scholarly journals Uncertainty matters: Bayesian modeling of bicycle crashes with incomplete exposure data

2022 ◽  
Vol 165 ◽  
pp. 106518
Author(s):  
Pengpeng Xu ◽  
Lu Bai ◽  
Xin Pei ◽  
S.C. Wong ◽  
Hanchu Zhou
Keyword(s):  
Bayesian Modeling ◽  
Exposure Data

scholarly journals Bayesian Modeling of Air Pollution Health Effects with Missing Exposure Data

2006 ◽  
Vol 164 (1) ◽  
pp. 69-76 ◽  
Author(s):  
John Molitor ◽  
Nuoo-Ting Molitor ◽  
Michael Jerrett ◽  
Rob McConnell ◽  
Jim Gauderman ◽  
...  
Keyword(s):  
Air Pollution ◽  
Health Effects ◽  
Bayesian Modeling ◽  
Exposure Data

Evaluation of the impact of public investment programs on social and economic performance of territories

2019 ◽  
pp. 109-123
Author(s):  
I. E. Limonov ◽  
M. V. Nesena
Keyword(s):  
Bayesian Modeling ◽  
Positive Impact ◽  
Public Investment ◽  
Difference In Differences ◽  
The Public ◽  
Export Activity ◽  
Regional Investment ◽  
The Difference ◽  
The Impact ◽  
Development Institution

The purpose of this study is to evaluate the impact of public investment programs on the socio-economic development of territories. As a case, the federal target programs for the development of regions and investment programs of the financial development institution — Vnesheconombank, designed to solve the problems of regional development are considered. The impact of the public interventions were evaluated by the “difference in differences” method using Bayesian modeling. The results of the evaluation suggest the positive impact of federal target programs on the total factor productivity of regions and on innovation; and that regional investment programs of Vnesheconombank are improving the export activity. All of the investments considered are likely to have contributed to the reduction of unemployment, but their implementation has been accompanied by an increase in social inequality.

RISCO DE MOVIMENTOS DE MASSA NAS COMUNIDADES MAZAGÃO 1 E JOSÉ DA SILVA SOBRAL, MUNICÍPIO DE ALAGOA NOVA / PB

2019 ◽  
Vol 21 (2) ◽  
pp. 122-135
Author(s):  
Caroline Barros de Sales ◽  
Samara Sayonara Cândida da Silva ◽  
Lutiane Queiroz de Almeida
Keyword(s):  
Social Vulnerability ◽  
Social Indicators ◽  
Environmental Indicators ◽  
Mass Movements ◽  
Critical Elements ◽  
Exposure Data ◽  
The Social ◽  
Bibliographical Survey ◽  
Photographic Records

O presente trabalho tem como objetivo caracterizar o risco nas comunidades Mazagão 1 e José da Silva Sobral, a partir de indicadores sociais de vulnerabilidade e ambientais de perigo para movimentos de massa. Para isso, buscou-se inicialmente o levantamento bibliográfico, respaldando-se em autores que trabalham com as temáticas de riscos e vulnerabilidade, e foram realizadas atividades de campo, as quais possibilitaram a aplicação dos questionários de vulnerabilidade social e das fichas de exposição a movimentos de massa, além de permitir a realização de registros fotográficos. A partir da sistematização dos dados de vulnerabilidade social e de exposição, permitiu-se estabelecer as características mais presentes nas comunidades, indicando os elementos mais críticos, os quais colaboram para que haja risco de movimentos de massa, apontando então para a necessidade de pesquisas que venham a estudar profundamente a situação, podendo vir a propor medidas mitigadoras diretamente aplicáveis à área de risco.Palavras-chave: Vulnerabilidade; Perigo; Desastre. ABSTRACTThe present work aims to characterize the risk in the communities Mazagão 1 and José da Silva Sobral, considering social indicators of vulnerability and environmental indicators of danger to mass movements. In order to do this, a bibliographical survey was sought, supported by authors working on the themes of risk and vulnerability, and field activities were carried out, which made possible the application of the social vulnerability questionnaires and the exposure sheets to mass movements, besides allowing the realization of photographic records. Systematizing social vulnerability and exposure data, the most present characteristics in the communities were established, indicating the most critical elements, which contribute to the risk of mass movements, pointing to the need for research that will deeply study the situation, and may propose mitigating measures directly applicable to the area of risk.Keywords: Vulnerability; Danger; Disaster. RESUMENEste trabajo tiene como objetivo caracterizar el riesgo en las comunidades Mazagão 1 y José da Silva Sobral, con base en indicadores sociales de vulnerabilidad y peligro ambiental para los movimientos de masas. Para ello, se buscó inicialmente la investigación bibliográfica, apoyada por autores que trabajan con los temas de riesgos y vulnerabilidad, y se llevaron a cabo actividades de campo, que permitieron la aplicación de cuestionarios de vulnerabilidad social y hojas de exposición al movimiento, además de permitir la realización de registros fotográficos. A partir de la sistematización de datos sobre vulnerabilidad social y exposición, fue posible establecer las características más comunes en las comunidades, indicando los elementos más críticos, que contribuyen al riesgo de movimientos masivos, señalando la necesidad de una investigación que Estudie la situación en profundidad y proponga medidas de mitigación directamente aplicables al área de riesgo.Palabras Claves: Vulnerabilidad; Peligro; Desastre.

Measuring Risks in Hedge Funds: Evaluation and Usefulness of Exposure Data in Form PF

2018 ◽  
Author(s):  
Phillip Monin ◽  
Matthew G. Pritsker ◽  
Stathis Tompaidis
Keyword(s):  
Hedge Funds ◽  
Exposure Data

scholarly journals Bayesian modeling of inconsistent plastic response due to material variability

2019 ◽  
Vol 353 ◽  
pp. 183-200 ◽  
Author(s):  
F. Rizzi ◽  
M. Khalil ◽  
R.E. Jones ◽  
J.A. Templeton ◽  
J.T. Ostien ◽  
...  
Keyword(s):  
Bayesian Modeling ◽  
Plastic Response

scholarly journals 1326. Vancomycin Area Under the Concentration-Time Curve (AUC) Estimation Using a Bayesian Approach Versus First-Order Pharmacokinetic Equations: A Pilot Study

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S673-S673
Author(s):  
Jeffrey Pearson ◽  
Yazed S Alsowaida ◽  
B S Pharm ◽  
David W Kubiak ◽  
Mary P Kovacevic ◽  
...  
Keyword(s):  
Pilot Study ◽  
Median Time ◽  
Bayesian Modeling ◽  
Surgical Prophylaxis ◽  
Time Curve ◽  
Team Members ◽  
First Order ◽  
Concentration Time ◽  
Study Team ◽  
Auc Estimation

Abstract Background Current guidelines endorse area under the concentration-time curve (AUC)-based monitoring over trough-only monitoring for systemic vancomycin. Vancomycin AUC can be estimated using either Bayesian modeling software or first-order pharmacokinetic (PK) calculations. The objective of this pilot study was to evaluate and compare the efficiency and feasibility of these two approaches for calculating the estimated vancomycin AUC. Methods A single-center crossover study was conducted in four medical/surgical units at Brigham and Women’s Hospital over a 3-month time period. All adult patients who received vancomycin were included. Patients were excluded if they were receiving vancomycin for surgical prophylaxis, were on hemodialysis, if vancomycin was being dosed by level, or if vancomycin levels were never drawn. The primary endpoint was the amount of time study team members spent calculating the estimated AUC and determining regimen adjustments with Bayesian modeling compared to first-order PK calculations. Secondary endpoints included the number of vancomycin levels drawn and the percent of those drawn that were usable for AUC calculations. Results One hundred twenty-four patients received vancomycin during the study, of whom 47 met inclusion criteria. The most likely reasons for exclusion were receiving vancomycin for surgical prophylaxis (n=40) or never having vancomycin levels drawn (n=32). The median time taken to assess levels in the Bayesian arm was 9.3 minutes [interquartile range (IQR) 7.8-12.4] versus 6.8 minutes (IQR 4.8-8.0) in the 2-level PK arm (p=0.004). However, if Bayesian software is integrated into the electronic health record (EHR), the median time to assess levels was 3.8 minutes (IQR 2.3-6.8, p=0.019). In the Bayesian arm, 30 of 34 vancomycin levels (88.2%) were usable for AUC calculations, compared to 28 of 58 (48.3%) in the 2-level PK arm. Conclusion With EHR integration, the use of Bayesian software to calculate the AUC was more efficient than first-order PK calculations. Additionally, vancomycin levels were more likely to be usable in the Bayesian arm, thereby avoiding delays in estimating the vancomycin AUC. Disclosures All Authors: No reported disclosures

scholarly journals scMET: Bayesian modeling of DNA methylation heterogeneity at single-cell resolution

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Chantriolnt-Andreas Kapourani ◽  
Ricard Argelaguet ◽  
Guido Sanguinetti ◽  
Catalina A. Vallejos
Keyword(s):  
Single Cell ◽  
Bayesian Modeling ◽  
Bayesian Model ◽  
Regulation Of Gene Expression ◽  
Differential Methylation ◽  
Hierarchical Bayesian Model ◽  
Genomic Features ◽  
Distinct Cell ◽  
Biological Heterogeneity

AbstractHigh-throughput single-cell measurements of DNA methylomes can quantify methylation heterogeneity and uncover its role in gene regulation. However, technical limitations and sparse coverage can preclude this task. scMET is a hierarchical Bayesian model which overcomes sparsity, sharing information across cells and genomic features to robustly quantify genuine biological heterogeneity. scMET can identify highly variable features that drive epigenetic heterogeneity, and perform differential methylation and variability analyses. We illustrate how scMET facilitates the characterization of epigenetically distinct cell populations and how it enables the formulation of novel hypotheses on the epigenetic regulation of gene expression. scMET is available at https://github.com/andreaskapou/scMET.

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