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Soil carbon stocks from soil organic carbon at the Teller 47, Teller 27, and Kougarok 86 field sites, Seward Peninsula, Alaska, 2021 – 2023

Carbon stored in permafrost soils represents the largest terrestrial storage and hence has key significance for the global carbon cycle, yet the site-specific estimates of permafrost soil carbon are limited. To better understand permafrost carbon storage, soil organic content (SOC) was measured from soils collected at the Teller 27, Teller 47, and Kougarok 86 field sites on the Seward Peninsula, Alaska in the summers of 2019 and 2021-2023. Soil samples were collected from locations with and without near-surface permafrost to varied depths within the permafrost, where present. In addition to sample collection for soil organic carbon analysis, bulk density samples were also collected within each soil profile to allow for calculation of carbon stocks. Carbon to nitrogen ratios are also reported. Location data were collected at each observation point using a handheld GPS unit with waypoint averaging to reduce location measurement error to within 3 m. SOC was measured using elemental analysis in the laboratory. This dataset contains a *.csv file of soil carbon stocks, a *.kml file of measurement locations, a *.pdf user guide, a *.csv data dictionary, and a *.csv file level metadata.

EARTH SCIENCE > CRYOSPHERE > FROZEN GROUND↗

A general framework for removing point-spread function additive systematics in cosmological weak lensing analysis

ABSTRACT Cosmological weak lensing measurements rely on a precise measurement of the shear two-point correlation function (2PCF) along with a deep understanding of systematics that affect it. In this work, we demonstrate a general framework for detecting and modelling the impact of PSF systematics on the cosmic shear 2PCF and mitigating its impact on cosmological analysis. Our framework can detect PSF leakage and modelling error from all spin-2 quantities contributed by the PSF second and higher moments, rather than just the second moments, using the cross-correlations between galaxy shapes and PSF moments. We interpret null tests using the HSC Year 3 (Y3) catalogs with this formalism and find that leakage from the spin-2 combination of PSF fourth moments is the leading contributor to additive shear systematics, with total contamination that is an order-of-magnitude higher than that contributed by PSF second moments alone. We conducted a mock cosmic shear analysis for HSC Y3 and find that, if uncorrected, PSF systematics can bias the cosmological parameters Ωm and S8 by ∼0.3σ. The traditional second moment-based model can only correct for a 0.1σ bias, leaving the contamination largely uncorrected. We conclude it is necessary to model both PSF second and fourth moment contaminations for HSC Y3 cosmic shear analysis. We also reanalyse the HSC Y1 cosmic shear analysis with our updated systematics model and identify a 0.07σ bias on Ωm when using the more restricted second moment model from the original analysis. We demonstrate how to self-consistently use the method in both real space and Fourier space, assess shear systematics in tomographic bins, and test for PSF model overfitting.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Shadow Distillation: Quantum Error Mitigation with Classical Shadows for Near-Term Quantum Processors

Mitigating errors in quantum information processing devices is especially important in the absence of fault tolerance. An effective method in suppressing state-preparation errors is using multiple copies to distill the ideal component from a noisy quantum state. Here, we use classical shadows and randomized measurements to circumvent the need for coherent access to multiple copies at an exponential cost. We study the scaling of resources using numerical simulations and find that the overhead is still favorable compared to full state tomography. We optimize measurement resources under realistic experimental constraints and apply our method to an experiment preparing a Greenberger-Horne-Zeilinger state with trapped ions. In addition to improving stabilizer measurements, the analysis of the improved results reveals the nature of errors affecting the experiment. Hence, our results provide a directly applicable method for mitigating errors in near-term quantum computers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

SU-E-T-509: Inter-Observer and Inter-Modality Contouring Analysis for Organs at Risk for HDR Gynecological Brachytherapy

Purpose This study quantifies errors associated with MR-guided High Dose Rate (HDR) gynecological brachytherapy. Uncertainties in this treatment results from contouring, organ motion between imaging and treatment delivery, dose calculation, and dose delivery. We focus on interobserver and inter-modality variability in contouring and the motion of organs at risk (OARs) in the time span between the MR and CT scans (∼1 hour). We report the change in organ volume and position of center of mass (CM) between the two imaging modalities. Methods A total of 8 patients treated with MR-guided HDR brachytherapy were included in this study. Two observers contoured the bladder and rectum on both MR and CT scans. The change in OAR volume and CM position between the MR and CT imaging sessions on both image sets were calculated. Results The absolute mean bladder volume change between the two imaging modalities is 67.1cc. The absolute mean inter-observer difference in bladder volume is much lower at 15.5cc (MR) and 11.0cc (CT). This higher inter-modality volume difference suggests a real change in the bladder filling between the two imaging sessions. Change in Rectum volume inter-observer standard error of means (SEM) is 3.18cc (MR) and 3.09cc (CT), while the inter-modality SEM is 3.65cc (observer 1), and 2.75cc (observer 2). The SEM for rectum CM position in the superior-inferior direction was approximately three times higher than in other directions for both the inter—observer (0.77 cm, 0.92 cm for observers 1 and 2, respectively) and inter-modality (0.91 cm, 0.95 cm for MR and CT, respectively) variability. Conclusion Bladder contours display good consistency between different observers on both CT and MR images. For rectum contouring the highest inconsistency stems from the observers’ choice of the superior-inferior borders. A complete analysis of a larger patient cohort will enable us to separate the true organ motion from the inter-observer variability.

60 APPLIED LIFE SCIENCES↗

Functional Principal Component Analysis of Radio–Optical Reference Frame Tie

The Gaia optical reference frame is intrinsically undefined with respect to global orientation and spin, so it needs to be anchored in the radio-based International Celestial Reference Frame (ICRF) to provide a referenced and quasi-inertial celestial coordinate system. The link between the two fundamental frames is realized through two samples of distant extragalactic sources, mostly active galactic nuclei and quasars, but only the smaller sample of radio-loud ICRF sources with optical counterparts is available to determine the mutual orientation. The robustness of this link can be mathematically formulated in the framework of functional principal component analysis using a set of vector spherical harmonics to represent the differences in celestial positions of the common objects. The weakest eigenvectors are computed, which describe the greatest deficiency of the link. The deficient or poorly determined terms are specific vector fields on the sphere that carry the largest errors of absolute astrometry using Gaia in reference to the ICRF. This analysis provides guidelines for the future development of the ICRF maximizing the accuracy of the link over the entire celestial sphere. A measure of the robustness of a least-squares solution, which can be applied to any linear model fitting problem, is introduced to help discriminate between reference frame tie models of different degrees.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Channeling analysis in studying ion irradiation damage in materials containing various types of defects

We present that ion channeling is a powerful quantitative technique for studying ion-irradiation induced defect evolution in single crystalline materials. An iterative procedure to determine dechanneling yields has been developed for decades, serving as a major method for analyzing experimental channeling data. The applicability of such procedure is, however, generally limited to the crystalline damage with only point defects and local amorphous domains. For the other cases, such as irradiated metals, the assumption of direct-backscattering free has usually been made. In the present study, Ni, TiAl, MgO, and SrTiO 3 single crystals are selected as four model materials, representing metals, intermetallic alloys, and ceramic compounds with different defect evolution processes under irradiation, to investigate the fidelity of applying dechanneling analysis on various types of defects. The pure dechanneling assumption is shown oversimplified in Ni irradiated with low fluence self-ions and may result in error on the derived damage profile. Moreover, the iterative procedure of dechanneling analysis is shown valid for more general situations than the randomly distributed atoms, including those not exhibiting a peak in channeling spectra. The disappearance of damage peak in channeling spectra is attributed to the combined effects of small (but non-zero) scattering factor, long-range damage effects, and non-ignorable damage level in pristine crystals. Furthermore, the ratio of direct backscattering to dechanneling areas provides information on defect configurations in the materials containing a well-defined damage peak in channeling spectra. Finally, the contribution from dechanneling sources increases from SrTiO 3 , TiAl, to MgO, according to the derived scattering and dechanneling factors.

36 MATERIALS SCIENCE↗

Wide‐Field Bond Quality Evaluation Using Frequency Domain Thermoreflectance with Deep Neural Network Feature Reconstruction

Heterogeneous integration of microelectronic components provides a pathway to improve circuit/component performance; however, this comes with assembly challenges, in particular due to complex interfaces via subsurface bump bonds. The ability of these bonds to transmit electrical signals and conduct heat to the carrier substrate limits component performance. In this work, hyperspectral frequency‐domain thermoreflectance (FDTR) imaging is demonstrated as a robust technique for evaluating the quality of subsurface indium bump bonds in a surrogate microelectronic sample. By performing microscale FDTR imaging with coarse motion image stitching, thermal phase maps that cover a 4 mm by 4 mm field‐of‐view with subsurface feature sensitivity at depths greater than 50 µm are obtained. The resulting FDTR hyperspectral data contains more than three million pixels and reveal the quality of subsurface microbump arrays. Wide‐field analysis of bonded versus gap regions is enabled by deep neural network feature reconstruction, that after training, rapidly provides an interpretable representation of bond quality. Utility of noisy higher frequency FDTR phase maps, i.e., near the computationally predicted sensing depth limit, results in an average prediction error of 11%. Taken together, FDTR with neural network‐based analysis demonstrates subsurface bond monitoring at length scales relevant for heterogeneously integrated microelectronics.

FDTR↗

Optimal subinterval selection approach for power system transient stability simulation

Power system transient stability analysis requires an appropriate integration time step to avoid numerical instability as well as to reduce computational demands. For fast system dynamics, which vary more rapidly than what the time step covers, a fraction of the time step, called a subinterval, is used. However, the optimal value of this subinterval is not easily determined because the analysis of the system dynamics might be required. This selection is usually made from engineering experiences, and perhaps trial and error. This paper proposes an optimal subinterval selection approach for power system transient stability analysis, which is based on modal analysis using a single machine infinite bus (SMIB) system. Fast system dynamics are identified with the modal analysis and the SMIB system is used focusing on fast local modes. An appropriate subinterval time step from the proposed approach can reduce computational burden and achieve accurate simulation responses as well. As a result, the performance of the proposed method is demonstrated with the GSO 37-bus system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Assessing laser powder bed fusion system geometric errors through artifact-based methods

Additive manufacturing (AM) machines have developed more rapidly than standardized frameworks needed for the qualification of their geometric capabilities. While some manufacturer-specific methods exist to test capabilities and perform some calibration tasks, standardization efforts have only recently been undertaken in the form of ISO/ASTM 52902. In this study, the recommended methodology prescribed by the standard was implemented by building geometric artifacts with a laser powder bed fusion (LPBF) system and performing dimensional inspection with a coordinate measurement machine (CMM), amongst other methods. Typical dimensional capabilities of the LPBF system are identified and commentary is made on applying metrology methods, detecting geometric error, and diagnosing base causes in the LPBF system. In doing so, favored metrology practices and measurement analysis methods auxiliary to the standard are proposed. Artifact measurements were used to characterize beam positioning error and beam offset error. Methods for decoupling the effects of error sources are proposed. Difficulties in the inspection of AM components are identified, and the effects of various CMM measurement strategies are evaluated. Insights on the application of the new standard are presented, along with commentary as to its fitness for the LPBF process.

Berez, J.↗

Novel application of the modal strain energy technique for state-of-the-art damping predictions

Structural damping, which measures the energy dissipation of a vibrating structure, is a key modeling input for lightweight structures but is notoriously hard to predict. This work utilizes vibration-based measurements of centimeter-scale coupons and the modal strain energy approach to predict structural damping of a lightly damped structure. The approach was originally validated with panels shorter than a meter in length. This work extends the validation to a 2.75 m beam made of unidirectional and biaxial glass fiber laminates bonded by adhesive. The comparison between three-dimensional finite element model predictions and full-scale experimental measurements of damping show an average error of 5.2% for the first five modes. Additionally, the modal strain energy approach is newly applied with a one-dimensional geometrically exact beam theory model and a two-dimensional sectional analysis solver. This beam approach accurately predicts the damping behavior of the first bending modes but loses accuracy for higher order modes that are dominated by three-dimensional effects. This novel approach provides faster simulations while allowing arbitrary beam cross sections. The paper also investigates traditional and high-force dynamic mechanical analysis to measure structural damping of coupons. Both alternatives show significant errors in attempted validation against the theoretical thermoelastic damping of aluminum coupons.

17 WIND ENERGY↗

Semi-analytical sensitivity analysis for nonlinear transient problems

Efficient analytical sensitivity computations are essential elements of gradient-based optimization schemes; however, they can be difficult to implement. This implementation issue is often resolved by adopting the semi-analytical method which exhibits the efficiency of the analytical methods and the ease of implementation of the finite difference method. However, care must be taken as semi-analytical sensitivities may exhibit errors due to truncation and round-off. Additional errors are introduced if the convergence tolerance of the primal analysis is not sufficiently small. This paper gives a general overview and some new developments of the analytical and semi-analytical sensitivity analyses for nonlinear steady-state, transient, and dynamic problems. We discuss the restrictive assumptions, accuracy, and consistency of these methods. Both adjoint and direct differentiation methods are studied. Numerical examples are provided.

42 ENGINEERING↗

Wavelet Denoising of Radio Observations of Rotating Radio Transients (RRATs): Improved Timing Parameters for Eight RRATs

Rotating radio transients (RRATs) are sporadically emitting pulsars detectable only through searches for single pulses. While over 100 RRATs have been detected, only a small fraction (roughly 20%) have phase-connected timing solutions, which are critical for determining how they relate to other neutron star populations. Detecting more pulses in order to achieve solutions is key to understanding their physical nature. Astronomical signals collected by radio telescopes contain noise from many sources, making the detection of weak pulses difficult. Applying a denoising method to raw time series prior to performing a single-pulse search typically leads to a more accurate estimation of their times of arrival (TOAs). Taking into account some features of RRAT pulses and noise, we present a denoising method based on wavelet data analysis, an image-processing technique. Assuming that the spin period of an RRAT is known, we estimate the frequency spectrum components contributing to the composition of RRAT pulses. This allows us to suppress the noise, which contributes to other frequencies. We apply the wavelet denoising method including selective wavelet reconstruction and wavelet shrinkage to the de-dispersed time series of eight RRATs with existing timing solutions. The signal-to-noise ratio (S/N) of most pulses are improved after wavelet denoising. Compared to the conventional approach, we measure 12%–69% more TOAs for the eight RRATs. The new timing solutions for the eight RRATs show 16%–90% smaller estimation error of most parameters. Thus, we conclude that wavelet analysis is an effective tool for denoising RRATs signal.

79 ASTRONOMY AND ASTROPHYSICS↗

Sensitivity analysis on optical performance of a novel linear Fresnel concentrating solar power collector

A novel, low-cost linear Fresnel collector for concentrating solar power applications is being developed by Hyperlight Energy (Hyperlight) and the National Renewable Energy Laboratory (NREL). Hyperlight is currently deploying their linear Fresnel collector technology in a half-acre pilot loop near Brawley, California. The optical performance of a concentrating solar power collector represents the largest loss in the efficiency of the overall system. The ability to accurately model the complex optical interactions of a collector becomes essential in successfully implementing a new collector technology. Here, this study presents a detailed sensitivity analysis of the optical performance of Hyperlight linear Fresnel technology, characterizing the effects of potential optomechanical error sources on collector performance. Optical models are implemented in SolTrace, a Monte-Carlo ray-tracing software developed at NREL. First, SolTrace is used to analyze collector sensitivity to individual optomechanical error perturbations in both the primary reflectors and the receiver assembly. Then, a high-fidelity optomechanical error model is adopted to capture the realistic performance of the installed Hyperlight linear Fresnel collector. Finally, the sensitivity analysis can provide insightful guidance to inform the tightening and relaxation of tolerances during manufacturing and implementation of a new collector technology.

14 SOLAR ENERGY↗

Numerical study on the Welander oscillatory natural circulation problem using high-order numerical methods

In this study, the classical Welander’s oscillatory natural circulation problem is investigated using high-order numerical methods. As originally studied by Welander, the fluid motion in a differentially heated fluid loop can exhibit stable, weakly instable, and strongly instable modes. A theoretical stability map has also been originally derived from the stability analysis. Numerical results obtained in this paper show very good agreement with Welander’s theoretical derivations. For stable cases, numerical results from both the high-order and low-order numerical methods agree well with the non-dimensional flow rate analytically derived. The high-order numerical methods give much less numerical errors compared to the low-order methods. For stability analysis, the high-order numerical methods could perfectly predict the stability map, while the low-order numerical methods failed to do so. For all theoretically unstable cases, the low-order methods predicted them to be stable. The result obtained in this paper is a strong evidence to show the benefits of using high-order numerical methods over the low-order ones, when they are applied to simulate natural circulation phenomenon that has already gain increasing interests in many future nuclear reactor designs.

42 ENGINEERING↗

Comparing Measured (a,n) Thick Target Yields to MCNP6 using TENDL 2012 Libraries - Paper 31

MCNP6, due to the heritage of MCNPX, has always possessed the capability to transport the light ions, such as alpha particles. Two types of competing physics take place during the particle transport: atomic and nuclear physics. Charged particles lose energy to media due to Coulombic interactions. MCNP6 models Coulombic interactions through the use of the continuous slowing down approximation. Stopping powers are calculated at a variety of energies using the Bethe-Bloch formula with Sternheimer and Peierls density effect correction. For energies less than 1.31 MeV/AMU, a low-energy SPAR model is used. When the energy of the particle is high enough, there is a transition from nuclear interactions to nucleon interactions. MCNP6 possess various physics models to account for these types of intra-nuclear cascades. These models are less accurate at low energies. Even though MCNP6 will transport these light ions to low energies (i.e. less than 20 MeV), most of the available model physics in MCNP6, for nuclear interactions, has a suggested minimum energy of ∼20-200 MeV. The result of the poorer prediction at low energies causes important light ion events, such as F-19(a,n)Na-22 from U-234 decay in UF{sub 6}, to produce orders of magnitude fewer neutrons in MCNP6 than should be emitted. As with neutrons, ACE (A Compact ENDF) formatted light ion libraries have been developed from several different evaluations. These libraries possess better physics at low energies where the physics models break down. The TENDL 2012 evaluations possess alpha transport libraries, in ACE format, such that they can easily be used with codes like MCNP6 that read ACE formatted cross sections. As a result, a capability was developed for MCNP6 to read and implement these library cross sections when the light ion reached energies below the library upper energy cutoff. Perfectly modelling an experiment for benchmark comparisons to a code calculation can be tricky. For complex setups, systematic error is always possible; and usually a hefty uncertainty analysis is required to quantify just the geometry setup and material combination choices. For an (a,n) interaction, a thick target yield is defined as the amount of neutrons emitted given that the alpha ranges out in the material. For alpha transport at low energy <10 MeV, in reasonably dense materials (>1-2 g/cc), with a material dimension length larger than a few hundred microns, alpha particles will tend to completely stop and range out in the material. For Li, Be, B, C, N, O, F, Na, Mg and Al thick target yields exist in 200 keV intervals from 1 to 9.8 MeV (most of the elements do have (a,n) thresholds above 1 MeV). Because modelling a thick target yield in MCNP6 is much easier than attempting to account for the complexity of systematic error from a full out experiment, we present here comparisons of (a,n) thick target yields to those calculated in MCNP6 using the TENDL 2012 alpha library evaluations.

61 RADIATION PROTECTION AND DOSIMETRY↗

SIMULATED HUMAN ERROR PROBABILITY AND ITS APPLICATION TO DYNAMIC HUMAN FAILURE EVENTS

Abstract Objectives: Human reliability analysis (HRA) methods typically analyze human failure events (HFEs) at the overall task level. For dynamic HRA, it is important to model human activities at the subtask level. There exists a disconnect between dynamic subtask level and static task level that presents issues when modeling dynamic scenarios. For example, the SPAR-H method is typically used to calculate the human error probability (HEP) at the task level. As demonstrated in this paper, quantification in SPAR-H does not translate to the subtask level. Methods: Two different discrete distributions were generated for each SPAR-H Performance Shaping Factor (PSF) to define the frequency of PSF levels. The first distribution was a uniform, or uninformed distribution that assumed the frequency of each PSF level was equally likely. The second non-continuous distribution took the frequency of PSF level as identified from an assessment of the HERA database. These two different approaches were created to identify the resulting distribution of the HEP. The resulting HEP that appears closer to the known distribution, a log-normal centered on 1E-3, is the more desirable. Each approach then has median, average and maximum HFE calculations applied. To calculate these three values, three events, A, B and C are generated from the PSF level frequencies comprised of subtasks. The median HFE selects the median PSF level from each PSF and calculates HEP. The average HFE takes the mean PSF level, and the maximum takes the maximum PSF level. The same data set of subtask HEPs yields starkly different HEPs when aggregated to the HFE level in SPAR-H. Results: Assuming that each PSF level in each HFE is equally likely creates an unrealistic distribution of the HEP that is centered at 1. Next the observed frequency of PSF levels was applied with the resulting HEP behaving log-normally with a majority of the values under 2.5% HEP. The median, average and maximum HFE calculations did yield different answers for the HFE. The HFE maximum grossly over estimates the HFE, while the HFE distribution occurs less than HFE median, and greater than HFE average. Conclusions: Dynamic task modeling can be perused through the framework of SPAR-H. Identification of distributions associated with each PSF needs to be defined, and may change depending upon the scenario. However it is very unlikely that each PSF level is equally likely as the resulting HEP distribution is strongly centered at 100%, which is unrealistic. Other distributions may need to be identified for PSFs, to facilitate the transition to dynamic task modeling. Additionally discrete distributions need to be exchanged for continuous so that simulations for the HFE can further advance. This paper provides a method to explore dynamic subtask to task translation and provides examples of the process using the SPAR-H method.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Misclassification in Workers’ Telecommuting Frequency Choices Using a Generalized Extreme Value Model

Telecommuting frequency is a response variable collected in travel surveys and is, therefore, prone to errors leading to mismeasurements or misclassification. Misclassification of explanatory variables is a common risk when using statistical modeling techniques. We define “misclassification” as a response reported or recorded in the wrong category; for example, a variable is recorded as a 1 when it should be 0. Here, in this context, this study aims to develop a statistical model to analyze telecommuting data which accounts for potential misclassification errors by building on existing literature in econometrics. The empirical analysis was undertaken using the 2017 National Household Travel Survey (NHTS) and the general extreme value (GEV) models available in the literature. Specifically, the frequency of telecommuting days was analyzed using the negative binomial (NB) model recast as the multinomial logit (MNL) model. By nature—and consistent with other studies—NHTS data are prone to errors that can be classified as intentional or unintentional misinformation provided by the person being interviewed. Ignoring these errors while modeling telecommuting frequencies using standard discrete count models can result in biased parameter estimates. The misclassification parameter was calculated for both over-reporting and under-reporting scenarios. The misclassification errors can be as high as 14% over-reported and 10% under-reported, particularly for the neighboring values. Statistical fit comparison between the models shows that models that ignore misclassification have worse data fit and biased parameter estimates with significant policy implications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

SU-G-TeP4-08: Automating the Verification of Patient Treatment Parameters

Purpose: To automate the daily verification of each patient’s treatment by utilizing the trajectory log files (TLs) written by the Varian TrueBeam linear accelerator while reducing the number of false positives including jaw and gantry positioning errors, that are displayed in the Treatment History tab of Varian’s Chart QA module. Methods: Small deviations in treatment parameters are difficult to detect in weekly chart checks, but may be significant in reducing delivery errors, and would be critical if detected daily. Software was developed in house to read TLs. Multiple functions were implemented within the software that allow it to operate via a GUI to analyze TLs, or as a script to run on a regular basis. In order to determine tolerance levels for the scripted analysis, 15,241 TLs from seven TrueBeams were analyzed. The maximum error of each axis for each TL was written to a CSV file and statistically analyzed to determine the tolerance for each axis accessible in the TLs to flag for manual review. The software/scripts developed were tested by varying the tolerance values to ensure veracity. After tolerances were determined, multiple weeks of manual chart checks were performed simultaneously with the automated analysis to ensure validity. Results: The tolerance values for the major axis were determined to be, 0.025 degrees for the collimator, 1.0 degree for the gantry, 0.002cm for the y-jaws, 0.01cm for the x-jaws, and 0.5MU for the MU. The automated verification of treatment parameters has been in clinical use for 4 months. During that time, no errors in machine delivery of the patient treatments were found. Conclusion: The process detailed here is a viable and effective alternative to manually checking treatment parameters during weekly chart checks.

60 APPLIED LIFE SCIENCES↗