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At least 271 records · Page 15

Characterization of promoter elements of isoprene‐responsive genes and the ability of isoprene to bind START domain transcription factors

Abstract Isoprene has recently been proposed to be a signaling molecule that can enhance tolerance of both biotic and abiotic stress. Not all plants make isoprene, but all plants tested to date respond to isoprene. We hypothesized that isoprene interacts with existing signaling pathways rather than requiring novel mechanisms for its effect on plants. We analyzed the cis‐regulatory elements (CREs) in promoters of isoprene‐responsive genes and the corresponding transcription factors binding these promoter elements to obtain clues about the transcription factors and other proteins involved in isoprene signaling. Promoter regions of isoprene‐responsive genes were characterized using the Arabidopsis cis‐regulatory element database. CREs bind ARR1, Dof, DPBF, bHLH112, GATA factors, GT‐1, MYB, and WRKY transcription factors, and light‐responsive elements were overrepresented in promoters of isoprene‐responsive genes; CBF‐, HSF‐, WUS‐binding motifs were underrepresented. Transcription factors corresponding to CREs overrepresented in promoters of isoprene‐responsive genes were mainly those important for stress responses: drought‐, salt/osmotic‐, oxidative‐, herbivory/wounding and pathogen‐stress. More than half of the isoprene‐responsive genes contained at least one binding site for TFs of the class IV (homeodomain leucine zipper) HD‐ZIP family, such as GL2, ATML1, PDF2, HDG11, ATHB17. While the HD‐zipper‐loop‐zipper (ZLZ) domain binds to the L1 box of the promoter region, a special domain called the steroidogenic acute regulatory protein‐related lipid transfer, or START domain, can bind ligands such as fatty acids (e.g., linolenic and linoleic acid). We tested whether isoprene might bind in such a START domain. Molecular simulations and modeling to test interactions between isoprene and a class IV HD‐ZIP family START‐domain‐containing protein were carried out. Without membrane penetration by the HDG11 START domain, isoprene within the lipid bilayer was inaccessible to this domain, preventing protein interactions with membrane bound isoprene. The cross‐talk between isoprene‐mediated signaling and other growth regulator and stress signaling pathways, in terms of common CREs and transcription factors could enhance the stability of the isoprene emission trait when it evolves in a plant but so far it has not been possible to say what how isoprene is sensed to initiate signaling responses.

60 APPLIED LIFE SCIENCES↗

Soft factorization in QED from 2D Kac-Moody symmetry

The soft factorization theorem for 4D abelian gauge theory states that the S -matrix factorizes into soft and hard parts, with the universal soft part containing all soft and collinear poles. Similarly, correlation functions on the sphere in a 2D CFT with a U(1) Kac-Moody current algebra factorize into current algebra and non-current algebra factors, with the current algebra factor fully determined by its pole structure. In this paper, we show that these 4D and 2D factorizations are mathematically the same phenomena. The soft ‘t Hooft-Wilson lines and soft photons are realized as a complexified 2D current algebra on the celestial sphere at null infinity. The current algebra level is determined by the cusp anomalous dimension. The associated complex U(1) boson lives on a torus whose modular parameter is τ=$\frac{2πi}{e^2}$ + $\frac{θ}{2π}$. The correlators of this 2D current algebra fully reproduce the known soft part of the 4D S -matrix, as well as a conjectured generalization involving magnetic charges.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Factors Associated with Secondary Functional Patency After Percutaneous Transluminal Angioplasty of the Early Failing or Immature Hemodialysis Arteriovenous Fistula

Purpose: To evaluate the efficacy of percutaneous transluminal angioplasty for early failing hemodialysis arteriovenous fistulas (AVFs) and predictors of secondary functional patency (FP). Methods: A review of our endovascular registry database showed that 61 patients with early failure after a surgically created AVF underwent endovascular intervention between 2011 and 2016. Median time from AVF creation to first intervention was 5.6 weeks. Median duration of follow-up was 14 months. Items related to the technical success rate and primary and secondary FP, and factors associated with secondary FP were analyzed. Results: Technical success was achieved in 55 (90%) of 61 patients. The primary and secondary FP rates were 42% and 65% at 12 months, respectively. Multivariate analysis showed that lesion length (HR; 1.15, P = 0.001) and lesions including juxta-AVF (the portion of fistula vein within 2 cm of the arteriovenous anastomosis, HR; 6.23, P = 0.008) were factors associated with reduced secondary FP. ROC curve analysis indicated lesion length with cutoff value ≥ 9 cm as a risk factor for reduced secondary FP. Secondary FP at 12 months for patients with no risk factors, with 1, and with 2 was 86%, 65%, and 0%, respectively. There was a significant difference in secondary FP rates among these groups (P = 0.001). Conclusions: A lesion length and juxta-AVF lesion are the risk factors for reduced secondary FP. The secondary FP rate at 12 months is acceptable in patients without risk factors.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Practical factors of envelope model setup and their effects on the performance of model predictive control for building heating, ventilating, and air conditioning systems

Model predictive control (MPC) for buildings is attracting significant attention in research and industry due to its potential to address a number of challenges facing the building industry, including energy cost reduction, grid integration, and occupant connectivity. However, the strategy has not yet been implemented at any scale, largely due to the significant effort required to configure and calibrate the model used in the MPC controller. While many studies have focused on methods to expedite model configuration and improve model accuracy, few have studied the impact a wide range of factors have on the accuracy of the resulting model. In addition, few have continued on to analyze these factors’ impact on MPC controller performance in terms of final operating costs. Therefore, this study first identifies the practical factors affecting model setup, specifically focusing on the thermal envelope. The seven that are identified are building design, model structure, model order, data set, data quality, identification algorithm and initial guesses, and software tool-chain. Then, through a large number of trials, it analyzes each factor's influence on model accuracy, focusing on grey-box models for a single zone building envelope. Finally, this study implements a subset of the models identified with these factor variations in heating, ventilating, and air conditioning MPC controllers, and tests them in simulation of a representative case that aims to optimally cool a single-zone building with time-varying electricity prices. It is found that a difference of up to 20%25 in cooling cost for the cases studied can occur between the best performing model and the worst performing model. The primary factors attributing to this were model structure and initial parameter guesses during parameter estimation of the model.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Differential effects of voluntary wheel running and toy rotation on the mRNA expression of neurotrophic factors and FKBP5 in a post-traumatic stress disorder rat model with the shuttle-box task

Highlights: • Running wheel or toy rotation produces almost the same behavioral effects. • The running wheel might alter PTSD-like behaviors via neurotrophic factors. • Toy rotation might alter PTSD-like behaviors via the HPA system. Life-threatening experiences can result in the development of post-traumatic stress disorder. We have developed an animal model for post-traumatic stress disorder (PTSD) using a shuttle box in rats. In this paradigm, the rats were exposed to inescapable foot-shock stress (IS) in a shuttle box, and then an avoidance/escape task was performed in the same box 2 weeks after IS. A previous study using this paradigm revealed that environmental enrichment (EE) ameliorated avoidance/numbing-like behaviors, but not hyperarousal-like behaviors, and EE also elevated hippocampal brain-derived neurotrophic factor (BDNF) expression. However, the differential effects of EE components, i.e., running wheel (RW) or toy rotation, on PTSD-like behaviors has remained unclear. In this experiment, we demonstrated that RW, toy rotation, and EE (containing RW and toy rotation) ameliorated avoidance/numbing-like behaviors, induced learning of avoidance responses, and improved depressive-like behaviors in traumatized rats. The RW increased the hippocampal mRNA expression of neurotrophic factors, especially BDNF and glial-cell derived neurotrophic factor. Toy rotation influenced FK506 binding protein 5 mRNA expression, which is believed to be a regulator of the hypothalamic-pituitary-adrenal (HPA)-axis system, in the hippocampus and amygdala. This is the first report to elucidate the differential mechanistic effects of RW and toy rotation. The former appears to exert its effects via neurotrophic factors, while the latter exerts its effects via the HPA axis. Further studies will lead to a better understanding of the influence of environmental factors on PTSD.

60 APPLIED LIFE SCIENCES↗

Customer enrollment and participation in building demand management programs: A review of key factors

Increasing the efficiency and flexibility of electricity demand is necessary for ensuring a cost-effective and reliable transition to zero-carbon electricity systems. Such demand-side management (DSM) resources have been procured by utilities for decades via energy efficiency and demand response programs; however, the key drivers of program enrollment and customer participation levels remain poorly understood — even as governments and grid planners seek to scale up the deployment of DSM assets to meet climate targets. Here we systematically review the evidence on multiple factors that may influence customer enrollment and participation in building DSM programs, focusing primarily on residential and commercial buildings. We examine the contexts in which relationships between DSM factors and outcomes are most often explored and with which methods; we also score the strength, direction, and internal consistency of each factor's reported impact on the enrollment and participation outcomes. We find that studies most commonly assess the effects of economic incentives for load flexibility on program participation levels, often using simulation-based methods in lieu of measured data. Few studies focus on program enrollment outcomes or regulatory drivers of either enrollment or participation, and gaps are also evident in the coverage of emerging DSM opportunities like load electrification. Removal of structural barriers (e.g., the lack of controls infrastructure) and the use of third party services (e.g., load aggregators) are the factors with the largest positive impacts on DSM outcomes, but no single factor emerges as clearly most impactful. For a given factor, the range of reported impacts typically varies widely across the relevant studies reviewed. Our findings provide a snapshot of the state of knowledge about building DSM and customer decision-making, and they expose key gaps in understanding that must be filled if building DSM is to expand as a critical resource for operating clean power grids.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Predicting transcription factor activity using prior biological information

Dysregulation of normal transcription factor activity is a common driver of disease. Therefore, the detection of aberrant transcription factor activity is important to understand disease pathogenesis. We have developed Priori, a method to predict transcription factor activity from RNA sequencing data. Priori has two key advantages over existing methods. First, Priori utilizes literature-supported regulatory information to identify transcription factor-target gene relationships. It then applies linear models to determine the impact of transcription factor regulation on the expression of its target genes. Second, results from a third-party benchmarking pipeline reveals that Priori detects aberrant activity from 124 single-gene perturbation experiments with higher sensitivity and specificity than 11 other methods. We applied Priori and other top-performing methods to predict transcription factor activity from two large primary patient datasets. Our work demonstrates that Priori uniquely discovered significant determinants of survival in breast cancer and identified mediators of drug response in leukemia.

59 BASIC BIOLOGICAL SCIENCES↗

Source of Processable Vitrimer Viscosities: Swap Frequencies and Steric Factors

Vitrimers exhibit high, processable viscosities, where other polymers do not, and are among the most promising polymers for closed-loop material circularity. We sought to investigate the underlying chemical kinetic factors that result in high viscosities for vitrimers, which are crucial to designing vitrimers with tunable viscosity. To interrogate these factors, we achieved the first simulated predictions of real vitrimer viscosities, using a novel kinetic Monte Carlo molecular dynamics method, overcoming the time and length scale gaps to predict experimental bulk viscosities. The vitrimer architecture investigated is based on poly(dimethylsiloxane) chains and vinylogous urethane bond swaps. We probed the effects of the extent of free swapping groups, %F, the activation energy, E A , and the steric factor, ρ. The steric factor is related to the intrinsic reaction probability for molecules with sufficient energy. All three factors were found to be significant, but the role of ρ was found to be the biggest and also the most underappreciated. The results show that the inclusion of accurate ρ is of critical importance for viscosity predictions, with the evidence suggesting that the typical assumption of ρ = 1 is not valid for vitrimers and that, indeed, very low steric factors are present in bond-swap vitrimers such that values of ρ < 10 –10 may be typical. This greatly influences the bond exchange rates and, ultimately, the viscosities. Recognition of this result is necessary for the prediction of vitrimer viscosities from molecular simulations and to make vitrimers by design from molecular dynamics. We also investigated the effects that E A , ρ, and the number of free swapping groups have upon vitreous range temperatures, TV, with respect to achieving a specific viscosity (η V = 1 × 10 8 Pa·s), as well as for a commonly reported higher viscosity extrapolation (η V = 1 × 10 12 Pa·s). The evidence suggests that vitrimers may follow universal curves for E A vs T V , as a function of ρ. Finally, this study achieves the first of these comparisons of molecular simulations to experiments and reveals critical insights toward creating vitrimers by design, while providing a route for the prediction of T V from kinetic Monte Carlo molecular dynamics simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Local self-interaction correction method with a simple scaling factor

A recently proposed local self-interaction correction (LSIC) method [Zope et al., J. Chem. Phys., 2019, 151, 214108] when applied to the simplest local density approximation provides a significant improvement over standard Perdew–Zunger SIC (PZSIC) for both equilibrium properties such as total or atomization energies as well as properties involving stretched bond such as barrier heights. The method uses an iso-orbital indicator to identify the single-electron regions. To demonstrate the LSIC method, Zope et al. used the ratio z σ of von Weizsäcker τ W σ and total kinetic energy densities τ σ , (z σ = τ W σ /τ σ ) as a scaling factor to scale the self-interaction correction. The present work further explores the LSIC method using a ratio of orbital and spin densities as a simpler scaling factor in place of the ratio of kinetic energy densities. We compute a wide array of both, equilibrium and non-equilibrium properties using LSIC and orbital scaling methods using this simple scaling factor and compare them with previously reported results. Our study shows that LSIC with the simple scaling factor performs better than PZSIC, with results comparable to those obtained by LSIC( z σ ) for most properties, but has slightly larger errors than LSIC( z σ ). Furthermore, we study the binding energies of small water clusters using both scaling factors. Our results show that LSIC with zσ has limitations in predicting the cluster binding energies of weakly bonded systems due to the inability of z σ to distinguish weakly bonded regions from slowly varying density regions. LSIC when used with the density ratio as a scaling factor, on the other hand, provides a good description of water cluster binding energies, thus highlighting the appropriate choice of the iso-orbital indicator.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Programmable gene regulation for metabolic engineering using decoy transcription factor binding sites

Abstract Transcription factor decoy binding sites are short DNA sequences that can titrate a transcription factor away from its natural binding site, therefore regulating gene expression. In this study, we harness synthetic transcription factor decoy systems to regulate gene expression for metabolic pathways in Escherichia coli. We show that transcription factor decoys can effectively regulate expression of native and heterologous genes. Tunability of the decoy can be engineered via changes in copy number or modifications to the DNA decoy site sequence. Using arginine biosynthesis as a showcase, we observed a 16-fold increase in arginine production when we introduced the decoy system to steer metabolic flux towards increased arginine biosynthesis, with negligible growth differences compared to the wild type strain. The decoy-based production strain retains high genetic integrity; in contrast to a gene knock-out approach where mutations were common, we detected no mutations in the production system using the decoy-based strain. We further show that transcription factor decoys are amenable to multiplexed library screening by demonstrating enhanced tolerance to pinene with a combinatorial decoy library. Our study shows that transcription factor decoy binding sites are a powerful and compact tool for metabolic engineering.

59 BASIC BIOLOGICAL SCIENCES↗

Measurement of the sodium and iodine scintillation quenching factors across multiple NaI(Tl) detectors to identify systematics

The amount of light produced by nuclear recoils in scintillating targets is strongly quenched compared to that produced by electrons. A precise understanding of the quenching factor is particularly interesting for weakly interacting massive particles (WIMP) searches and coherent elastic neutrino-nucleus scattering ( CE ν NS ) measurements since both rely on nuclear recoils, whereas energy calibrations are more readily accessible from electron recoils. There is a wide variation among the current measurements of the quenching factor in sodium iodide (NaI) crystals, especially below 10 keV, the energy region of interest for dark matter and CE ν NS studies. A better understanding of the quenching factor in NaI(Tl) is of particular interest for resolving the decades-old puzzle in the field of dark matter between the null results of most WIMP searches and the claim for dark matter detection by the DAMA/LIBRA collaboration. In this work, we measured sodium and iodine quenching factors for five small NaI(Tl) crystals grown with similar thallium concentrations and growth procedures. Unlike previous experiments, multiple crystals were tested, with measurements made in the same experimental setup to control systematic effects. The quenching factors agree in all crystals we investigated, and both sodium and iodine quenching factors are smaller than those reported by DAMA/LIBRA. The dominant systematic effect was due to the electron equivalent energy calibration originating from the nonproportional behavior of the NaI(Tl) light yield at lower energies, potentially the cause for the discrepancies among the previous measurements. Published by the American Physical Society 2024

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

What are the low- Q and large- x boundaries of collinear QCD factorization theorems?

Familiar factorized descriptions of classic QCD processes such as deeply-inelastic scattering (DIS) apply in the limit of very large hard scales, much larger than nonperturbative mass scales and other nonperturbative physical properties like intrinsic transverse momentum. Since many interesting DIS studies occur at kinematic regions where the hard scale, $Q \sim$ 1-2 GeV, is not very much greater than the hadron masses involved, and the Bjorken scaling variable $x_{bj}$ is large, $x_{bj} \gtrsim 0.5$, it is important to examine the boundaries of the most basic factorization assumptions and assess whether improved starting points are needed. Using an idealized field-theoretic model that contains most of the essential elements that a factorization derivation must confront, we retrace in this paper the steps of factorization approximations and compare with calculations that keep all kinematics exact. We examine the relative importance of such quantities as the target mass, light quark masses, and intrinsic parton transverse momentum, and argue that a careful accounting of parton virtuality is essential for treating power corrections to collinear factorization. Finally, we use our observations to motivate searches for new or enhanced factorization theorems specifically designed to deal with moderately low-$Q$ and large-$x_{bj}$ physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Connecting different TMD factorization formalisms in QCD

In the original Collins-Soper-Sterman (CSS) presentation of the results of transverse-momentum-dependent (TMD) factorization for the Drell-Yan process, results for perturbative coefficients can be obtained from calculations for collinear factorization. Here we show how to use these results, plus known results for the quark form factor, to obtain coefficients for TMD factorization in more recent formulations, e.g., that due to Collins, and apply them to known results at order $\alpha_s^2$ and $\alpha_s^3$. We also show that the ``non-perturbative'' functions as obtained from fits to data are equal in the two schemes. We compile the higher-order perturbative inputs needed for the updated CSS scheme by appealing to results obtained in a variety of different formalisms. In addition, we derive the connection between both versions of the CSS formalism and several formalisms based in soft-collinear effective theory (SCET). As a result, our work uses some important new results for factorization for the quark form factor, which we derive.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Individual tree damage dominates mortality risk factors across six tropical forests

Summary The relative importance of tree mortality risk factors remains unknown, especially in diverse tropical forests where species may vary widely in their responses to particular conditions. We present a new framework for quantifying the importance of mortality risk factors and apply it to compare 19 risks on 31 203 trees (1977 species) in 14 one‐year periods in six tropical forests. We defined a condition as a risk factor for a species if it was associated with at least a doubling of mortality rate in univariate analyses. For each risk, we estimated prevalence (frequency), lethality (difference in mortality between trees with and without the risk) and impact (‘excess mortality’ associated with the risk, relative to stand‐level mortality). The most impactful risk factors were light limitation and crown/trunk loss; the most prevalent were light limitation and small size; the most lethal were leaf damage and wounds. Modes of death (standing, broken and uprooted) had limited links with previous conditions and mortality risk factors. We provide the first ranking of importance of tree‐level mortality risk factors in tropical forests. Future research should focus on the links between these risks, their climatic drivers and the physiological processes to enable mechanistic predictions of future tree mortality.

Zuleta, Daniel↗

Combining Sparse Approximate Factorizations with Mixed-precision Iterative Refinement

The standard LU factorization-based solution process for linear systems can be enhanced in speed or accuracy by employing mixed-precision iterative refinement. Most recent work has focused on dense systems. We investigate the potential of mixed-precision iterative refinement to enhance methods for sparse systems based on approximate sparse factorizations. In doing so, we first develop a new error analysis for LU- and GMRES-based iterative refinement under a general model of LU factorization that accounts for the approximation methods typically used by modern sparse solvers, such as low-rank approximations or relaxed pivoting strategies. We then provide a detailed performance analysis of both the execution time and memory consumption of different algorithms, based on a selected set of iterative refinement variants and approximate sparse factorizations. Our performance study uses the multifrontal solver MUMPS, which can exploit block low-rank factorization and static pivoting. We evaluate the performance of the algorithms on large, sparse problems coming from a variety of real-life and industrial applications showing that mixed-precision iterative refinement combined with approximate sparse factorization can lead to considerable reductions of both the time and memory consumption.

97 MATHEMATICS AND COMPUTING↗

The Prediction Model of Risk Factors for COVID-19 Developing into Severe Illness Based on 1046 Patients with COVID-19

This study analyzed the risk factors for patients with COVID-19 developing severe illnesses and explored the value of applying the logistic model combined with ROC curve analysis to predict the risk of severe illnesses at COVID-19 patients’ admissions. The clinical data of 1046 COVID-19 patients admitted to a designated hospital in a certain city from July to September 2020 were retrospectively analyzed, the clinical characteristics of the patients were collected, and a multivariate unconditional logistic regression analysis was used to determine the risk factors for severe illnesses in COVID-19 patients during hospitalization. Based on the analysis results, a prediction model for severe conditions and the ROC curve were constructed, and the predictive value of the model was assessed. Logistic regression analysis showed that age (OR = 3.257, 95% CI 10.466–18.584), complications with chronic obstructive pulmonary disease (OR = 7.337, 95% CI 0.227–87.021), cough (OR = 5517, 95% CI 0.258–65.024), and venous thrombosis (OR = 7322, 95% CI 0.278–95.020) were risk factors for COVID-19 patients developing severe conditions during hospitalization. When complications were not taken into consideration, COVID-19 patients’ ages, number of diseases, and underlying diseases were risk factors influencing the development of severe illnesses. The ROC curve analysis results showed that the AUC that predicted the severity of COVID-19 patients at admission was 0.943, the optimal threshold was −3.24, and the specificity was 0.824, while the sensitivity was 0.827. The changes in the condition of severe COVID-19 patients are related to many factors such as age, clinical symptoms, and underlying diseases. This study has a certain value in predicting COVID-19 patients that develop from mild to severe conditions, and this prediction model is a useful tool in the quick prediction of the changes in patients’ conditions and providing early intervention for those with risk factors.

Lian, Zhichuang↗

Calculation of Friction Factors in Heat Pipes Using CFD in Support of the Sockeye Code

A heat pipe is two-phase heat transfer device which relies on surface tension and capillary pressure to provide a very efficient heat transfer mechanism. Currently, there is interest in designing micro nuclear power reactors using high temperature heat pipes to provide totally passive cooling. To support this, Sockeye is being developed as a heat pipe simulation capability. To support the development of Sockeye, individual phenomena must be tested. This work focuses on applying a CFD model to evaluate friction factors for use in Sockeye. A CFD model has been developed in Nek5000 which simulates each component fluid, i.e. sodium liquid and vapor, independently and captures the effects of the wick on friction factor. The model tests the effect of the wick permeability and the thickness of the wick occupied by each fluid component. The thickness of the wick occupied by each component can be directly related to the local vapor volume fraction from the Sockeye heat pipe model. Results from the CFD model indicate that friction factor in the liquid flow decreases with increasing wick permeability, while the friction factor in the vapor flow increases with increasing wick permeability. In the liquid, this is likely a direct result of the increased cross sectional area available for the flow. For the vapor, this is explained as the wick acting like a rough wall, while the increased area has only a negligible impact. Results for the tests of the thickness of the wick occupied by each fluid showed a thresholding behavior for both liquid and vapor. When the thickness of the wick occupied by each fluid was increased, it increased the effect of the wick, but only up to a certain point. Once a certain thickness was reached, the friction factors remained constant. When the fluid occupied only a very small fraction of the wick, friction factors returned to nominal values.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Update to the Finite Cloud Dose Correction Factors in MACCS

In WASH - 1400, external exposure from the finite radioactive cloud (cloudshine) is calculated by assuming that the cloud is semi-infinite, the concentration of radioactive material is uniform, and by using a correction factor to account for these approximations. This correction factor is originally based upon formulations by Healy and depends on the effective size of the plume and the distance from the plume center to the receptor. The range of the finite cloud dose correction factor table from WASH - 1400 developed using Healy formulations can be exceeded in certain situations. When the range of the table is exceeded, no extrapolation is performed; rather interpolation at the edge of the table is performed per WASH - 1400. The tabulated values of these finite cloud dose correction factors from WASH - 1400 and the interpolation at the edge of the table have been used in MACCS since its creation. An expanded table of finite cloud dose correction factors is one way to reduce the need of using interpolation at the edge of the table. The generation of an expanded finite cloud dose correction factor table for future use in MACCS is documented in this report.

54 ENVIRONMENTAL SCIENCES↗