scholarly journals Soft-Tissue Simulation for Computational Planning of Orthognathic Surgery

2021 ◽  
Vol 11 (10) ◽  
pp. 982
Author(s):  
Patricia Alcañiz ◽  
Jesús Pérez ◽  
Alessandro Gutiérrez ◽  
Héctor Barreiro ◽  
Ángel Villalobos ◽  
...  
Keyword(s):  
Soft Tissue ◽  
Orthognathic Surgery ◽  
Simulation Models ◽  
Simulation Methods ◽  
Imaging Data ◽  
Simulation Methodology ◽  
Complex Simulation ◽  
Model Set ◽  
Set Up ◽  
Computer Planning

Simulation technologies offer interesting opportunities for computer planning of orthognathic surgery. However, the methods used to date require tedious set up of simulation meshes based on patient imaging data, and they rely on complex simulation models that require long computations. In this work, we propose a modeling and simulation methodology that addresses model set up and runtime simulation in a holistic manner. We pay special attention to modeling the coupling of rigid-bone and soft-tissue components of the facial model, such that the resulting model is computationally simple yet accurate. The proposed simulation methodology has been evaluated on a cohort of 10 patients of orthognathic surgery, comparing quantitatively simulation results to post-operative scans. The results suggest that the proposed simulation methods admit the use of coarse simulation meshes, with planning computation times of less than 10 seconds in most cases, and with clinically viable accuracy.

scholarly journals Deep learning based discrimination of soft tissue profiles requiring orthognathic surgery by facial photographs

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Seung Hyun Jeong ◽  
Jong Pil Yun ◽  
Han-Gyeol Yeom ◽  
Hun Jun Lim ◽  
Jun Lee ◽  
...  
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Deep Learning ◽  
Soft Tissue ◽  
Convolutional Neural Networks ◽  
Orthognathic Surgery ◽  
Group I ◽  
Group Ii ◽  
Set Up

Abstract Facial photographs of the subjects are often used in the diagnosis process of orthognathic surgery. The aim of this study was to determine whether convolutional neural networks (CNNs) can judge soft tissue profiles requiring orthognathic surgery using facial photographs alone. 822 subjects with dentofacial dysmorphosis and / or malocclusion were included. Facial photographs of front and right side were taken from all patients. Subjects who did not need orthognathic surgery were classified as Group I (411 subjects). Group II (411 subjects) was set up for cases requiring surgery. CNNs of VGG19 was used for machine learning. 366 of the total 410 data were correctly classified, yielding 89.3% accuracy. The values of accuracy, precision, recall, and F1 scores were 0.893, 0.912, 0.867, and 0.889, respectively. As a result of this study, it was found that CNNs can judge soft tissue profiles requiring orthognathic surgery relatively accurately with the photographs alone.

Correlation of Pore Structure and Permeability by SEM-Image Analysis

1990 ◽  
Vol 48 (1) ◽  
pp. 428-429
Author(s):  
C. A. Callender ◽  
Wm. C. Dawson ◽  
J. J. Funk
Keyword(s):  
Image Analysis ◽  
Pore Structure ◽  
Imaging System ◽  
Pore Space ◽  
Simulation Models ◽  
Image Analyzer ◽  
Imaging Data ◽  
Sem Images ◽  
Thin Sections ◽  
Rock Types

The geometric structure of pore space in some carbonate rocks can be correlated with petrophysical measurements by quantitatively analyzing binaries generated from SEM images. Reservoirs with similar porosities can have markedly different permeabilities. Image analysis identifies which characteristics of a rock are responsible for the permeability differences. Imaging data can explain unusual fluid flow patterns which, in turn, can improve production simulation models.Analytical SchemeOur sample suite consists of 30 Middle East carbonates having porosities ranging from 21 to 28% and permeabilities from 92 to 2153 md. Engineering tests reveal the lack of a consistent (predictable) relationship between porosity and permeability (Fig. 1). Finely polished thin sections were studied petrographically to determine rock texture. The studied thin sections represent four petrographically distinct carbonate rock types ranging from compacted, poorly-sorted, dolomitized, intraclastic grainstones to well-sorted, foraminiferal,ooid, peloidal grainstones. The samples were analyzed for pore structure by a Tracor Northern 5500 IPP 5B/80 image analyzer and a 80386 microprocessor-based imaging system. Between 30 and 50 SEM-generated backscattered electron images (frames) were collected per thin section. Binaries were created from the gray level that represents the pore space. Calculated values were averaged and the data analyzed to determine which geological pore structure characteristics actually affect permeability.

Environmental model studies for the Istanbul master plan. Part I: hydrodynamical design basis and marine disposal of wastewater

1995 ◽  
Vol 32 (2) ◽  
pp. 141-148 ◽  
Author(s):  
I. S. Hansen ◽  
H. J. Vested ◽  
M. A. Latif
Keyword(s):  
Black Sea ◽  
Layer Structure ◽  
The Black Sea ◽  
Marmara Sea ◽  
Junction Area ◽  
3 Dimensional ◽  
Model Studies ◽  
Model Set ◽  
Characteristic Features ◽  
Set Up

A modelling study of the hydrodynamics and spreading of wastewater from existing and future outfalls in the Bosphorus region has been conducted applying a 3-Dimensional model. The modelling is based on SYSTEM 3, which is a general modelling system for baroclinic flow simulating unsteady currents, waterlevels, salinity and temperature within the model area. The model set-up covers the Black Sea-Bosphorus-Marmara Sea junction area. The set-up is calibrated by data from a dedicated field program and previous field experience. The model is designed to describe the characteristic features of the flow in the junction area such as the effects of variations in waterlevel differences between the Sea of Marmara and the Black Sea on the important two-layer structure in the strait and the flow fields generated by the upper layer jet in the Bosphorus-Marmara junction. This model has been applied for evaluation of disposal of wastewater and for the subsequent water quality studies. The general use of a baroclinic 3-D hydrodynamic model to simulate disposal of wastewater is discussed. Examples of the application of the model of the junction area to evaluate the different strategies for disposal of wastewater are presented.

Modelling of impregnation of γ-alumina with cobalt and molybdenum salts. CoCl2-(NH4)2MoO4-γ-Al2O3 (aluminate type) system

1987 ◽  
Vol 52 (3) ◽  
pp. 663-671 ◽  
Author(s):  
Jiří Hanika ◽  
Vladimír Janoušek ◽  
Karel Sporka
Keyword(s):  
Effective Diffusion ◽  
Type System ◽  
Catalyst Particle ◽  
Ammonium Molybdate ◽  
Active Components ◽  
Model Set ◽  
Cobalt Dichloride ◽  
Set Up ◽  
Electron Microanalysis ◽  
Kinetics Of

Adsorption data for the impregnation of alumina with an aqueous solution of cobalt dichloride and ammonium molybdate were treated in terms of the Langmuir adsorption isotherm and compared with a mathematical model set up to describe the kinetics of simultaneous impregnation of a support by two components. The effective diffusion coefficients of the two components at 25 °C in a cylindrical particle of alumina were obtained. The validity of the model used was verified qualitatively by comparing the numerical results with the experimental time dependent concentration profiles of the active components in a catalyst particle, measured by electron microanalysis technique.

scholarly journals Using CFD to Evaluate Natural Ventilation through a 3D Parametric Modeling Approach

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2197
Author(s):  
Nayara Rodrigues Marques Sakiyama ◽  
Jurgen Frick ◽  
Timea Bejat ◽  
Harald Garrecht
Keyword(s):  
Natural Ventilation ◽  
Parametric Modeling ◽  
Cfd Simulations ◽  
3D Design ◽  
Post Process ◽  
Test House ◽  
Model Set ◽  
Computational Fluid Dynamics Cfd ◽  
Set Up ◽  
Passive Strategy

Predicting building air change rates is a challenge for designers seeking to deal with natural ventilation, a more and more popular passive strategy. Among the methods available for this task, computational fluid dynamics (CFD) appears the most compelling, in ascending use. However, CFD simulations require a range of settings and skills that inhibit its wide application. With the primary goal of providing a pragmatic CFD application to promote wind-driven ventilation assessments at the design phase, this paper presents a study that investigates natural ventilation integrating 3D parametric modeling and CFD. From pre- to post-processing, the workflow addresses all simulation steps: geometry and weather definition, including incident wind directions, a model set up, control, results’ edition, and visualization. Both indoor air velocities and air change rates (ACH) were calculated within the procedure, which used a test house and air measurements as a reference. The study explores alternatives in the 3D design platform’s frame to display and compute ACH and parametrically generate surfaces where air velocities are computed. The paper also discusses the effectiveness of the reference building’s natural ventilation by analyzing the CFD outputs. The proposed approach assists the practical use of CFD by designers, providing detailed information about the numerical model, as well as enabling the means to generate the cases, visualize, and post-process the results.

scholarly journals Differences in subcortico-cortical interactions identified from connectome and microcircuit models in autism

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Bo-yong Park ◽  
Seok-Jun Hong ◽  
Sofie L. Valk ◽  
Casey Paquola ◽  
Oualid Benkarim ◽  
...  
Keyword(s):  
Data Exchange ◽  
Computational Models ◽  
Simulation Models ◽  
Autism Diagnostic Observation Schedule ◽  
Supervised Machine Learning ◽  
Global Network ◽  
Imaging Data ◽  
Phenotypic Data ◽  
Severity Scores ◽  
High Level

AbstractThe pathophysiology of autism has been suggested to involve a combination of both macroscale connectome miswiring and microcircuit anomalies. Here, we combine connectome-wide manifold learning with biophysical simulation models to understand associations between global network perturbations and microcircuit dysfunctions in autism. We studied neuroimaging and phenotypic data in 47 individuals with autism and 37 typically developing controls obtained from the Autism Brain Imaging Data Exchange initiative. Our analysis establishes significant differences in structural connectome organization in individuals with autism relative to controls, with strong between-group effects in low-level somatosensory regions and moderate effects in high-level association cortices. Computational models reveal that the degree of macroscale anomalies is related to atypical increases of recurrent excitation/inhibition, as well as subcortical inputs into cortical microcircuits, especially in sensory and motor areas. Transcriptomic association analysis based on postmortem datasets identifies genes expressed in cortical and thalamic areas from childhood to young adulthood. Finally, supervised machine learning finds that the macroscale perturbations are associated with symptom severity scores on the Autism Diagnostic Observation Schedule. Together, our analyses suggest that atypical subcortico-cortical interactions are associated with both microcircuit and macroscale connectome differences in autism.

SHOCKS AND FRICTIONS IN THAI ECONOMY: THROUGH THE LENS OF BUSINESS CYCLE ACCOUNTING

2020 ◽  
pp. 1-15
Author(s):  
VIMUT VANITCHAREARNTHUM
Keyword(s):  
Business Cycle ◽  
Open Economy ◽  
Prime Factor ◽  
Aggregate Fluctuations ◽  
Aggregate Output ◽  
Business Cycle Accounting ◽  
Labor Wedge ◽  
Model Set ◽  
Set Up ◽  
Investment Fluctuation

This paper applies business cycle accounting methodology to analyze the sources of aggregate fluctuations in Thai economy, especially during the recent severe recessions in 1997–1998 and 2008–2009. This exploration helps researchers uncover possible shocks and frictions that drive business cycle in a small and open economy within a minimal model set-up. Under this methodology, a fluctuation in aggregate output can be accounted for by exogenous time-varying wedges, namely efficiency wedge, investment wedge, labor wedge, government wedge, etc. This study found that the efficiency wedge is essential in accounting for aggregate output, consumption and investment fluctuation, while the bond wedge, which only present in an open economy setting, is a prime factor in accounting for movement in current accounts. I conducted counterfactual experiments to see what accounts for the output drop during recent recessions. I find that the efficiency wedge played a key role in recent recessions in Thailand, while the investment wedge was accounted for slow economic recovery after the recessions.

Human lung cancer explants model: Set up of a predictive model for treatment

2019 ◽  
Vol 110 ◽  
pp. S28
Author(s):  
B.M.A. Lenoir ◽  
D.S. Ferber ◽  
F. Eichhorn ◽  
M. Eichhorn ◽  
I. Zörnig ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Predictive Model ◽  
Human Lung ◽  
Human Lung Cancer ◽  
Model Set ◽  
Set Up

scholarly journals Projections of runoff in the Vistula and the Odra river basins with the help of the SWAT model

2017 ◽  
Vol 49 (2) ◽  
pp. 303-317 ◽  
Author(s):  
Mikołaj Piniewski ◽  
Mateusz Szcześniak ◽  
Shaochun Huang ◽  
Zbigniew W. Kundzewicz
Keyword(s):  
Assessment Tool ◽  
Statistical Significance ◽  
Swat Model ◽  
Climate Change Impacts ◽  
Odra River ◽  
Assess Climate Change ◽  
Rcp 8.5 ◽  
Model Set ◽  
Seasonal Runoff ◽  
Set Up

Abstract The objective of this paper is to assess climate change impacts on spatiotemporal changes in annual and seasonal runoff and its components in the basins of two large European rivers, the Vistula and the Odra, for future horizons. This study makes use of the Soil and Water Assessment Tool (SWAT) model, set up at high resolution, and driven by a multi-model ensemble (MME) of nine bias-corrected EURO-CORDEX simulations under two representative concentration pathways (RCPs), 4.5 and 8.5. This paper presents a wealth of illustrative material referring to the annual and seasonal runoff (R) in the reference period as well as projections for the future (MME mean change), with explicit illustration of the multi-model spread based on the agreement between models and statistical significance of change according to each model. Annual R increases are dominating, regardless of RCP and future horizon. The magnitude of the MME mean of spatially averaged increase varies between 15.8% (RCP 4.5, near future) and 41.6% (RCP 8.5, far future). The seasonal patterns show the highest increase in winter and the lowest in spring, whereas the spatial patterns show the highest increase in the inner, lowland part, and the lowest in the southern mountainous part of the basin.

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