Positive contrast visualization of nitinol devices using susceptibility gradient mapping.

MRI visualization of devices is traditionally based on signal loss due to T(2)* effects originating from local susceptibility differences. To visualize nitinol devices with positive contrast, a recently introduced postprocessing method is adapted to map the induced susceptibility gradients. This method operates on regular gradient-echo MR images and maps the shift in k-space in a (small) neighborhood of every voxel by Fourier analysis followed by a center-of-mass calculation. The quantitative map of the local shifts generates the positive contrast image of the devices, while areas without susceptibility gradients render a background with noise only. The positive signal response of this method depends only on the choice of the voxel neighborhood size. The properties of the method are explained and the visualizations of a nitinol wire and two stents are shown for illustration.

A geoprocessing approach for studying and controlling schistosomiasis in the state of Minas Gerais, Brazil

Geographical information systems (GIS) are tools that have been recently tested for improving our understanding of the spatial distribution of disease. The objective of this paper was to further develop the GIS technology to model and control schistosomiasis using environmental, social, biological and remote-sensing variables. A final regression model (R² = 0.39) was established, after a variable selection phase, with a set of spatial variables including the presence or absence of Biomphalaria glabrata, winter enhanced vegetation index, summer minimum temperature and percentage of houses with water coming from a spring or well. A regional model was also developed by splitting the state of Minas Gerais (MG) into four regions and establishing a linear regression model for each of the four regions: 1 (R² = 0.97), 2 (R² = 0.60), 3 (R² = 0.63) and 4 (R² = 0.76). Based on these models, a schistosomiasis risk map was built for MG. In this paper, geostatistics was also used to make inferences about the presence of Biomphalaria spp. The result was a map of species and risk areas. The obtained risk map permits the association of uncertainties, which can be used to qualify the inferences and it can be thought of as an auxiliary tool for public health strategies.

Anaerobic activation of the entire denitrification pathway in Pseudomonas aeruginosa requires Anr, an analog of Fnr.

The Pseudomonas aeruginosa gene anr, which encodes a structural and functional analog of the anaerobic regulator Fnr in Escherichia coli, was mapped to the SpeI fragment R, which is at about 59 min on the genomic map of P. aeruginosa PAO1. Wild-type P. aeruginosa PAO1 grew under anaerobic conditions with nitrate, nitrite, and nitrous oxide as alternative electron acceptors. An anr deletion mutant, PAO6261, was constructed. It was unable to grow with these alternative electron acceptors; however, its ability to denitrify was restored upon the introduction of the wild-type anr gene. In addition, the activities of two enzymes in the denitrification pathway, nitrite reductase and nitric oxide reductase, were not detectable under oxygen-limiting conditions in strain PAO6261 but were restored when complemented with the anr+ gene. These results indicate that the anr gene product plays a key role in anaerobically activating the entire denitrification pathway.

Assessment and mapping the sensitive areas to desertification in an insular Sahelian mountain region Case study of the Ribeira Seca Watershed, Santiago Island - Cabo Verde

This paper presents the assessment and mapping of the Ribeira Seca catchment, an insular Sahelian mountain region sensitive to desertification, located on the island of Santiago, Cabo Verde. Desertification is a threat to the global environment, representing a serious ecological problemin Cabo Verde. To successfully combat desertification, an evaluation of desertification consequences is required and the building of cartography of the sensitivity for arid and semi-arid ecosystems is required as a first step. The MEDALUS model was the basis for this study in which six quality indicators were used: climate, soil, vegetation, land management, erosion and social factors. Several parameters were defined for each indicator with weights varying between 1 (very low) and 2 (very high). The geometric mean of each of the six quality indicators was employed to produce a map of areas sensitive to desertification. The results of this study show that more than 50% of the watershed show clear evidence of becoming a desertified area.

Analysis of acute brain slices by electron microscopy: A correlative light-electron microscopy workflow based on Tokuyasu cryo-sectioning.

Acute brain slices are slices of brain tissue that are kept vital in vitro for further recordings and analyses. This tool is of major importance in neurobiology and allows the study of brain cells such as microglia, astrocytes, neurons and their inter/intracellular communications via ion channels or transporters. In combination with light/fluorescence microscopies, acute brain slices enable the ex vivo analysis of specific cells or groups of cells inside the slice, e.g. astrocytes. To bridge ex vivo knowledge of a cell with its ultrastructure, we developed a correlative microscopy approach for acute brain slices. The workflow begins with sampling of the tissue and precise trimming of a region of interest, which contains GFP-tagged astrocytes that can be visualised by fluorescence microscopy of ultrathin sections. The astrocytes and their surroundings are then analysed by high resolution scanning transmission electron microscopy (STEM). An important aspect of this workflow is the modification of a commercial cryo-ultramicrotome to observe the fluorescent GFP signal during the trimming process. It ensured that sections contained at least one GFP astrocyte. After cryo-sectioning, a map of the GFP-expressing astrocytes is established and transferred to correlation software installed on a focused ion beam scanning electron microscope equipped with a STEM detector. Next, the areas displaying fluorescence are selected for high resolution STEM imaging. An overview area (e.g. a whole mesh of the grid) is imaged with an automated tiling and stitching process. In the final stitched image, the local organisation of the brain tissue can be surveyed or areas of interest can be magnified to observe fine details, e.g. vesicles or gold labels on specific proteins. The robustness of this workflow is contingent on the quality of sample preparation, based on Tokuyasu's protocol. This method results in a reasonable compromise between preservation of morphology and maintenance of antigenicity. Finally, an important feature of this approach is that the fluorescence of the GFP signal is preserved throughout the entire preparation process until the last step before electron microscopy.

Iowa Railroad Base Map, July 1, 2009

Iowa railroad map of Iowa trains.

Iowa Railroad Service Map, July 1, 2009

Iowa railroad service map of Iowa trains in color.

Calculation of radio electrical coverage in Medium-Wave Frequencies

The aim of this project is to accomplish an application software based on Matlab to calculate the radioelectrical coverage by surface wave of broadcast radiostations in the band of Medium Wave (WM) all around the world. Also, given the location of a transmitting and a receiving station, the software should be able to calculate the electric field that the receiver should receive at that specific site. In case of several transmitters, the program should search for the existence of Inter-Symbol Interference, and calculate the field strenght accordingly. The application should ask for the configuration parameters of the transmitter radiostation within a Graphical User Interface (GUI), and bring back the resulting coverage above a map of the area under study. For the development of this project, it has been used several conductivity databases of different countries, and a high-resolution elevation database (GLOBE). Also, to calculate the field strenght due to groundwave propagation, it has been used ITU GRWAVE program, which must be integrated into a Matlab interface to be used by the application developed.

Domain Adaptation in remote sensing: increasing the portability of land-cover classifiers

Among the types of remote sensing acquisitions, optical images are certainly one of the most widely relied upon data sources for Earth observation. They provide detailed measurements of the electromagnetic radiation reflected or emitted by each pixel in the scene. Through a process termed supervised land-cover classification, this allows to automatically yet accurately distinguish objects at the surface of our planet. In this respect, when producing a land-cover map of the surveyed area, the availability of training examples representative of each thematic class is crucial for the success of the classification procedure. However, in real applications, due to several constraints on the sample collection process, labeled pixels are usually scarce. When analyzing an image for which those key samples are unavailable, a viable solution consists in resorting to the ground truth data of other previously acquired images. This option is attractive but several factors such as atmospheric, ground and acquisition conditions can cause radiometric differences between the images, hindering therefore the transfer of knowledge from one image to another. The goal of this Thesis is to supply remote sensing image analysts with suitable processing techniques to ensure a robust portability of the classification models across different images. The ultimate purpose is to map the land-cover classes over large spatial and temporal extents with minimal ground information. To overcome, or simply quantify, the observed shifts in the statistical distribution of the spectra of the materials, we study four approaches issued from the field of machine learning. First, we propose a strategy to intelligently sample the image of interest to collect the labels only in correspondence of the most useful pixels. This iterative routine is based on a constant evaluation of the pertinence to the new image of the initial training data actually belonging to a different image. Second, an approach to reduce the radiometric differences among the images by projecting the respective pixels in a common new data space is presented. We analyze a kernel-based feature extraction framework suited for such problems, showing that, after this relative normalization, the cross-image generalization abilities of a classifier are highly increased. Third, we test a new data-driven measure of distance between probability distributions to assess the distortions caused by differences in the acquisition geometry affecting series of multi-angle images. Also, we gauge the portability of classification models through the sequences. In both exercises, the efficacy of classic physically- and statistically-based normalization methods is discussed. Finally, we explore a new family of approaches based on sparse representations of the samples to reciprocally convert the data space of two images. The projection function bridging the images allows a synthesis of new pixels with more similar characteristics ultimately facilitating the land-cover mapping across images.

Report of the Workshop on Intelligent Compaction for Soils and HMA, April 2-4, 2008

This document summarizes the discussion and findings of a workshop on intelligent compaction for soils and hot-mix asphalt held in West Des Moines, Iowa, on April 2–4, 2008. The objective of the meeting was to provide a collaborative exchange of ideas for developing research initiatives that accelerate implementation of intelligent compaction (IC) technologies for soil, aggregates, and hot mix asphalt. Technical presentations, working breakout sessions, a panel discussion, and a group implementation strategy session comprised the workshop activities. About 100 attendees representing state departments of transportation, Federal Highway Administration, contractors, equipment manufacturers, and researchers participated in the workshop.

Rivers and Lakes of Iowa,2001.

A one page colored map of rivers and lakes in Iowa.

FOXC2 and NFATc1 control formation and maturation of collecting lymphatic vessels

The mechanisms of blood vessel maturation into distinct parts of the blood vasculature such as arteries, veins, and capillaries have been the subject of intense investigation over recent years. In contrast, our knowledge of lymphatic vessel maturation is still fragmentary. In this study, we provide a molecular and morphological characterization of the major steps in the maturation of the primary lymphatic capillary plexus into collecting lymphatic vessels during development and show that forkhead transcription factor Foxc2 controls this process. We further identify transcription factor NFATc1 as a novel regulator of lymphatic development and describe a previously unsuspected link between NFATc1 and Foxc2 in the regulation of lymphatic maturation. We also provide a genome-wide map of FOXC2-binding sites in lymphatic endothelial cells, identify a novel consensus FOXC2 sequence, and show that NFATc1 physically interacts with FOXC2-binding enhancers. These data provide novel insights into the molecular program of lymphatic vascular specification and suggest that FOXC2 and NFATc1 are potential targets for therapeutic intervention.

Iowa State Railroad Map, July 1, 2010

Iowa railroad map of Iowa trains.

Drainage Basins of Iowa, March 1, 2000

Map of Drainage Basins of Iowa produced by the Iowa Department of Transportation.

Drainage Basins of Iowa, September 1, 2008

Map of Drainage Basins of Iowa produced by the Iowa Department of Transportation.