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https://www.readbyqxmd.com/read/28340415/uncertainty-analysis-for-effluent-trading-planning-using-a-bayesian-estimation-based-simulation-optimization-modeling-approach
#1
J L Zhang, Y P Li, G H Huang, B W Baetz, J Liu
In this study, a Bayesian estimation-based simulation-optimization modeling approach (BESMA) is developed for identifying effluent trading strategies. BESMA incorporates nutrient fate modeling with soil and water assessment tool (SWAT), Bayesian estimation, and probabilistic-possibilistic interval programming with fuzzy random coefficients (PPI-FRC) within a general framework. Based on the water quality protocols provided by SWAT, posterior distributions of parameters can be analyzed through Bayesian estimation; stochastic characteristic of nutrient loading can be investigated which provides the inputs for the decision making...
March 6, 2017: Water Research
https://www.readbyqxmd.com/read/28338966/a-comparison-of-sensitivity-specificity-imputation-direct-imputation-and-fully-bayesian-analysis-to-adjust-for-exposure-misclassification-when-validation-data-are-unavailable
#2
Marine Corbin, Stephen Haslett, Neil Pearce, Milena Maule, Sander Greenland
Purpose: Measurement error is an important source of bias in epidemiological studies. We illustrate three approaches to sensitivity analysis for the effect of measurement error: imputation of the 'true' exposure based on specifying the sensitivity and specificity of the measured exposure (SS); direct imputation (DI) using a regression model for the predictive values; and adjustment based on a fully Bayesian analysis. Methods: We deliberately misclassify smoking status in data from a case-control study of lung cancer...
March 14, 2017: International Journal of Epidemiology
https://www.readbyqxmd.com/read/28338052/dissociable-diffusion-mri-patterns-of-white-matter-microstructure-and-connectivity-in-alzheimer-s-disease-spectrum
#3
Nhat Trung Doan, Andreas Engvig, Karin Persson, Dag Alnæs, Tobias Kaufmann, Jaroslav Rokicki, Aldo Córdova-Palomera, Torgeir Moberget, Anne Brækhus, Maria Lage Barca, Knut Engedal, Ole A Andreassen, Geir Selbæk, Lars T Westlye
Recent efforts using diffusion tensor imaging (DTI) have documented white matter (WM) alterations in Alzheimer's disease (AD). The full potential of whole-brain DTI, however, has not been fully exploited as studies have focused on individual microstructural indices independently. In patients with AD (n = 79), mild (MCI, n = 55) and subjective (SCI, n = 30) cognitive impairment, we applied linked independent component analysis (LICA) to model inter-subject variability across five complementary DTI measures (fractional anisotropy (FA), axial/radial/mean diffusivity, diffusion tensor mode), two crossing fiber measures estimated using a multi-compartment crossing-fiber model reflecting the volume fraction of the dominant (f1) and non-dominant (f2) diffusion orientation, and finally, connectivity density obtained from full-brain probabilistic tractography...
March 24, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28337719/an-early-health-economic-analysis-of-the-potential-cost-effectiveness-of-an-adherence-intervention-to-improve-outcomes-for-patients-with-cystic-fibrosis
#4
Paul Tappenden, Susannah Sadler, Martin Wildman
BACKGROUND: Cystic fibrosis (CF) negatively impacts upon health-related quality of life and survival. Adherence to nebulised treatments is low; improving adherence is hypothesised to reduce rates of exacerbation requiring intravenous antibiotics and lung function decline. OBJECTIVE: A state transition model was developed to assess the cost effectiveness of an intervention aimed at increasing patient adherence to nebulised and inhaled antibiotics compared with current CF care, in advance of the forthcoming CFHealthHub randomised controlled trial (RCT)...
March 23, 2017: PharmacoEconomics
https://www.readbyqxmd.com/read/28336305/from-point-process-observations-to-collective-neural-dynamics-nonlinear-hawkes-process-glms-low-dimensional-dynamics-and-coarse-graining
#5
Wilson Truccolo
This review presents a perspective on capturing collective dynamics in recorded neuronal ensembles based on multivariate point process models, inference of low-dimensional dynamics and coarse graining of spatiotemporal measurements. A general probabilistic framework for continuous time point processes is reviewed, with an emphasis on multivariate nonlinear Hawkes processes with exogenous inputs. A point process generalized linear model (PP-GLM) framework for the estimation of discrete time multivariate nonlinear Hawkes processes is described...
March 20, 2017: Journal of Physiology, Paris
https://www.readbyqxmd.com/read/28335769/cost-effectiveness-of-crag-lfa-screening-for-cryptococcal-meningitis-among-people-living-with-hiv-in-uganda
#6
Anu Ramachandran, Yukari Manabe, Radha Rajasingham, Maunank Shah
BACKGROUND: Cryptococcal meningitis (CM) constitutes a significant source of mortality in resource-limited regions. Cryptococcal antigen (CRAG) can be detected in the blood before onset of meningitis. We sought to determine the cost-effectiveness of implementing CRAG screening using the recently developed CRAG lateral flow assay in Uganda compared to current practice without screening. METHODS: A decision-analytic model was constructed to compare two strategies for cryptococcal prevention among people living with HIV with CD4 < 100 in Uganda: No cryptococcal screening vs...
March 23, 2017: BMC Infectious Diseases
https://www.readbyqxmd.com/read/28333689/computational-modelling-of-the-cerebral-cortical-microvasculature-effect-of-x-ray-microbeams-versus-broad-beam-irradiation
#7
Andreas Merrem, Stefan Bartzsch, Jean Laissue, Uwe Oelfke
Microbeam Radiation Therapy is an innovative pre-clinical strategy which uses arrays of parallel, tens of micrometre wide kilo-voltage photon beams to treat tumours. These X-ray beams are typically generated on a synchrotron source. It was shown that these beam geometries allow exceptional normal tissue sparing from radiation damage while still being effective in tumour ablation. A final biological explanation for this enhanced therapeutic ratio has still not been found, some experimental data support an important role of the vasculature...
March 23, 2017: Physics in Medicine and Biology
https://www.readbyqxmd.com/read/28333652/survivability-modeling-and-resource-planning-for-self-repairing-reconfigurable-device-fabrics
#8
Rashad S Oreifej, Rawad Al-Haddad, Ramtin Zand, Rizwan A Ashraf, Ronald F DeMara
A resilient system design problem is formulated as the quantification of uncommitted reconfigurable resources required for a system of components to survive its lifetime within mission availability specifications. We show that this survivability metric can be calculated according to the residual functionality obtained from pools of dynamically configurable elements constituting the amorphous resource pool (ARP). The ARP is depleted based on the failure rate to replenish the functionality lost in a reconfigurable fabric due to the occurrence of permanent faults during the mission lifetime...
March 21, 2017: IEEE Transactions on Cybernetics
https://www.readbyqxmd.com/read/28333085/ebasis-bioactive-substances-in-food-information-systems-and-bioactive-intakes-major-updates-of-the-bioactive-compound-composition-and-beneficial-bioeffects-database-and-the-development-of-a-probabilistic-model-to-assess-intakes-in-europe
#9
Jenny Plumb, Sandrine Pigat, Foteini Bompola, Maeve Cushen, Hannah Pinchen, Eric Nørby, Siân Astley, Jacqueline Lyons, Mairead Kiely, Paul Finglas
eBASIS (Bioactive Substances in Food Information Systems), a web-based database that contains compositional and biological effects data for bioactive compounds of plant origin, has been updated with new data on fruits and vegetables, wheat and, due to some evidence of potential beneficial effects, extended to include meat bioactives. eBASIS remains one of only a handful of comprehensive and searchable databases, with up-to-date coherent and validated scientific information on the composition of food bioactives and their putative health benefits...
March 23, 2017: Nutrients
https://www.readbyqxmd.com/read/28332433/the-cost-effectiveness-of-alectinib-in-anaplastic-lymphoma-kinase-positive-alk-advanced-nsclc-previously-treated-with-crizotinib
#10
J J Carlson, W Canestaro, A Ravelo, W Wong
Introduction Anaplastic lymphoma kinase (ALK) targeting drugs provide an important option for advanced non-small cell lung cancer patients with this distinct tumor type; however, there is considerable uncertainty as to which drug provides the optimal value after crizotinib treatment. This study estimated the cost-utility of alectinib vs ceritinib from a US payer perspective. Methods A cost-utility model was developed using partition survival methods and three health states: progression-free (PF), post-progression (PP), and death...
March 23, 2017: Journal of Medical Economics
https://www.readbyqxmd.com/read/28332417/cost-effectiveness-of-angiotensin-converting-enzyme-inhibitors-versus-angiotensin-ii-receptor-blockers-as-first-line-treatment-in-autosomal-dominant-polycystic-kidney-disease
#11
L A Clark, S Whitmire, S Patton, C Clark, C M Blanchette, R Howden
INTRODUCTION: Autosomal dominant polycystic kidney disease (ADPKD) is a rare kidney disorder impacting approximately 1:2500 individuals among the general US population. Hypertension is a significant predictor of ADPKD progression and risk factor for development of cardiovascular disease (CVD), the most common cause for mortality among ADPKD patients. Angiotensin-converting enzymes inhibitors (ACE-I) are widely used as first-line treatment in ADPKD for the management of hypertension. However, their cost-effectiveness relative to other hypertensive medications, such as angiotensin II receptor blockers (ARB) has never been assessed...
March 23, 2017: Journal of Medical Economics
https://www.readbyqxmd.com/read/28331548/discovering-feature-relevancy-and-dependency-by-kernel-guided-probabilistic-model-building-evolution
#12
Nestor Rodriguez, Sergio Rojas-Galeano
BACKGROUND: Discovering relevant features (biomarkers) that discriminate etiologies of a disease is useful to provide biomedical researchers with candidate targets for further laboratory experimentation while saving costs; dependencies among biomarkers may suggest additional valuable information, for example, to characterize complex epistatic relationships from genetic data. The use of classifiers to guide the search for biomarkers (the so-called wrapper approach) has been widely studied...
2017: BioData Mining
https://www.readbyqxmd.com/read/28329793/oral-disease-and-3-year-incidence-of-frailty-in-mexican-older-adults
#13
Roberto Carlos Castrejón-Pérez, Aida Jiménez-Corona, Eduardo Bernabé, Antonio R Villa-Romero, Elise Arrivé, Jean-François Dartigues, Luis Miguel Gutiérrez-Robledo, S Aída Borges-Yáñez
Background: Poor oral health has been associated with some components of frailty. The objective of this study was to identify the association between clinical measures of oral health and the incidence of frailty among community-dwelling older adults aged 70 or older in Mexico City. Methods: A 3-year cohort study with a probabilistic representative sample of home-dwelling elders of one district of Mexico City was performed. Baseline and follow-up interview and oral clinical evaluations were carried out by standardized examiners in participants' homes...
October 25, 2016: Journals of Gerontology. Series A, Biological Sciences and Medical Sciences
https://www.readbyqxmd.com/read/28328516/anrad-a-neuromorphic-anomaly-detection-framework-for-massive-concurrent-data-streams
#14
Qiuwen Chen, Ryan Luley, Qing Wu, Morgan Bishop, Richard W Linderman, Qinru Qiu
The evolution of high performance computing technologies has enabled the large-scale implementation of neuromorphic models and pushed the research in computational intelligence into a new era. Among the machine learning applications, unsupervised detection of anomalous streams is especially challenging due to the requirements of detection accuracy and real-time performance. Designing a computing framework that harnesses the growing computing power of the multicore systems while maintaining high sensitivity and specificity to the anomalies is an urgent research topic...
March 17, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28328514/dynamic-uncertain-causality-graph-for-knowledge-representation-and-reasoning-utilization-of-statistical-data-and-domain-knowledge-in-complex-cases
#15
Qin Zhang, Quanying Yao
The dynamic uncertain causality graph (DUCG) is a newly presented framework for uncertain causality representation and probabilistic reasoning. It has been successfully applied to online fault diagnoses of large, complex industrial systems, and decease diagnoses. This paper extends the DUCG to model more complex cases than what could be previously modeled, e.g., the case in which statistical data are in different groups with or without overlap, and some domain knowledge and actions (new variables with uncertain causalities) are introduced...
March 17, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28325918/robust-analysis-of-fluxes-in-genome-scale-metabolic-pathways
#16
Michael MacGillivray, Amy Ko, Emily Gruber, Miranda Sawyer, Eivind Almaas, Allen Holder
Constraint-based optimization, such as flux balance analysis (FBA), has become a standard systems-biology computational method to study cellular metabolisms that are assumed to be in a steady state of optimal growth. The methods are based on optimization while assuming (i) equilibrium of a linear system of ordinary differential equations, and (ii) deterministic data. However, the steady-state assumption is biologically imperfect, and several key stoichiometric coefficients are experimentally inferred from situations of inherent variation...
March 21, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28325881/probabilistic-models-of-species-discovery-and-biodiversity-comparisons
#17
Stewart M Edie, Peter D Smits, David Jablonski
Inferring large-scale processes that drive biodiversity hinges on understanding the phylogenetic and spatial pattern of species richness. However, clades and geographic regions are accumulating newly described species at an uneven rate, potentially affecting the stability of currently observed diversity patterns. Here, we present a probabilistic model of species discovery to assess the uncertainty in diversity levels among clades and regions. We use a Bayesian time series regression to estimate the long-term trend in the rate of species description for marine bivalves and find a distinct spatial bias in the accumulation of new species...
March 21, 2017: Proceedings of the National Academy of Sciences of the United States of America
https://www.readbyqxmd.com/read/28323355/the-modelled-cost-effectiveness-of-cognitive-dissonance-for-the-prevention-of-anorexia-nervosa-and-bulimia-nervosa-in-adolescent-girls-in-australia
#18
Long Khanh-Dao Le, Jan J Barendregt, Phillipa Hay, Susan M Sawyer, Susan J Paxton, Cathrine Mihalopoulos
BACKGROUND: Eating disorders (EDs), including anorexia nervosa (AN) and bulimia nervosa (BN), are prevalent disorders that carry substantial economic and social burden. The aim of the current study was to evaluate the modelled population cost-effectiveness of cognitive dissonance (CD), a school-based preventive intervention for EDs, in the Australian health care context. METHOD: A population-based Markov model was developed to estimate the cost per disability adjusted life-year (DALY) averted by CD relative to no intervention...
March 21, 2017: International Journal of Eating Disorders
https://www.readbyqxmd.com/read/28323161/seeg-dipole-source-localization-based-on-an-empirical-bayesian-approach-taking-into-account-forward-model-uncertainties
#19
S Le Cam, R Ranta, V Caune, G Korats, L Koessler, L Maillard, V Louis-Dorr
Electromagnetic brain source localization consists in the inversion of a forward model based on a limited number of potential measurements. A wide range of methods has been developed to regularize this severely ill-posed problem and to reduce the solution space, imposing spatial smoothness, anatomical constraint or sparsity of the activated source map. This last criteria, based on physiological assumptions stating that in some particular events (e.g., epileptic spikes, evoked potential) few focal area of the brain are simultaneously actives, has gained more and more interest...
March 17, 2017: NeuroImage
https://www.readbyqxmd.com/read/28322914/computer-aided-prediction-of-extent-of-motor-recovery-following-constraint-induced-movement-therapy-in-chronic-stroke
#20
Sarah Hulbert George, Mohammad Hossein Rafiei, Lynne Gauthier, Alexandra Borstad, John A Buford, Hojjat Adeli
Constraint-induced movement therapy (CI therapy) is a well-researched intervention for treatment of upper limb function. Overall, CI therapy yields clinically meaningful improvements in speed of task completion and greatly increases use of the more affected upper extremity for daily activities. However, individual improvements vary widely. It has been suggested that intrinsic feedback from somatosensation may influence motor recovery from CI therapy. To test this hypothesis, an enhanced probabilistic neural network (EPNN) prognostic computational model was developed to identify which baseline characteristics predict extent of motor recovery, as measured by the Wolf Motor Function Test (WMFT)...
March 17, 2017: Behavioural Brain Research
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