Hydrologic transport of fecal bacteria attenuated by flue gas desulfurization gypsum.

Flue gas desulfurization (FGD) gypsum is a byproduct of coal-fired power plants. Its application to agricultural fields may increase water infiltration, reduce soil erosion, and decrease nutrient losses from applications of animal manures. It may also reduce fecal bacterial contamination of surface waters. We tested the hypothesis that FGD gypsum applications would decrease the load of and the fecal indicator bacterium from poultry litter applications. Two rainfall simulation experiments were undertaken: one in spring 2009 and one in spring 2011. Six treatments consisted of four rates of FGD gypsum (0, 2.2, 4.5, and 9.0 Mg ha) with poultry litter (13.5 Mg ha and two controls) in a randomized, complete-block design with three replications. Each replicate 4- × 6-m plot contained a single 1- × 2-m subplot that was delineated by metal plates and a flume that captured total overland flow or runoff. Rainfall was applied at ∼64 mm h. Volume of overland runoff was measured and subsampled for analysis every 10 min for 1 h. Flow-weighted concentrations, total loads, and soil concentrations of were determined. was not detected in runoff. No significant differences between treatments were observed for the 2009 rainfall simulation. However, after 3 yr of FGD gypsum applications, the highest rate of FGD gypsum resulted in decreased flow-weighted concentrations and total loads of . Flue gas desulfurization gypsum applications may be a management practice that reduces microbial contamination of surface waters from manure applied to agricultural fields in the southeastern United States.

Ammonia volatilization from surface-applied poultry litter under conservation tillage management practices.

Land application of poultry litter can provide essential plant nutrients for crop production, but ammonia (NH(3)) volatilization from the litter can be detrimental to the environment. A multiseason study was conducted to quantify NH(3) volatilization rates from surface-applied poultry litter under no-till and paraplowed conservation tillage managements. Litter was applied to supply 90 to 140 kg N ha(-1). Evaluation of NH(3) volatilization was determined using gas concentrations and the flux-gradient gas transport technique using the momentum balance transport coefficient. Ammonia fluxes ranged from 3.3 to 24% of the total N applied during the winter and summer, respectively. Ammonia volatilization was rapid immediately after litter application and stopped within 7 to 8 d. Precipitation of 17 mm essentially halted volatilization, probably by transporting litter N into the soil matrix. Application of poultry to conservation-tilled cropland immediately before rainfall events would reduce N losses to the atmosphere but could also increase NO(3) leaching and runoff to streams and rivers.

Improvements in spiral MR imaging.

The basic principles of spiral MR image acquisition and reconstruction are summarised with the aim to explain how high quality spiral images can be obtained. The sensitivity of spiral imaging to off-resonance effects, gradient system imperfections and concomitant fields are outlined and appropriate measures for corrections are discussed in detail. Phantom experiments demonstrate the validity of the correction approaches. Furthermore, in-vivo results are shown to demonstrate the applicability of the corrections under in-vivo conditions. The spiral image quality thus obtained was found to be comparable to that obtainable with robust spin warp sequences.

Off-resonance correction of MR images.

In magnetic resonance imaging (MRI), the spatial inhomogeneity of the static magnetic field can cause degraded images if the reconstruction is based on inverse Fourier transformation. This paper presents and discusses a range of fast reconstruction algorithms that attempt to avoid such degradation by taking the field inhomogeneity into account. Some of these algorithms are new, others are modified versions of known algorithms. Speed and accuracy of all these algorithms are demonstrated using spiral MRI.

Tomographic image reconstruction from optical projections in light-diffusing media.

The recent developments in light generation and detection techniques have opened new possibilities for optical medical imaging, tomography, and diagnosis at tissue penetration depths of ~10 cm. However, because light scattering and diffusion in biological tissue are rather strong, the reconstruction of object images from optical projections needs special attention. We describe a simple reconstruction method for diffuse optical imaging, based on a modified backprojection approach for medical tomography. Specifically, we have modified the standard backprojection method commonly used in x-ray tomographic imaging to include the effects of both the diffusion and the scattering of light and the associated nonlinearities in projection image formation. These modifications are based primarily on the deconvolution of the broadened image by a spatially variant point-spread function that is dependent on the scattering of light in tissue. The spatial dependence of the deconvolution and nonlinearity corrections for the curved propagating ray paths in heterogeneous tissue are handled semiempirically by coordinate transformations. We have applied this method to both theoretical and experimental projections taken by parallel- and fan-beam tomography geometries. The experimental objects were biomedical phantoms with multiple objects, including in vitro animal tissue. The overall results presented demonstrate that image-resolution improvements by nearly an order of magnitude can be obtained. We believe that the tomographic method presented here can provide a basis for rapid, real-time medical monitoring by the use of optical projections. It is expected that such optical tomography techniques can be combined with the optical tissue diagnosis methods based on spectroscopic molecular signatures to result in a versatile optical diagnosis and imaging technology.

The gridding method for image reconstruction by Fourier transformation.

The authors explore a computational method for reconstructing an n-dimensional signal f from a sampled version of its Fourier transform f;. The method involves a window function w; and proceeds in three steps. First, the convolution g;=w;*f; is computed numerically on a Cartesian grid, using the available samples of f;. Then, g=wf is computed via the inverse discrete Fourier transform, and finally f is obtained as g/w. Due to the smoothing effect of the convolution, evaluating w;*f; is much less error prone than merely interpolating f;. The method was originally devised for image reconstruction in radio astronomy, but is actually applicable to a broad range of reconstructive imaging methods, including magnetic resonance imaging and computed tomography. In particular, it provides a fast and accurate alternative to the filtered backprojection. The basic method has several variants with other applications, such as the equidistant resampling of arbitrarily sampled signals or the fast computation of the Radon (Hough) transform.

Lateral inverse filtering of ultrasonic B-scan images.

The formation of ultrasonic B-scan images using parallel beams may be modelled as a lateral, one-dimensional convolution of the beam profile and an unknown but wanted reflection coefficient. Lateral inverse filtering, or deconvolution, might therefore be used to improve the image quality. Two different deconvolution techniques are applied to both an image of a tissue mimicking phantom and a human liver. An enhancement of the resolution (defined as the reciprocal of the half-width of the image of a point reflector) of about 1.4 is achieved. This is in good agreement with the previously derived formula R = square root 1n SNR, which relates the signal-to-noise ratio, SNR, to the resolution enhancement, R. However, each method also creates artifacts, and despite the slight resolution enhancement, the deconvoluted liver images do not exhibit more information nor are they more appealing. So it is felt that the computational effort is wasted. This failure is not a fault of the special deconvolution techniques tried here, but rather caused by the logarithmic dependence of R on SNR and by the noise level, which is largely due to macro- and microscopic inhomogeneities of the tissue and cannot be made arbitrarily small.