Quantitative Mapping of Waterways Characteristics at Bridge Sites, TR-569, 2008

Iowa state, county, and city engineering offices expend considerable effort monitoring the state’s approximately 25,000 bridges, most of which span small waterways. In fact, the need for monitoring is actually greater for bridges over small waterways because scour processes are exacerbated by the close proximity of abutments, piers, channel banks, approach embankments, and other local obstructions. The bridges are customarily inspected biennially by the county’s road department bridge inspectors. It is extremely time consuming and difficult to obtain consistent, reliable, and timely information on bridge-waterway conditions for so many bridges. Moreover, the current approaches to gather survey information is not uniform, complete, and quantitative. The methodology and associated software (DIGIMAP) developed through the present project enable a non-intrusive means to conduct fast, efficient, and accurate inspection of the waterways in the vicinity of the bridges and culverts using one technique. The technique combines algorithms image of registration and velocimetry using images acquired with conventional devices at the inspection site. The comparison of the current bridge inspection and monitoring methods with the DIGIMAP methodology enables to conclude that the new procedure assembles quantitative information on the waterway hydrodynamic and morphologic features with considerable reduced effort, time, and cost. It also improves the safety of the bridge and culvert inspections conducted during normal and extreme hydrologic events. The data and information are recorded in a digital format, enabling immediate and convenient tracking of the waterway changes over short or long time intervals.

Mapping of the binding domains of the axon guidance receptor Unc5B to Netrin-1 and FLRT3

Anàlisi de les interaccions, a nivell neuronal, que tenen lloc durant el desenvolupament embrionari entre el receptor Unc5B (receptor present a la membrana) i les proteïnes Netrin-1 i FLRT3 (fibronectin and leucine-rich transmembrane proteins). La interacció entre aquest receptor i Netrin-1 ha estat profundament estudiada fins al moment, de manera que es coneix que aquesta promou una repulsió en la guia d’axons durant el desenvolupament embrionari. A més, la interacció està implicada en la senyalització per a diferents processos com l’angiogènesi i la supervivència cel·lular. Per altra banda, la interacció entre neurones Unc5B positives i FLRT3, promou un retard en la migració de les neurones. Diversos estudis demostren que aquest retard en la migració està relacionat amb certes patologies mentals.

QTL mapping for protein content in soybean cultivated in two tropical environments

The objectives of this study were to detect quantitative trait loci (QTL) for protein content in soybean grown in two distinct tropical environments and to build a genetic map for protein content. One hundred eighteen soybean recombinant inbred lines (RIL), obtained from a cross between cultivars BARC 8 and Garimpo, were used. The RIL were cultivated in two distinct Brazilian tropical environments: Cascavel county, in Paraná, and Viçosa county, in Minas Gerais (24º57'S, 53º27'W and 20º45'S, 42º52'W, respectively). Sixty-six SSR primer pairs and 65 RAPD primers were polymorphic and segregated at a 1:1 proportion. Thirty poorly saturated linkage groups were obtained, with 90 markers and 41 nonlinked markers. For the lines cultivated in Cascavel, three QTL were mapped in C2, E and N linkage groups, which explained 14.37, 10.31 and 7.34% of the phenotypic variation of protein content, respectively. For the lines cultivated in Viçosa, two QTL were mapped in linkage groups G and #1, which explained 9.51 and 7.34% of the phenotypic variation of protein content. Based on the mean of the two environments, two QTL were identified: one in the linkage group E (9.90%) and other in the group L (7.11%). In order for future studies to consistently detect QTL effects of different environments, genotypes with greater stability should be used.

A hybrid algorithm combining metaheuristic with Monte Carlo simulation for solving the Stochastic Flow Shop problem

In this paper, a hybrid simulation-based algorithm is proposed for the StochasticFlow Shop Problem. The main idea of the methodology is to transform the stochastic problem into a deterministic problem and then apply simulation to the latter. In order to achieve this goal, we rely on Monte Carlo Simulation and an adapted version of a deterministic heuristic. This approach aims to provide flexibility and simplicity due to the fact that it is not constrained by any previous assumption and relies in well-tested heuristics.

Mapping the human connectome at multiple scales with diffusion spectrum MRI.

The global structural connectivity of the brain, the human connectome, is now accessible at millimeter scale with the use of MRI. In this paper, we describe an approach to map the connectome by constructing normalized whole-brain structural connection matrices derived from diffusion MRI tractography at 5 different scales. Using a template-based approach to match cortical landmarks of different subjects, we propose a robust method that allows (a) the selection of identical cortical regions of interest of desired size and location in different subjects with identification of the associated fiber tracts (b) straightforward construction and interpretation of anatomically organized whole-brain connection matrices and (c) statistical inter-subject comparison of brain connectivity at various scales. The fully automated post-processing steps necessary to build such matrices are detailed in this paper. Extensive validation tests are performed to assess the reproducibility of the method in a group of 5 healthy subjects and its reliability is as well considerably discussed in a group of 20 healthy subjects.

A hybrid algorithm combining metaheuristic with Monte Carlo simulation for solving the Stochastic Flow Shop problem

In this paper, a hybrid simulation-based algorithm is proposed for the StochasticFlow Shop Problem. The main idea of the methodology is to transform the stochastic problem into a deterministic problem and then apply simulation to the latter. In order to achieve this goal, we rely on Monte Carlo Simulation and an adapted version of a deterministic heuristic. This approach aims to provide flexibility and simplicity due to the fact that it is not constrained by any previous assumption and relies in well-tested heuristics.

Spatial mapping of exciton lifetimes in single ZnO nanowires

We investigate the spatial dependence of the exciton lifetimes in single ZnO nanowires. We have found that the free exciton and bound exciton lifetimes exhibit a maximum at the center of nanowires, while they decrease by 30% towards the tips. This dependence is explained by considering the cavity-like properties of the nanowires in combination with the Purcell effect. We show that the lifetime of the bound-excitons scales with the localization energy to the power of 3/2, which validates the model of Rashba and Gurgenishvili at the nanoscale.

J2 effect and elliptic inclined periodic orbits in the collision three-body problem

The existence of a new class of inclined periodic orbits of the collision restricted three-body problem is shown. The symmetric periodic solutions found are perturbations of elliptic kepler orbits and they exist only for special values of the inclination and are related to the motion of a satellite around an oblate planet

Automated Lesion Detection-Based Symptome Mapping In Patients With Sensory Deficits

The human brain is the most complex structure known. With its high number of cells, number of connections and number of pathways it is the source of every thought in the world. It consumes 25% of our oxygen and suffers very fast from a disruption of its supply. An acute event, like a stroke, results in rapid dysfunction referable to the affected area. A few minutes without oxygen and neuronal cells die and subsequently degenerate. Changes in the brains incoming blood flow alternate the anatomy and physiology of the brain. All stroke events leave behind a brain tissue lesion. To rapidly react and improve the prediction of outcome in stroke patients, accurate lesion detection and reliable lesion-based function correlation would be very helpful. With a number of neuroimaging and clinical data of cerebral injured patients this study aims to investigate correlations of structural lesion locations with sensory functions.

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.

Bayesian Networks and the Value of the Evidence for the Forensic Two-Trace Transfer Problem

Forensic scientists face increasingly complex inference problems for evaluating likelihood ratios (LRs) for an appropriate pair of propositions. Up to now, scientists and statisticians have derived LR formulae using an algebraic approach. However, this approach reaches its limits when addressing cases with an increasing number of variables and dependence relationships between these variables. In this study, we suggest using a graphical approach, based on the construction of Bayesian networks (BNs). We first construct a BN that captures the problem, and then deduce the expression for calculating the LR from this model to compare it with existing LR formulae. We illustrate this idea by applying it to the evaluation of an activity level LR in the context of the two-trace transfer problem. Our approach allows us to relax assumptions made in previous LR developments, produce a new LR formula for the two-trace transfer problem and generalize this scenario to n traces.