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Investigation of goodness of model data fit using PLSR and PCR regression models to determine informative wavelength band in NIR region for non-invasive blood glucose prediction

Diabetes mellitus is a metabolic disorder characterized by the deficiency in insulin secretion or insulin action on target tissues. Diabetes being diagnosed, requires frequent monitoring. Current measurement techniques are invasive in nature, which is painful. Non-invasive measurement methods for the prediction of blood glucose is a big challenge. Hence this paper focuses on a comparative study to analyze the performance of the two regression models: partial least square regression (PLSR) and principal component regression (PCR) models to arrive at the best regression model for the prediction of blood glucose non-invasively based on NIR diffuse reflectance spectroscopy. The regression model developed involves spectral data collected from 32 subjects from a diabetic center using diffuse reflectance spectrometer (DRS). The spectroscopic data were acquired from the subjects both invasively using clinical method and non-invasively using DRS setup in the NIR spectral range whose wavelength ranges from 750 to 1040 nm. Multivariate analysis using PLSR is found to be a better regression model in terms of the fitted response and estimated mean square prediction error. It is observed that the mean square error value is 0.04 mg/dl for the tenth component in the PLSR model. The developed regression model also proves to be a useful tool in identifying the informative wavelength bands for blood glucose measurement.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

An intermediate model for fitting triplet–triplet annihilation in phosphorescent organic light emitting diode materials

Triplet–triplet annihilation (TTA) is one of the primary contributors to efficiency roll-off and permanent material degradation in phosphorescent organic light-emitting diodes. Here, the two limiting case models typically used to quantify this quenching mechanism are multi-step Dexter and single-step Förster, which, respectively, assume ideal Fickian diffusion or perfect trapping of triplet excitons. For device-relevant guest doping levels (typically 5–12 vol. %), both significant diffusion of excitons and trapping due to spatial and energetic disorder exist, so neither conventional model fits experimental data well. We develop and validate an intermediate TTA model, which is a weighted average of the limiting cases of pure radiative decay (no TTA) and multi-step Dexter based TTA that returns an effective TTA rate constant and a parameter quantifying the portion of well-isolated excitons. Kinetic Monte-Carlo simulations and time-resolved photoluminescence measurements of an archetype host–guest system demonstrate that our intermediate model provides significantly improved fits with more realistic physical values, is more robust to variations in experimental conditions, and provides an analysis framework for the effects of trapping on TTA.

30 DIRECT ENERGY CONVERSION↗

THE HERSCHEL ORION PROTOSTAR SURVEY: SPECTRAL ENERGY DISTRIBUTIONS AND FITS USING A GRID OF PROTOSTELLAR MODELS

We present key results from the Herschel Orion Protostar Survey: spectral energy distributions (SEDs) and model fits of 330 young stellar objects, predominantly protostars, in the Orion molecular clouds. This is the largest sample of protostars studied in a single, nearby star formation complex. With near-infrared photometry from 2MASS, mid- and far-infrared data from Spitzer and Herschel , and submillimeter photometry from APEX, our SEDs cover 1.2–870 μ m and sample the peak of the protostellar envelope emission at ∼100 μ m. Using mid-IR spectral indices and bolometric temperatures, we classify our sample into 92 Class 0 protostars, 125 Class I protostars, 102 flat-spectrum sources, and 11 Class II pre-main-sequence stars. We implement a simple protostellar model (including a disk in an infalling envelope with outflow cavities) to generate a grid of 30,400 model SEDs and use it to determine the best-fit model parameters for each protostar. We argue that far-IR data are essential for accurate constraints on protostellar envelope properties. We find that most protostars, and in particular the flat-spectrum sources, are well fit. The median envelope density and median inclination angle decrease from Class 0 to Class I to flat-spectrum protostars, despite the broad range in best-fit parameters in each of the three categories. We also discuss degeneracies in our model parameters. Our results confirm that the different protostellar classes generally correspond to an evolutionary sequence with a decreasing envelope infall rate, but the inclination angle also plays a role in the appearance, and thus interpretation, of the SEDs.

79 ASTRONOMY AND ASTROPHYSICS↗

AI-Batt (Autonomous Identification of Battery Life Models) [SWR 21-36]

Autonomous Identification of Battery Life Models (AI-Batt) AI-Batt is a MATLAB code base for developing lifetime models for batteries from accelerated aging data. The code base provides many functions for processing, visualizing, and modeling battery aging data, making the data processing, exploration, and modeling workflow substantially faster. These tools are tailored for working with battery aging data sets, which usually consist of many separate time-series for each cell, with many test conditions and possible replicates at each condition, which makes it difficult to simply process or visualize the data set. Complex modeling tasks, such as cross-validation, sensitivity analysis, and uncertainty quantification have been implemented to enable thorough statistical investigation of model predictions. Additionally, several machine-learning algorithms are implemented to autonomously identify suitable models via symbolic regression. Data processing functions automatically cast data from the struct data type, which is commonly used to store experimental data, but is not an acceptable input for most algorithms, to the table data type, which can be easily used as input to any optimization algorithm. Also, the data can be separated into time-invariant and time-variant data tables, which is helpful for exploring the data set as well as developing separate models for time-variant and time-invariant aging mechanisms. For example, in aging tests with constant temperature, temperature is a time-invariant experimental condition. Visualization tools enable plotting of data, model fits, and model simulations possible with single-line function calls, empowering data exploration of complex data sets with both time-varying and time-invariant trends. Plots can be automatically generated for the whole data set, or separated by data group (groups of test replicates) or individual data series. Data points or data series can be automatically colored by the value of a variable with a variety of color maps, and model predictions can also be colored by the value of a fit statistic. Comparisons between data sets and the predictions/simulations of different models on the same data set can be easily plotted as well. Distributions of parameter values from bootstrap resampling can be plotted to visualize the reliability of parameter estimation, or determine any correlations between parameters. Modeling tools handle the complex task of creating and parsing symbolic equations for modeling battery lifetime. Equations are parsed to grab relevant data variables, parameter values, or specified sub-models for input into optimization, evaluation, or simulation functions. Models can be optimized locally (one set of parameters for each data series), bi-level (some parameters shared across the data set), or globally (single set of parameters for all data). Functions implementing symbolic regression algorithms help users to discover effective model equations, even in poorly sampled, high-dimensional data.

Smith, Kandler↗

Guiding Principles for Geochemical/Thermodynamic Model Development and Validation in Nuclear Waste Disposal: A Close Examination of Recent Thermodynamic Models for H + —Nd 3+ —NO 3 - (—Oxalate) Systems

Development of a defensible source-term model (STM), usually a thermodynamical model for radionuclide solubility calculations, is critical to a performance assessment (PA) of a geologic repository for nuclear waste disposal. Such a model is generally subjected to rigorous regulatory scrutiny. In this article, we highlight key guiding principles for STM model development and validation in nuclear waste management. We illustrate these principles by closely examining three recently developed thermodynamic models with the Pitzer formulism for aqueous H + —Nd 3+ —NO 3 - (—oxalate) systems in a reverse alphabetical order of the authors: the XW model developed by Xiong and Wang, the OWC model developed by Oakes et al., and the GLC model developed by Guignot et al., among which the XW model deals with trace activity coefficients for Nd(III), while the OWC and GLC models are for concentrated Nd(NO 3 ) 3 electrolyte solutions. The principles highlighted include the following: (1) Principle 1. Validation against independent experimental data: A model should be validated against experimental data or field observations that have not been used in the original model parameterization. We tested the XW model against multiple independent experimental data sets including electromotive force (EMF), solubility, water vapor, and water activity measurements. The results show that the XW model is accurate and valid for its intended use for predicting trace activity coefficients and therefore Nd solubility in repository environments. (2) Principle 2. Testing for relevant and sensitive variables: Solution pH is such a variable for an STM and easily acquirable. All three models are checked for their ability to predict pH conditions in Nd(NO 3 ) 3 electrolyte solutions. The OWC model fails to provide a reasonable estimate for solution pH conditions, thus casting serious doubt on its validity for a source-term calculation. In contrast, both the XW and GLC models predict close-to-neutral pH values, in agreement with experimental measurements. (3) Principle 3. Honoring physical constraints: Upon close examination, it is found that the Nd(III)-NO 3 association schema in the OWC model suffers from two shortcomings. Firstly, its second stepwise stability constant for Nd(NO 3 ) 2+ (log K 2 ) is much higher than the first stepwise stability constant for NdNO 3 2+ (log K 1 ), thus violating the general rule of (log K 2 –log K 1 ) < 0, or $\frac{K1}{K2}$>1. Secondly, the OWC model predicts abnormally high activity coefficients for Nd(NO 3 ) 2 + (up to ~900) as the concentration increases. (4) Principle 4. Minimizing degrees of freedom for model fitting: The OWC model with nine fitted parameters is compared with the GLC model with five fitted parameters, as both models apply to the concentrated region for Nd(NO 3 ) 3 electrolyte solutions. The latter appears superior to the former because the latter can fit osmotic coefficient data equally well with fewer model parameters. The work presented here thus illustrates the salient points of geochemical model development, selection, and validation in nuclear waste management.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

GADRAS-DRF Validation for Safeguards and Custom Peak Fit Enhancements

In previous years, SGTech funded enhancements to the isotopics routine in the software called Gamma Detector Response and Analysis Software-Detector Response Function (GADRAS-DRF), including the addition of peak fit customization capabilities. A project was also funded that focused on implementing a peak-based model fitting routine, allowing model fitting to be performed without dependence on export-controlled cross-sections. In FY25 significant improvements were made to the custom peak fitting interface, accompanied by several validation studies within GADRAS-DRF. These studies encompassed IsotopeID performance, distributed source analysis, isotopics validation, and activity estimation. Additionally, the peak-only model fitting option was validated using an HPGe measurement of a rotating drum with line sources.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

SU-F-T-685: Evaluation of Tumor Hypoxic Fraction Using Serial Volumetric Imaging During Radiation Therapy

Purpose: To develop a tumor response model which could be uses to compute tumor hypoxic fraction using serial volumetric tumor imaging. This algorithm may be used for treatment response assessment and also for guidance of more expensive PET imaging of hypoxia. Methods: Previously developed two-level cell population tumor response model was modified to include a third cell level describing hypoxic and necrotic cells. This third level was considered constant value during radiotherapy treatment; therefore, inclusion additional parameter did not compromise stability of model fitting to imaging data. Fitting the model to serial volumetric imaging data was performed using a least squares objective function and simulated annealing algorithm. The problem of reconstruction of radiobiological parameters from serial imaging data was considered as inverse ill-posed problem described by the Fredholm integral equation of the first kind. Variational regularization was used to stabilize solutions. Results: To evaluate performance of the algorithm, we used a set of serial CT imaging data on tumor-volume for 14 head and neck cancer patients. The hypoxic fractions were reconstructed for each patient and the distribution of hypoxic fractions was compared to the distribution of initial hypoxic fractions previously measured using histograph. The measured and reconstructed from imaging data distributions of hypoxic fractions are in good agreement. The reconstructed distribution of cell surviving fraction was also in better agreement with in vitro data than previously obtained using the two-level cell population model. Conclusion: Our results indicate that it is possible to evaluate the initial hypoxic tumor fraction using serial volumetric imaging and a tumor response model. This algorithm can be used for treatment response assessment and guidance of more expensive PET imaging.

60 APPLIED LIFE SCIENCES↗

MAJOR-MERGER GALAXY PAIRS AT Z = 0: DUST PROPERTIES AND COMPANION MORPHOLOGY

We present an analysis of dust properties of a sample of close major-merger galaxy pairs selected by K {sub s} magnitude and redshift. The pairs represent the two populations of spiral–spiral (S+S) and mixed morphology spiral–elliptical (S+E). The Code Investigating GALaxy Emission software is used to fit dust models to the Two Micron All Sky Survey, Wide-Field Infrared Survey Explorer , and Herschel flux density measurements, and to derive the parameters describing the polycyclic aromatic hydrocarbons contribution, interstellar radiation field, and photodissociation regions. Model fits verify our previous Spitzer Space Telescope analysis that S+S and S+E pairs do not have the same level of enhancement of star formation and differ in dust composition. The spirals of mixed-morphology galaxy pairs do not exhibit the enhancements in interstellar radiation field and therefore dust temperature for spirals in S+S pairs in contrast to what would be expected according to standard models of gas redistribution due to encounter torques. This suggests the importance of the companion environment/morphology in determining the dust properties of a spiral galaxy in a close major-merger pair.

79 ASTRONOMY AND ASTROPHYSICS↗

Measuring and predicting sooting tendencies of oxygenates, alkanes, alkenes, cycloalkanes, and aromatics on a unified scale

Databases of sooting indices, based on measuring some aspect of sooting behavior in a standardized combustion environment, are useful in providing information on the comparative sooting tendencies of different fuels or pure compounds. However, newer biofuels have varied chemical structures including both aromatic and oxygenated functional groups, which expands the chemical space of relevant compounds. In this work, we propose a unified sooting tendency database for pure compounds, including both regular and oxygenated hydrocarbons, which is based on combining two disparate databases of yield-based sooting tendency measurements in the literature. Unification of the different databases was made possible by leveraging the greater dynamic range of the color ratio pyrometry soot diagnostic. This unified database contains a substantial number of pure compounds (≥ 400 total) from multiple categories of hydrocarbons important in modern fuels and establishes the sooting tendencies of aromatic and oxygenated hydrocarbons on the same numeric scale for the first time. Then, using this unified sooting tendency database, we have developed a predictive model for sooting behavior applicable to a broad range of hydrocarbons and oxygenated hydrocarbons. The model decomposes each compound into single-carbon fragments and assigns a sooting tendency contribution to each fragment based on regression against the unified database. The model’s predictive accuracy (as demonstrated by leave-one-out cross-validation) is comparable to a previously developed, more detailed predictive model. The fitted model provides insight into the effects of chemical structure on soot formation, and cases where its predictions fail reveal the presence of more complicated kinetic sooting mechanisms. Our work will therefore enable the rational design of low-sooting fuel blends from a wide range of feedstocks and chemical functionalities.

09 BIOMASS FUELS↗

Herschel extreme lensing line observations: Dynamics of two strongly lensed star-forming galaxies near redshift z = 2

We report on two regularly rotating galaxies at redshift z ≈ 2, using high-resolution spectra of the bright [C II] 158 μm emission line from the HIFI instrument on the Herschel Space Observatory. Both SDSS090122.37+181432.3 ({sup S}0901{sup )} and SDSSJ120602.09+514229.5 ({sup t}he Clone{sup )} are strongly lensed and show the double-horned line profile that is typical of rotating gas disks. Using a parametric disk model to fit the emission line profiles, we find that S0901 has a rotation speed of vsin (i) ≈ 120 ± 7 km s{sup –1} and a gas velocity dispersion of σ {sub g} < 23 km s{sup –1} (1σ). The best-fitting model for the Clone is a rotationally supported disk having vsin (i) ≈ 79 ± 11 km s{sup –1} and σ {sub g} ≲ 4 km s{sup –1} (1σ). However, the Clone is also consistent with a family of dispersion-dominated models having σ {sub g} = 92 ± 20 km s{sup –1}. Our results showcase the potential of the [C II] line as a kinematic probe of high-redshift galaxy dynamics: [C II] is bright, accessible to heterodyne receivers with exquisite velocity resolution, and traces dense star-forming interstellar gas. Future [C II] line observations with ALMA would offer the further advantage of spatial resolution, allowing a clearer separation between rotation and velocity dispersion.

79 ASTRONOMY AND ASTROPHYSICS↗

NEOWISE: OBSERVATIONS OF THE IRREGULAR SATELLITES OF JUPITER AND SATURN

We present thermal model fits for 11 Jovian and 3 Saturnian irregular satellites based on measurements from the WISE/NEOWISE data set. Our fits confirm spacecraft-measured diameters for the objects with in situ observations (Himalia and Phoebe) and provide diameters and albedo for 12 previously unmeasured objects, 10 Jovian and 2 Saturnian irregular satellites. The best-fit thermal model beaming parameters are comparable to what is observed for other small bodies in the outer solar system, while the visible, W1, and W2 albedos trace the taxonomic classifications previously established in the literature. Reflectance properties for the irregular satellites measured are similar to the Jovian Trojan and Hilda Populations, implying common origins.

79 ASTRONOMY AND ASTROPHYSICS↗

Efficient lattice QCD computation of radiative-leptonic-decay form factors at multiple positive and negative photon virtualities

In previous work [D. Giusti, Methods for high-precision determinations of radiative-leptonic decay form factors using lattice QCD, Phys. Rev. D 107, 074507 (2023)], we showed that form factors for radiative leptonic decays of pseudoscalar mesons can be determined efficiently and with high precision from lattice QCD using the “three-dimensional (3D) method,” in which three-point functions are computed for all values of the current insertion time and the time integral is performed at the data-analysis stage. Here, we demonstrate another benefit of the 3D method: the form factors can be extracted for any number of nonzero photon virtualities from the same three-point functions at no extra cost. We present results for the $D_s → ℓνγ*$ vector form factor as a function of photon energy and photon virtuality, for both positive and negative virtuality, for a single ensemble with 340 MeV pion mass and 0.11 fm lattice spacing. In our analysis, we separately consider the two different time orderings and the different quark flavors in the electromagnetic current. We discuss in detail the behavior of the unwanted exponentials contributing to the three-point functions, as well as the choice of fit models and fit ranges used to remove them for various values of the virtuality. While positive photon virtuality is relevant for decays to multiple charged leptons, negative photon virtuality suppresses soft contributions and is of interest in QCD-factorization studies of the form factors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Constitutive model fingerprints in medium-amplitude oscillatory shear

Rheologists have expectations for signatures of linear viscoelastic properties, such as shapes of G'(ω) and G"(ω). Medium amplitude (or asymptotically-nonlinear) oscillatory shear (MAOS) provides additional nonlinear rheological information with low dimensional, well-defined material functions. Here, we develop expectations of signatures (or fingerprints) for the four asymptotically-nonlinear material functions associated with MAOS, [e 1 ](ω), [e 3 ](ω), [v 1 ](ω), [v 3 ](ω). Although the linear fingerprints may be identical for different models, the asymptotically-nonlinear fingerprints may be different in magnitude, frequency-scaling, curve shapes, and sign changes. To perform the analysis, we collect/translate a library of available analytical strain-controlled MAOS fingerprints for seven different constitutive models. Using this library, we identify general trends and highlight key differences of asymptotic-nonlinear viscoelasticity. Asymptotic nonlinearities for all models considered here obey the terminal regime inter-relations and frequency scaling predicted by Bharadwaj and Ewoldt. Unlike the positive linear viscoelastic measures, at least one of the four asymptotic nonlinearities changes signs with Deborah number (De). Following sign interpretations of Ewoldt and Bharadwaj, we show that nonlinearities tend to be driven by strain-rates at small De, and by strains at large De, a trend observed for nearly all the constitutive models studied here, the exception being the model for dilute rigid dumbbell suspensions. Some constitutive models exhibit multiple sign changes at intermediate De and there may be no universal behavior of asymptotically-nonlinear fingerprints in this regime. Therefore, frequency-dependent signatures can be material-specific. Furthermore, this will allow inverse problems to infer structure, select models, and fit model parameters using asymptotically-nonlinear signatures. To illustrate this aspect, we demonstrate a fingerprint matching exercise with experimental measurements on a transiently cross-linked hydrogel system. We find that currently available model fingerprints can match the qualitative magnitudes and frequency dependence, but not the signs of the experimental transient network response.

42 ENGINEERING↗

DETECTION OF SOLAR-LIKE OSCILLATIONS, OBSERVATIONAL CONSTRAINTS, AND STELLAR MODELS FOR θ CYG, THE BRIGHTEST STAR OBSERVED BY THE KEPLER MISSION

θ Cygni is an F3 spectral type magnitude V = 4.48 main-sequence star that was the brightest star observed by the original Kepler spacecraft mission. Short-cadence (58.8 s) photometric data using a custom aperture were first obtained during Quarter 6 (2010 June–September) and subsequently in Quarters 8 and 12–17. We present analyses of solar-like oscillations based on Q6 and Q8 data, identifying angular degree l = 0, 1, and 2 modes with frequencies of 1000–2700 μ Hz, a large frequency separation of 83.9 ± 0.4 μ Hz, and maximum oscillation amplitude at frequency ν {sub max} = 1829 ± 54 μ Hz. We also present analyses of new ground-based spectroscopic observations, which, combined with interferometric angular diameter measurements, give T {sub eff} = 6697 ± 78 K, radius 1.49 ± 0.03 R {sub ⊙}, [Fe/H] = -0.02 ± 0.06 dex, and log g = 4.23 ± 0.03. We calculate stellar models matching these constraints using the Yale Rotating Evolution Code and the Asteroseismic Modeling Portal. The best-fit models have masses of 1.35–1.39 M {sub ⊙} and ages of 1.0–1.6 Gyr. θ Cyg’s T {sub eff} and log g place it cooler than the red edge of the γ Doradus instability region established from pre- Kepler ground-based observations, but just at the red edge derived from pulsation modeling. The pulsation models show γ Dor gravity modes driven by the convective blocking mechanism, with frequencies of 1–3 cycles per day (11 to 33 μ Hz). However, gravity modes were not seen in Kepler data; one signal at 1.776 cycles per day (20.56 μ Hz) may be attributable to a faint, possibly background, binary.

79 ASTRONOMY AND ASTROPHYSICS↗

SIMPLIFIED PREDICTIVE MODELS FOR CO₂ SEQUESTRATION PERFORMANCE ASSESSMENT RESEARCH TOPICAL REPORT ON TASK #3 STATISTICAL LEARNING BASED MODELS

We compare two approaches for building a statistical proxy model (metamodel) for CO₂ geologic sequestration from the results of full-physics compositional simulations. The first approach involves a classical Box-Behnken or Augmented Pairs experimental design with a quadratic polynomial response surface. The second approach used a space-filling maxmin Latin Hypercube sampling or maximum entropy design with the choice of five different meta-modeling techniques: quadratic polynomial, kriging with constant and quadratic trend terms, multivariate adaptive regression spline (MARS) and additivity and variance stabilization (AVAS). Simulations results for CO₂ injection into a reservoir-caprock system with 9 design variables (and 97 samples) were used to generate the data for developing the proxy models. The fitted models were validated with using an independent data set and a cross-validation approach for three different performance metrics: total storage efficiency, CO₂ plume radius and average reservoir pressure. The Box-Behnken–quadratic polynomial metamodel performed the best, followed closely by the maximin LHS–kriging metamodel.

Mishra, Srikanta↗

Semi-analytic spectral fitting: simultaneously modelling the mass accumulation and chemical evolution in MaNGA spiral galaxies

We develop a novel semi-analytic spectral fitting approach to quantify the star formation histories (SFHs) and chemical enrichment histories (ChEHs) of individual galaxies. We construct simple yet general chemical evolution models that account for gas inflow and outflow processes as well as star formation, to investigate the evolution of merger-free star-forming systems. These models are fitted directly to galaxies’ absorption-line spectra, while their emission lines are used to constrain current gas phase metallicity and star formation rate. We apply this method to spiral galaxies selected from the SDSS-IV Mapping Nearby Galaxies at Apache Point Observatory survey. By fitting the co-added absorption-line spectra for each galaxy, and using the emission-line constraints on present-day metallicity and star formation, we reconstruct both the SFHs and the ChEHs for all objects in the sample. We can use these reconstructions to obtain archaeological measures of derived correlations such as the mass–metallicity relation at any redshift, which compare favourably with direct observations. We find that both the SFHs and ChEHs have strong mass dependence: massive galaxies accumulate their stellar masses and become enriched earlier. This mass dependence causes the observed flattening of the mass–metallicity relation at lower redshifts. The model also reproduces the observed gas-to-stellar mass ratio and its mass dependence. Moreover, we are able to determine that more massive galaxies have earlier gas infall times and shorter infall time-scales, and that the early chemical enrichment of low-mass galaxies is suppressed by strong outflows, while outflows are not very significant in massive galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗

Theoretical Systematics of Future Baryon Acoustic Oscillation Surveys

Future Baryon Acoustic Oscillation surveys aim at observing galaxy clustering over a wide range of redshift and galaxy populations at great precision, reaching tenths of a percent, in order to detect any deviation of dark energy from the lambda cold dark matter ( ΛCDM ) model. We utilize a set of paired quasi- N -body FastPM simulations that were designed to mitigate the sample variance effect on the BAO feature and evaluated the BAO systematics as precisely as ~0.01 percent. We report anisotropic BAO scale shifts before and after density field reconstruction in the presence of redshift-space distortions over a wide range of redshift, galaxy/halo biases, and shot noise levels. We test different reconstruction schemes and different smoothing filter scales, and introduce physically motivated BAO fitting models. For the first time, we derive a Galilean-invariant infrared resummed model for halos in real and redshift space. We test these models from the perspective of robust BAO measurements and non-BAO information such as growth rate and non-linear bias. We find that pre-reconstruction BAO scale has moderate fitting-model dependence at the level of 0.1–0.2 percent for matter while the dependence is substantially reduced to less than 0.07 percent for halos. We find that post-reconstruction BAO shifts are generally reduced to below 0.1 percent in the presence of galaxy/halo bias and show much smaller fitting model dependence. Different reconstruction conventions can potentially make a much larger difference on the line-of-sight BAO scale, upto 0.3 percent. Furthermore, the precision (error) of the BAO measurements is quite consistent regardless of the choice of the fitting model or reconstruction convention.

(cosmology:) cosmological parameters↗

Performance characterization of nanofiltration, reverse osmosis, and ion exchange technologies for acetic acid separation

A major obstacle to widespread implementation of bio-based fuels and chemicals is the lack of efficient and costeffective separation methods. To purify acetic acid produced by biochemical conversion of biomass via anaerobic digestion, this work employs two commonly used separation technologies: (1) ion-exchange (IX) resin and (2) pressure-driven membranes. This study tested five commercially available strong- and weak-base anion-exchange resins and five commercially available nanofiltration (NF) and reverse osmosis (RO) membranes. The pH of the feed solution significantly affected adsorption capacity. At pH 6.3, a strong-base IX resin (IRN-78) performed best (95.1% acetate removal). With strong-base IX resins, the Langmuir isotherm model fit well, whereas for weak-base IX resins, the Freundlich isotherm provided a better fit. A pseudo-second-order kinetic model fit well for both IRN-78 and IRA-67. Regarding membrane separation, RO (BW30XFR membrane) achieved the highest rejection (98.6% acetate rejection), whereas an NF membrane (NF*) achieved the best combination of permeate flux (105 L/(h∙m 2 )) and rejection (83.1% acetate rejection). For membrane performance, the experimental data were fit using the solution diffusion model. Increased pH in the feed solution lowered permeate flux but increased acetic acid rejection. Finally, then the acetic acid concentration in the feed solution increased, both permeate flux and acetic acid rejection decreased for membrane NF*.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗