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24 results for “rate maximization”
Particle trajectories - Freilich et al. "Diversity of growth rates maximizes phytoplankton productivity in an eddying ocean"
<p>The files provided here are the offline particle trajectories analyzed in Freilich, Flierl, and Mahadevan “Diversity of growth rates maximizes phytoplankton productivity in an eddying ocean”</p> <p>Both files are sqlite databases containing information about the same particle trajectories which are identified by the variable “iD”</p> <p> </p> <p>ini_day135_z115_forward_biology.db contains nutrient concentration on particle trajectories. A different biological rate lambda is used for each variable denoted NX where X is 0-13. The rates are: 0.015,0.075,0.15,0.3,0.75,1.5,3,10,15,20,50,75,100,120</p> <p>The variable DOY is the model day. </p> <p> </p> <p>ini_day135_z115_physical_forward.db contains the physical variables on particle trajectories. The variables are:</p> <p>x - east-west position</p> <p>y - north-south position</p> <p>z - vertical position</p> <p>u - east-west velocity</p> <p>v - north-south velocity</p> <p>w - vertical velocity</p> <p>vorticity - vertical component of relative vorticity</p>
Expectation-Maximization enables phylogenetic dating under a Categorical Rate Model
<div> <div> <div> <p>Dating phylogenetic trees to obtain branch lengths in the unit of time is essential for many downstream applications but has remained challenging. Dating requires inferring mutation rates that can change across the tree. While we can assume to have information about a small subset of nodes from the fossil record or sampling times (for fast-evolving organisms), inferring the ages of the other nodes essentially requires extrapolation and interpolation. Assuming a clock model that defines a distribution over rates, we can formulate dating as a constrained maximum likelihood (ML) estimation problem. While ML dating methods exist, their accuracy degrades in the face of model misspecification where the assumed parametric statistical clock model vastly differs from the true distribution. Notably, existing methods tend to assume rigid, often unimodal rate distributions. A second challenge is that the likelihood function involves an integral over the continuous domain of the rates and often leads to difficult non-convex optimization problems. To tackle these two challenges, we propose a new method called Molecular Dating using Categorical-models (MD-Cat). MD-Cat uses a categorical model of rates inspired by non-parametric statistics and can approximate a large family of models by discretizing the rate distribution into k categories. Under this model, we can use the Expectation-Maximization (EM) algorithm to co-estimate rate categories and branch lengths in the time unit. Our model has fewer assumptions about the true clock model than parametric models such as Gamma or LogNormal distribution. Our results on two simulated and real datasets of Angiosperms and HIV and a wide selection of rate distributions show that MD-Cat is often more accurate than the alternatives, especially on datasets with nonmodal or multimodal clock models.</p> </div> </div> </div>
Expectation-Maximization enables phylogenetic dating under a Categorical Rate Model
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Scalable Digital Delivery of Evidence-based Training for Professionals to Maximize Treatment Rates of OUD in Families
ClinicalTrials.gov study NCT05875142. IPD Sharing: NO. Countries: 1. Publications: 0.
Data from: Do the high energy lifestyles of shorebirds result in high maximal metabolic rates? - Basal and maximal metabolic rates in least and pectoral sandpipers during migration
Shorebirds have high resting and field metabolic rates relative to many other bird groups, and this is posited to be related to their high-energy lifestyle. Maximum metabolic outputs for cold or exercise are also often high for bird groups with energetically demanding lifestyles. Moreover, shorebirds demonstrate flexible basal and maximal metabolic rates, which vary with changing energy demands throughout the annual cycle. Consequently, shorebirds might be expected to have high maximum metabolic rates, especially during migration periods. We captured least (Calidris minutilla) and pectoral (C. melanotos) sandpipers during spring and fall migration in southeastern South Dakota and measured maximal exercise metabolic rate (MMR; least sandpipers only), summit metabolic rate (Msum, maximal cold-induced metabolic rate) and basal metabolic rate (BMR, minimum maintenance metabolic rate) with open-circuit respirometry. BMR for both least and pectoral sandpipers exceeded allometric predictions by 3-14%, similar to other shorebirds, but Msum and MMR for both species were either similar to or lower than allometric predictions, suggesting that the elevated BMR in shorebirds does not extend to maximal metabolic capacities. Old World shorebirds show the highest BMR during the annual cycle on the Arctic breeding grounds. Similarly, least sandpiper BMR during migration was lower than on the Arctic breeding grounds, but this was not the case for pectoral sandpipers, so our data only partially support the idea of similar seasonal patterns of BMR variation in New World and Old World shorebirds. We found no correlations of BMR with either Msum or MMR for either raw or mass-independent data, suggesting that basal and maximum aerobic metabolic rates are modulated independently in these species.
Data from: Ecological influences and morphological correlates of resting and maximal metabolic rates across teleost fish species
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Data from: Do the high energy lifestyles of shorebirds result in high maximal metabolic rates? - Basal and maximal metabolic rates in least and pectoral sandpipers during migration
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Data from: Mass-independent maximal metabolic rate predicts geographic range size of placental mammals
1.Understanding the mechanisms driving geographic range sizes of species is a central issue in ecology, but remarkably few rules link physiology with the distributions of species. Maximal metabolic rate (MMR) during exercise is an important measure of physiological performance. It sets an upper limit to sustained activity and locomotor capacity, so MMR may influence ability to migrate, disperse, and maintain population connectivity. Using both conventional ordinary least squares (OLS) analyses and phylogenetically generalized least squares (PGLS), we tested whether MMR helps explain geographic range size in 51 species of placental mammals. 2.Log body mass alone (OLS r2 = 0.074, p = 0.053; PGLS r2 = 0.016, p = 0.373) and log MMR alone (OLS r2 = 0.140, p = 0.007; PGLS r2 = 0.061, p = 0.081) were weak predictors of log range size. 3.However, multiple regression of log body mass and log MMR accounted for over half of the variation in log range size (OLS R2 = 0.527, p < 0.001). The relationship was also strong after correcting for the phylogenetic non-independence (PGLS R2 = 0.417, p < 0.001). 4.In analyses restricted to rodents (34 species), neither log body mass alone (OLS r2 = 0.004, p = 0.720; PGLS r2 = 0.003, p = 0.77) nor log MMR alone was useful in predicting log geographic range size (OLS r2 = 0.008, p = 0.626; PGLS r2 = 0.046, p = 0.225), but multiple regressions of log body mass and log MMR accounted for roughly a third to a half of the variation in log range size (OLS R2= 0.443, p < 0.001, PGLS r2 = 0.381, p < 0.001). 5.Mass-independent MMR is a strong predictor of mass-independent geographic range size in placental mammals. The ability of body mass and MMR to explain nearly 50% of the variation in the geographic ranges of mammals is surprising and powerful, particularly when neither variable alone is strongly predictive. 6.A better understanding of MMR during exercise may be important to understanding the limits of geographic ranges of mammals, and perhaps other animal groups.
Data from: Mass-independent maximal metabolic rate predicts geographic range size of placental mammals
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Data from: Rate maximization and hyperbolic discounting in human experiential intertemporal decision making
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Data from: Digestive capacity and toxicity cause mixed diets in red knots that maximize energy intake rate
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Data from: Speeding up growth: selection for mass-independent maximal metabolic rate alters growth rates
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Data from: A strong response to selection on mass-independent maximal metabolic rate without a correlated response in basal metabolic rate
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Adaptive Approach to Neoadjuvant Therapy to Maximize Resection Rates for Pancreatic Adenocarcinoma
ClinicalTrials.gov study NCT04594772. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Maximal Rate of Force Development of Ankle Muscles and Functional Ability in Patients With Knee Osteoarthritis
ClinicalTrials.gov study NCT06063889. IPD Sharing: NO. Countries: 1. Publications: 0.
Maximal Effort-dependent Respiratory Flow Rates
ClinicalTrials.gov study NCT03197701. IPD Sharing: NO. Countries: 1. Publications: 0.
Phase II: Scalable Digital Delivery of CRAFT Training for Professionals to Maximize Treatment Rates of OUD in Families
ClinicalTrials.gov study NCT06685003. IPD Sharing: NO. Countries: 1. Publications: 0.
Milk Vs Wheat Protein Intake to Maximize Whole-body Protein Synthesis Rates in Healthy Older Adults
ClinicalTrials.gov study NCT06783075. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Sperm Separation Efficiency to Maximize Pregnancy Rates: MACS vs. FERTILE Chip
ClinicalTrials.gov study NCT04061486. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Scalable Digital Delivery of Evidence-based Training for Family to Maximize Treatment Admission Rates of Opioid Use Disorder in Loved Ones
ClinicalTrials.gov study NCT05666856. IPD Sharing: NO. Countries: 1. Publications: 0.
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International Brain Laboratory public data
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OpenNeuro
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