Leptonic decay constants fDs and fD in three flavor lattice QCD

ManuscriptWe determine the leptonic decay constants fDs and fD in three flavor unquenched lattice QCD. We use O(a2)-improved staggered light quarks and O(a)-improved charm quarks in the Fermilab heavy quark formalism. Our preliminary results, based upon an analysis at a single lattice spacing, are fDs = 263+5 −9 ± 24 MeV and fD = 225+11 −13 ± 21 MeV. In each case, the first reported error is statistical while the second is the combined systematic uncertainty

Charmonium mass splittings at the physical point

We present results from an ongoing study of mass splittings of the lowest lying states in the charmonium system. We use clover valence charm quarks in the Fermilab interpretation, an improved staggered (asqtad) action for sea quarks, and the one-loop, tadpole-improved gauge action for gluons. This study includes five lattice spacings, 0.15, 0.12, 0.09, 0.06, and 0.045 fm, with two sets of degenerate up- and down-quark masses for most spacings. We use an enlarged set of interpolation operators and a variational analysis that permits study of various low-lying excited states. The masses of the sea quarks and charm valence quark are adjusted to their physical values. This large set of gauge configurations allows us to extrapolate results to the continuum physical point and test the methodology.Comment: 7 pp, 6 figs, Lattice 201

Low lying charmonium states at the physical point

We present results for the mass splittings of low-lying charmonium states from a calculation with Wilson clover valence quarks with the Fermilab interpretation on an asqtad sea. We use five lattice spacings and two values of the light sea quark mass to extrapolate our results to the physical point. Sources of systematic uncertainty in our calculation are discussed and we compare our results for the 1S hyperfine splitting, the 1P-1S splitting and the P-wave spin orbit and tensor splittings to experiment.Comment: For the Fermilab Lattice and MILC Collaborations; 7 pages, 6 figures; Contribution to the 32nd International Symposium on Lattice Field Theory, 23-28 June, 2014, Columbia University New York, N

Modeling Approaches for Treatment Wetlands

Although treatment wetlands can reduce pollutant loads, reliably predicting their performance remains a challenge because removal processes are often complex, spatially heterogeneous, and incompletely understood. Although initially popular for characterizing wetland performance, plug flow reactor models are problematic because their parameters exhibit correlation with hydraulic loading. One-dimensional advective-dispersive-reactive (ADE) models are also inadequate because longitudinal dispersion in wetlands is often non-Fickian as a result of steep velocity gradients. Models that make use of residence time distributions have shown promise in improving performance characterization, particularly when interdependencies of stream-tube scale velocities and reaction rate coefficients are considered (the "DND" approach). However this approach is limited to steady-state conditions, and to an assumption that transverse mixing is nil. This dissertation investigates three aspects of wetland modeling and is organized in a journal paper format. The first paper describes development of a DND model which accommodates non-steady-state conditions. The model processes flow and inlet concentration time series, and calculates as output effluent concentration time series. A version of the code allows optimization of model parameters by minimization of summed squared deviations between predicted and measured effluent concentrations. In example comparisons, model results compare favorably with measured data. The second paper develops an analytical solution to a two-dimensional advective-dispersive-reactive equation, in which all flux terms are expressed as power functions of the transverse dimension. For uniform inlet concentration this idealized heterogeneity model is similar to a DND model, but with the inclusion of transverse diffusion. An example is used to illustrate the beneficial impact that transverse mixing has on reactor performance. The third paper describes development of a model based upon a stochastic interpretation of the ADE. The solution technique that is employed results in a bicontinuum model that for steady-state conditions becomes a weighted sum of two exponential decline functions. For low and intermediate degrees of mixing, model results nicely match those of the corresponding idealized heterogeneity model, and for high mixing they match results of the corresponding one-dimensional ADE. Comparisons against data suggest the bicontinuum model may represent wetland performance better than the DND model in some but not all cases

The Jew of Celsus and adversus Judaeos literature

Abstract:The appearance in Celsus’ work,This is the final version of the article. It first appeared from De Gruyter via https://doi.org/10.1515/zac-2017-001

Deep subsurface drip irrigation using coal-bed sodic water: Part II. Geochemistry

Waters with low salinity and high sodium adsorption ratios (SARs) present a challenge to irrigation because they degrade soil structure and infiltration capacity. In the Powder River Basin of Wyoming, such low salinity (electrical conductivity, EC 2.1 mS cm−1) and high-SAR (54) waters are co-produced with coal-bed methane and some are used for subsurface drip irrigation (SDI). The SDI system studied mixes sulfuric acid with irrigation water and applies water year-round via drip tubing buried 92 cm deep. After six years of irrigation, SAR values between 0 and 30 cm depth (0.5–1.2) are only slightly increased over non-irrigated soils (0.1–0.5). Only 8–15% of added Na has accumulated above the drip tubing. Sodicity has increased in soil surrounding the drip tubing, and geochemical simulations show that two pathways can generate sodic conditions. In soil between 45-cm depth and the drip tubing, Na from the irrigation water accumulates as evapotranspiration concentrates solutes. SAR values \u3e12, measured by 1:1 water–soil extracts, are caused by concentration of solutes by factors up to 13. Low-EC (\u3c0.7 mS cm−1) is caused by rain and snowmelt flushing the soil and displacing ions in soil solution. Soil below the drip tubing experiences lower solute concentration factors (1–1.65) due to excess irrigation water and also contains relatively abundant native gypsum (2.4 ± 1.7 wt.%). Geochemical simulations show gypsum dissolution decreases soil-water SAR to \u3c7 and increases the EC to around 4.1 mS cm−1, thus limiting negative impacts from sodicity. With sustained irrigation, however, downward flow of excess irrigation water depletes gypsum, increasing soil-water SAR to \u3e14 and decreasing EC in soil water to 3.2 mS cm−1. Increased sodicity in the subsurface, rather than the surface, indicates that deep SDI can be a viable means of irrigating with sodic waters

Deep subsurface drip irrigation using coal-bed sodic water: Part II. Geochemistry

Waters with low salinity and high sodium adsorption ratios (SARs) present a challenge to irrigation because they degrade soil structure and infiltration capacity. In the Powder River Basin of Wyoming, such low salinity (electrical conductivity, EC 2.1 mS cm−1) and high-SAR (54) waters are co-produced with coal-bed methane and some are used for subsurface drip irrigation (SDI). The SDI system studied mixes sulfuric acid with irrigation water and applies water year-round via drip tubing buried 92 cm deep. After six years of irrigation, SAR values between 0 and 30 cm depth (0.5–1.2) are only slightly increased over non-irrigated soils (0.1–0.5). Only 8–15% of added Na has accumulated above the drip tubing. Sodicity has increased in soil surrounding the drip tubing, and geochemical simulations show that two pathways can generate sodic conditions. In soil between 45-cm depth and the drip tubing, Na from the irrigation water accumulates as evapotranspiration concentrates solutes. SAR values \u3e12, measured by 1:1 water–soil extracts, are caused by concentration of solutes by factors up to 13. Low-EC (\u3c0.7 mS cm−1) is caused by rain and snowmelt flushing the soil and displacing ions in soil solution. Soil below the drip tubing experiences lower solute concentration factors (1–1.65) due to excess irrigation water and also contains relatively abundant native gypsum (2.4 ± 1.7 wt.%). Geochemical simulations show gypsum dissolution decreases soil-water SAR to \u3c7 and increases the EC to around 4.1 mS cm−1, thus limiting negative impacts from sodicity. With sustained irrigation, however, downward flow of excess irrigation water depletes gypsum, increasing soil-water SAR to \u3e14 and decreasing EC in soil water to 3.2 mS cm−1. Increased sodicity in the subsurface, rather than the surface, indicates that deep SDI can be a viable means of irrigating with sodic waters

Low-resolution spectrograph for the IOTA interferometer

The design and scientific objectives of a near infrared channeled spectrometer planned at the IOTA interferometer are discussed. The spectrometer has the flexibility to reconfigure easily for conventional broadband operations in addition to multi-channel mode. This instrument makes use of the existing PICNIC camera at the IOTA in order to be cost efficient. The spectrometer has been designed specifically for studying Mira stars. However, it will find its application in other areas of astrophysical interests such as studies of circumstellar disks around young stars and binary stars

Student Perceptions of a 21st Century Learning Space

Higher education institutions are increasingly building or remodeling classrooms to become flexible spaces that support learner-centered instruction. However, little is known about the actual impact of these spaces on student outcomes. Using a mixed method design, this study examined student perceptions of a flexible learning space on student learning and engagement compared to traditional classrooms. Students reported that the flexible space enhanced their learning experience by supporting classroom engagement. This study demonstrates the importance of incorporating student perceptions when planning learning spaces and suggests a need for further studies on the complex relationships among space, student learning and motivation.