Beyond thermal limits: comprehensive metrics of performance identify key axes of thermal adaptation in ants
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Purpose: Complexity metrics have been suggested as a complement to measurement-based quality assurance for intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT). However, these metrics have not yet been sufficiently validated. This study develops and evaluates new aperture-based complexity metrics in the context of static multileaf collimator (MLC) openings and compares them to previously published metrics. Methods: This study develops the converted aperture metric and the edge area metric. The converted aperture metric is based on small and irregular parts within the MLC opening that are quantified as measured distances between MLC leaves. The edge area metric is based on the relative size of the region around the edges defined by the MLC. Another metric suggested in this study is the circumference/area ratio. Earlier defined aperture-based complexity metrics—the modulation complexity score, the edge metric, the ratio monitor units (MU)/Gy, the aperture area, and the aperture irregularity—are compared to the newly proposed metrics. A set of small and irregular static MLC openings are created which simulate individual IMRT/VMAT control points of various complexities. These are measured with both an amorphous silicon electronic portal imaging device and EBT3 film. The differences between calculated and measured dose distributions are evaluated using a pixel-by-pixel comparison with two global dose difference criteria of 3% and 5%. The extent of the dose differences, expressed in terms of pass rate, is used as a measure of the complexity of the MLC openings and used for the evaluation of the metrics compared in this study. The different complexity scores are calculated for each created static MLC opening. The correlation between the calculated complexity scores and the extent of the dose differences (pass rate) are analyzed in scatter plots and using Pearson’s r-values. Results: The complexity scores calculated by the edge area metric, converted aperture metric, circumference/area ratio, edge metric, and MU/Gy ratio show good linear correlation to the complexity of the MLC openings, expressed as the 5% dose difference pass rate, with Pearson’s r-values of −0.94, −0.88, −0.84, −0.89, and −0.82, respectively. The overall trends for the 3% and 5% dose difference evaluations are similar. Conclusions: New complexity metrics are developed. The calculated scores correlate to the complexity of the created static MLC openings. The complexity of the MLC opening is dependent on the penumbra region relative to the area of the opening. The aperture-based complexity metrics that combined either the distances between the MLC leaves or the MLC opening circumference with the aperture area show the best correlation with the complexity of the static MLC openings.
METRIC is a robotic science laboratory that can determine the mineralogy, elemental chemistry, micromorphology, and thermophysical properties of planetary regolith. The METRIC suite comprises METRIC XRD/F, an X-ray diffraction/X-ray fluorescence instrument that can determine the mineralogy and elemental chemistry of regolith samples; METRIC XCT, a micro X-ray computed tomography instrument that can be used to evaluate grain/crystallite sizes and textures; METRIC IRS, an imaging spectrometer mounted on a rover that can determine mineralogy and thermophysical properties at the landing site; and a pneumatic sample collection, processing, distribution system developed by Honeybee Robotics. The payload elements could be deployed on a static lander or a rover. Data returned from the METRIC payload would inform origin, formation, and evolution of rocky planetary bodies. METRIC XRD/F draws on heritage from the CheMin instrument on the Mars Science Laboratory (MSL) Curiosity rover [1], with a few important improvements. Like CheMin, METRIC XRD/F operates in transmission geometry and uses piezoelectric actuators on sample cells in a tuning fork geometry to induce convective grain motion of the regolith to create a randomly oriented powder. MSL CheMin uses an energy-sensitive CCD to collect XRD patterns and XRF spectra simultaneously from the same sample cell, resulting in qualitative XRF data. METRIC XRD/F uses two different sample cells, one optimized for XRD and one optimized for XRF, and a silicon drift detector to detect fluoresced X-rays. This improvement to the XRF capabilities provides quantitative geochemical data of major elements down to Z = 11 and allows for the detection of minor and trace elements that are critical for evaluating geologic evolution of the Moon (e.g., P and Th). Modest improvements to the XRD geometry and hardware allow for better angular resolution and the ability to distinguish between members of the pyroxene group. METRIC XCT uses the same geometry and much of the same hardware as METRIC XRD/F, where a CCD would capture images of a regolith sample in a 3 mm diameter sample tube that is rotated 360° in steps <1°. Image brightness can be used to infer compositional data, where brighter materials indicate a higher Z, much like scanning electron microscopy. Data from METRIC XCT complement those from METRIC XRD/F. Particle size, shape, and texture can provide petrologic and provenance information, whereas vesicle size and morphology in volcanic or impact melt lithologies can inform cooling rates. METRIC IRS is a hyperspectral thermal imager that can be mounted to a lander or rover to provide mineralogical data from the broader landing site and help determine whether the samples analyzed by METRIC XRD/F and XCT are representative. The METRIC IRS spectral range (8–14 μm) and resolution (10.8 cm-1) allow for quantitative mineralogy from modelling Reststrahlen bands of major rock-forming minerals (e.g., silicates, phosphates). Radiance cubes can be processed and modelled with an onboard high-performance computer to determine mineral abundances of plagioclase, high-Ca pyroxene, pigeonite, orthopyroxene, olivine, and glass. Regolith samples can be acquired, processed, and delivered to the X-ray instruments via multiple sample handling systems, but the pneumatic sampling systems developed by Honeybee Robotics [e.g., 2] are best suited for relatively low-cost missions that are being competed for the Moon (e.g., NASA’s Payloads and Research Investigations for the Surface of the Moon program). There are pneumatic sampling systems that collect surface material and other systems that pneumatically drill up to ~1 m below the surface, providing material that has not been space weathered and has not been affected by the lander’s exhaust. [1] Blake, D. F., Vaniman, D., Achilles, C., Anderson, R., Bish, D., et al. (2012). Space Sci. Rev. 170, 341-478. https://doi.org/10.1007/s11214-012-9905-1. [2] Zacny, K., Betts, B., Hedlund, M., Long, P., Gramlich, M., Tura, K., Chu, P., Jacob, A., Garcia, A. (2014). IEEE Aerospace Conference, 3-7 March 2014, Big Sky, MT, U.S.A.
Purpose: HDR brachytherapy consensus dose tolerance recommendations for organs at risk (OARs) remain widely debated. Prospective trials reporting metrics must be sufficiently data-dense to assess adverse affects and identify optimally predictive tolerances. We explore the tradeoffs between reporting dose-metrics versus volume-metrics and the potential impact on trial outcome analysis and tolerance recommendations. Methods: We analyzed 26 prostate patients receiving 15 Gy HDR single-fraction brachytherapy boost to 45 Gy external beam radiation therapy and 28 cervical patients receiving 28 Gy HDR brachytherapy monotherapy in 4 fractions using 2 implants. For each OAR structure, a robust linear regression fit was performed for the dose-metrics as a function of the volume-metrics. The plan quality information provided by recommended dose-metric and volume-metric values were compared. Results: For prostate rectal dose, D2cc and V75 lie close to the regression line, indicating they are similarly informative. Two outliers for prostate urethral dose are substantially different from the remaining cohort in terms of D0.1cc and V75, but not D1cc, suggesting the choice of reporting dose metric is essential. For prostate bladder and cervical bladder, rectum, and bowel, dose outliers are more apparent via V75 than recommended dose-metrics. This suggests that for prostate bladder dose and all cervical OAR doses, the recommended volume-metrics may be better predictors of clinical outcome than dose-metrics. Conclusion: For plan acceptance criteria, dose and volume-metrics are reciprocally equivalent. However, reporting dosemetrics or volume-metrics alone provides substantially different information. Our results suggest that volume-metrics may be more sensitive to differences in planned dose, and if one metric must be chosen, volumemetrics are preferable. However, reporting discrete DVH points severely limits the ability to identify planning tolerances most predictive of adverse effects. Thus, we recommend that full OAR DVH reporting be required for future prospective trials.
NASA science publications have used the metric system of measurement since 1970. Although NASA has maintained a metric use policy since 1979, practical constraints have restricted actual use of metric units. In 1988, an amendment to the Metric Conversion Act of 1975 required the Federal Government to adopt the metric system except where impractical. In response to Public Law 100-418 and Executive Order 12770, NASA revised its metric use policy and developed this Metric Transition Plan. NASA's goal is to use the metric system for program development and functional support activities to the greatest practical extent by the end of 1995. The introduction of the metric system into new flight programs will determine the pace of the metric transition. Transition of institutional capabilities and support functions will be phased to enable use of the metric system in flight program development and operations. Externally oriented elements of this plan will introduce and actively support use of the metric system in education, public information, and small business programs. The plan also establishes a procedure for evaluating and approving waivers and exceptions to the required use of the metric system for new programs. Coordination with other Federal agencies and departments (through the Interagency Council on Metric Policy) and industry (directly and through professional societies and interest groups) will identify sources of external support and minimize duplication of effort.
Abstract Precipitation sustains life and supports human activities, making its prediction one of the most societally relevant challenges in weather and climate modeling. Limitations in modeling precipitation underscore the need for diagnostics and metrics to evaluate precipitation in simulations and predictions. While routine use of basic metrics is important for documenting model skill, more sophisticated diagnostics and metrics aimed at connecting model biases to their sources and revealing precipitation characteristics relevant to how model precipitation is used are critical for improving models and their uses. This paper illustrates examples of exploratory diagnostics and metrics including 1) spatiotemporal characteristics metrics such as diurnal variability, probability of extremes, duration of dry spells, spectral characteristics, and spatiotemporal coherence of precipitation; 2) process-oriented metrics based on the rainfall–moisture coupling and temperature–water vapor environments of precipitation; and 3) phenomena-based metrics focusing on precipitation associated with weather phenomena including low pressure systems, mesoscale convective systems, frontal systems, and atmospheric rivers. Together, these diagnostics and metrics delineate the multifaceted and multiscale nature of precipitation, its relations with the environments, and its generation mechanisms. The metrics are applied to historical simulations from phases 5 and 6 of the Coupled Model Intercomparison Project. Models exhibit diverse skill as measured by the suite of metrics, with very few models consistently ranked as top or bottom performers compared to other models in multiple metrics. Analysis of model skill across metrics and models suggests possible relationships among subsets of metrics, motivating the need for more systematic analysis to understand model biases for informing model development.