scholarly journals Models of the cardiac L-type calcium current: a quantitative comparison

2021 ◽  
Author(s):  
Aditi Agrawal ◽  
Ken Wang ◽  
Liudmila Polonchuk ◽  
Jonathan Cooper ◽  
Gary R Mirams ◽  
...  
Keyword(s):  
Calcium Current ◽  
Cardiac Electrophysiology ◽  
Critical Role ◽  
Data Driven ◽  
Consensus Model ◽  
Simulation Code ◽  
Large Variability ◽  
Critical Comparison ◽  
Mathematical Equations ◽  
Major Data

The L-type calcium current (ICaL) plays a critical role in cardiac electrophysiology, and models of ICaL are vital tools to predict arrhythmogenicity of drugs and mutations. Five decades of measuring and modelling ICaL have resulted in several competing theories (encoded in mathematical equations). However, the introduction of new models has not typically been accompanied by a data-driven critical comparison with previous work, so that it is unclear where predictions overlap or conflict, or which model is best suited for any particular application. We gathered 71 mammalian ICaL models, compared their structure, and reproduced simulated experiments to show that there is a large variability in their predictions, which was not substantially diminished when grouping by species or other categories. By highlighting the differences in these competing theories, listing major data sources, and providing simulation code, we have laid strong foundations for the development of a consensus model of ICaL.

scholarly journals Machine learning applied to simulations of collisions between rotating, differentiated planets

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Miles L. Timpe ◽  
Maria Han Veiga ◽  
Mischa Knabenhans ◽  
Joachim Stadel ◽  
Stefano Marelli
Keyword(s):  
Machine Learning ◽  
Planet Formation ◽  
Critical Role ◽  
Ensemble Methods ◽  
Terrestrial Planet ◽  
Data Driven ◽  
Analytic Methods ◽  
Accurate Treatment ◽  
Post Impact ◽  
The Cost

AbstractIn the late stages of terrestrial planet formation, pairwise collisions between planetary-sized bodies act as the fundamental agent of planet growth. These collisions can lead to either growth or disruption of the bodies involved and are largely responsible for shaping the final characteristics of the planets. Despite their critical role in planet formation, an accurate treatment of collisions has yet to be realized. While semi-analytic methods have been proposed, they remain limited to a narrow set of post-impact properties and have only achieved relatively low accuracies. However, the rise of machine learning and access to increased computing power have enabled novel data-driven approaches. In this work, we show that data-driven emulation techniques are capable of classifying and predicting the outcome of collisions with high accuracy and are generalizable to any quantifiable post-impact quantity. In particular, we focus on the dataset requirements, training pipeline, and classification and regression performance for four distinct data-driven techniques from machine learning (ensemble methods and neural networks) and uncertainty quantification (Gaussian processes and polynomial chaos expansion). We compare these methods to existing analytic and semi-analytic methods. Such data-driven emulators are poised to replace the methods currently used in N-body simulations, while avoiding the cost of direct simulation. This work is based on a new set of 14,856 SPH simulations of pairwise collisions between rotating, differentiated bodies at all possible mutual orientations.

Investigating the Role of Data-Driven Decision-Making Within School Improvement Processes

2021 ◽  
pp. 1707-1725
Author(s):  
Venesser Fernandes
Keyword(s):  
Decision Making ◽  
Organizational Change ◽  
School Improvement ◽  
Critical Role ◽  
Data Driven ◽  
Evidence Based ◽  
Data Driven Decision Making ◽  
Continuous School Improvement ◽  
Decision Making Processes

This chapter provides a detailed literature review exploring the importance of data-driven decision-making processes in current Australian school improvement processes within a context of evidence-based organizational change and development. An investigation into the concept of decision-making and its effect on organizational culture is conducted as change and development are considered to be the new constants in the current discourse around continuous school improvement in schools. In a close examination of literature, this chapter investigates how key factors such as collaboration, communication, and organizational trust are achieved through data-driven decision-making within continuous school improvement processes. The critical role of leadership in sustaining data cultures is also examined for its direct impact on continuous school improvement processes based on evidence-based organizational change and development practices. Future implications of data-driven decision-making to sustain continuous school improvement and accountability processes in Australian schools are discussed.

scholarly journals Active Disturbance Rejection Control of Boiler Forced Draft System: A Data-Driven Practice

2020 ◽  
Vol 12 (10) ◽  
pp. 4171
Author(s):  
Qianchao Wang ◽  
Hongcan Xu ◽  
Lei Pan ◽  
Li Sun
Keyword(s):  
Disturbance Rejection ◽  
Critical Role ◽  
Back Propagation ◽  
Data Driven ◽  
Active Disturbance Rejection Control ◽  
Time Data ◽  
Plant Safety ◽  
Active Disturbance Rejection ◽  
Disturbance Rejection Control ◽  
Forced Draft

Boiler forced draft systems play a critical role in maintaining power plant safety and efficiency. However, their control is notoriously intractable in terms of modelling difficulty, multiple disturbances and severe noise. To this end, this paper develops a data-driven paradigm by combining some popular data analytics methods in both modelling and control. First, singular value decomposition (SVD) is utilized for data classification, which further cooperates with back propagation (BP) neural network to de-noise the measurements. Second, prediction error method (PEM) is used to analyze the historical data and identify the dynamic model, whose responses agree well with the actual plant data. Third, by estimating the lumped disturbances via the real-time data, active disturbance rejection control (ADRC) is employed to control the forced draft system, whose stability is analyzed in the frequency domain. Simulation results demonstrate the efficiency and superiority of the proposed method over proportional-integral-differential (PID) controller and model predictive controller, depicting a promising prospect in the future industry practice.

AMPK mediates regulation of voltage-gated calcium channels by leptin in isolated neurons from arcuate nucleus

2020 ◽  
Vol 319 (6) ◽  
pp. E1112-E1120
Author(s):  
K. Bermeo ◽  
H. Castro ◽  
I. Arenas ◽  
D. E. Garcia
Keyword(s):  
Energy Balance ◽  
Calcium Current ◽  
Arcuate Nucleus ◽  
Critical Role ◽  
Fine Tuning ◽  
Isolated Neurons ◽  
Voltage Gated ◽  
Voltage Gated Calcium Channels ◽  
General Energy

Our results readily support the hypothesis that AMPK is responsible for the maintenance of the calcium current and mediates the fine-tuning modulation of the leptin response. The novelty of these results strengthens the critical role of AMPK in the general energy balance and homeostasis.

scholarly journals Sources of individual variation in plasma testosterone levels

2007 ◽  
Vol 363 (1497) ◽  
pp. 1711-1723 ◽  
Author(s):  
Bart Kempenaers ◽  
Anne Peters ◽  
Katharina Foerster
Keyword(s):  
Individual Variation ◽  
Critical Role ◽  
Time Of Day ◽  
Integrative Approach ◽  
Plasma Testosterone ◽  
Extrinsic Factors ◽  
Honest Signalling ◽  
Large Variability ◽  
Trade Offs ◽  
Potential Sources

The steroid hormone testosterone (T) plays a central role in the regulation of breeding in males, because many physiological, morphological and behavioural traits related to reproduction are T dependent. Moreover, in many seasonally breeding vertebrates, male plasma T levels typically show a pronounced peak during the breeding season. While such population-level patterns are fairly well worked out, the sources and the implications of the large variability in individual T levels within the seasonal cycle remain surprisingly little understood. Understanding the potential sources of individual variation in T levels is important for behavioural and evolutionary ecologists, for at least two reasons. First, in ‘honest signalling’ theory, T is hypothesized to play a critical role as the assumed factor that enforces honesty of the expression of sexually selected quality indicators. Second, T is often considered a key mediator of central life-history trade-offs, such as investment in survival versus reproduction or in mating versus parental care. Here, we discuss the patterns of within- and between-individual variation in male plasma T levels in free-living populations of birds. We argue that it is unclear whether this variability mainly reflects differences in underlying individual quality (intrinsic factors such as genetic or maternal effects) or in the environment (extrinsic factors including time of day, individual territorial status and past experience). Research in avian behavioural endocrinology has mainly focused on the effects of extrinsic factors, while other sources of variance are often ignored. We suggest that studies that use an integrative approach and investigate the relative importance of all potential sources of variation are essential for the interpretation of data on individual plasma T levels.

scholarly journals Comparative Evaluation of Control-Oriented Zone Temperature Prediction Modeling Strategies in Buildings

2015 ◽  
Author(s):  
Venkatesh Chinde ◽  
Jeffrey C. Heylmun ◽  
Adam Kohl ◽  
Zhanhong Jiang ◽  
Soumik Sarkar ◽  
...  
Keyword(s):  
Comparative Evaluation ◽  
Performance Monitoring ◽  
Control Strategies ◽  
Critical Role ◽  
Energy Resource ◽  
Real Data ◽  
Data Driven ◽  
Monitoring And Control ◽  
Test Bed ◽  
Occupant Comfort

Predictive modeling of zone environment plays a critical role in developing and deploying advanced performance monitoring and control strategies for energy usage minimization in buildings while maintaining occupant comfort. The task remains extremely challenging, as buildings are fundamentally complex systems with large uncertainties stemming from weather, occupants, and building dynamics. Over the past few years, purely data-driven various control-oriented modeling techniques have been proposed to address different requirements, such as prediction accuracy, flexibility, computation and memory complexity. In this context, this paper presents a comparative evaluation among representative methods of different classes of models, such as first principles driven (e.g., lumped parameter autoregressive models using simple physical relationships), data-driven (e.g., artificial neural networks, Gaussian processes) and hybrid (e.g., semi-parametric). Apart from quantitative metrics described above, various qualitative aspects such as cost of commissioning, robustness and adaptability are discussed as well. Real data from Iowa Energy Center’s Energy Resource Station (ERS) test bed is used as the basis of evaluation presented here.

scholarly journals Automated Decision-Making and Environmental Impact Assessments: Decisions, Data Analysis and Predictions

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Zoe Nay ◽  
Anna Huggins ◽  
Felicity Deane
Keyword(s):  
Decision Making ◽  
Data Analysis ◽  
Environmental Impact ◽  
Environmental Law ◽  
Critical Role ◽  
Data Driven ◽  
Data Driven Decision Making ◽  
Environmental Impact Assessments ◽  
Decision Making Processes ◽  
Automated Decision Making

This article critically examines the opportunities and challenges that automated decision-making (ADM) poses for environmental impact assessments (EIAs) as a crucial aspect of environmental law. It argues that while fully or partially automating discretionary EIA decisions is legally and technically problematic, there is significant potential for data-driven decision-making tools to provide superior analysis and predictions to better inform EIA processes. Discretionary decision-making is desirable for EIA decisions given the inherent complexity associated with environmental regulation and the prediction of future impacts. This article demonstrates that current ADM tools cannot adequately replicate human discretionary processes for EIAs—even if there is human oversight and review of automated outputs. Instead of fully or partially automating EIA decisions, data-driven decision-making can be more appropriately deployed to enhance data analysis and predictions to optimise EIA decision-making processes. This latter type of ADM can augment decision-making processes without displacing the critical role of human discretion in weighing the complex environmental, social and economic considerations inherent in EIA determinations.

Fast Data-Driven Calibration of a Cardiac Electrophysiology Model from Images and ECG

2013 ◽  
pp. 1-8 ◽  
Author(s):  
Oliver Zettinig ◽  
Tommaso Mansi ◽  
Bogdan Georgescu ◽  
Elham Kayvanpour ◽  
Farbod Sedaghat-Hamedani ◽  
...  
Keyword(s):  
Cardiac Electrophysiology ◽  
Data Driven

Consumer Information for Data-Driven Decision Making: Teaching Socially Responsible Use of Data

2018 ◽  
Vol 41 (2) ◽  
pp. 109-126 ◽  
Author(s):  
Kristen L. Walker ◽  
Nora Moran
Keyword(s):  
Decision Making ◽  
Critical Role ◽  
Consumer Information ◽  
Data Driven ◽  
Socially Responsible ◽  
Privacy And Security ◽  
Data Usage ◽  
Use Of Data ◽  
Resource Requirements ◽  
Data Driven Decisions

The marketing field is undergoing dramatic shifts in the digital age. The increasing reliance on, collection, and use of data enabled by technological innovations requires teaching the responsible use of data for personalization, and marketing educators play a critical role. Students, universities, accrediting agencies, and employers demand curriculum that equips students with appropriate knowledge, skills, and abilities to make data-driven decisions. We explore the curricular advantages of a unique marketing course that applies a social science lens to frame the emerging issue of socially responsible data usage. This type of curriculum fulfills students’ needs for current and relevant courses; provides key knowledge, skills, and abilities for prospective employers; meets department curriculum and resource requirements, all while addressing existing and newer AACSB guidelines for “Technology Agility” with a focus on “evidence-based decision making that integrates current and emerging technologies, . . . [the] ethical use and dissemination of data, including privacy and security of data.”

scholarly journals Utility of hERG Assays as Surrogate Markers of Delayed Cardiac Repolarization and QT Safety

2006 ◽  
Vol 34 (1) ◽  
pp. 81-90 ◽  
Author(s):  
Gary A. Gintant ◽  
Zhi Su ◽  
Ruth L. Martin ◽  
Bryan F. Cox
Keyword(s):  
Cardiac Electrophysiology ◽  
Critical Role ◽  
Drug Effects ◽  
Torsades De Pointes ◽  
Cardiac Repolarization ◽  
Surrogate Markers ◽  
Related Gene ◽  
Drug Induced ◽  
Herg Current

HERG (human-ether-a-go-go-related gene) encodes for a cardiac potassium channel that plays a critical role in defining ventricular repolarization. Noncardiovascular drugs associated with a rare but potentially lethal ventricular arrhythmia (Torsades de Pointes) have been linked to delayed cardiac repolarization and block of hERG current. This brief overview will discuss the role of hERG current in cardiac electrophysiology, its involvement in drug-induced delayed repolarization, and approaches used to define drug effects on hERG current. In addition, examples of hERG blocking drugs acting differently (i.e., overt and covert hERG blockade due to multichannel block) together with the utility and limitations of hERG assays as tools to predict the risk of delayed repolarization and proarrhythmia are discussed.

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