Piscataquis County, Maine, 1858 (Image 1 of 2) (Raster Image)

This layer is a georeferenced raster image of the historic paper map entitled: Map of Piscataquis County Maine, from surveys under the direction of H. F. Walling; field notes under the direction of L. H. Eaton Esq. civil engineer. It was published by Lee & Marsh in 1858. Scale [ca 1:63,360]. This layer is image 1 of 2 total images, representing the northeast portion of the four sheet source map. The image inside the map neatline is georeferenced to the surface of the earth and fit to the Universal Transverse Mercator projection (UTM Zone 19N, meters, NAD1983). All map collar and inset information is also available as part of the raster image, including any inset maps, profiles, statistical tables, directories, text, illustrations, index maps, legends, or other information associated with the principal map. This map shows features such as roads, railroads, drainage, public buildings, schools, churches, cemeteries, industry locations (e.g. mills, factories, mines, etc.), private buildings with names of property owners, town boundaries, and more. Relief shown by hachures. It includes many cadastral insets of individual county towns and villages. It also includes illustrations, business directories, and tables of statistics and distances.This layer is part of a selection of digitally scanned and georeferenced historic maps of New England from the Harvard Map Collection. These maps typically portray both natural and manmade features. The selection represents a range of regions, originators, ground condition dates, scales, and map purposes.

Piscataquis County, Maine, 1858 (Image 2 of 2) (Raster Image)

This layer is a georeferenced raster image of the historic paper map entitled: Map of Piscataquis County Maine, from surveys under the direction of H. F. Walling; field notes under the direction of L. H. Eaton Esq. civil engineer. It was published by Lee & Marsh in 1858. Scale [ca 1:63,360]. This layer is image 2 of 2 total images, representing the northwest portion of the four sheet source map. The image inside the map neatline is georeferenced to the surface of the earth and fit to the Universal Transverse Mercator projection (UTM Zone 19N, meters, NAD1983). All map collar and inset information is also available as part of the raster image, including any inset maps, profiles, statistical tables, directories, text, illustrations, index maps, legends, or other information associated with the principal map. This map shows features such as roads, railroads, drainage, public buildings, schools, churches, cemeteries, industry locations (e.g. mills, factories, mines, etc.), private buildings with names of property owners, town boundaries, and more. Relief shown by hachures. It includes many cadastral insets of individual county towns and villages. It also includes illustrations, business directories, and tables of statistics and distances.This layer is part of a selection of digitally scanned and georeferenced historic maps of New England from the Harvard Map Collection. These maps typically portray both natural and manmade features. The selection represents a range of regions, originators, ground condition dates, scales, and map purposes.

Local and systemic delivery of a novel group of inhibitors of transglutaminase enzyme: A potential approach for treating of catheter-related complications and liver fibrosis

The present thesis investigates targeted (locally and systemically) delivery of a novel group of inhibitors of enzyme transglutaminases (TGs). TGs are a widely distributed group of enzymes that catalyse the formation of isopeptide bonds between the y-carboxamide group of protein-bound glutamines and the a-amino group of protein-bound lysines or polyamines. The first group of the novel inhibitors tested were the tluorescently labelled inhibitors of Factor XIIIa (FXIIIa). These small, non-toxic inhibitors have the potential to prevent stabilisation of thrombi by FXIIIa and consequently increase the natural rate of thrombolysis, in addition it reduces staphylococcal colonisation of catheters by inhibiting their FXIIIa¬mediated cross-linking to blood clot proteins on the central venous catheter (CVCs) surface. The aim of this work was to incorporate the FXIIIa inhibitor either within coating of polyurethane (PU) catheters or to integrate it into silicone catheters, so as to reduce the incidence of thrombotic occlusion and associated bacterial infection in CVCs. The initial work focused on the incorporation of FXIIIa inhibitors within polymeric coatings of PU catheters. After defining the key characteristics desired for an effective polymeric-coating, polyvinylpyrrolidone (PVP), poly(lactic-co-glycolic acid) (PLGA) or their combination were studies as polymers of choice for coating of the catheters_ The coating was conducted by dip-coating method in a polymer solution containing the inhibitor. Upon incubation of the inhibitor-and polymer-coated strips in buffer, PVP was dissolved instantly, generating fast and significant drug release, whilst PLGA did not dissolve, yielding a slow and an insufficient amount of drug release. Nevertheless, the drug release profile was enhanced upon employing a blend solution of PVP and PLGA. The second part of the study was to incorporate the FXIIIa inhibitor into a silicone elastomer; results demonstrated that FXIIIa inhibitor can be incorporated and released from silicone by using citric acid (CA) and sodium bicarbonate (SB) as additives and the drug release rate can be controlled by the amount of incorporated additives in the silicone matrix. Furthermore, it was deemed that the inhibitor was still biologically active subsequent to being released from the silicone elastomer strips. Morphological analysis confirmed the formation of channels and cracks inside the specimens upon the addition of CA and SB. Nevertheless, the tensile strength, in addition to Young's modulus of silicone elastomer strips, decreased constantly with an increasing amount of amalgamated CA/ SB in the formulations. According to our results, incorporation of FXIIIa inhibitor into catheters and other medical implant devices could offer new perspectives in preventing bio-material associated infections and thrombosis. The use of tissue transglutaminase (T02) inhibitor for treating of liver fibrosis was also investigated. Liver fibrosis is characterized by increased synthesis and decreased degradation of the extracellular matrix (ECM). Transglutaminase-mediated covalent cross-linking is involved in the stabilization of ECM in human liver fibrosis. Thus, TG2 inhibitors may be used to counteract the decreased degradation of the ECM. The potential of a liposome based drug delivery system for site specific delivery of the fluorescent TG2 inhibitor into the liver was investigated; results indicated that the TG2 inhibitor can be successfully integrated into liposomes and delivered to the liver, therefore demonstrating that liposomes can be employed for site-specific delivery of TG2 inhibitors into the liver and TG2 inhibitor incorporating liposomes could offer a new approach in treating liver fibrosis and its end stage disease cirrhosis.

Data Assimilation Technique For Flood Monitoring and Prediction

This paper focuses on the development of methods and cascade of models for flood monitoring and forecasting and its implementation in Grid environment. The processing of satellite data for flood extent mapping is done using neural networks. For flood forecasting we use cascade of models: regional numerical weather prediction (NWP) model, hydrological model and hydraulic model. Implementation of developed methods and models in the Grid infrastructure and related projects are discussed.

Wind power forecasts using Gaussian processes and numerical weather prediction

Since wind at the earth's surface has an intrinsically complex and stochastic nature, accurate wind power forecasts are necessary for the safe and economic use of wind energy. In this paper, we investigated a combination of numeric and probabilistic models: a Gaussian process (GP) combined with a numerical weather prediction (NWP) model was applied to wind-power forecasting up to one day ahead. First, the wind-speed data from NWP was corrected by a GP, then, as there is always a defined limit on power generated in a wind turbine due to the turbine controlling strategy, wind power forecasts were realized by modeling the relationship between the corrected wind speed and power output using a censored GP. To validate the proposed approach, three real-world datasets were used for model training and testing. The empirical results were compared with several classical wind forecast models, and based on the mean absolute error (MAE), the proposed model provides around 9% to 14% improvement in forecasting accuracy compared to an artificial neural network (ANN) model, and nearly 17% improvement on a third dataset which is from a newly-built wind farm for which there is a limited amount of training data. © 2013 IEEE.

Short-term wind power forecasting using Gaussian processes

Since wind has an intrinsically complex and stochastic nature, accurate wind power forecasts are necessary for the safety and economics of wind energy utilization. In this paper, we investigate a combination of numeric and probabilistic models: one-day-ahead wind power forecasts were made with Gaussian Processes (GPs) applied to the outputs of a Numerical Weather Prediction (NWP) model. Firstly the wind speed data from NWP was corrected by a GP. Then, as there is always a defined limit on power generated in a wind turbine due the turbine controlling strategy, a Censored GP was used to model the relationship between the corrected wind speed and power output. To validate the proposed approach, two real world datasets were used for model construction and testing. The simulation results were compared with the persistence method and Artificial Neural Networks (ANNs); the proposed model achieves about 11% improvement in forecasting accuracy (Mean Absolute Error) compared to the ANN model on one dataset, and nearly 5% improvement on another.

Charged-current inclusive neutrino cross sections in the SuperScaling model

SuperScaling model (SuSA) predictions to neutrino-induced charged-current pi(+) production in the Delta-resonance region are explored under MiniBooNE experimental conditions. The SuSA charged-current pi(+) results are in good agreement with data on neutrino flux-averaged double-differential cross sections. The SuSA model for quasielastic scattering and its extension to the pion production region are used for predictions of charged-current inclusive neutrino-nucleus cross sections. Results are also compared with the T2K experimental data for inclusive scattering.

Global relativistic folding optical potential and the relativistic Green's function model

Optical potentials provide critical input for calculations on a wide variety of nuclear reactions, in particular, for neutrino-nucleus reactions, which are of great interest in the light of the new neutrino oscillation experiments. We present the global relativistic folding optical potential (GRFOP) fits to elastic proton scattering data from C-12 nucleus at energies between 20 and 1040 MeV. We estimate observables, such as the differential cross section, the analyzing power, and the spin rotation parameter, in elastic proton scattering within the relativistic impulse approximation. The new GRFOP potential is employed within the relativistic Green's function model for inclusive quasielastic electron scattering and for (anti) neutrino-nucleus scattering at MiniBooNE kinematics.

A revised L-band radio-brightness sensitivity to extreme winds under tropical cyclones: The 5 year SMOS-Storm database

Five years of SMOS L-band brightness temperature data intercepting a large number of tropical cyclones (TCs) are analyzed. The storm-induced half-power radio-brightness contrast (ΔI) is defined as the difference between the brightness observed at a specific wind force and that for a smooth water surface with the same physical parameters. ΔI can be related to surface wind speed and has been estimated for ~ 300 TCs that intercept with SMOS measurements. ΔI, expressed in a common storm-centric coordinate system, shows that mean brightness contrast monotonically increases with increased storm intensity ranging from ~ 5 K for strong storms to ~ 24 K for the most intense Category 5 TCs. A remarkable feature of the 2D mean ΔI fields and their variability is that maxima are systematically found on the right quadrants of the storms in the storm-centered coordinate frame, consistent with the reported asymmetric structure of the wind and wave fields in hurricanes. These results highlight the strong potential of SMOS measurements to improve monitoring of TC intensification and evolution. An improved empirical geophysical model function (GMF) was derived using a large ensemble of co-located SMOS ΔI, aircraft and H*WIND (a multi-measurement analysis) surface wind speed data. The GMF reveals a quadratic relationship between ΔI and the surface wind speed at a height of 10 m (U10). ECMWF and NCEP analysis products and SMOS derived wind speed estimates are compared to a large ensemble of H*WIND 2D fields. This analysis confirms that the surface wind speed in TCs can effectively be retrieved from SMOS data with an RMS error on the order of 10 kt up to 100 kt. SMOS wind speed products above hurricane force (64 kt) are found to be more accurate than those derived from NWP analyses products that systematically underestimate the surface wind speed in these extreme conditions. Using co-located estimates of rain rate, we show that the L-band radio-brightness contrasts could be weakly affected by rain or ice-phase clouds and further work is required to refine the GMF in this context.

Extrapolating Satellite Winds to Turbine Operating Heights

Ocean wind retrievals from satellite sensors are typically performed for the standard level of 10 m. This restricts their full exploitation for wind energy planning, which requires wind information at much higher levels where wind turbines operate. A new method is presented for the vertical extrapolation of satellite-based wind maps. Winds near the sea surface are obtained from satellite data and used together with an adaptation of the Monin–Obukhov similarity theory to estimate the wind speed at higher levels. The thermal stratification of the atmosphere is taken into account through a long-term stability correction that is based on numerical weather prediction (NWP) model outputs. The effect of the long-term stability correction on the wind profile is significant. The method is applied to Envisat Advanced Synthetic Aperture Radar scenes acquired over the south Baltic Sea. This leads to maps of the long-term stability correction and wind speed at a height of 100 m with a spatial resolution of 0.02°. Calculations of the corresponding wind power density and Weibull parameters are shown. Comparisons with mast observations reveal that NWP model outputs can correct successfully for long-term stability effects and also, to some extent, for the limited number of satellite samples. The satellite-based and NWP-simulated wind profiles are almost equally accurate with respect to those from the mast. However, the satellite-based maps have a higher spatial resolution, which is particularly important in nearshore areas where most offshore wind farms are built.