Multisensor satellite data integration for sea surface wind speed and direction determination

Techniques to integrate meteorological data from various satellite sensors to yield a global measure of sea surface wind speed and direction for input to the Navy's operational weather forecast models were investigated. The sensors were launched or will be launched, specifically the GOES visible and infrared imaging sensor, the Nimbus-7 SMMR, and the DMSP SSM/I instrument. An algorithm for the extrapolation to the sea surface of wind directions as derived from successive GOES cloud images was developed. This wind veering algorithm is relatively simple, accounts for the major physical variables, and seems to represent the best solution that can be found with existing data. An algorithm for the interpolation of the scattered observed data to a common geographical grid was implemented. The algorithm is based on a combination of inverse distance weighting and trend surface fitting, and is suited to combing wind data from disparate sources

Cloud cover typing from environmental satellite imagery. Discriminating cloud structure with Fast Fourier Transforms (FFT)

The use of two dimensional Fast Fourier Transforms (FFTs) subjected to pattern recognition technology for the identification and classification of low altitude stratus cloud structure from Geostationary Operational Environmental Satellite (GOES) imagery was examined. The development of a scene independent pattern recognition methodology, unconstrained by conventional cloud morphological classifications was emphasized. A technique for extracting cloud shape, direction, and size attributes from GOES visual imagery was developed. These attributes were combined with two statistical attributes (cloud mean brightness, cloud standard deviation), and interrogated using unsupervised clustering amd maximum likelihood classification techniques. Results indicate that: (1) the key cloud discrimination attributes are mean brightness, direction, shape, and minimum size; (2) cloud structure can be differentiated at given pixel scales; (3) cloud type may be identifiable at coarser scales; (4) there are positive indications of scene independence which would permit development of a cloud signature bank; (5) edge enhancement of GOES imagery does not appreciably improve cloud classification over the use of raw data; and (6) the GOES imagery must be apodized before generation of FFTs

Sequence homology between RNAs encoding rat α-fetoprotein and rat serum albumin

We have determined the sequences of the recombinant DNA inserts of three bacterial plasmid cDNA clones containing most of the rat α-fetoprotein mRNA. The resultant nucleotide sequence of α-fetoprotein was exhaustively compared to the nucleotide sequence of the mRNA encoding rat serum albumin. These two mRNAs have extensive homology (50%) throughout and the same intron locations. The amino acid sequence of rat α-fetoprotein has been deduced from the nucleotide sequence, and its comparison to rat serum albumin's amino acid sequence reveals a 34% homology. The regularly spaced positions of the cysteines found in serum albumin are conserved in rat α-fetoprotein, indicating that these two proteins may have a similar secondary folding structure. These homologies indicate that α-fetoprotein and serum albumin were derived by duplication of a common ancestral gene and constitute a gene family

Application of image processing technology to problems in manuscript encapsulation

The long term effects of encapsulation individual sheets of the Codex Hammer were investigated. The manuscript was simulated with similar sheets of paper which were photographed under repeatable raking light conditions to enhance their surface texture, encapsulated in plexiglas, cycled in an environmental test chamber, and rephotographed at selected intervals. The film images were digitized, contrast enhanced, geometrically registered, and apodized. An FFT analysis of a control sheet and two experimental sheets indicates no micro-burnishing, but reveals that the ""mesoscale'' deformations with sizes 8mm are degrading monotonically, which is of no concern. Difference image analysis indicates that the sheets were increasingly stressed with time and that the plexiglas did not provide a sufficient environmental barrier under the simulation conditions. The relationship of these results to the Codex itself is to be determined

Sensing of explosive vapor by hybrid perovskites : effect of dimensionality

Funding: Engineering and Physical Sciences Research Council under grants EP/T01119X/1 and EP/K503940/1, and the NATO Science for Peace & Security programme under grant agreement MYP G5355.Lead halide perovskites are very promising materials for many optoelectronic devices. They are low cost, photostable, and strongly photoluminescent materials, but so far have been little studied for sensing. In this article, we explore hybrid perovskites as sensors for explosive vapor. We tune the dimensionality of perovskite films in order to modify their exciton binding energy and film morphology and explore the effect on sensing response. We find that tuning from the 3D to the 0D regime increases the PL quenching response of perovskite films to the vapor of dinitrotoluene (DNT)—a molecule commonly found in landmines. We find that films of 0D perovskite nanocrystals work as sensitive and stable sensors, with strong PL responses to DNT molecules at concentrations in the parts per billion range. The PL quenching response can easily be reversed, making the sensors reusable. We compare the response to several explosive vapors and find that the response is strongest for DNT. These results show that hybrid perovskites have great potential for vapor sensing applications.Publisher PDFPeer reviewe

Computational modeling with spiking neural networks

This chapter reviews recent developments in the area of spiking neural networks (SNN) and summarizes the main contributions to this research field. We give background information about the functioning of biological neurons, discuss the most important mathematical neural models along with neural encoding techniques, learning algorithms, and applications of spiking neurons. As a specific application, the functioning of the evolving spiking neural network (eSNN) classification method is presented in detail and the principles of numerous eSNN based applications are highlighted and discussed

CD19+CD24hiCD38hi B Cells Are Expanded in Juvenile Dermatomyositis and Exhibit a Pro-Inflammatory Phenotype After Activation Through Toll-Like Receptor 7 and Interferon-α

Juvenile dermatomyositis (JDM) is a rare form of childhood autoimmune myositis that presents with proximal muscle weakness and skin rash. B cells are strongly implicated in the pathogenesis of the disease, but the underlying mechanisms are unknown. Therefore, the main objective of our study was to investigate mechanisms driving B cell lymphocytosis and define pathological features of B cells in JDM patients. Patients were recruited through the UK JDM Cohort and Biomarker study. Peripheral blood B cell subpopulations were immunophenotyped by flow cytometry. The results identified that immature transitional B cells were significantly expanded in active JDM, actively dividing, and correlated positively with disease activity. Protein and RNAseq analysis revealed high interferon alpha (IFNa) and TLR7-pathway signatures pre-treatment. Stimulation of B cells through TLR7/8 promoted both IL-10 and IL-6 production in controls but failed to induce IL-10 in JDM patient cells. Interrogation of the CD40-CD40L pathway (known to induce B cell IL-10 and IL-6) revealed similar expression of IL-10 and IL-6 in B cells cultured with CD40L from both JDM patients and controls. In conclusion, JDM patients with active disease have a significantly expanded immature transitional B cell population which correlated with the type I IFN signature. Activation through TLR7 and IFNa may drive the expansion of immature transitional B cells in JDM and skew the cells toward a pro-inflammatory phenotype

Youth representations of environmental protest

A necessary condition for a functioning democracy is the participation of its citizens, including its youth. This is particularly true for political participation in environmental decisions because these decisions can have intergenerational consequences. In this article we examine young people’s beliefs about one form of political participation - protest - in the context of communities affected by fracking and associated anti-fracking protest, and discuss the implications of these representations for education. Drawing on focus groups with 121 young people (age 15-19) in 5 schools and colleges near sites which have experienced anti-fracking protest in England and Northern Ireland, we find young people well-informed about avenues for formal and non-formal political participation against a background of disillusionment with formal political processes and varying levels of support for protest. We find representations of protest as disruptive, divisive, extreme, less desirable than other forms of participation, and ineffective in bringing about change but effective in awareness-raising. These representations are challenging, not least because the way protest is interpreted is critical to the way people think and act in the world. These representations of environmental protest must be challenged through formal education in order to safeguard the UN Convention on the Rights of the Child and ensure that the spirit of Article 11 of the UK Human Rights Act is protected