Search

The incidence of breast cancer has been increasing in China and the age of breast cancer onset is earlier compared with Western countries. Compounds commonly used in Traditional Chinese Medicine (TCM) are an important source of anticancer drugs. Ginseng is one of the most common medicines used in TCM. Ginsenosides, which are saponins found in the ginseng plant, are the major active components responsible for the chemopreventive effects of ginseng in cancer. However, the mechanisms by which ginsenosides exert their anticancer effects remain elusive. The current study combined tandem mass tag (TMT)-based quantification with titanium dioxide-based phosphopeptide enrichment to quantitatively analyze the changes in phosphoproteomes in breast cancer MDA-MB-231 cells that occur following treatment with the ginsenoside Rg3. A total of 5,140 phosphorylation sites on 2,041 phosphoproteins were quantified and it was demonstrated that the phosphorylation status of 13 sites were altered in MDA-MB-231 cells following treatment with Rg3. The perturbed phosphoproteins were: Cleavage and polyadenylation specificity factor subunit 7, elongation factor 2 (EEF2), HIRA-interacting protein 3, melanoma-associated antigen D2, myosin phosphatase Rho-interacting protein, probable E3 ubiquitin-protein ligase MYCBP2, PRKC apoptosis WT1 regulator protein, protein phosphatase 1 regulatory subunit 12A, E3 SUMO-protein ligase RanBP2, Septin-9, thymopoietin, and E3 UFM1-protein ligase 1. Western blotting confirmed that Rg3 increased the phosphorylation of EEF2 on Thr57 but did not alter the protein expression of EEF2 in MDA-MB-231 and HCC1143 cells. These ginsenoside Rg3-regulated proteins are involved in various biological processes, including protein synthesis, cell division and the inhibition of nuclear factor-κB signaling. The results of the present study revealed that Rg3 exerts its anticancer effects via a combination of different signaling pathways.

The effect of Co doping on ceria-zirconia mixed oxides was investigated for Co0.1Ce0.6Zr0.3Ox sample prepared by sol-gel method. The Pd-only three-way catalyst (TWC) was obtained by incipient wetness impregnation with 0.5 wt.% Pd loading. The structural and oxygen handling properties were analyzed by X-ray diffraction (XRD), H2-temperature programmed reduction (H2-TPR) and the dynamic oxygen storage capacity (DOSC). The introduction of Co into ceria-zirconia lattice strongly modified the mobility of oxygen and enhanced the DOSC performance. Pd-only TWC based on the Co0.1Ce0.6Zr0.3Ox support exhibited superior activity for water-gas shift and steam reforming and amplified amplitude of stoichiometric window.

A diagnostic pressure equation is incorporated into a storm-scale three-dimensional variational data assimilation (3DVAR) system in the form of a weak constraint in addition to a mass continuity equation constraint (MCEC). The goal of this diagnostic pressure equation constraint (DPEC) is to couple different model variables to help build a more dynamic consistent analysis, and therefore improve the data assimilation results and subsequent forecasts. Observational System Simulation Experiments (OSSEs) are first performed to examine the impact of the pressure equation constraint on storm-scale radar data assimilation using an idealized tornadic thunderstorm simulation. The impact of MCEC is also investigated relative to that of DPEC. It is shown that DPEC can improve the data assimilation results slightly after a given period of data assimilation. Including both DPEC and MCEC yields the best data assimilation results. Sensitivity tests show that MCEC is not very sensitive to the choice of its weighting coefficients in the cost function, while DPEC is more sensitive and its weight should be carefully chosen. The updated 3DVAR system with DPEC is further applied to the 5 May 2007 Greensburg, Kansas, tornadic supercell storm case assimilating real radar data. It is shown that the use of DPEC can speed up the spinup of precipitation during the intermittent data assimilation process and also improve the follow-on forecast in terms of the general evolution of storm cells and mesocyclone rotation near the time of observed tornado.

FeOx-CeO2 mixed oxides with increasing Fe/(Ce+Fe) atomic ratio (1–20 mol%) were prepared by sol-gel method and characterized by X-ray powder diffraction (XRD), Brunauer-Emmett-Teller (BET) and Hydrogen temperature-programmed reduction (H2-TPR) techniques. The dynamic oxygen storage capacity (DOSC) was investigated by mass spectrometry with CO/O2 transient pulses. The powder XRD data following Rietveld refinement revealed that the solubility limit of iron oxides in the CeO2 was 5 mol% based on Fe/(Ce+Fe). The lattice parameters experienced a decrease followed by an increase due to the influence of the maximum solubility limit of iron oxides in the CeO2. TPR analysis revealed that Fe introduction into ceria strongly modified the textual and structural properties, which influenced the oxygen handling properties. DOSC results revealed that Ce-based materials containing Fe oxides with multiple valences contribute to the majority of DOSC. The kinetic analysis indicated that the calculated apparent kinetic parameters obey the compensation effect. The three-way catalytic performance for Pd-only catalysts based on the Fe doping support exhibited the redundant iron species separated out of the CeO2 and interacted with the ceria and Pd species on the surface, which seriously influenced the catalytic properties, especially after hydrothermal aging treatment.

The impact of assimilating radar reflectivity and radial velocity data with an intermittent, cycled three-dimensional variational assimilation (3DVAR) system is explored using an idealized thunderstorm case and a real data case on 8 May 2003. A new forward operator for radar reflectivity is developed that uses a background temperature field provided by a numerical weather prediction model for automatic hydrometeor classification. Three types of experiments are performed on both the idealized and real data cases. The first experiment uses radial velocity data only, the second experiment uses both radial velocity and reflectivity data without hydrometeor classification, and the final experiment uses both radial velocity and reflectivity data with hydrometeor classification. All experiments advance the analysis state to the next observation time using a numerical model prediction, which is then used as the background for the next analysis. Results from both the idealized and real data cases show that, assimilating only radial velocity data, the model can reconstruct the supercell thunderstorm after several cycles, but the development of precipitation is delayed because of the well-known spinup problem. The spinup problem is reduced dramatically when assimilating reflectivity without hydrometeor classification. The analyses are further improved using the new reflectivity formulation with hydrometeor classification. This study represents a successful first effort in variational convective-scale data assimilation to partition hydrometeors using a background temperature field from a numerical weather prediction model.

The NOAA Hazardous Weather Testbed (HWT) conducts annual spring forecasting experiments organized by the Storm Prediction Center and National Severe Storms Laboratory to test and evaluate emerging scientific concepts and technologies for improved analysis and prediction of hazardous mesoscale weather. A primary goal is to accelerate the transfer of promising new scientific concepts and tools from research to operations through the use of intensive real-time experimental forecasting and evaluation activities conducted during the spring and early summer convective storm period. The 2010 NOAA/HWT Spring Forecasting Experiment (SE2010), conducted 17 May through 18 June, had a broad focus, with emphases on heavy rainfall and aviation weather, through collaboration with the Hydrometeorological Prediction Center (HPC) and the Aviation Weather Center (AWC), respectively. In addition, using the computing resources of the National Institute for Computational Sciences at the University of Tennessee, the Center for A...

This study presents a 2-yr-long comparison of Weather Surveillance Radar-1988 Doppler (WSR-88D) refractivity retrievals with Oklahoma Mesonetwork (“Mesonet”) and sounding measurements and discusses some challenges to implementing radar refractivity operationally. Temporal and spatial analyses of radar refractivity exhibit high correlation with Mesonet data; however, periods of large refractivity differences between the radar and Mesonet are observed. Several sources of refractivity differences are examined to determine the cause of large refractivity differences. One source for nonklystron radars includes magnetron frequency drift, which can introduce errors up to 10 N-units if the frequency drift is not corrected. Different reference maps made at different times can “shift” refractivity values. A semiautomated method for producing reference maps is presented, including trade-offs for making reference maps under different conditions. Refractivity from six Mesonet stations within the clutter domain of the Oklahoma City, Oklahoma, WSR-88D (KTLX) is compared with radar refractivity retrievals. The analysis revealed that the six Mesonet stations exhibited a prominent diurnal trend in differences between radar and Mesonet refractivity measurements. The diurnal range of the refractivity differences sometimes exceeded 20 or 30 N-units in the warm season, which translated to a potential dewpoint temperature difference of several degrees Celsius. A seasonal analysis revealed that large refractivity differences primarily occurred during the warm season when refractivity is most sensitive to moisture. Ultimately, the main factor in determining the magnitude of the differences between the two refractivity platforms is the vertical gradient of refractivity because of the difference in observation height between the radar and a surface station.

The impact of radar and Oklahoma Mesonet data assimilation on the prediction of mesovortices in a tornadic mesoscale convective system (MCS) is examined. The radar data come from the operational Weather Surveillance Radar-1988 Doppler (WSR-88D) and the Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere’s (CASA) IP-1 radar network. The Advanced Regional Prediction System (ARPS) model is employed to perform high-resolution predictions of an MCS and the associated cyclonic line-end vortex that spawned several tornadoes in central Oklahoma on 8–9 May 2007, while the ARPS three-dimensional variational data assimilation (3DVAR) system in combination with a complex cloud analysis package is used for the data analysis. A set of data assimilation and prediction experiments are performed on a 400-m resolution grid nested inside a 2-km grid, to examine the impact of radar data on the prediction of meso-γ-scale vortices (mesovortices). An 80-min assimilation window is used in radar data assimilation experiments. An additional set of experiments examines the impact of assimilating 5-min data from the Oklahoma Mesonet in addition to the radar data. Qualitative comparison with observations shows highly accurate forecasts of mesovortices up to 80 min in advance of their genesis are obtained when the low-level shear in advance of the gust front is effectively analyzed. Accurate analysis of the low-level shear profile relies on assimilating high-resolution low-level wind information. The most accurate analysis (and resulting prediction) is obtained in experiments that assimilate low-level radial velocity data from the CASA radars. Assimilation of 5-min observations from the Oklahoma Mesonet has a substantial positive impact on the analysis and forecast when high-resolution low-level wind observations from CASA are absent; when the low-level CASA wind data are assimilated, the impact of Mesonet data is smaller. Experiments that do not assimilate low-level wind data from CASA radars are unable to accurately resolve the low-level shear profile and gust front structure, precluding accurate prediction of mesovortex development.

CoO x –CeO 2 mixed oxides with increasing Co/(Ce + Co) atomic ratio (1–20 mol%) are prepared by sol–gel method and characterized by means of by X-ray powder diffraction (XRD), Brunauer–Emmett–Teller (BET) and Hydrogen temperature-programmed reduction (H 2 -TPR) techniques. The dynamic oxygen storage capacity (DOSC) is investigated by mass spectrometry with CO/O 2 transient pulses. The powder XRD data following Rietveld refinement reveal that the solubility limit of cobalt oxides in the CeO 2 was 5 mol% based on Co/(Ce + Co). The lattice parameters have been observed to experience a decrease followed by an increase due to the influence of the maximum solubility limit of cobalt oxides in the CeO 2 . TPR analysis reveals that Co introduction into ceria strongly modifies the textual and structural properties, which influenced the oxygen handling properties. DOSC results reveal that Ce-based materials containing Co oxides with multiple valences contribute to the majority of DOSC. The kinetic analysis indicates that the calculated apparent kinetic parameters obey the compensation effect.

Probabilistic quantitative precipitation forecasts (PQPFs) from the storm-scale ensemble forecast system run by the Center for Analysis and Prediction of Storms during the spring of 2009 are evaluated using area under the relative operating characteristic curve (ROC area). ROC area, which measures discriminating ability, is examined for ensemble size n from 1 to 17 members and for spatial scales ranging from 4 to 200 km. Expectedly, incremental gains in skill decrease with increasing n. Significance tests comparing ROC areas for each n to those of the full 17-member ensemble revealed that more members are required to reach statistically indistinguishable PQPF skill relative to the full ensemble as forecast lead time increases and spatial scale decreases. These results appear to reflect the broadening of the forecast probability distribution function (PDF) of future atmospheric states associated with decreasing spatial scale and increasing forecast lead time. They also illustrate that efficient allocation of computing resources for convection-allowing ensembles requires careful consideration of spatial scale and forecast length desired.

The Advanced Regional Prediction System (ARPS) model is employed to perform high-resolution numerical simulations of a mesoscale convective system and associated cyclonic line-end vortex (LEV) that spawned several tornadoes in central Oklahoma on 8–9 May 2007. The simulation uses a 1000 km × 1000 km domain with 2-km horizontal grid spacing. The ARPS three-dimensional variational data assimilation (3DVAR) is used to assimilate a variety of data types. All experiments assimilate routine surface and upper-air observations as well as wind profiler and Oklahoma Mesonet data over a 1-h assimilation window. A subset of experiments assimilates radar data. Cloud and hydrometeor fields as well as in-cloud temperature are adjusted based on radar reflectivity data through the ARPS complex cloud analysis procedure. Radar data are assimilated from the Weather Surveillance Radar-1988 Doppler (WSR-88D) network as well as from the Engineering Research Center for Collaborative and Adaptive Sensing of the Atmosphere (CASA) network of four X-band Doppler radars. Three-hour forecasts are launched at the end of the assimilation window. The structure and evolution of the forecast MCS and LEV are markedly better throughout the forecast period in experiments in which radar data are assimilated. The assimilation of CASA radar data in addition to WSR-88D data increases the structural detail of the modeled squall line and MCS at the end of the assimilation window, which appears to yield a slightly better forecast track of the LEV.

The center for Analysis and Prediction of Storms (CAPS) has developed a radar data assimilation system. The system consists of several principal components: (1) a program that quality-controls and remaps (or super-ob) radar data to the analysis grid, (2) a Bratseth analysis method (ADAS), or a 3DVAR method for analyzing all the data except for clouds and precipitation, (3) a cloud and hydrometer analysis package that applies diabetic adjustments to the temperature field, and (4) a non-hydrostatic forecast model named ARPS. In this study, the system is applied to a small cyclone named OGNI, which formed over Bay of Bengal, India during the last week of October 2006. Three experiments are carried out to test the impact of the radar data from Chennai, India. These experiments include (1) using NCEP GFS data to initialize the ARPS model (2) using initial and boundary condition produced from the ADAS and the cloud analysis, (3) using initial and boundary condition produced from the 3DVAR and cloud analysis. The inter-comparison of results reveals that the experiment with the 3DVAR assimilation technique produces more realistic forecast to capture the genesis, structure, and northward movement of the cyclone in the short-range time scale.

The impacts of assimilating radar data and other mesoscale observations in real-time, convection-allowing model forecasts were evaluated during the spring seasons of 2008 and 2009 as part of the Hazardous Weather Test Bed Spring Experiment activities. In tests of a prototype continental U.S.-scale forecast system, focusing primarily on regions with active deep convection at the initial time, assimilation of these observations had a positive impact. Daily interrogation of output by teams of modelers, forecasters, and verification experts provided additional insights into the value-added characteristics of the unique assimilation forecasts. This evaluation revealed that the positive effects of the assimilation were greatest during the first 3–6 h of each forecast, appeared to be most pronounced with larger convective systems, and may have been related to a phase lag that sometimes developed when the convective-scale information was not assimilated. These preliminary results are currently being evaluated further using advanced objective verification techniques.

The radar ray path and beam broadening equations are important for assimilation of radar data into numerical weather prediction (NWP) models. They can be used to determine the physical location of each radar measurement and to properly map the atmospheric state variables from the model grid to the radar measurement space as part of the forward observation operators. Historically, different degrees of approximations have been made with these equations; however, no systematic evaluation of their impact exists, at least in the context of variational data assimilation. This study examines the effects of simplifying ray path and ray broadening calculations on the radar data assimilation in a 3D variational data assimilation (3DVAR) system. Several groups of Observational System Simulation Experiments (OSSEs) are performed to test the impact of these equations to radar data assimilation with an idealized tornadic thunderstorm case. This study shows that the errors caused by simplifications vary with the distance between the analyzed storm and the radar. For single time level wind analysis, as the surface range increases, the impact of beam broadening on analyzed wind field becomes evident and can cause relatively large error for distances beyond 150 km. The impact of the earth’s curvature is more significant, even for distances beyond 60 km, because it places the data at the wrong vertical location. The impact of refractive index gradient is also tested. It is shown that the variations of refractive index gradient have a very small impact on the wind analysis results. Two time series of 1-h-long data assimilation experiments are further conducted to illustrate the impact of the beam broadening and earth curvature on all retrieved model variables. It is shown that all model variables can be retrieved to some degrees in all data assimilation experiments. Similar to the wind analysis experiments, the impacts of both factors are not obvious when radars are relatively close to the storm. When the radars are far from the storm (especially beyond 150 km), overlooking beam broadening degrades the accuracy of assimilation results slightly, whereas ignoring the earth’s curvature leads to significant errors.

The assimilation of operational Doppler radar observations into convection-resolving numerical weather prediction models for very short-range forecasting represents a significant scientific and technological challenge. Numerical experiments over the past few years indicate that convective-scale forecasts are sensitive to the details of the data assimilation methodology, the quality of the radar data, the parameterized microphysics, and the storm environment. In this study, the importance of horizontal environmental variability to very short-range (0–1 h) convective-scale ensemble forecasts initialized using Doppler radar observations is investigated for the 4–5 May 2007 Greensburg, Kansas, tornadic thunderstorm event. Radar observations of reflectivity and radial velocity from the operational Doppler radar network at 0230 UTC 5 May 2007, during the time of the first large tornado, are assimilated into each ensemble member using a three-dimensional variational data assimilation system (3DVAR) developed at the Center for Analysis and Prediction of Storms (CAPS). Very short-range forecasts are made using the nonhydrostatic Advanced Regional Prediction System (ARPS) model from each ensemble member and the results are compared with the observations. Explicit three-dimensional environmental variability information is provided to the convective-scale ensemble using analyses from a 30-km mesoscale ensemble data assimilation system. Comparisons between convective-scale ensembles with initial conditions produced by 3DVAR using 1) background fields that are horizontally homogeneous but vertically inhomogeneous (i.e., have different vertical environmental profiles) and 2) background fields that are horizontally and vertically inhomogeneous are undertaken. Results show that the ensemble with horizontally and vertically inhomogeneous background fields provides improved predictions of thunderstorm structure, mesocyclone track, and low-level circulation track than the ensemble with horizontally homogeneous background fields. This suggests that knowledge of horizontal environmental variability is important to successful convective-scale ensemble predictions and needs to be included in real-data experiments.

Aim: The objective of this study is to disclose the association of polycythemia with lifestyle-related diseases (hypertension, obesity and glucose intolerance) among the three ethnicities in Qinghai, China. Methods: The subjects were 393 elderly people (247 Han, 97 Tibetan and 49 Mongolian) aged 60 years and more living in Qinghai (3000 m a.s.l.) in China. The associated factors with polycythemia were analyzed in the subjects. Excessive polycythemia was defined as hemoglobin concentration over 20 mg/dL. Results: Polycythemia was associated with men, hypoxemia, obesity and high diastolic blood pressure (DBP) in the elderly in Qinghai. Male sex was associated with polycythemia in all ethnicities. Obesity was associated with Han and Tibetan men. Glucose intolerance and activities of daily living were not directly associated with polycythemia after adjustment for sex. There were 7.9% with excessive polycythemia. Independently-associated factors for excessive polycythemia were male sex, body mass index of 25 or more, SpO2 of less than 85%, DBP of 85 mmHg or more and Han ethnicity (vs Tibetan) by multiple logistic regression. Conclusion: There was a close association of polycythemia with diastolic hypertension and obesity in lifestyle-related diseases in high-altitude elderly people. Han people had a higher hemoglobin concentration after adjustment of lifestyle-related diseases compared with Tibetan people. The difference of hemoglobin concentration may be due to Tibetans undergoing a much longer period of adaptation than Han people. Further study is needed to disclose the association between the difference of hypoxic adaptation, lifestyle-related diseases and chronic mountain sickness for their prevention.

The utility of the anelastic vertical vorticity equation in a weak-constraint (least squares error) variational dual-Doppler wind analysis procedure is explored. The analysis winds are obtained by minimizing a cost function accounting for the discrepancies between observed and analyzed radial winds, errors in the mass conservation equation, errors in the anelastic vertical vorticity equation, and spatial smoothness constraints. By using Taylor’s frozen-turbulence hypothesis to shift analysis winds to observation points, discrepancies between radially projected analysis winds and radial wind observations can be calculated at the actual times and locations the data are acquired. The frozen-turbulence hypothesis is also used to evaluate the local derivative term in the vorticity equation. Tests of the analysis procedure are performed with analytical pseudo-observations of an array of translating and temporally decaying counterrotating updrafts and downdrafts generated from a Beltrami flow solution of the Navier–Stokes equations. The experiments explore the value added to the analysis by the vorticity equation constraint in the common scenario of substantial missing low-level data (radial wind observations at heights beneath 1.5 km are withheld from the analysis). Experiments focus on the sensitivity of the most sensitive analysis variable—the vertical velocity component—to values of the weighting coefficients, volume scan period, number of volume scans, and errors in the estimated frozen-turbulence pattern-translation components. Although the vorticity equation constraint is found to add value to many of these analyses, the analysis can become significantly degraded if estimates of the pattern-translation components are largely in error or if the frozen-turbulence hypothesis itself breaks down. However, tests also suggest that these negative impacts can be mitigated if data are available in a rapid-scan mode.

A new multiple-Doppler radar analysis technique is presented for the objective detection and characterization of tornado-like vortices. The technique consists of fitting radial wind data from two or more radars to a simple analytical model of a vortex and its near-environment. The model combines a uniform flow, linear shear flow, linear divergence flow (all of which compose a broadscale flow), and a modified combined Rankine vortex (representing the tornado). The vortex and its environment are allowed to translate. The parameters in the low-order model are determined by minimizing a cost function that accounts for the discrepancy between the model and observed radial winds. Since vortex translation is taken into account, the cost function can be evaluated over time as well as space, and thus the observations can be used at the actual times and locations where they were acquired. The technique is first tested using analytically simulated observations whose wind field and error characteristics are systematically varied. An Advanced Regional Prediction System (ARPS) high-resolution numerical simulation of a supercell and associated tornado is then used to emulate an observation dataset. The method is tested with two virtual radars for several radar-sampling strategies. Finally, the technique is applied to a dataset of real dual-Doppler observations of a tornado that struck central Oklahoma on 8 May 2003. The method shows skill in retrieving the tornado path and radar-grid-scale features of the horizontal wind field in the vicinity of the tornado. The best results are obtained using a two-step procedure in which the broadscale flow is retrieved first.

In order to improve the ocean forecasting in the North Sea and Baltic Sea, an assimilation scheme based on a bottom-topography-dependent anisotropic recursive filter has been used in this study. This scheme can stretch or flatten the shape of a local representative contour surface of the background error covariance function into the form of an ellipse. Furthermore, the computing efficiency has been largely improved due to implicit computation of the background error covariance. A two-month experiment has been used for verifying the impact of assimilating ocean profile observations on ocean forecasting. The results indicate that the use of temperature and salinity profiles can largely improve the oceanic forecasting. The root mean square differences between the forecasts and observations for temperature and salinity have been reduced by 36% and 18% in the experiment period, respectively. Moreover, it is found that the anisotropic recursive filter approach is especially efficient in areas with complex coastlines and sharp fronts, e.g., inner Danish waters. The results also show that the propagation of observation information from an observation position to its neighboring grid points is closely related to currents.

In this study, the variation of radio refractivity with respect to temperature and moisture is analyzed. Also, the effects of vertical gradients in temperature and moisture on the propagation paths of electromagnetic waves of weather radar are examined for several sites across the United States using several years of sounding data from the National Weather Service. The ray path is important for identifying storm characteristics and for properly using the radar data in initializing numerical weather prediction models. It is found that during the warm season the radio refractivity gradient is more sensitive to moisture gradients than to temperature gradients. Ray paths from the commonly accepted vertical ray path model are compared to a ray path computed from a stepwise ray tracing algorithm using data from actual soundings. For the sample of about 16 000 soundings examined, we find that only a small fraction of the ray paths diverge significantly from those calculated using a ray path model based on the US Standard Atmosphere. While the problem of ray ducting in the presence of a temperature inversion is fairly well known, we identify the presence of a strong vertical moisture gradient as the culprit in the majority of the cases where significant deviations occurred.

A new efficient dual-resolution (DR) data assimilation algorithm is developed based on the ensemble Kalman filter (EnKF) method and tested using simulated radar radial velocity data for a supercell storm. Radar observations are assimilated on both high-resolution and lower-resolution grids using the EnKF algorithm with flow-dependent background error covariances estimated from the lower-resolution ensemble. It is shown that the flow-dependent and dynamically evolved background error covariances thus estimated are effective in producing quality analyses on the high-resolution grid. The DR method has the advantage of being able to significantly reduce the computational cost of the EnKF analysis. In the system, the lower-resolution ensemble provides the flow-dependent background error covariance, while the single-high-resolution forecast and analysis provides the benefit of higher resolution, which is important for resolving the internal structures of thunderstorms. The relative smoothness of the covariance obtained from the lower 4-km-resolution ensemble does not appear to significantly degrade the quality of analysis. This is because the cross covariance among different variables is of first-order importance for “retrieving” unobserved variables from the radar radial velocity data. For the DR analysis, an ensemble size of 40 appears to be a reasonable choice with the use of a 4-km horizontal resolution in the ensemble and a 1-km resolution in the high-resolution analysis. Several sensitivity tests show that the DR EnKF system is quite robust to different observation errors. A 4-km thinned data resolution is a compromise that is acceptable under the constraint of real-time applications. A data density of 8 km leads to a significant degradation in the analysis.

Summary In this paper, a new three-dimensional variational analysis scheme capable of retrieving three-dimensional winds from single Doppler observations of convective storms is developed. The method incorporates, in a single cost function, Doppler radar observations, a background field, smoothness and mass continuity constraints, and the residual of reflectivity or radial velocity conservation. By minimizing this cost function, an analysis with the desired fit to these constraints is obtained in a single procedure. In tests with both simulated and real thunderstorm cases, detailed structures of the storms are well retrieved in comparison with reference analysis. Unlike most kinematic retrieval methods, our scheme is capable of directly dealing with data voids. When an analysis background is available, say from a proximity sounding, a wind profiler, or a numerical model forecast, the method naturally blends Doppler radar observations with it. Thus, a smooth transition is obtained between data-rich and datavoid areas. These features, among others, are important if the analysis is to be used to initialize storm-scale numerical models or for diagnostic studies of storm structures.

The radar ray path equations are used to determine the physical location of each radar measurement. These equations are necessary for mapping radar data to computational grids for diagnosis, display and numerical weather prediction (NWP). They are also used to determine the forward operators for assimilation of radar data into forecast models. In this paper, a stepwise ray tracing method is developed. The influence of the atmospheric refractive index on the ray path equations at different locations related to an intense cold front is examined against the ray path derived from the new tracing method. It is shown that the radar ray path is not very sensitive to sharp vertical gradients of refractive index caused by the strong temperature inversion and large moisture gradient in this case. In the paper, the errors caused by using the simplified straight ray path equations are also examined. It is found that there will be significant errors in the physical location of radar measurements if the earth’s curvature is not considered, especially at lower elevation angles. A reduced form of the equation for beam height calculation is derived using Taylor series expansion. It is computationally more efficient and also avoids the need to use double precision variables to mitigate the small difference between two large terms in the original form. The accuracy of this reduced form is found to be sufficient for modeling use.

In this two-part paper, the impact of level-II Weather Surveillance Radar-1988 Doppler (WSR-88D) radar reflectivity and radial velocity data on the prediction of a cluster of tornadic thunderstorms in the Advanced Regional Prediction System (ARPS) model is studied. Radar reflectivity data are used primarily in a cloud analysis procedure that retrieves the amount of hydrometeors and adjusts in-cloud temperature, moisture, and cloud fields, while radial velocity data are analyzed through a three-dimensional variational (3DVAR) data assimilation scheme that contains a 3D mass divergence constraint in the cost function. In Part I, the impact of the cloud analysis and modifications to the scheme are discussed. In this part, the impact of radial velocity data and the mass divergence constraint in the 3DVAR cost function are studied. The case studied is that of the 28 March 2000 Fort Worth tornadoes. The addition of the radial velocity improves the forecasts beyond that experienced with the cloud analysis alone. The prediction is able to forecast the morphology of individual storm cells on the 3-km grid up to 2 h; the rotating supercell characteristics of the storm that spawned two tornadoes are well captured; timing errors in the forecast are less than 15 min and location errors are less than 10 km at the time of the tornadoes. When forecasts were made with radial velocity assimilation but not reflectivity, they failed to predict nearly all storm cells. Using the current 3DVAR and cloud analysis procedure with 10-min intermittent assimilation cycles, reflectivity data are found to have a greater positive impact than radial velocity. The use of radial velocity does improve the storm forecast when combined with reflectivity assimilation, by, for example, improving the forecasting of the strong low-level vorticity centers associated with the tornadoes. Positive effects of including a mass divergence constraint in the 3DVAR cost function are also documented.

A variational scheme for the analysis of scalar variables is developed and compared to two-pass and threepass versions of the Barnes analysis scheme. The variational scheme, appropriate for diagnostic studies, is similar to a previously developed variational method in that scalar gradient ‘‘observations’’—derived directly from the scalar observations—are used in addition to the scalar observations themselves. The current scheme is different in that the cost function does not require analyses of the scalar field and its gradient; it simply requires scalar and gradient observations at their native locations. For the evaluation, randomly selected model gridpoint data are chosen to serve as pseudo-observations for the analysis schemes. By choosing appropriate model gridpoint data to serve as pseudo-observations, artificial data networks can be generated so as to mimic the spatial characteristics of real observational networks. Results indicate that the proposed variational scheme is superior to both two-pass and three-pass Barnes schemes, increasingly so as the observations become more irregularly spaced. This is true even when the gradient information is not allowed to affect the variational analyses. When the observations are relatively sparse and irregularly distributed, further improvements in the variational analyses occur when the gradient information is properly included within the analysis scheme.

Velocity folding, or aliasing, is one of most significant impediments to the use of radial winds from Doppler weather radar. In this note, a variational algorithm is developed in which dealiasing is performed using wind gradient information. The key to the proposed method is that, by operating on gradients of velocity rather than on the velocity itself, aliasing ambiguities are readily identified and eliminated. The viability of the method is demonstrated by applying it to Weather Surveillance Radar-1988 Doppler (WSR-88D) observations from a winter-weather event and a tornadic supercell storm.

In this paper, a new method of dual-Doppler radar wind analysis based on a three-dimensional variational data assimilation (3DVAR) approach is proposed. In it, a cost function, including background term and radial observation term, is minimized through a limited memory, quasi-Newton conjugate-gradient algorithm with the mass continuity equation imposed as a weak constraint. In the method, the background error covariance matrix, though simple in this case, is modeled by a recursive filter. Furthermore, the square root of this matrix is used to precondition the minimization problem. The current method is applied to Doppler radar observation of a supercell storm, and the analysis results are compared to a conceptual model and previous research. It is shown that the horizontal circulations, both within and around the storms, as well as the strong updraft and the associated downdraft, are well analyzed. Because no explicit integration of the anelastic mass continuity equation is involved, error accumu...

An approximate (rapid scan) dynamical model for single-Doppler retrieval of the vector wind field is investigated. This approximate model is based on the Lagrangian form of the radial component of the equation of motion and is valid for retrieval time windows that are smaller than the effective timescale of the flow but larger than the product of the effective timescale and (nondimensional) relative error in the radial wind observations. The retrieval was tested with data gathered by two Doppler-on-Wheels mobile Doppler research radars of a cold front on 16 June 2000 near Grandfield, Oklahoma. Experiments focused on the impact of time resolution and the utility of a background constraint obtained from a volume velocity processing (VVP)-like estimate of the wind field. Retrieval error statistics were substantially improved as the volume scan intervals decreased from 5 min [characterizing the current Weather Surveillance Radar-1988 Doppler (WSR-88D) scan rates] down to 1 min. Use of the background constraint also improved the results, with superior results obtained in the high temporal resolution experiments when the background constraint was selectively imposed.

In this paper, we first describe the current status of the Advanced Regional Prediction System of the Center for Analysis and Prediction of Storms at the University of Oklahoma. A brief outline of future plans is also given. Two rather successful cases of explicit prediction of tornadic thunderstorms are then presented. In the first case, a series of supercell storms that produced a historical number of tornadoes was successfully predicted more than 8 hours in advance, to within tens of kilometers in space with initiation timing errors of less than 2 hours. The general behavior and evolution of the predicted thunderstorms agree very well with radar observations. In the second case, reflectivity and radial velocity observations from Doppler radars were assimilated into the model at 15-minute intervals. The ensuing forecast, covering a period of several hours, accurately reproduced the intensification and evolution of a tornadic supercell that in reality spawned two tornadoes over a major metropolitan area. These results make us optimistic that a model system such as the ARPS will be able to deterministically predict future severe convective events with significant lead time. The paper also includes a brief description of a new 3DVAR system developed in the ARPS framework. The goal is to combine several steps of Doppler radar retrieval with the analysis of other data types into a single 3-D variational framework and later to incorporate the ARPS adjoint to establish a true 4DVAR data assimilation system that is suitable for directly assimilating a wide variety of observations for flows ranging from synoptic down to the small nonhydrostatic scales.

To analyze the relationship between the expression level of Ki67 and clinicopathological features in breast cancer.Data of 918 female patients with invasive ductal breast carcinoma treated in the Cancer Hospital, Chinese Academy of Medical Sciences from Jan. to Dec. 2010 were analyzed retrospectively. The correlation of Ki67 expression and other clinicopathological features in the breast cancer was analyzed.Among the 918 cases, the Ki67 index was 0.9% to 95% (mean value 27.8%). Taking the Ki67 index 14% as the boundary to divide the patients into two subgroups, 263 cases (28.6%) were ≤ 14%, and 655 cases (71.4%) were14%. There were significant differences between the Ki67 expression and age, tumor size, axillary lymph nodes status, histological grade and the expressions of C-erbB-2, estrogen receptor (ER) and progesterone receptor (PR) (P0.05 for all). All the Ki67 indexes of Ki67 expression in luminal B (30.44%), HER-2 overexpression (36.77%) and triple negative (47.40%) subtypes were significantly higher than that in the luminal A subtype (21.36%)(P0.01). The expression level of Ki67 in triple-negative subtype (47.40%) was significantly higher than that in the non-triple-negative subtype (24.79%)(P0.001).Ki67 index is significantly correlated with the age, tumor TNM stage, axillary lymph node status, histological grading, ER status, PR status and HER-2 status. A high expression level of Ki67 is a poor prognostic factor for breast cancer. The expression level of Ki67 should be detected routinely and it may become a useful prognostic marker in the treatment of breast cancer.

In this paper, the original simple adjoint method of Qiu and Xu is improved and tested for retrieving the 3D storm-scale wind field from single-Doppler radar data. The method incorporates single-radar data and background fields, along with a dynamical constraint, smoothness, and anelastic mass continuity constraint, in a cost function. The minimization of the cost function, with the desired fit to these constraints, is obtained in an iterative procedure. The current method is tested on simulated datasets of supercell storms. It is shown that the circulation inside and around the storms, including the strong updraft and associated downdraft, are well retrieved. Furthermore, the method is robust in the presence of data error.

Four-dimensional variational data assimilation (4D-Var) seeks to find an optimal initial field that minimizes a cost function defined as the squared distance between model solutions and observations within an assimilation window. For a perfect linear model, Lorenc showed that the 4D-Var forecast at the end of the window coincides with a Kalman filter analysis if two conditions are fulfilled: (a) addition to the cost function of a term that measures the distance to the background at the beginning of the assimilation window, and (b) use of the Kalman filter background error covariance in this term. The standard 4D-Var requires minimization algorithms along with adjoint models to compute gradient information needed for the minimization. In this study, an alternative method is suggested based on the use of the quasi-inverse model that, for certain applications, may help accelerate the solution of problems close to 4D-Var. The quasi-inverse approach for the forecast sensitivity problem is introduced, and then a closely related variational assimilation problem using the quasi-inverse model is formulated (i.e., the model is integrated backward but changing the sign of the dissipation terms). It is shown that if the cost function has no background term, and has a complete set of observations (as assumed in many classical 4D-Var papers), the new method solves the 4D-Var-minimization problem efficiently, and is in fact equivalent to the Newton algorithm but without having to compute a Hessian. If the background term is included but computed at the end of the interval, allowing the use of observations that are not complete, the minimization can still be carried out very efficiently. In this case, however, the method is much closer to a 3D-Var formulation in which the analysis is attained through a model integration. For this reason, the method is called ‘‘inverse 3D-Var’’ (I3D-Var). The I3D-Var method was applied to simple models (viscous Burgers’ equation and Lorenz model), and it was found that when the background term is ignored and complete fields of noisy observations are available at multiple times, the inverse 3D-Var method minimizes the same cost function as 4D-Var but converges much faster. Tests with the Advanced Regional Prediction System (ARPS) indicate that I3D-Var is about twice as fast as the adjoint Newton method and many times faster than the quasi-Newton LBFGS algorithm, which uses the adjoint model. Potential problems (including the growth of random errors during the integration back in time) and possible applications to preconditioning, and to problems such as storm-scale data assimilation and reanalysis are also discussed.

This paper proposes a new method of dual-Doppler radar analysis based on a variational approach. In it, a cost function, defined as the distance between the analysis and the observations at the data points, is minimized through a limited memory, quasi-Newton conjugate gradient algorithm with the mass continuity equation imposed as a weak constraint. The analysis is performed in Cartesian space. Compared with traditional methods, the variational method offers much more flexibility in its use of observational data and various constraints. Using the radar data directly at observation locations avoids an interpolation step, which is often a source of error, especially in the presence of data voids. In addition, using the mass continuity equation as a weak instead of strong constraint avoids the error accumulation and the subsequent somewhat arbitrary adjustment associated with the explicit vertical integration of the continuity equation. The current method is tested on both model-simulated and observed datasets of supercell storms. It is shown that the circulation inside and around the storms, including the strong updraft and associated downdraft, is well analyzed in both cases. Furthermore, the authors found that the analysis is not very sensitive to the specification of boundary conditions and to data contamination. The method also has the potential for retrieving, with reasonable accuracy, the wind in regions of single-Doppler radar coverage.

Generalized adjoint with modified discretization and generalized coarse-grain adjoint are derived for a vector system of equations that contains parameterized on/off switches. With vector examples, it is shown that the conventional adjoint minimization may have a convergence problem in multidimensional space. The problem can be solved by the generalized adjoint with modified discretization or by the generalized coarse-grain adjoint without modifying the traditional discretization in the forward model.

A two-dimensional viscous semigeostrophic model is developed to study the evolution of the baroclinic Eady wave and fronts with two types (free-slip and nonslip) of boundary conditions. With the free-slip boundary condition, the solution is very similar to the inviscid one but the frontal collapse is prevented by the diffusive effect. When the fronts become sharp in the mature stage, strong horizontal diffusions of momentum and potential temperature cause strong inward fluxes of geostrophic potential vorticity (GPV) at the surface fronts, so high GPV anomalies are generated at the surface fronts and advected into the interior, forming two backward-tilted plumes along the upper and lower fronts. The wave and front development can be interpreted by the interaction between the lower- and upper-level GPV anomalies in terms of GPV thinking similarly to that in the inviscid case. When the boundary condition is nonslip, the initial growth and subsequent nonlinear evolution of the solution are significan...

When on/off switches are triggered at discrete time levels by a threshold condition in a traditionally discretized model, the model solution is not continuously dependent on the initial state and this causes problems in tangent linearization and adjoint computations. It is shown in this paper that the problems can be avoided by introducing coarse-grain tangent linearization and adjoint without modifying the traditional discretization, although the coarse-grain gradient check can be performed only for finite perturbations.

MicroRNA (miRNA) 200s regulate E-cadherin by directly targeting ZEB1/ZEB2, which are transcriptional repressors of E-cadherin. Decreased expression of E-cadherin results in cancer cells losing interaction with the extracellular matrix and detaching from the primary tumor. Normally, cells will undergo anoikis after losing interaction with the extracellular matrix. Cancer cells must, therefore, possess the ability to resist anoikis during the process of metastasis. Here we show that miRNA-200b regulates anoikis by directly targeting the 3′ UTR of Pin1 mRNA and regulating Pin1 expression at the translational level. We found that down-regulation of miRNA-200b promotes cancer cells survival during metastasis, and the homeless state of these cells resulted in decreased expression of miRNA-200b in the MCF-7 cell line. We also found that expression of miRNA-200b is down-regulated in human breast cancer during lymph node metastasis, which has a significant negative correlation with Pin1 expression. Two members of the ETS (E-26) family (PEA3 and ELK-1) regulate the expression of miRNA-200b. PEA3 promotes the expression of miRNA-200b, and ELK-1 is a transcriptional repressor of miRNA-200b. In addition, miRNA-200b regulates the activity of PEA3 and ELK-1 via the Pin1-pERK pathway and forms self-regulated feedback loops. This study characterizes the role of miRNA-200b in the regulation of anoikis and demonstrates the regulation of its own expression in the process of metastasis.

A three-dimensional variational (3DVAR) assimilation technique developed for a convective-scale NWP model—advanced regional prediction system (ARPS)—is used to analyze the 8 May 2003, Moore/Midwest City, Oklahoma tornadic supercell thunderstorm. Previous studies on this case used only one or two radars that are very close to this storm. However, three other radars observed the upper-level part of the storm. Because these three radars are located far away from the targeted storm, they were overlooked by previous studies. High-frequency intermittent 3DVAR analyses are performed using the data from five radars that together provide a more complete picture of this storm. The analyses capture a well-defined mesocyclone in the midlevels and the wind circulation associated with a hook-shaped echo. The analyses produced through this technique are used as initial conditions for a 40-minute storm-scale forecast. The impact of multiple radars on a short-term NWP forecast is most evident when compared to forecasts using data from only one and two radars. The use of all radars provides the best forecast in which a strong low-level mesocyclone develops and tracks in close proximity to the actual tornado damage path.

e13089Background: Even obesity has been accused to predispose to breast cancer worldwide, there are still some inconsistencies regarding the association between obesity and breast cancer. As BMI (b...

With increasing stringent automobile exhaust emission regulations for diesel vehicles advanced emission control systems may require SCR catalysts with substantially improved thermal durability. Zirconia–Titania–Ceria–Tungsten (ZrTiCeW) mixed oxides were evaluated in the selective catalytic reduction of nitrogen oxides (NOx) by ammonia (NH3-SCR). The hydrothermal aging and sulfur aging were performed under severe conditions. They were compared with a commercial V/W/Ti SCR catalyst treated in the same manner. ZrTiCeW exhibits the superior NOx conversion performance and higher selectivity. The influence of space velocity, NOx/NH3 and NO/NO2 on the NOx conversion were investigated. The presence of NO2 in the feed (NO2/NO = 50/450) boosts the NO conversion in the low temperature range.

Components in NOx storage reduction (NSR) catalysts have been studied in order to identify their impact on NSR performance. In order to enhance the catalytic performance of the NSR catalyst, the hydrothermal stability and sulfur tolerance of the NSR catalyst were improved by developing new NSR formula. The results show that Pt/BaO/Ce0.7Zr0.3O2 + Rh/Al2O3 catalyst has superior NSR activity, thermal stability and sulfur tolerance. The influence of space velocity, oxygen concentration and Lean-Rich period on the NSR activity was investigated.

Urban air pollution caused by vehicle exhaust already became a great public concern. Among the vehicle pollutants, diesel combustion PM (particulate matter) was deeply explored by some health and scientific institutes and proved toxic even carcinogenic. An urban bus was tested on road with a real-time aerosol instrument to measure its PM emission. The result shows that PM emitted by the bus mainly range from 0 to 1.5µm. Particles smaller than 300nm take up nearly 90 percent of the total number emission, while ones of 300nm-1.5µm take up more than four fifths of the total mass emission. Particulate emission rate during acceleration stages is 5-6 times more in number and 10 times more in mass than that generated during steady cruise. Aggressive acceleration processes at velocity of about 30km/h will cause the most serious particulate emission, with number concentration as high as 1.0E8/cm3. It was also found that the PM number and mass emission coefficients of the tested bus are respectively 2.72E14#/km and 0.468g/km, which is more than 2 times of that limited by the emission regulation.

Background: Although there are several factors which may contribute to oxidative stress at high altitude, little is known about the association between oxidative stress and aging in the community-dwelling elderly in the Tibetan Plateau. Methods: Reactive oxygen species (ROS) and comprehensive geriatric functions were examined among 235 community-dwelling elderly subjects aged 60 years or more (146 Hans and 89 Tibetans). As a marker of ROS, the levels of reactive oxygen metabolites (ROM) were measured using the d-ROM test. Results: The rate of dependence of basic activities of daily living (basic ADL) among Tibetan elderly highlanders was significantly higher than that among Han elderly highlanders. The d-ROM level was higher among the Tibetan elderly than those among the Han elderly (Tibetan 465.6 ± 97.9 Carr U, Han 415.3 ± 72.0 Carr U, P = 0.003). The ROM level was higher among women than those among men. Stepwise multiple regression analysis showed that being Tibetan, female, and oxygen saturation were independent predictors of increasing d-ROM level (Tibetan β, 0.241; female β, 0.206; oxygen saturation β, 0.218). The high levels of ROM (d-ROM >500 Carr U) were significantly associated with dependence of basic ADL after adjustment for age, sex and ethnicity (odds ratio = 2.51, P = 0.028). Conclusion: The findings of this study imply the possibility that ROS is higher among Tibetan elderly highlanders than that of Han, which related to the geriatric items. Further studies are needed to show the impact of oxidative stress on the aging of highlanders.

To reveal the comparison of comprehensive geriatric functions of elderly highlanders in Qinghai Plateau in China among three different ethnic groups.Activities of daily living (ADL), screening-based depression, quality of life (QOL) and checking-up of metabolic syndrome including community-based oral glucose tolerance test were assessed in 393 community-dwelling elderly subjects aged 60 years or more (247 Han elderly subjects, 49 Mongolian ones and 97 Tibetan ones).Tibetan elderly highlanders were more disabled in ADL, but had higher QOL than Han elderly ones in Qinghai Plateau. Blood pressure measurements, rate of hypertension and hemoglobin concentrations in Tibetan elderly highlanders were lower than Han ones. Rates of diabetes and impaired glucose tolerance in elderly highlanders were relatively lower than other Asian elderly lowlanders.Prevalence of metabolic syndrome in elderly highlanders in Qinghai was still not high, however, we should pay attention to its tendency related with socialglobalism in the near future. Further investigation on physiological adaptability to hypoxic environment and human ageing phenomena in a global context may open a new research frontier for ageing science.

Aim: To examine the association between food diversity and health status of Han and Tibetan elderly highlanders in Qinghai Plateau, China. Methods: The study population consisted of 240 community-dwelling elderly subjects aged 60 years or more (176 Han elderly subjects, 64 Tibetan ones). Food diversity was determined using an 11-item Food Diversity Score Kyoto (FDSK-11). Subjects were interviewed on health status including activities of daily living (ADL), screening-based depression and quality of life (QOL). Blood chemical investigation was carried out in association with food diversity. Results: ADL was significantly lower in both Han and Tibetan elderly with lower food diversity than those with higher diversity. In Han elderly with lower food diversity, QOL was significantly lower in the items of subjective sense of health, relationship with family and subjective happiness, but not significant in Tibetan elderly. A close association was found between lower food diversity and lower financial satisfaction in both Han and Tibetan subjects. No association was found between food diversity and age or body mass index. Higher food diversity was associated with lower blood glucose level in Han elderly subjects, but the opposite association was found in Tibetan ones. Conclusion: Food diversity was associated with ADL and QOL in highlanders in Qinghai, China. Food assessment is very important as a useful indicator to establish the actual condition of diet and its relation to health status of community-dwelling elderly as well as the change of economic background in the Qinghai highlands.