Article
Chemistry, Physical
Matthieu Dubarry, David Howey, Billy Wu
Summary: Digital twins are cyber-physical systems that integrate real-time sensor data and models for accurate predictions and optimal decisions in specific assets. In the case of batteries, this concept has been applied at different scales. However, a comprehensive approach is needed for battery digital twins to achieve their full potential in industrial settings. Standardized and transparent data sharing, as well as principled methods to quantify and propagate uncertainty, are essential. Physical modeling and sensing approaches for battery manufacturing and thermal runaway also need improvement.
Article
Health Care Sciences & Services
Joseph Rinehart, Sean Coeckelenbergh, Ishita Srivastava, Maxime Cannesson, Alexandre Joosten
Summary: Computational modeling has become routine in the development of medical devices. The FDA has published a manuscript on the development and validation of a computational model for blood volume, cardiac stroke volume, and blood pressure. This study expanded on the model to include the pharmacologic effect of sodium nitroprusside and calibrated it against experimental animal model data.
JOURNAL OF PERSONALIZED MEDICINE
(2023)
Article
Mathematics
Nathalie Verdiere, Oscar Navarro, Aude Naud, Alexandre Berred, Damienne Provitolo
Summary: This study investigates the calibration of a mathematical model describing behaviors during catastrophes, developed in collaboration with geographers and psychologists. Through virtual reality experiments and measuring electrocardiograms, stress levels were collected to calibrate the behavioral model. The estimation procedure and theoretical analysis revealed the system's capability to understand non-observable human processes.
Review
Agriculture, Dairy & Animal Science
Rafael Munoz-Tamayo, Luis O. Tedeschi
Summary: Constructing dynamic mathematical models of biological systems involves parameter estimation using statistical fitting procedures and structural identifiability analysis. Structural identifiability analysis helps determine actions needed to improve the identifiability of model parameters. Dedicated software tools make this analysis accessible to non-expert users. This paper encourages the integration of identifiability analysis into animal science modeling practices.
JOURNAL OF ANIMAL SCIENCE
(2023)
Article
Multidisciplinary Sciences
Dominique Joubert, J. D. Stigter, Jaap Molenaar
Summary: Structural identifiability is crucial in model development, and problematic initial values may lead to unidentifiability, which can be resolved by changing these values.
SCIENTIFIC REPORTS
(2021)
Article
Environmental Sciences
Befekadu Taddesse Woldegiorgis, Helen Baulch, Howard Wheater, Jill Crossman, Martyn Clark, Tricia Stadnyk, Ajay Bajracharya
Summary: Proper numerical representation is crucial in mechanistic hydrological models for robust predictions. The commonly used sequential calculation method for multiple fluxes in hydrological models can lead to errors. This study compares two versions of the HYPE model and finds that the original model and the sequential calculation method have limitations in simulating interflow, while a modified version with implicit Euler method provides more accurate results.
WATER RESOURCES RESEARCH
(2023)
Article
Mathematics, Applied
Amal Zeaiter, Etienne Videcoq, Matthieu Fenot
Summary: The aim of this paper is to identify unknown losses in a permanent-magnet synchronous motor through thermal assessment. A new approach based on solving a heat transfer inverse problem in real time is proposed. The results show that the thermal heat dissipated due to losses can be accurately estimated.
Article
Acoustics
Xu Zhong, Dong Zhang
Summary: Attenuation and latency are important performance indicators of earmuffs, and a lumped parameter model can be used to predict these two performances. By decreasing the stiffness, damping, and air stiffness of the earmuff cushion, or increasing the mass of the earmuff, a longer passive latency can be achieved.
Article
Multidisciplinary Sciences
Sahil Bhola, Karthik Duraisamy
Summary: This paper proposes a novel information-theoretic approach to assess the practical identifiability of Bayesian statistical models globally. The method does not rely on any assumptions about the model structure or prior distribution, and can take into account different forms of uncertainties. By analyzing the dependencies between parameters, a subset of parameters that can be estimated with high certainty is found.
SCIENTIFIC REPORTS
(2023)
Article
Engineering, Civil
Kirsten E. Faulkner, Bryant C. Jurgens, Stefan A. Voss, Danielle I. Dupuy, Zeno F. Levy
Summary: This study investigates the penetration depth of post-1950s recharge in aquifers to identify groundwater vulnerable to human contamination. The study uses a four-dimensional approach to compute, interpolate, and project the depth values across time in the Central Valley aquifer system in California. The results show that the penetration depth is expected to increase in the future, which may lead to an increase in anthropogenic contaminants.
JOURNAL OF HYDROLOGY
(2023)
Article
Biology
Jiade Qiu, Xin Chen, Dengfeng Wu, Xianren Zhang, Daojian Cheng
Summary: Based on the generalized Darcy model, a linear one-dimensional (1D) composite model is developed to predict the effects of the inserted balloon on blood flow dynamics in flexible arterial networks during REBOA operations. The model considers the decrease of cardiac output under different degrees of blood loss and incorporates the effect of the inserted balloon using a neural network approach. The accuracy of the 1D composite model is verified through comparison with computational fluid dynamics simulations and it is proven to reproduce the main features of the systemic circulation under balloon occlusion during REBOA surgery. The model's ability to provide instant predictions of working parameters during RABOA operations is particularly valuable.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Engineering, Multidisciplinary
Hui Wang, Ronggang Yang, Jiawei Xiang
Summary: This study uses a lumped parameter model in the numerical simulation of gears to generate enough training samples, aiming to achieve fault diagnosis. By constructing and updating the lumped parameter model, and generating a sample matrix using simulated and measured signals, artificial intelligence models are used to classify unknown fault samples. The results show that using lumped parameter models to generate sample data is a feasible approach for fault classification.
Article
Biochemical Research Methods
Xabier Rey Barreiro, Alejandro F. Villaverde
Summary: In this study, we conducted a comprehensive investigation on the available computational resources for analyzing structural identifiability. We evaluated the performance of 13 different software tools developed in 7 programming languages. Our results provide insights into the strengths and weaknesses of these tools, and offer guidance for selecting the most appropriate tool for specific problems. We also identify opportunities for future developments in this field.
Article
Computer Science, Interdisciplinary Applications
Hao Sun, Bao Li, Jincheng Liu, Xiaolu Xi, Liyuan Zhang, Yanping Zhang, Guangfei Li, Huamei Guo, Kenan Gu, Tongna Wang, Chuanqi Wen, Youjun Liu
Summary: This study established a lumped-parameter model (BTM-LPM) of brain tissue microcirculation based on computed tomography angiography (CTA), which can accurately calculate cerebral perfusion in real time and demonstrate the importance of Circle of Willis anatomy in different ischemic injuries to cerebral tissue. The calculated cerebral perfusion would serve as a reference value for early diagnosis and preoperative planning of different ischemic injuries to cerebral tissue, showing great potential for replacing computed tomography perfusion (CTP) examination.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Automation & Control Systems
Longfei Cao, Xinggang Fan, Dawei Li, Wubin Kong, Ronghai Qu, Zirui Liu
Summary: This article proposes an improved lumped parameter thermal network (LPTN) based online temperature prediction method for permanent magnet (PM) machines. The method incorporates global parameter identification and considers nonlinear characteristics such as magnetic saturation, cross-saturation, strand skin effect, and speed-dependent convective heat transfer. By using the identified multiphysical magneto-thermal model, the critical temperatures, online losses, and torque of PM machines can be predicted in real time. Experimental results show that the proposed method can track the real temperature variation within 5 degrees C.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Computer Science, Interdisciplinary Applications
Antoine Pironet, Paul D. Docherty, Pierre C. Dauby, J. Geoffrey Chase, Thomas Desaive
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2019)
Article
Chemistry, Multidisciplinary
Sina G. Yazdi, Larissa Huetter, Paul D. Docherty, Petra N. Williamson, Don Clucas, Mark Jermy, Patrick H. Geoghegan
APPLIED SCIENCES-BASEL
(2019)
Article
Multidisciplinary Sciences
Sina G. Yazdi, Paul D. Docherty, Adib Khanafer, Mark Jermy, Natalia Kabaliuk, Patrick H. Geoghegan, Petra Williamson
Summary: The study concluded that a compliance mismatch between the graft and parent artery can lead to hemodynamic disturbances at the distal edge of the graft, potentially causing limb occlusion.
JOURNAL OF THE ROYAL SOCIETY OF NEW ZEALAND
(2021)
Article
Cardiac & Cardiovascular Systems
Petra N. Williamson, Paul D. Docherty, Sina G. Yazdi, Adib Khanafer, Natalia Kabaliuk, Mark Jermy
Summary: Through in-vitro modelling techniques, researchers successfully simulated the Type 1B endoleak of the FET stent graft, finding that the endoleak occurred at the peak of diastole and sustained until the onset of diastole. The asymmetrical endoleak may indicate variation in the phantom artery wall thickness or stent alignment. These findings can assist in future remediation techniques or stent design.
CARDIOVASCULAR ENGINEERING AND TECHNOLOGY
(2021)
Article
Engineering, Biomedical
Tamer Abdulbaki Alshirbaji, Nour Aldeen Jalal, Paul D. Docherty, Thomas Neumuth, Knut Moeller
Summary: This study proposed a deep learning framework that combines spatial and temporal information for detecting surgical tools in laparoscopic videos. Through six-fold cross-validation on a large dataset, the approach achieved superior performance, surpassing state-of-the-art methods by 3.00% in mean average precision.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2021)
Article
Engineering, Biomedical
Frederick Wright, Paul D. Docherty, Elisabeth Williams, Desney Greybe, Hari Arora, Natalia Kabaliuk
Summary: Accurate analysis of head impact telemetry data is crucial for developing biomechanical models to reduce the risk of traumatic brain injury. This study demonstrates the importance of considering the non-linear nature of skin when measuring head acceleration during impacts with a sensor mounted to the skin. The findings suggest that non-linearity of skin-skull dynamics may lead to drastic over-estimates of skull acceleration in large impacts.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2021)
Article
Endocrinology & Metabolism
Nicholas Lam, Rua Murray, Paul D. Docherty, Lisa Te Morenga, J. Geoffrey Chase
Summary: This study compared a mixing model with local depot site compartments with an existing clinically validated insulin sensitivity test model and found that while the mixing model effectively captured the dynamics of mixing behavior, it did not significantly improve insulin sensitivity identification.
JOURNAL OF DIABETES SCIENCE AND TECHNOLOGY
(2022)
Article
Automation & Control Systems
Feng Cao, Paul D. Docherty, XiaoQi Chen
Summary: The paper introduces a sensorless external force estimation approach that combines Weighted Moving Average (WMA) and the standard Kalman filter (SKF) to improve confidence in motor output torque, while continuously adapting the filter span for optimal tradeoff between response time and estimation precision in real time. The proposed method results in a significant reduction of root-mean-square error and response time compared to established methods, making it suitable for application in various robotic manipulators for cost-effective collision recognition.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Article
Education & Educational Research
Wendy H. Fox-Turnbull, Paul D. Docherty, Pinelopi Zaka, Tessa Impey
Summary: There is a recognized lack of women in engineering and STEM fields in most western countries. Teachers play a significant role in influencing students' career decisions, but many education students have limited or stereotypical views of engineering, which may lead to gender bias when providing career advice.
INTERNATIONAL JOURNAL OF TECHNOLOGY AND DESIGN EDUCATION
(2023)
Article
Multidisciplinary Sciences
Baxter Williams, Daniel Bishop, Paul Docherty
Summary: This paper compares different methods of HWC temperature control and presents a methodology to assess the amount of thermal storage available in HWCs for demand side management based on use behavior in different household types. By using simple stochastic methods to predict domestic hot water demand, a smart controller was designed to achieve lower rates of unmet demand and higher available storage compared to traditional controllers. The average storage available for DSM from the use of this smart controller is predicted to be between 3.63 and 7.20 kWh per household. These findings suggest that using HWCs for thermal storage is a cost-effective solution for peak shaving and reducing greenhouse gas emissions in countries like New Zealand.
JOURNAL OF THE ROYAL SOCIETY OF NEW ZEALAND
(2023)
Article
Chemistry, Analytical
Nour Aldeen Jalal, Tamer Abdulbaki Alshirbaji, Paul David Docherty, Herag Arabian, Bernhard Laufer, Sabine Krueger-Ziolek, Thomas Neumuth, Knut Moeller
Summary: Adapting intelligent context-aware systems (CAS) to future operating rooms aims to improve situational awareness and provide surgical decision support systems to medical teams. In this work, a deep learning approach for analyzing laparoscopic videos for surgical phase recognition, tool classification, and weakly-supervised tool localization was proposed. The experimental results demonstrated the ability of the model to learn discriminative features for all tasks and highlighted the importance of integrating attention modules and multi-stage feature fusion for more robust and precise detection of surgical phases and tools.
Article
Chemistry, Analytical
Bernhard Laufer, Paul D. Docherty, Rua Murray, Sabine Krueger-Ziolek, Nour Aldeen Jalal, Fabian Hoeflinger, Stefan J. Rupitsch, Leonhard Reindl, Knut Moeller
Summary: This research focuses on measuring respiratory volume using upper body movements and a smart shirt. By using motion capture and regression methods, the study determines the optimal selection and placement of sensors on the shirt to accurately recover respiratory parameters. The results show that the Lasso method outperforms Ridge regression, providing sparse solutions and better handling of outliers. The smart shirt could potentially replace spirometry and offer a more convenient way to measure respiratory parameters in home care or hospital settings.
Article
Health Care Sciences & Services
Rebecca H. K. Emanuel, Paul D. Docherty, Helen Lunt, Rebecca E. Campbell
Summary: This study explores the feasibility of using a web-based forum for clinical research by analyzing laboratory test results posted in a PCOS subreddit. The results suggest that the forum participants were representative of research-identified PCOS cohorts, with most laboratory test values showing consistency with published literature for PCOS.
JMIR FORMATIVE RESEARCH
(2023)
Article
Education & Educational Research
Paul D. Docherty, Pinelopi A. Zaka, Wendy Fox-Turnbull
Summary: The study examined the impact of the flipped classroom approach on the academic performance of engineering students and found no significant differences in performance in the first year dynamics class due to the teaching method used.
RESEARCH PAPERS IN EDUCATION
(2022)
Article
Education & Educational Research
Pinelopi A. Zaka, Wendy H. Fox, Paul D. Docherty
AUSTRALASIAN JOURNAL OF EDUCATIONAL TECHNOLOGY
(2019)