Spatial Scale of Clustering of Motor Vehicle Crash Types and Appropriate Countermeasures, 2009

This project analyzes the characteristics and spatial distributions of motor vehicle crash types in order to evaluate the degree and scale of their spatial clustering. Crashes occur as the result of a variety of vehicle, roadway, and human factors and thus vary in their clustering behavior. Clustering can occur at a variety of scales, from the intersection level, to the corridor level, to the area level. Conversely, other crash types are less linked to geographic factors and are more spatially “random.” The degree and scale of clustering have implications for the use of strategies to promote transportation safety. In this project, Iowa's crash database, geographic information systems, and recent advances in spatial statistics methodologies and software tools were used to analyze the degree and spatial scale of clustering for several crash types within the counties of the Iowa Northland Regional Council of Governments. A statistical measure called the K function was used to analyze the clustering behavior of crashes. Several methodological issues, related to the application of this spatial statistical technique in the context of motor vehicle crashes on a road network, were identified and addressed. These methods facilitated the identification of crash clusters at appropriate scales of analysis for each crash type. This clustering information is useful for improving transportation safety through focused countermeasures directly linked to crash causes and the spatial extent of identified problem locations, as well as through the identification of less location-based crash types better suited to non-spatial countermeasures. The results of the K function analysis point to the usefulness of the procedure in identifying the degree and scale at which crashes cluster, or do not cluster, relative to each other. Moreover, for many individual crash types, different patterns and processes and potentially different countermeasures appeared at different scales of analysis. This finding highlights the importance of scale considerations in problem identification and countermeasure formulation.

An essential role for transmembrane TNF in the resolution of the inflammatory lesion induced by Leishmania major infection.

TNF is an essential player in infections with Leishmania major, contributing to the control of the inflammatory lesion and, to a lesser degree, to parasite killing. However, the relative contribution of the soluble and transmembrane forms of TNF in these processes is unknown. To investigate the role of transmembrane TNF (mTNF) in the control of L. major infections, mTNF-knock-in (mTNF(Delta/Delta)) mice, which express functional mTNF but do not release soluble TNF, were infected with L. major, and the development of the inflammatory lesion and the immune response was compared to that occurring in L. major-infected TNF(-/-) and wild-type mice. mTNF(Delta/Delta) mice controlled the infection and resolved their inflammatory lesion as well as wild-type mice, a process associated with the early clearance of neutrophils at the site of parasite infection. In contrast, L. major-infected TNF(-/-) mice developed non-healing lesions, characterized by an elevated presence of neutrophils at the site of infection and partial control of parasite number within the lesions. Altogether, the results presented here demonstrate that mTNF, in absence of soluble TNF, is sufficient to control infection due to L. major, enabling the regulation of inflammation, and the optimal killing of Leishmania parasites at the site of infection.

An investigation of the resolution of inflammation (catabasis) in COPD.

Background: Chronic Obstructive Pulmonary Disease (COPD) is characterized by an enhanced inflammatory response to smoking that persists despite quitting. The resolution of inflammation (catabasis) is a complex and highly regulated process where tissue resident macrophages play a key role since they phagocytose apoptotic cells (efferocytosis), preventing their secondary necrosis and the spill-over of their pro-inflammatory cytoplasmic content, and release pro-resolution and tissue repair molecules, such as TGFβ, VEGF and HGF. Because inflammation does not resolve in COPD, we hypothesized that catabasis may be abnormal in these patients. Methods: To explore this hypothesis, we studied lung tissue samples obtained at surgery from 21 COPD patients,22 smokers with normal spirometry and 13 non-smokers controls. In these samples we used: (1)immunohistochemistry to assess the expression of CD44, CD36, VEGF and TGFβ in lung macrophages; (2) real time PCR to determine HGF, PPARγ, TGFβ, VEGF and MMP-9 gene expression; and, (3) ELISA to quantify lipoxin A4, a lipid mediator of catabasis. Results: We found that current and former smokers with COPD showed: (1) more inflammation (higher MMP-9 expression); (2) reduced macrophage surface expression of CD44, a key efferocytosis receptor; and, (3) similar levels of TGFβ, VEGF, HGF, PPARγ, and lipoxin A4 than smokers with normal spirometry, despite the presence of inflammation and disease. Conclusions: These results identify several potential abnormalities of catabasis in patients with COPD.

Feasibility of direct mapping of cerebral fluorodeoxy-D-glucose metabolism in situ at subcellular resolution using soft X-ray fluorescence.

Glucose metabolism is difficult to image with cellular resolution in mammalian brain tissue, particularly with (18) fluorodeoxy-D-glucose (FDG) positron emission tomography (PET). To this end, we explored the potential of synchrotron-based low-energy X-ray fluorescence (LEXRF) to image the stable isotope of fluorine (F) in phosphorylated FDG (DG-6P) at 1 μm(2) spatial resolution in 3-μm-thick brain slices. The excitation-dependent fluorescence F signal at 676 eV varied linearly with FDG concentration between 0.5 and 10 mM, whereas the endogenous background F signal was undetectable in brain. To validate LEXRF mapping of fluorine, FDG was administered in vitro and in vivo, and the fluorine LEXRF signal from intracellular trapped FDG-6P over selected brain areas rich in radial glia was spectrally quantitated at 1 μm(2) resolution. The subsequent generation of spatial LEXRF maps of F reproduced the expected localization and gradients of glucose metabolism in retinal Müller glia. In addition, FDG uptake was localized to periventricular hypothalamic tanycytes, whose morphological features were imaged simultaneously by X-ray absorption. We conclude that the high specificity of photon emission from F and its spatial mapping at ≤1 μm resolution demonstrates the ability to identify glucose uptake at subcellular resolution and holds remarkable potential for imaging glucose metabolism in biological tissue. © 2012 Wiley Periodicals, Inc.

Eighty-Sixth General Assembly House Code of Ethics (House Resolution 5) Adopted 2-3-2015, February 3, 2015

Eighty-Sixth General Assembly House Code of Ethics (House Resolution 5) Adopted 2-3-2015. Every legislator and legislative employee has a duty to uphold the integrity and honor of the general assembly, to encourage respect for the law and for the general assembly, and to observe the house code of ethics. The members and employees of the house have a responsibility to conduct themselves so as to reflect credit on the general assembly, and to inspire the confidence, respect, and trust of the public. The following rules are adopted pursuant to chapter 68B of the Code, to assist the members and employees in the conduct of their activities.

Eighty-Sixth General Assembly Senate Code of Ethics (Senate Resolution 4-Adopted 2-4-2015), February 4, 2015

Eighty-Sixth General Assembly Senate Code of Ethics (Senate Resolution 4-Adopted 2-4-2015)Every legislator owes a duty to uphold the integrity and honor of the general assembly, to encourage respect for the law and for the general assembly and the members thereof, and to observe the legislative code of ethics.

Eighty-Sixth General Assembly House Rules (House Resolution 4-Adopted 2-3-2015), February 3, 2015

Eighty-Sixth General Assembly House Rules (House Resolution 4-Adopted 2-3-2015)

Eighty-Sixth General Assembly Joint Rules Governing Lobbyists (House Concurrent Resolution 7) House Adopted 2-3-2015, Senate Adopted 2-4-2015, February 5, 2015

Eighty-Sixth General Assembly Joint Rules Governing Lobbyists (House Concurrent Resolution 7) House Adopted 2-3-2015, Senate Adopted 2-4-2015

Eighty-Sixth General Assembly Senate Rules (Senate Resolution 1 — Adopted 2/4/15), February 6, 2015

Eighty-Sixth General Assembly House Rules (House Resolution 4-Adopted 2-3-2015)

A connectome-based comparison of diffusion MRI schemes.

Diffusion MRI has evolved towards an important clinical diagnostic and research tool. Though clinical routine is using mainly diffusion weighted and tensor imaging approaches, Q-ball imaging and diffusion spectrum imaging techniques have become more widely available. They are frequently used in research-oriented investigations in particular those aiming at measuring brain network connectivity. In this work, we aim at assessing the dependency of connectivity measurements on various diffusion encoding schemes in combination with appropriate data modeling. We process and compare the structural connection matrices computed from several diffusion encoding schemes, including diffusion tensor imaging, q-ball imaging and high angular resolution schemes, such as diffusion spectrum imaging with a publically available processing pipeline for data reconstruction, tracking and visualization of diffusion MR imaging. The results indicate that the high angular resolution schemes maximize the number of obtained connections when applying identical processing strategies to the different diffusion schemes. Compared to the conventional diffusion tensor imaging, the added connectivity is mainly found for pathways in the 50-100mm range, corresponding to neighboring association fibers and long-range associative, striatal and commissural fiber pathways. The analysis of the major associative fiber tracts of the brain reveals striking differences between the applied diffusion schemes. More complex data modeling techniques (beyond tensor model) are recommended 1) if the tracts of interest run through large fiber crossings such as the centrum semi-ovale, or 2) if non-dominant fiber populations, e.g. the neighboring association fibers are the subject of investigation. An important finding of the study is that since the ground truth sensitivity and specificity is not known, the comparability between results arising from different strategies in data reconstruction and/or tracking becomes implausible to understand.

Improved SNR efficiency in gradient echo coronary MRA with high temporal resolution using parallel imaging.

Contemporary coronary magnetic resonance angiography techniques suffer from signal-to-noise ratio (SNR) constraints. We propose a method to enhance SNR in gradient echo coronary magnetic resonance angiography by using sensitivity encoding (SENSE). While the use of sensitivity encoding to improve SNR seems counterintuitive, it can be exploited by reducing the number of radiofrequency excitations during the acquisition window while lowering the signal readout bandwidth, therefore improving the radiofrequency receive to radiofrequency transmit duty cycle. Under certain conditions, this leads to improved SNR. The use of sensitivity encoding for improved SNR in three-dimensional coronary magnetic resonance angiography is investigated using numerical simulations and an in vitro and an in vivo study. A maximum 55% SNR enhancement for coronary magnetic resonance angiography was found both in vitro and in vivo, which is well consistent with the numerical simulations. This method is most suitable for spoiled gradient echo coronary magnetic resonance angiography in which a high temporal and spatial resolution is required.

Mixed spectral-structural classification of very high resolution images with summation kernels

In this paper, mixed spectral-structural kernel machines are proposed for the classification of very-high resolution images. The simultaneous use of multispectral and structural features (computed using morphological filters) allows a significant increase in classification accuracy of remote sensing images. Subsequently, weighted summation kernel support vector machines are proposed and applied in order to take into account the multiscale nature of the scene considered. Such classifiers use the Mercer property of kernel matrices to compute a new kernel matrix accounting simultaneously for two scale parameters. Tests on a Zurich QuickBird image show the relevance of the proposed method : using the mixed spectral-structural features, the classification accuracy increases of about 5%, achieving a Kappa index of 0.97. The multikernel approach proposed provide an overall accuracy of 98.90% with related Kappa index of 0.985.

Prediction of soil orders with high spatial resolution: response of different classifiers to sampling density

The objective of this work was to evaluate sampling density on the prediction accuracy of soil orders, with high spatial resolution, in a viticultural zone of Serra Gaúcha, Southern Brazil. A digital elevation model (DEM), a cartographic base, a conventional soil map, and the Idrisi software were used. Seven predictor variables were calculated and read along with soil classes in randomly distributed points, with sampling densities of 0.5, 1, 1.5, 2, and 4 points per hectare. Data were used to train a decision tree (Gini) and three artificial neural networks: adaptive resonance theory, fuzzy ARTMap; self‑organizing map, SOM; and multi‑layer perceptron, MLP. Estimated maps were compared with the conventional soil map to calculate omission and commission errors, overall accuracy, and quantity and allocation disagreement. The decision tree was less sensitive to sampling density and had the highest accuracy and consistence. The SOM was the less sensitive and most consistent network. The MLP had a critical minimum and showed high inconsistency, whereas fuzzy ARTMap was more sensitive and less accurate. Results indicate that sampling densities used in conventional soil surveys can serve as a reference to predict soil orders in Serra Gaúcha.