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Molecular Biology and Evolution Apr 2021Nearly all current Bayesian phylogenetic applications rely on Markov chain Monte Carlo (MCMC) methods to approximate the posterior distribution for trees and other...
Nearly all current Bayesian phylogenetic applications rely on Markov chain Monte Carlo (MCMC) methods to approximate the posterior distribution for trees and other parameters of the model. These approximations are only reliable if Markov chains adequately converge and sample from the joint posterior distribution. Although several studies of phylogenetic MCMC convergence exist, these have focused on simulated data sets or select empirical examples. Therefore, much that is considered common knowledge about MCMC in empirical systems derives from a relatively small family of analyses under ideal conditions. To address this, we present an overview of commonly applied phylogenetic MCMC diagnostics and an assessment of patterns of these diagnostics across more than 18,000 empirical analyses. Many analyses appeared to perform well and failures in convergence were most likely to be detected using the average standard deviation of split frequencies, a diagnostic that compares topologies among independent chains. Different diagnostics yielded different information about failed convergence, demonstrating that multiple diagnostics must be employed to reliably detect problems. The number of taxa and average branch lengths in analyses have clear impacts on MCMC performance, with more taxa and shorter branches leading to more difficult convergence. We show that the usage of models that include both Γ-distributed among-site rate variation and a proportion of invariable sites is not broadly problematic for MCMC convergence but is also unnecessary. Changes to heating and the usage of model-averaged substitution models can both offer improved convergence in some cases, but neither are a panacea.
Topics: Genetic Techniques; Markov Chains; Monte Carlo Method; Phylogeny
PubMed: 33185685
DOI: 10.1093/molbev/msaa295 -
Journal of the Air & Waste Management... Jun 2019Maritime greenhouse gas emissions are projected to increase significantly by 2050, highlighting the need for reliable inventories as a first step in analyzing ship...
Maritime greenhouse gas emissions are projected to increase significantly by 2050, highlighting the need for reliable inventories as a first step in analyzing ship emission control policies. The impact of ship power models on marine emissions inventories has garnered little attention, with most inventories employing simple, load-factor-based models to estimate ship power consumption. The availability of more expansive ship activity data provides the opportunity to investigate the inventory impacts of adopting complex power models. Furthermore, ship parameter fields can be sparsely populated in ship registries, making gap-filling techniques and averaging processes necessary. Therefore, it is important to understand of the impact of averaged ship parameters on ship power and emission estimations. This paper examines power estimation differences between results from two complex, resistance-based and two simple, load-factor-based power models on a baseline inventory with unique ship parameters. These models are additionally analyzed according to their sensitivities toward average ship parameters. Automated Identification System (AIS) data from a fleet of commercial marine vessels operating over a 6-month period off the coast of the southwestern United States form the basis of the analysis. To assess the inventory impacts of using averaged ship parameters, fleet-level carbon dioxide (CO) emissions are calculated using ship parameter data averaged across ship types and their subtype size classes. Each of the four ship power models are used to generate four CO emissions inventories, and results are compared with baseline estimates for the same sample fleet where no averaged values were used. The results suggest that a change in power model has a relatively high impact on emission estimates. They also indicate relatively little sensitivity, by all power models, to the use of ship characteristics averaged by ship and subtype. : Commercial marine vessel emissions inventories were calculated using four different models for ship engine power. The calculations used 6 months of Automated Identification System (AIS) data from a sample of 248 vessels as input data. The results show that more detailed, resistance-based models tend to estimate a lower propulsive power, and thus lower emissions, for ships than traditional load-factor-based models. Additionally, it was observed that emission calculations using averaged values for physical ship parameters had a minimal impact on the resulting emissions inventories.
Topics: Algorithms; Carbon Dioxide; Environmental Monitoring; Environmental Pollutants; Forecasting; Ships; Vehicle Emissions
PubMed: 30794070
DOI: 10.1080/10962247.2019.1580229 -
Philosophical Transactions. Series A,... Jun 2022The problem of finding bounds of time-averaged characteristics of dynamical systems, such as the bound on the mean energy dissipation rate in a turbulent flow governed...
The problem of finding bounds of time-averaged characteristics of dynamical systems, such as the bound on the mean energy dissipation rate in a turbulent flow governed by incompressible Navier-Stokes equations, is considered. It is shown that the direct method described by Seis (2015 , 591-603. (doi:10.1017/jfm.2015.384)) and the auxiliary functional method by Chernyshenko (2014 , 20130350. (doi:10.1098/rsta.2013.0350)) are related and can lead to the same bound. The well-known background flow method of Doering and Constantin is equivalent to the auxiliary functional method with a quadratic auxiliary functional. The known implementations of the direct method apparently also correspond to quadratic auxiliary functionals. The findings are illustrated by the analysis of the plane Couette flow. Three routes of further progress using non-quadratic auxiliary functionals and at the same time allowing to use the experience accumulated with the background flow method are proposed: making the balance parameter dependent on the energy, making the background flow time-dependent in a specific way and adding helicity to the auxiliary functional. This article is part of the theme issue 'Mathematical problems in physical fluid dynamics (part 1)'.
Topics: Hydrodynamics
PubMed: 35465714
DOI: 10.1098/rsta.2021.0044 -
Magnetic Resonance in Medicine Jun 2023To develop a motion-robust reconstruction technique for free-breathing cine imaging with multiple averages.
PURPOSE
To develop a motion-robust reconstruction technique for free-breathing cine imaging with multiple averages.
METHOD
Retrospective motion correction through multiple average k-space data elimination (REMAKE) was developed using iterative removal of k-space segments (from individual k-space samples) that contribute most to motion corruption while combining any remaining segments across multiple signal averages. A variant of REMAKE, termed REMAKE+, was developed to address any losses in SNR due to k-space information removal. With REMAKE+, multiple reconstructions using different initial conditions were performed, co-registered, and averaged. Both techniques were validated against clinical "standard" signal averaging reconstruction in a static phantom (with simulated motion) and 15 patients undergoing free-breathing cine imaging with multiple averages. Quantitative analysis of myocardial sharpness, blood/myocardial SNR, myocardial-blood contrast-to-noise ratio (CNR), as well as subjective assessment of image quality and rate of diagnostic quality images were performed.
RESULTS
In phantom, motion artifacts using "standard" (RMS error [RMSE]: 2.2 ± 0.5) were substantially reduced using REMAKE/REMAKE+ (RMSE: 1.5 ± 0.4/1.0 ± 0.4, p < 0.01). In patients, REMAKE/REMAKE+ led to higher myocardial sharpness (0.79 ± 0.09/0.79 ± 0.1 vs. 0.74 ± 0.12 for "standard", p = 0.004/0.04), higher image quality (1.8 ± 0.2/1.9 ± 0.2 vs. 1.6 ± 0.4 for "standard", p = 0.02/0.008), and a higher rate of diagnostic quality images (99%/100% vs. 94% for "standard"). Blood/myocardial SNR for "standard" (94 ± 30/33 ± 10) was higher vs. REMAKE (80 ± 25/28 ± 8, p = 0.002/0.005) and tended to be lower vs. REMAKE+ (105 ± 33/36 ± 12, p = 0.02/0.06). Myocardial-blood CNR for "standard" (61 ± 22) was higher vs. REMAKE (53 ± 19, p = 0.003) and lower vs. REMAKE+ (69 ± 24, p = 0.007).
CONCLUSIONS
Compared to "standard" signal averaging reconstruction, REMAKE and REMAKE+ provide improved myocardial sharpness, image quality, and rate of diagnostic quality images.
Topics: Humans; Magnetic Resonance Imaging, Cine; Retrospective Studies; Heart; Respiration; Motion; Artifacts
PubMed: 36763898
DOI: 10.1002/mrm.29613 -
International Journal of Environmental... Mar 2022The aim of this study was to examine the sleep-wake behaviour of 200-mile ultra-marathon runners before, during, and after a competition. A longitudinal, observational... (Observational Study)
Observational Study
The aim of this study was to examine the sleep-wake behaviour of 200-mile ultra-marathon runners before, during, and after a competition. A longitudinal, observational study was conducted to collect the sleep data of four (two females; mean age: 45.5 ± 3.1 years) runners competing in a 200-mile ultra-marathon (N = 4). Wrist-worn activity monitors, in conjunction with self-report sleep diaries, were used to measure sleep, beginning seven days prior to the race and concluding seven days following the race (2-19 June 2021). Descriptive analysis of runners' subjective and objective sleep data was conducted. All runners completed the 200-mile event in an average of 82.5 ± 7.1 h. On average, runners obtained 4.7 ± 3.0 h of sleep from 4.8 ± 2.4 sleep episodes, averaging 59.9 ± 49.2 min of sleep per episode. Runners averaged 6.0 ± 1.3 h of sleep per night in the week before the competition and 6.3 ± 1.3 h per night in the week following the competition. Runners in the 200-mile (326 km) ultra-marathon drastically restricted their sleep. However, obtained sleep, the number of sleep episodes, and sleep episode length were greater than those previously reported with 100-mile (161 km) runners. In-race sleep data suggest an increased need for sleep as race duration increases. Interestingly, runners obtained less than the recommended ~8 h of sleep per night, in both pre-race and post-race phases of the competition.
Topics: Adult; Female; Humans; Longitudinal Studies; Marathon Running; Middle Aged; Physical Endurance; Running; Sleep
PubMed: 35270699
DOI: 10.3390/ijerph19053006 -
Journal of Vision Jan 2023Many studies have shown that observers can accurately estimate the average feature of a group of objects. However, the way the visual system relies on the information...
Many studies have shown that observers can accurately estimate the average feature of a group of objects. However, the way the visual system relies on the information from each individual item is still under debate. Some models suggest some or all items sampled and averaged arithmetically. Another strategy implies "robust averaging," when middle elements gain greater weight than outliers. One version of a robust averaging model was recently suggested by Teng et al. (2021), who studied motion direction averaging in skewed feature distributions and found systematic biases toward their modes. They interpreted these biases as evidence for robust averaging and suggested a probabilistic weighting model based on minimization of the virtual loss function. In four experiments, we replicated systematic skew-related biases in another feature domain, namely, orientation averaging. Importantly, we show that the magnitude of the bias is not determined by the locations of the mean or mode alone, but is substantially defined by the shape of the whole feature distribution. We test a model that accounts for such distribution-dependent biases and robust averaging in a biologically plausible way. The model is based on well-established mechanisms of spatial pooling and population encoding of local features by neurons with large receptive fields. Both the loss functions model and the population coding model with a winner-take-all decoding rule accurately predicted the observed patterns, suggesting that the pooled population response model can be considered a neural implementation of the computational algorithms of information sampling and robust averaging in ensemble perception.
Topics: Humans; Motion Perception; Neurons; Motion
PubMed: 36602815
DOI: 10.1167/jov.23.1.5 -
Kidney International Oct 2003Understanding the clinical variability of hemoglobin measurements in epoetin-treated hemodialysis patients is important, particularly when this therapy is aimed at...
BACKGROUND
Understanding the clinical variability of hemoglobin measurements in epoetin-treated hemodialysis patients is important, particularly when this therapy is aimed at maintaining patient hemoglobin levels within a narrow range, such as the 11 to 12 g/dL range recommended in National Kidney Foundation Kidney Dialysis Outcomes Quality Initiative (NKF-K/DOQI) guidelines. This study examines hemoglobin variability under conditions of standard clinical practice in epoetin-treated hemodialysis patients.
METHODS
We studied 987 hemodialysis patients participating in an observational retrospective study that evaluated anemia management practices from October 1, 1996 to December 31, 1997 at 11 United States dialysis centers that were randomly selected from a pool of nearly all United States dialysis facilities. Each participating facility maintained its own anemia management protocols without specific anemia management recommendations or interventions made as part of this study. Hemoglobin variability was determined by calculating the 1-month and 2- to 6-month rolling average hemoglobin for each patient. The range of mean hemoglobin values that included the middle 50% (25th to 75th percentile), 80% (10th to 90th percentile), and 90% (5th to 95th percentile) of values were determined. The hemoglobin ranges that included 1 standard deviation (SD) (67%) of the study values and 2 SD (95%) of the study values for each time period were calculated.
RESULTS
The mean hemoglobin was between 10.9 and 11.2 g/dL throughout the study. The hemoglobin range encompassing 50%, 80%, and 90% of values from a single month was 1.7, 3.3, and 4.4 g/dL, respectively. A progressive narrowing in the range of hemoglobin values encompassed by each percentile grouping (i.e., hemoglobin variability) was observed as longer rolling intervals were averaged. The hemoglobin range within the 25th to 75th percentile was 1.7 g/dL using single-month hemoglobin values and 1.1 g/dL using a 6-month rolling average. The range of hemoglobin values that encompassed 90% of patients was 4.4 g/dL using single-month values, 3.7 g/dL using 3-month rolling averages, and 3.2 g/dL using 6-month rolling averages. Fewer than 50% of patients had hemoglobin values within the 1.0 g/dL NKF-K/DOQI recommended range, even when a 6-month rolling average was applied. When hemoglobin values were measured for 1 month, 1 SD was 1.4 g/dL; for the 3-month rolling average, 1 SD was 1.1 g/dL; and for the 4-, 5-, and 6-month rolling averages, 1 SD was 1.0 g/dL. Greater hemoglobin variability correlated with higher mean corpuscular hemoglobin (P = 0.003) and serum ferritin (P = 0.047), and inversely correlated with age (P = 0.006) and serum albumin (P = 0.0001).
CONCLUSION
Substantial variability occurs in hemoglobin values in epoetin-treated hemodialysis patients. The NKF-K/DOQI recommended hemoglobin range appears to be too narrow in clinical practice. Expanding the target range and use of rolling average hemoglobin intervals of 3 to 6 months as a clinical and quality assurance measure avoids clinical variability inherent with the use of isolated hemoglobin values or single-month hemoglobin averages.
Topics: Aged; Erythropoietin; Female; Hemoglobins; Humans; Male; Middle Aged; Recombinant Proteins; Renal Dialysis; Retrospective Studies; Time Factors
PubMed: 12969173
DOI: 10.1046/j.1523-1755.2003.00229.x -
Journal of Cardiovascular Magnetic... Feb 2016Traditional cine imaging for cardiac functional assessment requires breath-holding, which can be problematic in some situations. Free-breathing techniques have relied on...
BACKGROUND
Traditional cine imaging for cardiac functional assessment requires breath-holding, which can be problematic in some situations. Free-breathing techniques have relied on multiple averages or real-time imaging, producing images that can be spatially and/or temporally blurred. To overcome this, methods have been developed to acquire real-time images over multiple cardiac cycles, which are subsequently motion corrected and reformatted to yield a single image series displaying one cardiac cycle with high temporal and spatial resolution. Application of these algorithms has required significant additional reconstruction time. The use of distributed computing was recently proposed as a way to improve clinical workflow with such algorithms. In this study, we have deployed a distributed computing version of motion corrected re-binning reconstruction for free-breathing evaluation of cardiac function.
METHODS
Twenty five patients and 25 volunteers underwent cardiovascular magnetic resonance (CMR) for evaluation of left ventricular end-systolic volume (ESV), end-diastolic volume (EDV), and end-diastolic mass. Measurements using motion corrected re-binning were compared to those using breath-held SSFP and to free-breathing SSFP with multiple averages, and were performed by two independent observers. Pearson correlation coefficients and Bland-Altman plots tested agreement across techniques. Concordance correlation coefficient and Bland-Altman analysis tested inter-observer variability. Total scan plus reconstruction times were tested for significant differences using paired t-test.
RESULTS
Measured volumes and mass obtained by motion corrected re-binning and by averaged free-breathing SSFP compared favorably to those obtained by breath-held SSFP (r = 0.9863/0.9813 for EDV, 0.9550/0.9685 for ESV, 0.9952/0.9771 for mass). Inter-observer variability was good with concordance correlation coefficients between observers across all acquisition types suggesting substantial agreement. Both motion corrected re-binning and averaged free-breathing SSFP acquisition and reconstruction times were shorter than breath-held SSFP techniques (p < 0.0001). On average, motion corrected re-binning required 3 min less than breath-held SSFP imaging, a 37% reduction in acquisition and reconstruction time.
CONCLUSIONS
The motion corrected re-binning image reconstruction technique provides robust cardiac imaging that can be used for quantification that compares favorably to breath-held SSFP as well as multiple average free-breathing SSFP, but can be obtained in a fraction of the time when using cloud-based distributed computing reconstruction.
Topics: Adult; Algorithms; Cloud Computing; Feasibility Studies; Female; Heart Diseases; Humans; Image Interpretation, Computer-Assisted; Magnetic Resonance Imaging, Cine; Male; Middle Aged; Observer Variation; Predictive Value of Tests; Reproducibility of Results; Respiration; Stroke Volume; Ventricular Function, Left; Workflow; Young Adult
PubMed: 26915830
DOI: 10.1186/s12968-016-0231-8 -
Cureus May 2021Background The Connecticut Orthopaedic Institute (COI) conceptualized a Pivot Plan during an elective surgery moratorium at the beginning of the severe acute respiratory...
Background The Connecticut Orthopaedic Institute (COI) conceptualized a Pivot Plan during an elective surgery moratorium at the beginning of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic with the goal of planning and executing orthopedic procedures safely. With the resumption of elective surgeries and the continued planning of surgical recovery over the months (and possibly years) to follow, facilities must brace themselves for repeat waves of COVID-19. Thereby, herein we share the Pivot Plan, its implementation process, evaluation of patient safety, and program performance during a pandemic. This could inform the efforts of other institutions seeking to restart non-emergent surgeries during similarly trying times in the future. Methods The COI formed a multidisciplinary team of leaders that met weekly to design a Pivot Plan and a dashboard to guide the resumption of surgeries and assess the performance of the Pivot Plan. The plan revolved around four domains: safety, space, staff, and supplies. It was implemented in two COI-affiliated facilities: MidState Medical Center (MMC) and St. Vincent's Medical Center (SVMC). Monthly metrics from May to November 2020 were compared to the six-month averages for the pre-pandemic baseline period from September 2019 to February 2020. Results The total number (N) of elective orthopaedic cases prior to the pandemic pre-COVID averaged 372 cases per month for MMC and 197 cases for SVMC. During the pandemic post-COVID, N averaging at 361 for MMC and 243 for SVMC illustrates COI was able to perform elective surgeries amid a worsening pandemic. Same-day (SD) discharge rates for total joint arthroplasty (TJA) pre-COVID averaged 8% for MMC and 3% for SVMC. Post-COVID, the SD average was 16.7% for MMC and 11.4% for SVMC. This data indicates that orthopaedic providers were cognizant of length of stay in order to reduce the risk of in-hospital exposure to COVID-19. The 30-day readmission (30R) rate for TJA pre-COVID averaged 1.4% for MMC and 2.7% for SVMC. A high level of care and follow-up is reflected in a lower average 30R post-COVID, 1.1% for both MMC and SVMC. Transitions for TJA patients to their home settings after surgery also reflect the quality of care and the efficiency of the patient throughput process with necessary precautions in place. Post-COVID, the patient transition to home (T) averaged 98.1% for MMC and 97.5% for SVMC compared to T = 96.8% for MMC and 88% for SVMC pre-COVID. No patients experienced deep vein thrombosis or pulmonary embolism during the time period of the project. Positive COVID-19 diagnosis 23 days after discharge was 0% at MMC and 0.2% at SVMC. Conclusion The COI Pivot Plan was successfully implemented at two different hospitals offering elective orthopaedic surgeries to a varied patient population. The precautions taken by COI were effective in controlling the spread of the SARS-CoV-2 virus while returning to elective orthopaedic surgery. Furthermore, data collected before and after the onset of the COVID-19 pandemic indicated that program performance and quality improved.
PubMed: 34150411
DOI: 10.7759/cureus.15077 -
Boundary-layer Meteorology 2019When canopy flows are horizontally averaged to obtain mean profiles, the averaging operation can be defined either as an intrinsic average, normalized by the variable...
When canopy flows are horizontally averaged to obtain mean profiles, the averaging operation can be defined either as an intrinsic average, normalized by the variable fluid volume, or as a superficial average, normalized by the total volume including solid canopy elements. Properties of spatial averages have been explored extensively in the context of flow through plant canopies, albeit with the assumption that the solid volume fraction is negligible. Without this simplification, properties relevant for non-linear terms apply to intrinsic averages while properties of gradients apply to superficial averages. To avoid inconsistencies and inaccuracies the impact of a non-negligible solid volume fraction should be considered carefully when interpreting mean profiles, when deriving mathematical relations for averaged quantities, and when introducing modelling assumptions for such terms. On this basis, we review the definitions and properties of the method of volume averaging, as developed in the more general context of flow through porous media, and discuss its application to urban canopy flows. We illustrate the properties of intrinsic and superficial averages and their effect on mean profiles with example data from a simulation of flow over constant-height cubes.
PubMed: 31708585
DOI: 10.1007/s10546-019-00470-3