Fluid Tonicity Affects Peritoneal Characteristics Derived by 3-PORE Model

2019 ◽  
Vol 39 (3) ◽  
pp. 243-251 ◽  
Author(s):  
Joanna Stachowska-Pietka ◽  
Jan Poleszczuk ◽  
Josep Teixido-Planas ◽  
Josep Bonet-Sol ◽  
Maria I. Troya-Saborido ◽  
...  
Keyword(s):  
Model Fitting ◽  
Hydraulic Conductance ◽  
Membrane Properties ◽  
Patient Specific ◽  
Model Parameters ◽  
Peritoneal Membrane ◽  
Substantial Impact ◽  
Pore Model ◽  
Using Data ◽  
The Impact

Background It is typically assumed that within short time-frames, patient-specific peritoneal membrane characteristics are constant and do not depend on the initial fluid tonicity and dwell duration. The aim of this study was to check whether this assumption holds when membrane properties are estimated using the 3-pore model (3PM). Methods Thirty-two stable peritoneal dialysis (PD) patients underwent 3 8-hour peritoneal equilibration tests (PETs) with different glucose-based solutions (1.36%, 2.27%, and 3.86%). Temporary drainage was performed at 1 and 4 hours. Glucose, urea, creatinine, sodium, and phosphate concentrations were measured in dialysate and blood samples. Three-pore model parameters were estimated for each patient and each 8-hour PET separately. In addition, model parameters were estimated using data truncated to the initial 4 hours of peritoneal dwell. Results In all cases, model-estimated parameter values were within previously reported ranges. The peritoneal absorption (PA) and diffusive permeability for all solutes except sodium increased with fluid tonicity, with about 18% increase when switching from glucose 2.27% to 3.86%. Glucose peritoneal reflection coefficient and osmotic conductance (OsmCond), and fraction of hydraulic conductance for ultrasmall pores decreased with fluid tonicity (over 40% when switching from glucose 1.36%). Model fitting to the truncated 4-hour data resulted in little change in the parameters, except for PA, peritoneal hydraulic conductance, and OsmCond, for which higher values for the 4-hour dwell were found. Conclusion Initial fluid tonicity has a substantial impact on the 3PM-estimated characteristics of the peritoneal membrane, whereas the impact of dwell duration was relatively small and possibly influenced by the change in the patient's activity.

scholarly journals Applications of percolation theory to fungal spread with synergy

2011 ◽  
Vol 9 (70) ◽  
pp. 949-956 ◽  
Author(s):  
Jonathan J. Ludlam ◽  
Gavin J. Gibson ◽  
Wilfred Otten ◽  
Christopher A. Gilligan
Keyword(s):  
Control Strategies ◽  
Model Fitting ◽  
Structured Populations ◽  
Synergistic Interactions ◽  
Non Invasive ◽  
History Of ◽  
Disease Spreading ◽  
Strict Requirement ◽  
Using Data ◽  
The Impact

There is increasing interest in the use of the percolation paradigm to analyse and predict the progress of disease spreading in spatially structured populations of animals and plants. The wider utility of the approach has been limited, however, by several restrictive assumptions, foremost of which is a strict requirement for simple nearest-neighbour transmission, in which the disease history of an individual is influenced only by that of its neighbours. In a recent paper, the percolation paradigm has been generalized to incorporate synergistic interactions in host infectivity and susceptibility, and the impact of these interactions on the invasive dynamics of an epidemic has been demonstrated. In the current paper, we elicit evidence that such synergistic interactions may underlie transmission dynamics in real-world systems by first formulating a model for the spread of a ubiquitous parasitic and saprotrophic fungus through replicated populations of nutrient sites and subsequently fitting and testing the model using data from experimental microcosms. Using Bayesian computational methods for model fitting, we demonstrate that synergistic interactions are necessary to explain the dynamics observed in the replicate experiments. The broader implications of this work in identifying disease-control strategies that deflect epidemics from invasive to non-invasive regimes are discussed.

Constraining predictions of the carbon cycle using data

2011 ◽  
Vol 369 (1943) ◽  
pp. 1955-1966 ◽  
Author(s):  
P. J. Rayner ◽  
E. Koffi ◽  
M. Scholze ◽  
T. Kaminski ◽  
J.-L. Dufresne
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Carbon Cycle ◽  
Model Parameters ◽  
Atmospheric Measurements ◽  
Using Data ◽  
Linearized Model ◽  
The Impact ◽  
Data Assimilation System ◽  
Assimilation System

We use a carbon-cycle data assimilation system to estimate the terrestrial biospheric CO 2 flux until 2090. The terrestrial sink increases rapidly and the increase is stronger in the presence of climate change. Using a linearized model, we calculate the uncertainty in the flux owing to uncertainty in model parameters. The uncertainty is large and is dominated by the impact of soil moisture on heterotrophic respiration. We show that this uncertainty can be greatly reduced by constraining the model parameters with two decades of atmospheric measurements.

The effect of random-effects misspecification on classification accuracy

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Riham El Saeiti ◽  
Marta García-Fiñana ◽  
David M. Hughes
Keyword(s):  
Normal Distribution ◽  
Random Effects ◽  
Mixed Models ◽  
Classification Accuracy ◽  
Multivariate Normal Distribution ◽  
Joint Distribution ◽  
Patient Specific ◽  
Model Parameters ◽  
Multivariate Normal ◽  
The Impact

Abstract Mixed models are a useful way of analysing longitudinal data. Random effects terms allow modelling of patient specific deviations from the overall trend over time. Correlation between repeated measurements are captured by specifying a joint distribution for all random effects in a model. Typically, this joint distribution is assumed to be a multivariate normal distribution. For Gaussian outcomes misspecification of the random effects distribution usually has little impact. However, when the outcome is discrete (e.g. counts or binary outcomes) generalised linear mixed models (GLMMs) are used to analyse longitudinal trends. Opinion is divided about how robust GLMMs are to misspecification of the random effects. Previous work explored the impact of random effects misspecification on the bias of model parameters in single outcome GLMMs. Accepting that these model parameters may be biased, we investigate whether this affects our ability to classify patients into clinical groups using a longitudinal discriminant analysis. We also consider multiple outcomes, which can significantly increase the dimensions of the random effects distribution when modelled simultaneously. We show that when there is severe departure from normality, more flexible mixture distributions can give better classification accuracy. However, in many cases, wrongly assuming a single multivariate normal distribution has little impact on classification accuracy.

Reducing uncertainty in the calibration and validation of the INCA-N model by using soft data

2013 ◽  
Vol 45 (1) ◽  
pp. 73-88 ◽  
Author(s):  
J. Randall Etheridge ◽  
Ahti Lepistö ◽  
Kirsti Granlund ◽  
Katri Rankinen ◽  
François Birgand ◽  
...  
Keyword(s):  
Model Parameters ◽  
Soft Data ◽  
Catchment Scale ◽  
Adequate Model ◽  
Accurate Model ◽  
Scale Models ◽  
Nitrate Concentrations ◽  
Using Data ◽  
Stream Nitrate ◽  
The Impact

Process-based nutrient models are increasingly used to determine the impact of future changes in land use, agriculture production practices and climate on the quantity and timing of nutrients reaching surface waters. Calibration of catchment-scale models to observed conditions can be difficult due to parameter uncertainty and the heterogeneity of catchment processes. Soft data, i.e. knowledge of processes gained through experimentation, have been suggested as one method of reducing uncertainty and producing a more accurate model of the processes that occur in a catchment. In this work, the Integrated Catchment model for Nitrogen was calibrated and validated for the Yläneenjoki catchment in south-western Finland by incorporating soft data. The calibration for 2003–2008 produced an adequate model of the in-stream nitrate concentrations (R2 = 0.45, NS = 0.42). However, model validation using data from 1997–2002 showed that the simulated in-stream nitrate concentrations were above the observed concentrations throughout the entire period (R2 = 0.34, NS < 0). These results show that soft data can be used to constrain model parameters, resulting in a more accurate model of the catchment, but do not guarantee the best validation results as the simulated processes may not occur at the same time and rate as they did in the catchment.

scholarly journals Application of the Frier Distributed Model for Estimating the Impact of Land use Changes on the Water Balance in Selected Basins in Slovakia

2009 ◽  
Vol 57 (4) ◽  
pp. 213-225 ◽  
Author(s):  
Oliver Horvát ◽  
Kamila Hlavčová ◽  
Silvia Kohnová ◽  
Michal Danko
Keyword(s):  
Land Use ◽  
Water Balance ◽  
Land Use Changes ◽  
Hydrological Regime ◽  
Distributed Model ◽  
Model Parameters ◽  
Hydrologic Processes ◽  
Rainfall Runoff Model ◽  
Using Data ◽  
The Impact

Application of the Frier Distributed Model for Estimating the Impact of Land use Changes on the Water Balance in Selected Basins in SlovakiaIn this study, the FRIER rainfall-runoff model with distributed parameters was developed to assess changes in runoff and water balance due to changes in land use and climate. The water balance was calculated at 3 levels: on the surface and in unsaturated and saturated zones. Six basins from the central and eastern parts of Slovakia were selected on the basis of their similar size, but different topography, land use, soil texture and climate: the upper Hornád, the upper Hron, the Poprad, the Rimava, the Slaná and the Torysa River basins. Model parameters were estimated using data from the period from June 1998 to May 2000 in daily time steps. The differences and similarities of the hydrologic processes in individual basins were investigated during the calibration period. Several scenarios of changes in land use and two simple scenarios of changes in climate were developed to estimate the impact of these changes on water balance and runoff. The changes in the hydrological regime were compared and discussed.

scholarly journals The Impact of Grants on Homeowner Decisions to Retrofit to Reduce Hurricane-Induced Wind and Flood Damage

2020 ◽  
Vol 12 (1) ◽  
pp. 31-46 ◽  
Author(s):  
Esther Chiew ◽  
Rachel A. Davidson ◽  
Joseph E. Trainor ◽  
Linda K. Nozick ◽  
Jamie L. Kruse
Keyword(s):  
Stated Preference ◽  
Mixed Logit ◽  
Revealed Preference ◽  
Flood Damage ◽  
Substantial Impact ◽  
Grant Program ◽  
State And Local ◽  
Using Data ◽  
Dollar Amount ◽  
The Impact

AbstractAn increasing number of national, state, and local programs have offered grants or other monetary incentives to encourage homeowners to retrofit their homes to reduce damage from natural hazard events. Despite this fact, little is known about how these offerings influence a homeowner’s decision to carry out such structural retrofits. This paper studies the impact that different grant program designs in particular have on the decision to undertake different types of retrofits to mitigate against hurricane damage. Using data from a survey of homeowners in the eastern half of North Carolina, we implement a mixed logit model that allows for the combination of both revealed-preference and stated-preference data available from the survey. Our findings show that offering a grant results in households being, on average, 3 times as likely to retrofit as when a grant is not offered. In addition, both the percentage of retrofit cost and the maximum dollar amount covered by the grant have a substantial impact on the probability that households choose to retrofit. Living closer to the coastline also has a significant impact on the probability that households will choose to retrofit. Counter to some previous research, we find that households who have experienced two or more hurricanes are less likely to choose to retrofit their homes. From our research, we find that the percentage of retrofit cost covered by the grant and the total cost are both important factors when deciding on the best grant program configuration.

scholarly journals Statistical analysis of Goal Attainment Scaling endpoints in randomised trials

2018 ◽  
Vol 28 (6) ◽  
pp. 1893-1910 ◽  
Author(s):  
S Urach ◽  
CMW Gaasterland ◽  
M Posch ◽  
B Jilma ◽  
K Roes ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Statistical Analysis ◽  
Goal Attainment ◽  
Assessment Instrument ◽  
Ordinal Scale ◽  
Patient Specific ◽  
Goal Attainment Scaling ◽  
Model Parameters ◽  
Variable Approach ◽  
The Impact

Goal Attainment Scaling is an assessment instrument to evaluate interventions on the basis of individual, patient-specific goals. The attainment of these goals is mapped in a pre-specified way to attainment levels on an ordinal scale, which is common to all goals. This approach is patient-centred and allows one to integrate the outcomes of patients with very heterogeneous symptoms. The latter is of particular importance in clinical trials in rare diseases because it enables larger sample sizes by including a broader patient population. In this paper, we focus on the statistical analysis of Goal Attainment Scaling outcomes for the comparison of two treatments in randomised clinical trials. Building on a general statistical model, we investigate the properties of different hypothesis testing approaches. Additionally, we propose a latent variable approach to generate Goal Attainment Scaling data in a simulation study, to assess the impact of model parameters such as the number of goals per patient and their correlation, the choice of discretisation thresholds and the type of design (parallel group or cross-over). Based on our findings, we give recommendations for the design of clinical trials with a Goal Attainment Scaling endpoint. Furthermore, we discuss an application of Goal Attainment Scaling in a clinical trial in mastocytosis.

scholarly journals Fueling Factionalism? The Impact of Peace Processes on Rebel Group Fragmentation in Civil Wars

2020 ◽  
pp. 002200272095806
Author(s):  
Allard Duursma ◽  
Feike Fliervoet
Keyword(s):  
Civil Wars ◽  
Peace Process ◽  
Theoretical Framework ◽  
Peace Agreement ◽  
Substantial Impact ◽  
Peace Processes ◽  
Rebel Group ◽  
Using Data ◽  
The Moment ◽  
The Impact

While peace processes increase the likelihood that a civil war is resolved, they can also complicate peace by increasing the risk of rebel fragmentation. In this article, we argue that negotiations exacerbate pre-existing structural and substantial divisions within rebel organizations, therefore increasing the likelihood of a rebel split. More specifically, we put forward a theoretical framework that specifies why factions within a rebel group may disagree with the onset of negotiations, the conclusion of a peace agreement, or the implementation of an agreement—and thus break away during the peace process. We empirically assess the merit of this framework by systematically comparing the impact of these phases in a peace process on the fragmentation of rebel organizations. Using data that more accurately reflect the moment a rebel split takes place than earlier studies, we find that peace processes have a greater substantial impact on rebel fragmentation than previously assumed.

scholarly journals Evaluating the impacts of release in São Paulo State (Brazil) on the epidemic of covid-19 based on mathematical model

2020 ◽  
Author(s):  
Hyun Mo Yang ◽  
Luis Pedro Pedro Lombardi Junior ◽  
Ariana Campos Yang ◽  
Fabio Fernandes Morato Castro
Keyword(s):  
Mathematical Model ◽  
Sao Paulo ◽  
Model Parameters ◽  
Isolated Population ◽  
São Paulo ◽  
Paulo State ◽  
History Of ◽  
São Paulo State ◽  
Using Data ◽  
The Impact

To flatten the curve of the natural epidemic of covid-19, many countries adopted lockdown or isolation resulting in the containment of the SARS-CoV-2 transmission. However, an important question arises about the strategies of release of isolated persons to avoid overloaded hospitals and increased deaths. São Paulo State (Brazil) implemented the isolation of the population in non- essential activities on March 24, and the progressive flexibilization considering the characteristics of each location (release of the isolated population) initiated on June 15. A mathematical model based on the natural history of covid-19 was applied to describe the epidemiological scenario with isolation in São Paulo State, and assess the impact of release on the covid-19 epidemic. Using data collected from São Paulo State, we estimated the model parameters to obtain the curves of the epidemic, the number of deaths, and the clinical evolution of covid-19. The epidemic under isolation was the framework to evaluate the strategies of the release, that is, how these curves are changed with the release of isolated persons. We evaluated three strategies of release. First two strategies considered four releases in the isolated population in four equal proportions, but successive releases elapsed by 14 and 21 days. In each strategy the beginning of the release was on June 29 and July 13, when the effective reproduction number Ref was evaluated. The third strategy aimed at the protection of the elder subpopulation. We observed that the delay to begin the release and the increased elapse between successive releases resulted in a better scenario by decreasing severe covid-19 cases and, consequently, to avoid overloaded hospitals. We also observed that the release delayed to achieve lower values for Ref and infectious persons retarded in several months the quick increasing phase of the forthcoming epidemic. However, this epidemic can be flattened or even suppressed by isolation of infectious persons by mass testing and/or by rigid adoption of protective measures and social distancing.

Accent Policy and Accent Modification Enterprises as Potential Indicators of Intercultural Power Relations: A Call for an Updated Research Agenda

2013 ◽  
Vol 3 (1) ◽  
pp. 22-33 ◽  
Author(s):  
Brynne D. Ovalle ◽  
Rahul Chakraborty
Keyword(s):  
International Relations ◽  
Identity Construction ◽  
Social Theory ◽  
Power Relations ◽  
Linguistic Diversity ◽  
Cultural Organization ◽  
Using Data ◽  
The Individual ◽  
The Impact ◽  
The Relationship

This article has two purposes: (a) to examine the relationship between intercultural power relations and the widespread practice of accent discrimination and (b) to underscore the ramifications of accent discrimination both for the individual and for global society as a whole. First, authors review social theory regarding language and group identity construction, and then go on to integrate more current studies linking accent bias to sociocultural variables. Authors discuss three examples of intercultural accent discrimination in order to illustrate how this link manifests itself in the broader context of international relations (i.e., how accent discrimination is generated in situations of unequal power) and, using a review of current research, assess the consequences of accent discrimination for the individual. Finally, the article highlights the impact that linguistic discrimination is having on linguistic diversity globally, partially using data from the United Nations Educational, Scientific and Cultural Organization (UNESCO) and partially by offering a potential context for interpreting the emergence of practices that seek to reduce or modify speaker accents.

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