scholarly journals An Uncertainty Modeling Framework for Intracardiac Electrogram Analysis

2020 ◽  
Vol 7 (2) ◽  
pp. 62
Author(s):  
Amirhossein Koneshloo ◽  
Dongping Du ◽  
Yuncheng Du
Keyword(s):  
Statistical Approach ◽  
Cardiac Tissue ◽  
Multinomial Distribution ◽  
Uncertainty Modeling ◽  
Data Uncertainty ◽  
Conduction Path ◽  
Modeling Framework ◽  
Intracardiac Electrogram ◽  
Guide Catheter ◽  
Electrical Impulses

Intracardiac electrograms (EGMs) are electrical signals measured within the chambers of the heart, which can be used to locate abnormal cardiac tissue and guide catheter ablations to treat cardiac arrhythmias. EGMs may contain large amounts of uncertainty and irregular variations, which pose significant challenges in data analysis. This study aims to introduce a statistical approach to account for the data uncertainty while analyzing EGMs for abnormal electrical impulse identification. The activation order of catheter sensors was modeled with a multinomial distribution, and maximum likelihood estimations were done to track the electrical wave conduction path in the presence of uncertainty. Robust optimization was performed to locate the electrical impulses based on the local conduction velocity and the geodesic distances between catheter sensors. The proposed algorithm can identify the focal sources when the electrical conduction is initiated by irregular electrical impulses and involves wave collisions, breakups, and spiral waves. The statistical modeling framework can efficiently deal with data uncertainties and provide a reliable estimation of the focal source locations. This shows the great potential of a statistical approach for the quantitative analysis of the stochastic activity of electrical waves in cardiac disorders and suggests future investigations integrating statistical methods with a deterministic geometry-based method to achieve advanced diagnostic performance.

scholarly journals Assembly of the Cardiac Pacemaking Complex: Electrogenic Principles of Sinoatrial Node Morphogenesis

2021 ◽  
Vol 8 (4) ◽  
pp. 40
Author(s):  
Marietta Easterling ◽  
Simone Rossi ◽  
Anthony J Mazzella ◽  
Michael Bressan
Keyword(s):  
Cardiac Tissue ◽  
Sinoatrial Node ◽  
Cardiac Pacemaker ◽  
Tissue Level ◽  
Rhythmic Contraction ◽  
Entire Volume ◽  
Impulse Generation ◽  
Cardiac Pacemaking ◽  
Electrical Impulses ◽  
Sufficient Strength

Cardiac pacemaker cells located in the sinoatrial node initiate the electrical impulses that drive rhythmic contraction of the heart. The sinoatrial node accounts for only a small proportion of the total mass of the heart yet must produce a stimulus of sufficient strength to stimulate the entire volume of downstream cardiac tissue. This requires balancing a delicate set of electrical interactions both within the sinoatrial node and with the downstream working myocardium. Understanding the fundamental features of these interactions is critical for defining vulnerabilities that arise in human arrhythmic disease and may provide insight towards the design and implementation of the next generation of potential cellular-based cardiac therapeutics. Here, we discuss physiological conditions that influence electrical impulse generation and propagation in the sinoatrial node and describe developmental events that construct the tissue-level architecture that appears necessary for sinoatrial node function.

scholarly journals A statistical approach to fast nowcasting of lightning potential fields

2020 ◽  
Vol 6 (2) ◽  
pp. 79-90
Author(s):  
Joshua North ◽  
Zofia Stanley ◽  
William Kleiber ◽  
Wiebke Deierling ◽  
Eric Gilleland ◽  
...  
Keyword(s):  
Statistical Approach ◽  
Potential Fields ◽  
Short Term ◽  
Modeling Framework ◽  
Image Deformation ◽  
Atmospheric Research ◽  
Advection Scheme ◽  
Complex Image ◽  
Short Term Prediction ◽  
Deformation Approach

Abstract. Thunderstorms and associated hazards like lightning can pose a serious threat to people outside and infrastructure. Thus, very short-term prediction capabilities (called nowcasting) have been developed to capture this threat and aid in decision-making on when to bring people inside for safety reasons. The atmospheric research and operational communities have been developing and using nowcasting methods for decades, but most methods do not rely on formal statistical approaches. A novel and fast statistical approach to nowcasting of lightning threats is presented here that builds upon an integro-difference modeling framework. Inspiration from the heat equation is used to define a redistribution kernel, and a simple linear advection scheme is shown to work well for the lightning prediction example. The model takes only seconds to estimate and nowcast and is competitive with a more complex image deformation approach that is computationally infeasible for very short-term nowcasts.

scholarly journals An improved statistical approach for reconstructing past climates from biotic assemblages

2020 ◽  
Vol 476 (2243) ◽  
pp. 20200346
Author(s):  
Mengmeng Liu ◽  
Iain Colin Prentice ◽  
Cajo J. F. ter Braak ◽  
Sandy P. Harrison
Keyword(s):  
Statistical Approach ◽  
Climate Models ◽  
Likelihood Function ◽  
Model Performance ◽  
Multinomial Distribution ◽  
Weighted Averaging ◽  
Training Dataset ◽  
Least Squares Regression ◽  
Climate Variable ◽  
Modern Pollen

Quantitative reconstructions of past climates are an important resource for evaluating how well climate models reproduce climate changes. One widely used statistical approach for making such reconstructions from fossil biotic assemblages is weighted averaging partial least-squares regression (WA-PLS). There is however a known tendency for WA-PLS to yield reconstructions compressed towards the centre of the climate range used for calibration, potentially biasing the reconstructed past climates. We present an improvement of WA-PLS by assuming that: (i) the theoretical abundance of each taxon is unimodal with respect to the climate variable considered; (ii) observed taxon abundances follow a multinomial distribution in which the total abundance of a sample is climatically uninformative; and (iii) the estimate of the climate value at a given site and time makes the observation most probable, i.e. it maximizes the log-likelihood function. This climate estimate is approximated by weighting taxon abundances in WA-PLS by the inverse square of their climate tolerances. We further improve the approach by considering the frequency (  fx ) of the climate variable in the training dataset. Tolerance-weighted WA-PLS with fx correction greatly reduces the compression bias, compared with WA-PLS, and improves model performance in reconstructions based on an extensive modern pollen dataset.

scholarly journals Versatile electrical stimulator for providing cardiac-like electrical impulses in vitro

2020 ◽  
Author(s):  
Stefano Gabetti ◽  
Giovanni Putame ◽  
Federica Montrone ◽  
Giuseppe Isu ◽  
Anna Marsano ◽  
...  
Keyword(s):  
Cardiac Tissue ◽  
Animal Experiments ◽  
Cost Effective ◽  
Culture Conditions ◽  
Animal Testing ◽  
Electrical Stimulator ◽  
Electrical Impulses ◽  
Reliable Methods

In the perspective of reliable methods alternative to in vivo animal testing for cardiac tissue engineering (CTE) research, the versatile electrical stimulator ELETTRA has been developed. ELETTRA delivers controlled and stable cardiac-like electrical impulses, and it can be coupled to already existing bioreactors for providing in vitro combined biomimetic culture conditions. Designed to be cost-effective and easy to use, this device could contribute to the reduction and replacement of in vivo animal experiments in CTE.

scholarly journals Quantifying the uncertainty of precipitation forecasting using probabilistic deep learning

2021 ◽  
Author(s):  
Lei Xu ◽  
Nengcheng Chen ◽  
Chao Yang
Keyword(s):  
Deep Learning ◽  
Model Uncertainty ◽  
Uncertainty Modeling ◽  
Data Driven ◽  
Data Uncertainty ◽  
Precipitation Event ◽  
Input Uncertainty ◽  
Predictive Uncertainty ◽  
Precipitation Forecasting ◽  
Target Data

Abstract. Precipitation forecasting is an important mission in weather science. In recent years, data-driven precipitation forecasting techniques could complement numerical prediction, such as precipitation nowcasting, monthly precipitation projection and extreme precipitation event identification. In data-driven precipitation forecasting, the predictive uncertainty arises mainly from data and model uncertainties. Current deep learning forecasting methods could model the parametric uncertainty by random sampling from the parameters. However, the data uncertainty is usually ignored in the forecasting process and the derivation of predictive uncertainty is incomplete. In this study, the input data uncertainty, target data uncertainty and model uncertainty are jointly modeled in a deep learning precipitation forecasting framework to estimate the predictive uncertainty. Specifically, the data uncertainty is estimated a priori and the input uncertainty is propagated forward through model weights according to the law of error propagation. The model uncertainty is considered by sampling from the parameters and is coupled with input and target data uncertainties in the objective function during the training process. Finally, the predictive uncertainty is produced by propagating the input uncertainty and sampling the weights in the testing process. The experimental results indicate that the proposed joint uncertainty modeling and precipitation forecasting framework exhibits comparable forecasting accuracy with existing methods, while could reduce the predictive uncertainty to a large extent relative to two existing joint uncertainty modeling approaches. The developed joint uncertainty modeling method is a general uncertainty estimation approach for data-driven forecasting applications.

scholarly journals Integration of a semi-automatic in-vitro RFA procedure into an experimental setup

2016 ◽  
Vol 2 (1) ◽  
pp. 77-81 ◽  
Author(s):  
Stefan Pollnow ◽  
Lisa-Mareike Busch ◽  
Eike Moritz Wülfers ◽  
Robert Arnold ◽  
Olaf Dössel
Keyword(s):  
Cardiac Tissue ◽  
Circuit Board ◽  
Experimental Setup ◽  
Lesion Formation ◽  
Lesion Development ◽  
Time System ◽  
Real Time System ◽  
Intracardiac Electrogram ◽  
Protection Circuit

AbstractRadiofrequency ablation (RFA) is a standard clinical procedure for treating many cardiac arrhythmias. In order to increase the success rate of this treatment, the evaluation of lesion development with the help of intracardiac electrogram (EGM) criteria has to be improved further. We are investigating in-vitro the electrophysiological characteristics of cardiac tissue by using fluorescence-optical and electrical techniques. In this project, it is intended to create ablation lesions under defined conditions in rat atria or ventricle and to determine the electrical activity in the myocardium surrounding these lesions less than 1 s after the ablation. Therefore, we developed a semi-automatic RFA procedure, which was integrated into an existing experimental setup. Firstly, a controllable protection circuit board was designed to galvanically isolate the sensitive amplifiers for measuring extracellular potentials during the ablation. Secondly, a real-time system was implemented to control and to autonomously monitor the RFA procedure. We verified each component as well as the different sequences of the RFA procedure. In conclusion, the expanded setup will be used in future in-vitro experiments to determine new EGM criteria to assess lesion formation during the RFA procedure.

Requirement Uncertainty Modeling for Service Oriented Self-Adaptive Software

2012 ◽  
Vol 433-440 ◽  
pp. 4798-4801
Author(s):  
Wei Liu ◽  
Chen Wan He ◽  
Zai Wen Feng
Keyword(s):  
Adaptive Systems ◽  
Domain Knowledge ◽  
Uncertainty Modeling ◽  
Limited Attention ◽  
Requirement Analysis ◽  
Modeling Framework ◽  
Modeling And Analysis ◽  
Service Oriented ◽  
Solving Strategy ◽  
Self Adaptive

Service-oriented software utilizes services as fundamental elements for developing applications that have the capability to autonomously modify their behavior at run-time in response to changes in their environment. While a few techniques have been developed to support the modeling and analysis of requirements for self-adaptive systems, limited attention has been paid to the description of service requirements and uncertainty in requirements of service-oriented software. In this paper, we propose a task solving strategy for requirement analysis and modeling framework as a fundamental of self-adaptation evolution. We introduce task solving strategy method for requirement analysis process; a context snapshot model to represent uncertainty in requirement with domain knowledge; goal-oriented context requirement to model user requirements and process-oriented context requirement to model service requirements; and finally, propose means-c-end analysis to relate user and service requirement with context condition.

scholarly journals Crosstalk between TGF-β and WNT signalling pathways during cardiac fibrogenesis

2018 ◽  
Vol 65 (3) ◽  
pp. 341-349 ◽  
Author(s):  
Edyta Działo ◽  
Karolina Tkacz ◽  
Przemysław Błyszczuk
Keyword(s):  
Stromal Cells ◽  
Cardiac Fibrosis ◽  
Cardiac Tissue ◽  
Transforming Growth Factor ◽  
Current Knowledge ◽  
Transforming Growth Factor Β ◽  
Cellular Level ◽  
Wnt Signalling ◽  
Signalling Pathways ◽  
Electrical Impulses

Cardiac fibrosis is referred to as an excessive accumulation of stromal cells and extracellular matrix proteins in the myocardium. Progressive fibrosis causes stiffening of the cardiac tissue and affects conduction of electrical impulses, leading to heart failures in a broad range of cardiac conditions. At the cellular level, activation of the cardiac stromal cells and myofibroblast formation are considered as hallmarks of fibrogenesis. At the molecular level, transforming growth factor β (TGF-β) is traditionally considered as a master regulator of the profibrotic processes. More recently, the WNT signalling pathway has also been found to be implicated in the development of myocardial fibrosis. In this review, we summarize current knowledge on the involvement of TGF-β and WNT downstream molecular pathways to cardiac fibrogenesis and describe a crosstalk between these two profibrotic pathways. TGF-β and WNT ligands bind to different receptors and trigger various outputs. However, a growing body of evidence points to cross-regulation between these two pathways. It has been recognized that in cardiac pathologies TGF-β activates WNT/β-catenin signalling, which in turn stabilizes the TGF-β/Smad response. Furthermore both, the non-canonical TGF-β and non-canonical WNT signalling pathways, activate the same mitogen-activated protein kinases (MAPKs): the extracellular signal-regulated kinase (Erk), the c-Jun N-terminal kinases (JNKs) and p38. The cross-talk between TGF-β and WNT pathways seems to play an essential role in switching on the genetic machinery initiating profibrotic changes in the heart. Better understanding of these mechanisms will open new opportunities for development of targeted therapeutic approaches against cardiac fibrosis in the future.

The Application of Restricted Counter Schemes to Three Models of Linear Search

1992 ◽  
Vol 6 (3) ◽  
pp. 371-389 ◽  
Author(s):  
Micha Hofri ◽  
Hadas Shachnai
Keyword(s):  
Statistical Approach ◽  
Multinomial Distribution ◽  
Linear Search ◽  
Linear List ◽  
Time Required ◽  
Linear Lists

The mechanism of the Counter Scheme (CS) has been shown to be an effective statistical approach for the reorganization of linear lists, where the records in the list are referenced independently with a time homogeneous multinomial distribution. In this paper we show that derivative schemes can be used effectively in other contexts as well. Specifically, we consider (a) linear lists that are doubly linked, so that they may be accessed at both ends, (b) multilists, which result from dissecting a linear list into several pieces that are accessed independently and reside in WORM (write-once-read-many) store, and (c) reorganizing a disk, by copying its contents to another disk, so as to minimize the expected seek time required to access a record.

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