 94 percent compared with 88 percent for back-propagation artificial neural networks and 80 percent for binary decision tree classifiers. The neural network data fusion classification is currently under progress to be integrated in an image processing system at NOAA and to be implemented in a prototype of a massively parallel and dynamically reconfigurable Modular Neural Ring (MNR)

Increased Hematopoietic Extracellular RNAs and Vesicles in the Lung during Allergic Airway Responses.

Extracellular RNAs (exRNAs) can be released by numerous cell types in vitro, are often protected within vesicles, and can modify recipient cell function. To determine how the composition and cellular sources of exRNAs and the extracellular vesicles (EVs) that carry them change in vivo during tissue inflammation, we analyzed bronchoalveolar lavage fluid (BALF) from mice before and after lung allergen challenge. In the lung, extracellular microRNAs (ex-miRNAs) had a composition that was highly correlated with airway-lining epithelium. Using cell type-specific membrane tagging and single vesicle flow, we also found that 80% of detected vesicles were of epithelial origin. After the induction of allergic airway inflammation, miRNAs selectively expressed by immune cells, including miR-223 and miR-142a, increased and hematopoietic-cell-derived EVs also increased >2-fold. These data demonstrate that infiltrating immune cells release ex-miRNAs and EVs in inflamed tissues to alter the local extracellular environment

Applications of simulation technique on debris-flow hazard zone delineation: a case study in Hualien County, Taiwan

Debris flows pose severe hazards to communities in mountainous areas, often resulting in the loss of life and property. Helping debris-flow-prone communities delineate potential hazard zones provides local authorities with useful information for developing emergency plans and disaster management policies. In 2003, the Soil and Water Conservation Bureau of Taiwan proposed an empirical model to delineate hazard zones for all creeks (1420 in total) with potential of debris flows and utilized the model to help establish a hazard prevention system. However, the model does not fully consider hydrologic and physiographical conditions for a given creek in simulation. The objective of this study is to propose new approaches that can improve hazard zone delineation accuracy and simulate hazard zones in response to different rainfall intensity. In this study, a two-dimensional commercial model FLO-2D, physically based and taking into account the momentum and energy conservation of flow, was used to simulate debris-flow inundated areas. <br><br> Sensitivity analysis with the model was conducted to determine the main influence parameters which affect debris flow simulation. Results indicate that the roughness coefficient, yield stress and volumetric sediment concentration dominate the computed results. To improve accuracy of the model, the study examined the performance of the rainfall-runoff model of FLO-2D as compared with that of the HSPF (Hydrological Simulation Program Fortran) model, and then the proper values of the significant parameters were evaluated through the calibration process. Results reveal that the HSPF model has a better performance than the FLO-2D model at peak flow and flow recession period, and the volumetric sediment concentration and yield stress can be estimated by the channel slope. The validation of the model for simulating debris-flow hazard zones has been confirmed by a comparison of field evidence from historical debris-flow disaster data. The model can successfully replicate the influence zone of the debris-flow disaster event with an acceptable error and demonstrate a better result than the empirical model adopted by the Soil and Water Conservation Bureau of Taiwan

Patchy Interspecific Sequence Similarities Efficiently Identify Positive cis-Regulatory Elements in the Sea Urchin

We demonstrate that interspecific sequence conservation can provide a systematic guide to the identification of functional cis-regulatory elements within a large expanse of genomic DNA. The test was carried out on the otx gene of Strongylocentrotus purpuratus. This gene plays a major role in the gene regulatory network that underlies endomesoderm specification in the embryo. The cis-regulatory organization of the otx gene is expected to be complex, because the gene has three different start sites (X. Li, C.-K. Chuang, C.-A. Mao, L. M. Angerer, and W. H. Klein, 1997, Dev. Biol. 187, 253–266), and it is expressed in many different spatial domains of the embryo. BAC recombinants containing the otx gene were isolated from Strongylocentrotus purpuratus and Lytechinus variegatus libraries, and the ordered sequence of these BACs was obtained and annotated. Sixty kilobases of DNA flanking the gene, and included in the BAC sequence from both species, were scanned computationally for short conserved sequence elements. For this purpose, we used a newly constructed software package assembled in our laboratory, “FamilyRelations.” This tool allows detection of sequence similarities above a chosen criterion within sliding windows set at 20–50 bp. Seventeen partially conserved regions, most a few hundred base pairs long, were amplified from the S. purpuratus BAC DNA by PCR, inserted in an expression vector driving a CAT reporter, and tested for cis-regulatory activity by injection into fertilized S. purpuratus eggs. The regulatory activity of these constructs was assessed by whole-mount in situ hybridization (WMISH) using a probe against CAT mRNA. Of the 17 constructs, 11 constructs displayed spatially restricted regulatory activity, and 6 were inactive in this test. The domains within which the cis-regulatory constructs were expressed are approximately consistent with results from a WMISH study on otx expression in the embryo, in which we used probes specific for the mRNAs generated from each of the three transcription start sites. Four separate cis-regulatory elements that specifically produce endomesodermal expression were identified, as well as ubiquitously active elements, and ectoderm-specific elements. We confirm predictions from other work with respect to target sites for specific transcription factors within the elements that express in the endoderm

GUT theories from Calabi-Yau 4-folds with SO(10) Singularities

We consider an SO(10) GUT model from F-theory compactified on an elliptically fibered Calabi-Yau with a D5 singularity. To obtain the matter curves and the Yukawa couplings, we use a global description to resolve the singularity. We identify the vector and spinor matter representations and their Yukawa couplings and we explicitly build the G-fluxes in the global model and check the agreement with the semi-local results. As our bundle is of type SU(2k), some extra conditions need to be applied to match the fluxes.Comment: 27 page