E-COMMERCE IN AGRICULTURE: DEVELOPMENT, STRATEGY, AND MARKET IMPLICATIONS

Marketing,

Comparison of Regional Wall Motion Parameters Between Angiographic and Echocardiographic Images

Conference PaperBiomedical Informatic

Synthesis and evaluation of nanoglobule-cystamine-(Gd-DO3A), a biodegradable nanosized magnetic resonance contrast agent for dynamic contrast-enhanced magnetic resonance urography

Dynamic contrast-enhanced magnetic resonance imaging has been recently shown to be effective for diagnostic urography. High-resolution urographic images can be acquired with T1 contrast agents for the kidney and urinary tract with minimal noise in the abdomen. Currently, clinical contrast agents are low molecular weight agents and can rapidly extravasate from blood circulation, leading to slow contrast agent elimination through kidney and consequently providing limited contrast enhancement in urinary tract. In this study, a new biodegradable macromolecular contrast agent, nanoglobule-G4-cystamine-(Gd-DO3A), was prepared by conjugating Gd-DO3A chelates on the surface of a generation 4 nanoglobule, poly-l-lysine octa(3-aminopropyl)silsesquioxane dendrimer, via a disulfide spacer, where the carrier had a precisely defined nanosize that is far smaller than the renal filtration threshold. The in vivo contrast enhancement and dynamic imaging of the urinary tract of the agent was evaluated in nude mice using a low molecular weight agent Gd(DTPA-BMA) as a control. The agent eliminated rapidly from blood circulation and accumulated more abundantly in urinary tract than Gd(DTPA-BMA). The fast elimination kinetics is ideal for functional evaluation of the kidneys. The morphology of the kidneys and urinary tract was better visualized by the biodegradable nanoglobular contrast agent than Gd(DTPA-BMA). The agent also resulted in low liver contrast enhancement, indicating low nonspecific tissue deposition. These features render the G4 nanoglobule-cystamine-(Gd-DO3A) conjugate a promising contrast agent for magnetic resonance urography

Simulating Flaring Events in Complex Active Regions Driven by Observed Magnetograms

We interpret solar flares as events originating from active regions that have reached the Self Organized Critical state, by using a refined Cellular Automaton model with initial conditions derived from observations. Aims: We investigate whether the system, with its imposed physical elements,reaches a Self Organized Critical state and whether well-known statistical properties of flares, such as scaling laws observed in the distribution functions of characteristic parameters, are reproduced after this state has been reached. Results: Our results show that Self Organized Criticality is indeed reached when applying specific loading and relaxation rules. Power law indices obtained from the distribution functions of the modeled flaring events are in good agreement with observations. Single power laws (peak and total flare energy) as well as power laws with exponential cutoff and double power laws (flare duration) are obtained. The results are also compared with observational X-ray data from GOES satellite for our active-region sample. Conclusions: We conclude that well-known statistical properties of flares are reproduced after the system has reached Self Organized Criticality. A significant enhancement of our refined Cellular Automaton model is that it commences the simulation from observed vector magnetograms, thus facilitating energy calculation in physical units. The model described in this study remains consistent with fundamental physical requirements, and imposes physically meaningful driving and redistribution rules.Comment: 14 pages; 12 figures; 6 tables - A&A, in pres

Solar Flares as Cascades of Reconnecting Magnetic Loops

A model for the solar coronal magnetic field is proposed where multiple directed loops evolve in space and time. Loops injected at small scales are anchored by footpoints of opposite polarity moving randomly on a surface. Nearby footpoints of the same polarity aggregate, and loops can reconnect when they collide. This may trigger a cascade of further reconnection, representing a solar flare. Numerical simulations show that a power law distribution of flare energies emerges, associated with a scale free network of loops, indicating self-organized criticality.Comment: 4 pages, 4 figures, To be published in Phys. Rev. Let

Deterministically Driven Avalanche Models of Solar Flares

We develop and discuss the properties of a new class of lattice-based avalanche models of solar flares. These models are readily amenable to a relatively unambiguous physical interpretation in terms of slow twisting of a coronal loop. They share similarities with other avalanche models, such as the classical stick--slip self-organized critical model of earthquakes, in that they are driven globally by a fully deterministic energy loading process. The model design leads to a systematic deficit of small scale avalanches. In some portions of model space, mid-size and large avalanching behavior is scale-free, being characterized by event size distributions that have the form of power-laws with index values, which, in some parameter regimes, compare favorably to those inferred from solar EUV and X-ray flare data. For models using conservative or near-conservative redistribution rules, a population of large, quasiperiodic avalanches can also appear. Although without direct counterparts in the observational global statistics of flare energy release, this latter behavior may be relevant to recurrent flaring in individual coronal loops. This class of models could provide a basis for the prediction of large solar flares.Comment: 24 pages, 11 figures, 2 tables, accepted for publication in Solar Physic

Fast stable direct fitting and smoothness selection for Generalized Additive Models

Existing computationally efficient methods for penalized likelihood GAM fitting employ iterative smoothness selection on working linear models (or working mixed models). Such schemes fail to converge for a non-negligible proportion of models, with failure being particularly frequent in the presence of concurvity. If smoothness selection is performed by optimizing `whole model' criteria these problems disappear, but until now attempts to do this have employed finite difference based optimization schemes which are computationally inefficient, and can suffer from false convergence. This paper develops the first computationally efficient method for direct GAM smoothness selection. It is highly stable, but by careful structuring achieves a computational efficiency that leads, in simulations, to lower mean computation times than the schemes based on working-model smoothness selection. The method also offers a reliable way of fitting generalized additive mixed models

Validation of an arterial tortuosity measure with application to hypertension collection of clinical hypertensive patients

<p>Abstract</p> <p>Background</p> <p>Hypertension may increase tortuosity or twistedness of arteries. We applied a centerline extraction algorithm and tortuosity metric to magnetic resonance angiography (MRA) brain images to quantitatively measure the tortuosity of arterial vessel centerlines. The most commonly used arterial tortuosity measure is the distance factor metric (DFM). This study tested a DFM based measurement’s ability to detect increases in arterial tortuosity of hypertensives using existing images. Existing images presented challenges such as different resolutions which may affect the tortuosity measurement, different depths of the area imaged, and different artifacts of imaging that require filtering.</p> <p>Methods</p> <p>The stability and accuracy of alternative centerline algorithms was validated in numerically generated models and test brain MRA data. Existing images were gathered from previous studies and clinical medical systems by manually reading electronic medical records to identify hypertensives and negatives. Images of different resolutions were interpolated to similar resolutions. Arterial tortuosity in MRA images was measured from a DFM curve and tested on numerically generated models as well as MRA images from two hypertensive and three negative control populations. Comparisons were made between different resolutions, different filters, hypertensives versus negatives, and different negative controls.</p> <p>Results</p> <p>In tests using numerical models of a simple helix, the measured tortuosity increased as expected with more tightly coiled helices. Interpolation reduced resolution-dependent differences in measured tortuosity. The Korean hypertensive population had significantly higher arterial tortuosity than its corresponding negative control population across multiple arteries. In addition one negative control population of different ethnicity had significantly less arterial tortuosity than the other two.</p> <p>Conclusions</p> <p>Tortuosity can be compared between images of different resolutions by interpolating from lower to higher resolutions. Use of a universal negative control was not possible in this study. The method described here detected elevated arterial tortuosity in a hypertensive population compared to the negative control population and can be used to study this relation in other populations.</p