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This report provides models for predicting composition-properties for tellurite glasses, namely specific gravity and glass transition temperature. Included are the partial specific coefficients for each model, the component validity ranges, and model fit parameters.
In anticipation of new observational results for Jupiter's axial moment of inertia and gravitational zonal harmonic coefficients from the forthcoming Juno orbiter, we present a number of preliminary Jupiter interior models. We combine results from ab initio computer simulations of hydrogen–helium mixtures, including immiscibility calculations, with a new nonperturbative calculation of Jupiter's zonal harmonic coefficients, to derive a self-consistent model for the planet's external gravity and moment of inertia. We assume helium rain modified the interior temperature and composition profiles. Our calculation predicts zonal harmonic values to which measurements can be compared. Although some models fit the observed (pre-Juno) second- and fourth-order zonal harmonics to within their error bars, our preferred reference model predicts a fourth-order zonal harmonic whose absolute value lies above the pre-Juno error bars. This model has a dense core of about 12 Earth masses and a hydrogen–helium-rich envelope with approximately three times solar metallicity.
We present a catalog of uniformly determined stellar properties and abundances for 1,617 F, G, and K stars using an automated spectral synthesis modeling procedure. All stars were observed using the HIRES spectrograph at Keck Observatory. Our procedure used a single line list to fit model spectra to observations of all stars to determine effective temperature, surface gravity, metallicity, projected rotational velocity, and the abundances of 15 elements (C, N, O, Na, Mg, Al, Si, Ca, Ti, V, Cr, Mn, Fe, Ni, and Y). Sixty percent of the sample had Hipparcos parallaxes and V-band photometry, which we combined with the spectroscopic results to obtain mass, radius, and luminosity. Additionally, we used the luminosity, effective temperature, metallicity and α-element enhancement to interpolate in the Yonsei–Yale isochrones to derive mass, radius, gravity, and age ranges for those stars. Finally, we determined new relations between effective temperature and macroturbulence for dwarfs and subgiants. Our analysis achieved precisions of 25 K in T{sub eff}, 0.01 dex in [M/H], 0.028 dex for logg, and 0.5 km s{sup −1} in vsin i based on multiple observations of the same stars. The abundance results were similarly precise, between ∼0.01 and ∼0.04 dex, though trends with respect to T{sub eff} remained for which we derived empirical corrections. The trends, though small, were much larger than our uncertainties and are shared with published abundances. We show that changing our model atmosphere grid accounts for most of the trend in [M/H] between 5000 and 5500 K, indicating a possible problem with the atmosphere models or opacities.
This paper presents an in-depth look at the jet and coronal properties of 41 active galactic nuclei (AGNs). Utilizing the highest quality NuSTAR, XMM-Newton, and NRAO VLA Sky Survey 1.4 GHz data, we find that the radio Eddington luminosity inversely scales with X-ray reflection fraction, and positively scales with the distance between the corona and the reflected regions in the disk. We next investigate a model fit to the data that predicts the corona is outflowing and propagates into the large-scale jet. We find this model describes the data well and predicts that the corona has mildly relativistic velocities, 0.04<β<0.40. We discuss our results in the context of disk–jet connections in AGNs.
RXJ 1301.9+2747 is an optically identified very-low-mass AGN candidate with M{sub BH}∼1×10{sup 6} M{sub ⊙}, which shows extremely soft X-ray emission and unusual X-ray variability in the form of short-lived flares. We present an analysis of multiwavelength observations of RXJ 1301.9+2747 in order to study the properties of the active nucleus and its host galaxy. The UV-to-X-ray spectrum in the quiescent state can be well and self-consistently described by a thermal and a Comptonized emission from the accretion disk, with the black body dominating ∼70% of the X-rays in the 0.2–2 keV. The same model can describe the X-ray spectrum in the flare state, but the Comptonized component becomes dominant (∼80%). The best fit implies an Eddington ratio of ∼0.14 and a black-hole mass of (1.7−2.8)×10{sup 6} M {sub ⊙}, in agreement with the estimation from the optical data within errors. However, the best-fitting model under predicts the optical flux for the HST point source by a factor of ∼2. The excess of nuclear optical emission could be attributed to a nuclear stellar cluster, which is frequently seen in low-mass AGNs. The X-ray to optical spectral slope (α{sub ox}) is lower than in most other active galaxies, which may be attributed to intrinsically X-ray weakness due to very little hot and optically thin coronal emission. We performed a pilot search for weak or hidden broad emission lines using optical spectropolarimetry observations, but no polarized broad lines are detected. The host galaxy appears to be a disk galaxy with a boxy pseudobulge or nuclear bar accounting for ∼15% of the total starlight, which is consistent with the general characteristics of the host of low-mass AGNs.
Pore-resolved direct numerical simulations are performed to investigate the interactions between streamflow turbulence and groundwater flow through a randomly packed porous sediment bed for three permeability Reynolds numbers, Re K = 2.56 , 5.17 and 8.94, representative of natural stream or river systems. Time–space averaging is used to quantify the Reynolds stress, form-induced stress, mean flow and shear penetration depths, and mixing length at the sediment–water interface (SWI). Here, the mean flow and shear penetration depths increase with Re K and are found to be nonlinear functions of non-dimensional permeability. The peaks and significant values of the Reynolds stresses, form-induced stresses, and pressure variations are shown to occur in the top layer of the bed, which is also confirmed by conducting simulations of just the top layer as roughness elements over an impermeable wall. The probability distribution functions (p.d.f.s) of normalized local bed stress are found to collapse for all Reynolds numbers, and their root-mean-square fluctuations are assumed to follow logarithmic correlations. The fluctuations in local bed stress and resultant drag and lift forces on sediment grains are mainly a result of the top layer; their p.d.f.s are symmetric with heavy tails, and can be well represented by a non-Gaussian model fit. The bed stress statistics and the pressure data at the SWI potentially can be used in providing better boundary conditions in modelling of incipient motion and reach-scale transport in the hyporheic zone.
Mitigation of failure modes in the continuous synthesis (CS) of a drug substance (DS) has the potential to widen the adoption of continuous manufacturing (CM) technologies by the pharmaceutical industry. Here, this work demonstrates the development of a robust continuous process for the synthesis of carbamazepine (CBZ), an essential medicine as per the World Health Organization (WHO), facilitated by kinetic modelling and monitored by in-line Raman spectroscopy. Accurate kinetic modelling and the use of validated process analytical technology (PAT) models for quantitative measurement were found to play an important role in developing CS of drug substances. Kinetic data for the formation of CBZ from iminostilbene (ISB) were collected by batch reaction sampling and high-performance liquid chromatography (HPLC) analysis. A non-linear solver and iterative method was applied to determine two sets of Arrhenius parameters simultaneously for the reaction system by minimizing the standard error of the model fit. The start-up and dynamic equilibrium stages for the CS of CBZ using a continuous stirred tank reactor (CSTR) were modelled based on the batch kinetic data and employed to optimize conversion and simulate process disturbances. An in-line Raman spectroscopy method was successfully developed, validated, and integrated to determine the concentrations of CBZ and ISB within the operating range for the CS. The CS kinetic model was evaluated experimentally from startup to dynamic equilibrium over 10 residence times with monitoring by HPLC and in-line Raman spectroscopy. The developed kinetic model in tandem with in-line Raman spectroscopy successfully predicted disturbances due to changes in process variables and can serve as a useful tool in the future design of advanced process control strategies for the continuous synthesis of CBZ.
In this study, we analyze three-dimensional particle-laden, isotropic turbulence to develop an understanding of inertial particle dynamics from a kinetic energy perspective. Data trends implying inhomogeneous sampling of the flow by particles are identified and used to support a proposed particle behavior: particles appear to accumulate in regions of low flow kinetic energy over time because they lose kinetic energy and slow down in such regions, ultimately causing them to spend more time there. To elucidate this behavior, we derive a particle kinetic energy equation from the particle momentum equation, which incorporates inertial effects through the Schiller–Naumann drag correlation. Upon extracting fundamental physics from this equation, hypotheses regarding the role of the Stokes number in the temporal change of particle kinetic energy and the previously proposed particle behavior are evaluated using simulation data considering three Stokes numbers. Finally, a Fokker–Planck equation is used to derive the steady-state probability density function of the particle kinetic energy. The model fits the simulation data well and provides a tool for further investigation into understanding preferential concentration, as well as a reduced order model for predicting particle kinetic energy in turbulent flows.
Purpose: One of the most critical steps in radiation therapy treatment is accurate tumor and critical organ-at-risk (OAR) contouring. Both manual and automated contouring processes are prone to errors and to a large degree of inter- and intraobserver variability. These are often due to the limitations of imaging techniques in visualizing human anatomy as well as to inherent anatomical variability among individuals. Physicians/physicists have to reverify all the radiation therapy contours of every patient before using them for treatment planning, which is tedious, laborious, and still not an error-free process. In this study, the authors developed a general strategy based on novel geometric attribute distribution (GAD) models to automatically detect radiation therapy OAR contouring errors and facilitate the current clinical workflow. Methods: Considering the radiation therapy structures’ geometric attributes (centroid, volume, and shape), the spatial relationship of neighboring structures, as well as anatomical similarity of individual contours among patients, the authors established GAD models to characterize the interstructural centroid and volume variations, and the intrastructural shape variations of each individual structure. The GAD models are scalable and deformable, and constrained by their respective principal attribute variations calculated from training sets with verified OAR contours. A new iterative weighted GAD model-fitting algorithm was developed for contouring error detection. Receiver operating characteristic (ROC) analysis was employed in a unique way to optimize the model parameters to satisfy clinical requirements. A total of forty-four head-and-neck patient cases, each of which includes nine critical OAR contours, were utilized to demonstrate the proposed strategy. Twenty-nine out of these forty-four patient cases were utilized to train the inter- and intrastructural GAD models. These training data and the remaining fifteen testing data sets were separately employed to test the effectiveness of the proposed contouring error detection strategy. Results: An evaluation tool was implemented to illustrate how the proposed strategy automatically detects the radiation therapy contouring errors for a given patient and provides 3D graphical visualization of error detection results as well. The contouring error detection results were achieved with an average sensitivity of 0.954/0.906 and an average specificity of 0.901/0.909 on the centroid/volume related contouring errors of all the tested samples. As for the detection results on structural shape related contouring errors, an average sensitivity of 0.816 and an average specificity of 0.94 on all the tested samples were obtained. The promising results indicated the feasibility of the proposed strategy for the detection of contouring errors with low false detection rate. Conclusions: The proposed strategy can reliably identify contouring errors based upon inter- and intrastructural constraints derived from clinically approved contours. It holds great potential for improving the radiation therapy workflow. ROC and box plot analyses allow for analytically tuning of the system parameters to satisfy clinical requirements. Future work will focus on the improvement of strategy reliability by utilizing more training sets and additional geometric attribute constraints.
WISE J085510.83–071442.5 (hereafter WISE 0855–0714) is the coldest known brown dwarf (∼250 K) and the fourth-closest known system to the Sun (2.2 pc). It has been previously detected only in the J band and two mid-IR bands. To better measure its spectral energy distribution (SED), we have performed deep imaging of WISE 0855–0714 in six optical and near-IR bands with Gemini Observatory, the Very Large Telescope, and the Hubble Space Telescope . Five of the bands show detections, although one detection is marginal (S/N ∼ 3). We also have obtained two epochs of images with the Spitzer Space Telescope for use in refining the parallax of the brown dwarf. By combining astrometry from this work and previous studies, we have derived a parallax of 0.449 ± 0.008″ (2.23 ± 0.04 pc). We have compared our photometry for WISE 0855–0714 to data for known Y dwarfs and to the predictions of three suites of models by Saumon et al. and Morley et al. that are defined by the presence or absence of clouds and nonequilibrium chemistry. Our estimates of Y − J and J − H for WISE 0855–0714 are redder than colors of other Y dwarfs, confirming a predicted reversal of near-IR colors to redder values at temperatures below 300–400 K. In color–magnitude diagrams, no single suite of models provides a clearly superior match to the sequence formed by WISE 0855–0714 and other Y dwarfs. Instead, the best-fitting model changes from one diagram to the next. Similarly, all of the models have substantial differences from the SED of WISE 0855–0714. As a result, we are currently unable to constrain the presence of clouds or nonequilibrium chemistry in its atmosphere.
The filamentary network of intergalactic medium (IGM) gas that gives origin to the Lyα forest in the spectra of distant quasars encodes information on the physics of structure formation and the early thermodynamics of diffuse baryonic material. Here we use a massive suite of more than 400 high-resolution cosmological hydrodynamical simulations run with the Graphics Processing Unit–accelerated code Cholla to study the IGM at high spatial resolution maintained over the entire computational volume. The simulations capture a wide range of possible IGM thermal histories by varying the photoheating and photoionizing background produced by star-forming galaxies and active galactic nuclei. A statistical comparison of synthetic spectra with the observed 1D flux power spectra of hydrogen at redshifts 2.2 ≤ z ≤ 5.0 and with the helium Lyα opacity at redshifts 2.4 < z < 2.9 tightly constrains the photoionization and photoheating history of the IGM. By leveraging the constraining power of the available Lyα forest data to break model degeneracies, we find that the IGM experienced two main reheating events over 1.2 Gyr of cosmic time. For our best-fit model, hydrogen reionization completes by z R ≈ 6.0 with a first IGM temperature peak of T 0 ≃ 1.3 × 10 4 K and is followed by the reionization of He ii that completes by z R ≈ 3.0 and yields a second temperature peak of T 0 ≃ 1.4 × 10 4 K. We discuss how our results can be used to obtain information on the timing and the sources of hydrogen and helium reionization.
Atomic coordinate models are important for the interpretation of 3D maps produced with cryoEM and cryoET (3D electron microscopy; 3DEM). In addition to visual inspection of such maps and models, quantitative metrics can inform about the reliability of the atomic coordinates, in particular how well the model is supported by the experimentally determined 3DEM map. A recently introduced metric, Q-score, was shown to correlate well with the reported resolution of the map for well fitted models. Here, we present new statistical analyses of Q-score based on its application to ∼10 000 maps and models archived in the EMDB (Electron Microscopy Data Bank) and PDB (Protein Data Bank). Further, we introduce two new metrics based on Q-score to represent each map and model relative to all entries in the EMDB and those with similar resolution. We explore through illustrative examples of proteins, nucleic acids and small molecules how Q-scores can indicate whether the atomic coordinates are well fitted to 3DEM maps and also whether some parts of a map may be poorly resolved due to factors such as molecular flexibility, radiation damage and/or conformational heterogeneity. These examples and statistical analyses provide a basis for how Q-scores can be interpreted effectively in order to evaluate 3DEM maps and atomic coordinate models prior to publication and archiving.
Gross ecosystem productivity (GEP) in tropical forests varies both with the environment and with biotic changes in photosynthetic infrastructure, but our understanding of the relative effects of these factors across timescales is limited. Here, we used a statistical model to partition the variability of seven years of eddy covariance-derived GEP in a central Amazon evergreen forest into two main causes: variation in environmental drivers (solar radiation, diffuse light fraction, and vapor pressure deficit) that interact with model parameters that govern photosynthesis and biotic variation in canopy photosynthetic light-use efficiency associated with changes in the parameters themselves. Our fitted model was able to explain most of the variability in GEP at hourly (R 2 = 0.77) to interannual (R 2 = 0.80) timescales. At hourly timescales, we found that 75% of observed GEP variability could be attributed to environmental variability. When aggregating GEP to the longer timescales (daily, monthly, and yearly), however, environmental variation explained progressively less GEP variability: At monthly timescales, it explained only 3%, much less than biotic variation in canopy photosynthetic light-use efficiency, which accounted for 63%. These results challenge modeling approaches that assume GEP is primarily controlled by the environment at both short and long timescales. Our approach distinguishing biotic from environmental variability can help to resolve debates about environmental limitations to tropical forest photosynthesis. For example, we found that biotically regulated canopy photosynthetic light-use efficiency (associated with leaf phenology) increased with sunlight during dry seasons (consistent with light but not water limitation of canopy development) but that realized GEP was nonetheless lower relative to its potential efficiency during dry than wet seasons (consistent with water limitation of photosynthesis in given assemblages of leaves). Lastly, this work highlights the importance of accounting for differential regulation of GEP at different timescales and of identifying the underlying feedbacks and adaptive mechanisms.
The survey of the mid-infrared sky by the Wide-field Infrared Survey Explorer ( WISE ) led to the discovery of extremely cold, low-mass brown dwarfs, classified as Y dwarfs, which extend the T class to lower temperatures. Twenty-four Y dwarfs are known at the time of writing. Here we present improved parallaxes for four of these, determined using Spitzer images. We give new photometry for four late-type T and three Y dwarfs and new spectra of three Y dwarfs, obtained at Gemini Observatory. We also present previously unpublished photometry taken from HST , ESO, Spitzer , and WISE archives of 11 late-type T and 9 Y dwarfs. The near-infrared data are put onto the same photometric system, forming a homogeneous data set for the coolest brown dwarfs. We compare recent models to our photometric and spectroscopic data set. We confirm that nonequilibrium atmospheric chemistry is important for these objects. Nonequilibrium cloud-free models reproduce well the near-infrared spectra and mid-infrared photometry for the warmer Y dwarfs with 425 ≤ T {sub eff} (K) ≤ 450. A small amount of cloud cover may improve the model fits in the near-infrared for the Y dwarfs with 325 ≤ T {sub eff} (K) ≤ 375. Neither cloudy nor cloud-free models reproduce the near-infrared photometry for the T {sub eff} = 250 K Y dwarf W0855. We use the mid-infrared region, where most of the flux originates, to constrain our models of W0855. We find that W0855 likely has a mass of 1.5–8 Jupiter masses and an age of 0.3–6 Gyr. The Y dwarfs with measured parallaxes are within 20 pc of the Sun and have tangential velocities typical of the thin disk. The metallicities and ages we derive for the sample are generally solar-like. We estimate that the known Y dwarfs are 3 to 20 Jupiter-mass objects with ages of 0.6–8.5 Gyr.
An integrated nondestructive assay (NDA) system combining active (neutron generator) and passive neutron detection and passive gamma (PG) detection is being analyzed in order to estimate the amount of plutonium, verify initial enrichment, burnup, and cooling time, and detect partial defects in a spent fuel assembly (SFA). Active signals are measured using the differential die-away (DDA), delayed neutron (DN), and delayed gamma (DG) techniques. Passive signals are measured using total neutron (TN) counts and both gross and spectral resolved gamma counts. To quantify how a system of several NDA techniques is expected to perform, all of the relevant NDA techniques listed above were simulated as a function of various reactor conditions such as initial enrichment, burnup, cooling time, assembly shuffling pattern, reactor operating conditions (including temperature, pressure, and the presence of burnable poisons) by simulating the NDA response for five sets of light water reactor assemblies. In this study, we compare the performance of several exploratory model-fitting options (including neural networks, adaptive regression with splines, iterative bias reduction smoothing, projection pursuit regression, and regression with quadratic terms and interaction terms) to relate data simulated with measurement and model error effects from various subsets of the NDA techniques to the total Pu mass. Isotope masses for SFAs and expected detector responses (DRs) for several NDA techniques are simulated using MCNP, and the DRs become inputs to the fitting process. Such responses include eight signals from DDA, one from DN, one from TN, and up to seven from PG; the DG signal will be examined separately. Results are summarized using the root-mean-squared estimation error for plutonium mass in held-out subsets of the data for a range of model and measurement error variances. Different simulation assumptions lead to different spent fuel libraries relating DRs to Pu mass. Some results for training with one library and testing with another library are also given.
The B cell response to influenza infection of the respiratory tract contributes to viral clearance and establishes profound resistance to reinfection by related viruses. Numerous studies have measured virus-specific antibody-secreting cell (ASC) frequencies in different anatomical compartments after influenza infection and provided a general picture of the kinetics of ASC formation and dispersion. However, the dynamics of ASC populations are difficult to determine experimentally and have received little attention. Here, we applied mathematical modeling to investigate the dynamics of ASC growth, death, and migration over the 2-week period following primary influenza infection in mice. Experimental data for model fitting came from high frequency measurements of virus-specific IgM, IgG, and IgA ASCs in the mediastinal lymph node (MLN), spleen, and lung. Model construction was based on a set of assumptions about ASC gain and loss from the sampled sites, and also on the directionality of ASC trafficking pathways. Most notably, modeling results suggest that differences in ASC fate and trafficking patterns reflect the site of formation and the expressed antibody class. Essentially all early IgA ASCs in the MLN migrated to spleen or lung, whereas cell death was likely the major reason for IgM and IgG ASC loss from the MLN. In contrast, the spleen contributed most of the IgM and IgG ASCs that migrated to the lung, but essentially none of the IgA ASCs. This finding points to a critical role for regional lymph nodes such as the MLN in the rapid generation of IgA ASCs that seed the lung. Results for the MLN also suggest that ASC death is a significant early feature of the B cell response. Overall, our analysis is consistent with accepted concepts in many regards, but it also indicates novel features of the B cell response to influenza that warrant further investigation.
We have imaged GM Aurigae with the Hubble Space Telescope , detected its disk in scattered light at 1400 and 1650 Å, and compared these with observations at 3300 Å, 5550 Å, 1.1 μ m, and 1.6 μ m. The scattered light increases at shorter wavelengths. The radial surface brightness profile at 3300 Å shows no evidence of the 24 au radius cavity that has been previously observed in submillimeter observations. Comparison with dust grain opacity models indicates that the surface of the entire disk is populated with submicron grains. We have compiled a spectral energy distribution from 0.1 μ m to 1 mm and used it to constrain a model of the star + disk system that includes the submillimeter cavity using the Monte Carlo radiative transfer code by Barbara Whitney. The best-fit model image indicates that the cavity should be detectable in the F330W bandpass if the cavity has been cleared of both large and small dust grains, but we do not detect it. The lack of an observed cavity can be explained by the presence of submicron grains interior to the submillimeter cavity wall. We suggest one explanation for this that could be due to a planet of mass <9 M {sub J} interior to 24 au. A unique cylindrical structure is detected in the far-UV data from the Advanced Camera for Surveys/Solar Blind Channel. It is aligned along the system semiminor axis, but does not resemble an accretion-driven jet. The structure is limb brightened and extends 190 ± 35 au above the disk midplane. The inner radius of the limb brightening is 40 ± 10 au, just beyond the submillimeter cavity wall.
Notice on corrigendum: This paper has a corresponding corrigendum published. Please read the corrigendum first. Old-growth forests are subject to substantial changes in structure and species composition due to the intensification of human activities, gradual climate change and extreme weather events. Trees store ca. 90 % of the total aboveground biomass (AGB) in tropical forests and precise tree biomass estimation models are crucial for management and conservation. In the central Amazon, predicting AGB at large spatial scales is a challenging task due to the heterogeneity of successional stages, high tree species diversity and inherent variations in tree allometry and architecture. We parameterized generic AGB estimation models applicable across species and a wide range of structural and compositional variation related to species sorting into height layers as well as frequent natural disturbances. We used 727 trees (diameter at breast height ≥ 5 cm) from 101 genera and at least 135 species harvested in a contiguous forest near Manaus, Brazil. Sampling from this data set we assembled six scenarios designed to span existing gradients in floristic composition and size distribution in order to select models that best predict AGB at the landscape level across successional gradients. We found that good individual tree model fits do not necessarily translate into reliable predictions of AGB at the landscape level. When predicting AGB (dry mass) over scenarios using our different models and an available pantropical model, we observed systematic biases ranging from -31 % (pantropical) to +39 %, with root-mean-square error (RMSE) values of up to 130 Mg ha -1 (pantropical). Our first and second best models had both low mean biases (0.8 and 3.9 %, respectively) and RMSE (9.4 and 18.6 Mg ha -1 ) when applied over scenarios. Predicting biomass correctly at the landscape level in hyperdiverse and structurally complex tropical forests, especially allowing good performance at the margins of data availability for model construction/calibration, requires the inclusion of predictors that express inherent variations in species architecture. The model of interest should comprise the floristic composition and size-distribution variability of the target forest, implying that even generic global or pantropical biomass estimation models can lead to strong biases. Reliable biomass assessments for the Amazon basin (i.e., secondary forests) still depend on the collection of allometric data at the local/regional scale and forest inventories including species-specific attributes, which are often unavailable or estimated imprecisely in most regions.