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Discrete-event simulation models generate random variates from input distributions and compute outputs according to the simulation logic. The input distributions are typically fitted to finite real-world data and thus are subject to estimation errors that can propagate to the simulation outputs: an issue commonly known as input uncertainty (IU). This paper investigates quantifying IU using the output confidence intervals (CIs) computed from bootstrap quantile estimators. The standard direct bootstrap method has overcoverage due to convolution of the simulation error and IU; however, the brute-force way of washing away the former is computationally demanding. We present two new bootstrap methods to enhance direct resampling in both statistical and computational efficiencies using shrinkage strategies to down-scale the variabilities encapsulated in the CIs. Our asymptotic analysis shows how both approaches produce tight CIs accounting for IU under limited input data and simulation effort along with the simulation sample-size requirements relative to the input data size. We demonstrate performances of the shrinkage strategies with several numerical experiments and investigate the conditions under which each method performs well. We also show advantages of nonparametric approaches over parametric bootstrap when the distribution family is misspecified and over metamodel approaches when the dimension of the distribution parameters is high. History: Accepted by Bruno Tuffin, Area Editor for Simulation. Funding: This work was supported by the National Science Foundation [CAREER CMMI-1834710, CAREER CMMI-2045400, DMS-1854659, and IIS-1849280]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2022.0044 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2022.0044 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ . 

ABSTRACT IntroductionCurrent wearables that collect heart rate and acceleration were not designed for children and/or do not allow access to raw signals, making them fundamentally unverifiable. This study describes the creation and calibration of an open-source multichannel platform (PATCH) designed to measure heart rate and acceleration in children ages 3–8 yr. MethodsChildren (N = 63; mean age, 6.3 yr) participated in a 45-min protocol ranging in intensities from sedentary to vigorous activity. Actiheart-5 was used as a comparison measure. We calculated mean bias, mean absolute error (MAE) mean absolute percent error (MA%E), Pearson correlations, and Lin’s concordance correlation coefficient (CCC). ResultsMean bias between PATCH and Actiheart heart rate was 2.26 bpm, MAE was 6.67 bpm, and M%E was 5.99%. The correlation between PATCH and Actiheart heart rate was 0.89, and CCC was 0.88. For acceleration, mean bias was 1.16 mg and MAE was 12.24 mg. The correlation between PATCH and Actiheart was 0.96, and CCC was 0.95. ConclusionsThe PATCH demonstrated clinically acceptable accuracies to measure heart rate and acceleration compared with a research-grade device. 

The purpose of this study was to evaluate the reliability and validity of the raw accelerometry output from research-grade and consumer wearable devices compared to accelerations produced by a mechanical shaker table. Raw accelerometry data from a total of 40 devices (i.e., n = 10 ActiGraph wGT3X-BT, n = 10 Apple Watch Series 7, n = 10 Garmin Vivoactive 4S, and n = 10 Fitbit Sense) were compared to reference accelerations produced by an orbital shaker table at speeds ranging from 0.6 Hz (4.4 milligravity-mg) to 3.2 Hz (124.7mg). Two-way random effects absolute intraclass correlation coefficients (ICC) tested inter-device reliability. Pearson product moment, Lin’s concordance correlation coefficient (CCC), absolute error, mean bias, and equivalence testing were calculated to assess the validity between the raw estimates from the devices and the reference metric. Estimates from Apple, ActiGraph, Garmin, and Fitbit were reliable, with ICCs = 0.99, 0.97, 0.88, and 0.88, respectively. Estimates from ActiGraph, Apple, and Fitbit devices exhibited excellent concordance with the reference CCCs = 0.88, 0.83, and 0.85, respectively, while estimates from Garmin exhibited moderate concordance CCC = 0.59 based on the mean aggregation method. ActiGraph, Apple, and Fitbit produced similar absolute errors = 16.9mg, 21.6mg, and 22.0mg, respectively, while Garmin produced higher absolute error = 32.5mg compared to the reference. ActiGraph produced the lowest mean bias 0.0mg (95%CI = -40.0, 41.0). Equivalence testing revealed raw accelerometry data from all devices were not statistically significantly within the equivalence bounds of the shaker speed. Findings from this study provide evidence that raw accelerometry data from Apple, Garmin, and Fitbit devices can be used to reliably estimate movement; however, no estimates were statistically significantly equivalent to the reference. Future studies could explore device-agnostic and harmonization methods for estimating physical activity using the raw accelerometry signals from the consumer wearables studied herein. 

We apply a recently developed measurement technique for methane (CH4) isotopologues* (isotopic variants of CH4—13CH4, 12CH3D, 13CH3D, and 12CH2D2) to identify contributions to the atmospheric burden from fossil fuel and microbial sources. The aim of this study is to constrain factors that ultimately control the concentration of this potent greenhouse gas on global, regional, and local levels. While predictions of atmospheric methane isotopologues have been modeled, we present direct measurements that point to a different atmospheric methane composition and to a microbial flux with less clumping (greater deficits relative to stochastic) in both 13CH3D and 12CH2D2 than had been previously assigned. These differences make atmospheric isotopologue data sufficiently sensitive to variations in microbial to fossil fuel fluxes to distinguish between emissions scenarios such as those generated by different versions of EDGAR (the Emissions Database for Global Atmospheric Research), even when existing constraints on the atmospheric CH4 concentration profile as well as traditional isotopes are kept constant. 

Lead-208 is the heaviest known doubly magic nucleus and its structure is therefore of special interest. Despite this magicity, which acts to provide a strong restorative force toward sphericity, it is known to exhibit both strong octupole correlations and some of the strongest quadrupole collectivity observed in doubly magic systems. In this Letter, we employ state-of-the-art experimental equipment to conclusively demonstrate, through four Coulomb-excitation measurements, the presence of a large, negative, spectroscopic quadrupole moment for both the vibrational octupole $3_1^{-}$and quadrupole $2_1^{+}$state, indicative of a preference for prolate deformation of the states. The observed quadrupole moment is discussed in the context of the expected splitting of the $3^{-}\otimes 3^{-}$two-phonon states, due to the coupling of the quadrupole and octupole motion. These results are compared with theoretical values from three different methods, which are unable to reproduce both the sign and magnitude of this deformation. Thus, in spite of its well-studied nature, ${}^{208}\mathrm{Pb}$remains a puzzle for our understanding of nuclear structure. Published by the American Physical Society2025 

abstract The marine coastal region makes up just 10% of the total area of the global ocean but contributes nearly 20% of its total primary production and over 80% of fisheries landings. Unicellular phytoplankton dominate primary production. Climate variability has had impacts on various marine ecosystems, but most sites are just approaching the age at which ecological responses to longer term, unidirectional climate trends might be distinguished. All five marine pelagic sites in the US Long Term Ecological Research (LTER) network are experiencing warming trends in surface air temperature. The marine physical system is responding at all sites with increasing mixed layer temperatures and decreasing depth and with declining sea ice cover at the two polar sites. Their ecological responses are more varied. Some sites show multiple population or ecosystem changes, whereas, at others, changes have not been detected, either because more time is needed or because they are not being measured. 

Abstract BackgroundDiapause is a seasonal dormancy that allows organisms to survive unfavorable conditions and optimizes the timing of reproduction and growth. Emergence from diapause reverses the state of arrested development and metabolic suppression returning the organism to an active state. The physiological mechanisms that regulate the transition from diapause to post-diapause are still unknown. In this study, this transition has been characterized for the sub-arctic calanoid copepod Neocalanus flemingeri, a key crustacean zooplankter that supports the highly productive North Pacific fisheries. Transcriptional profiling of females, determined over a two-week time series starting with diapausing females collected from > 400 m depth, characterized the molecular mechanisms that regulate the post-diapause trajectory. ResultsA complex set of transitions in relative gene expression defined the transcriptomic changes from diapause to post-diapause. Despite low temperatures (5–6 °C), the switch from a “diapause” to a “post-diapause” transcriptional profile occurred within 12 h of the termination stimulus. Transcriptional changes signaling the end of diapause were activated within one-hour post collection and included the up-regulation of genes involved in the 20E cascade pathway, the TCA cycle and RNA metabolism in combination with the down-regulation of genes associated with chromatin silencing. By 12 h, females exhibited a post-diapause phenotype characterized by the up-regulation of genes involved in cell division, cell differentiation and multiple developmental processes. By seven days post collection, the reproductive program was fully activated as indicated by up-regulation of genes involved in oogenesis and energy metabolism, processes that were enriched among the differentially expressed genes. ConclusionsThe analysis revealed a finely structured, precisely orchestrated sequence of transcriptional changes that led to rapid changes in the activation of biological processes paving the way to the successful completion of the reproductive program. Our findings lead to new hypotheses related to potentially universal mechanisms that terminate diapause before an organism can resume its developmental program.