We apply Bayesian inference to instrument calibration and experimental-data uncertainty analysis for the specific application of measuring radiative intensity with a narrow-angle radiometer. We develop a physics-based instrument model that describes temporally varying radiative intensity, the indirectly measured quantity of interest, as a function of scenario and model parameters. We identify a set of five uncertain parameters, find their probability distributions (the posterior or inverse problem) given the calibration data by applying Bayes’ Theorem, and employ a local linearization to marginalize the nuisance parameters resulting from errors-in-variables. We then apply the instrument model to a new scenario that is the intended use of the instrument, a 1.5 MW coal-fired furnace. Unlike standard error propagation, this Bayesian method infers values for the five uncertain parameters by sampling from the posterior distribution and then computing the intensity with quantifiable uncertainty at the point of a new, in-situ furnace measurement (the posterior predictive or forward problem). Given the instrument-model context of this analysis, the propagated uncertainty provides a significant proportion of the measurement error for each in-situ furnace measurement. With this approach, we produce uncertainties at each temporal measurement of the radiative intensity in the furnace, successfully identifying temporal variations that were otherwise indistinguishable from measurement uncertainty.
Localization of the components of the cardiac conduction system (CCS) is essential for many therapeutic procedures in cardiac surgery and interventional cardiology. While histological studies provided fundamental insights into CCS localization, this information is incomplete and difficult to translate to aid in intraprocedural localization. To advance our understanding of CCS localization, we set out to establish a framework for quantifying nodal region morphology. Using this framework, we quantitatively analyzed the sinoatrial node (SAN) and atrioventricular node (AVN) in ovine with menstrual age ranging from 4.4 to 58.3 months. In particular, we studied the SAN and AVN in relation to the epicardial and endocardial surfaces, respectively. Using anatomical landmarks, we excised the nodes and adjacent tissues, sectioned those at a thickness of 4 µm at 100 µm intervals, and applied Masson’s trichrome stain to the sections. These sections were then imaged, segmented to identify nodal tissue, and analyzed to quantify nodal depth and superficial tissue composition. The minimal SAN depth ranged between 20 and 926 µm. AVN minimal depth ranged between 59 and 1192 µm in the AVN extension region, 49 and 980 µm for the compact node, and 148 and 888 µm for the transition to His Bundle region. Using a logarithmic regression model, we found that minimal depth increased logarithmically with age for the AVN (R2=0.818, P=0.002). Also, the myocardial overlay of the AVN was heterogeneous within different regions and decreased with increasing age. Age associated alterations of SAN minimal depth were insignificant. Our study presents examples of characteristic tissue patterns superficial to the AVN and within the SAN. We suggest that the presented framework provides quantitative information for CCS localization. Our studies indicate that procedural methods and localization approaches in regions near the AVN should account for the age of patients in cardiac surgery and interventional cardiology.
This dataset contains GIS map data and monitoring datasets collected between 2018 and 2022 at the Courthouse Mesa rock slope instability near Moab, Utah. Map data consist of an orthophoto, a polyline shapefile delineating mapped surficial cracks, and a point shapefile showing the locations of crack width monitoring points (M1–M5) and a vibrating wire crackmeter. Monitoring data include four years of continuous crack aperture measurements from the crackmeter, periodic crack width measurements from M1–M5, and three sets of air temperature measurements recorded between 2018 and 2022. Air temperatures were measured at the surface and inside the crack at several depths throughout the monitoring period.
This dataset contains code used to generate and the results of 2D numerical modeling simulations of ambient resonance in damaged rock slopes. All simulations were performed using the Universal Distinct Element Code (UDEC) version 7.0. We simulated progressive damage for three different landslide types: slab toppling, flexural toppling, and planar sliding. For each scenario we simulated several stages of progressive rock slope damage. Subsequently, we recorded the resonance response of the rock slope at each stage by measuring x-direction velocity at one or more measuring points throughout the model.
Abstract from Paper (Lange et. al, 2022): Atypical atrial flutter is seen post-ablation in patients, and it can be challenging to map. These flutters are typically set up around areas of scar in the left atrium. MRI can reliably identify left atrial scar. We propose a personalized computational model using patient specific scar information, to generate a monodomain model. In the model conductivities are adjusted for different tissue regions and flutter was induced with a premature pacing protocol. The model was tested prospectively in patients undergoing atypical flutter ablation. The simulation-predicted flutters were visualized and presented to clinicians. Validation of the computational model was motivated by recording from electroanatomical mapping. These personalized models successfully predicted clinically observed atypical flutter circuits and at times even better than invasive maps leading to flutter termination at isthmus sites predicted by the model.
The objective of using the wireless sensors was to improve understanding of the heterogeneity of healthcare worker (HCW) contact with patients and the physical environment in patients’ rooms. The framework and design were based on contact networks with a) nodes defined by HCW’s, rooms, and items in the room and b) edges defined by HCW’s in the room, near the bed, and touching items. Nodes had characteristics of HCW role and room number. Edges had characteristics of day, start time, and duration. Thus, patterns and heterogeneity could be understood within contexts of time, space, roles, and patient characteristics. At the University of Utah Hospital Cardiovascular ICU (CVICU), a 20-bed unit, we collected data for 54 days. HCW contact with patients was measured using wireless sensors to capture time spent in patient rooms as well as time spent near the patient bed. HCW contact with the physical environment was measured using wireless sensors on the following items in patient rooms: door, sink, toilet, over-bed table, keyboard, vital signs monitor touchscreen, and cart. HCW’s clipped a sensor to their clothing or lanyard.
The purpose of this derived dataset was to analyze menstrual cycle lengths in relation to lunar calendar. This datafile of start and end date of 3324 menstrual cycles of 581 women is part of a combined dataset of three cohorts of heterosexually active women who received instruction in the Creighton Model FertilityCare System (CrM) through centres across the United States and Canada. The CrM has standardised protocols for teaching women how to observe, record, and interpret daily vaginal discharge from bleeding and cervical fluid on a daily diary, called a CrM chart, and to use these standardised observations to identify the estimated time of ovulation and days when intercourse is likely to result in pregnancy. The cohorts included: "Creighton Model Effectiveness, Intentions, and Behaviours Assessment" (CEIBA) (2009–2013), a prospective cohort of women without known subfertility, aimed to evaluate and classify pregnancy rates and pregnancy intentions during use of the CrM; "Creighton Model MultiCenter Fecundability Study" (CMFS) (1990–1996), a retrospective cohort of presumably fertile and subfertile women using CrM, aimed to assess the relationship between vulvar mucus observations and the day and cycle-specific probabilities of conception; and "Time to Pregnancy in Normal Fertility" (TTP) (2003–2006), a parallel-randomised trial, which aimed to assess the impact of CrM use on time to pregnancy in couples of proven fertility trying to conceive. Each of the cohorts aimed to include heterosexually active couples with normal fecundity. Eligibility criteria were assessed by women's responses to the CrM general intake form and/or a screening questionnaire. Eligibility requirements in the original studies included women, age 18–40 years old (upper limit of 35 years for TTP), not pregnant at entry, having regular menstrual bleeding, and not breast feeding (CMFS and TTP), or if breast feeding, not doing so exclusively (CEIBA). Recent users of oral contraceptives had to have at least one menstrual bleed (CEIBA) or two menstrual bleeds (TTP) since stopping the oral contraceptives; however, for CMFS there was no restriction for time since discontinuing oral contraceptives. All studies also required normal menstrual patterns since last use of depo-medroxy-progesterone acetate or a hormonal intra-uterine device.