Although existing mechanics-based models of concentric tube robots have been experimentally demonstrated to approximate the actual kinematics, determining accurate estimates of model parameters remains difficult due to the complex relationship between the parameters and available measurements. Further, because the mechanics-based models neglect some phenomena like friction, nonlinear elasticity, and cross section deformation, it is also not clear if model error is due to model simplification or to parameter estimation errors. The parameters of the superelastic materials used in these robots can be slowly time-varying, necessitating periodic re-estimation. This paper proposes a method for estimating the mechanics-based model parameters using an extended Kalman filter as a step toward on-line parameter estimation. Our methodology is validated through both simulation and experiments.
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http://dx.doi.org/10.1109/IROS.2016.7759374 | DOI Listing |
Exp Ther Med
February 2025
Department of Biochemistry, Faculty of Science, Beni-Suef University, Beni-Suef 62511, Egypt.
Inefficient control of elevated blood sugar levels can lead to certain health complications such as diabetic nephropathy (DN) and cardiovascular disease (CVD). The identification of effective biomarkers for monitoring diabetes was performed in the present study. The present study aimed to investigate the implications of long non-coding RNA megacluster (lnc-MGC), microRNA (miR)-132 and miR-133a, and their correlation with lactate dehydrogenase (LDH) activity and glycated hemoglobin (HbA1C) levels to identify biomarkers for the early diagnosis of diabetes mellitus, induced DN and CVD.
View Article and Find Full Text PDFBiol Imaging
November 2024
Institut de Recherche en Informatique de Toulouse (IRIT), CNRS & Université de Toulouse, Toulouse, France.
We propose a neural network architecture and a training procedure to estimate blurring operators and deblur images from a single degraded image. Our key assumption is that the forward operators can be parameterized by a low-dimensional vector. The models we consider include a description of the point spread function with Zernike polynomials in the pupil plane or product-convolution expansions, which incorporate space-varying operators.
View Article and Find Full Text PDFEcol Evol
January 2025
Whale and Dolphin Conservation Adelaide South Australia Australia.
Understanding population demography of threatened species and how they vary in relation to natural and anthropogenic stressors is essential for effective conservation. We used a long-term photographic capture-recapture dataset (1993-2020) of Indo-Pacific bottlenose dolphins () in the highly urbanised Adelaide Dolphin Sanctuary (ADS), South Australia, to estimate key demographic parameters and their variability over time. These parameters were analysed in relation to environmental variables used as indicators of local and large-scale climatic events.
View Article and Find Full Text PDFStat Comput
August 2024
Department of Mathematics, University of Texas at Arlington, Texas, USA 76019.
Cure rate models have been thoroughly investigated across various domains, encompassing medicine, reliability, and finance. The merging of machine learning (ML) with cure models is emerging as a promising strategy to improve predictive accuracy and gain profound insights into the underlying mechanisms influencing the probability of cure. The current body of literature has explored the benefits of incorporating a single ML algorithm with cure models.
View Article and Find Full Text PDFCurr Cardiol Rep
January 2025
Director, Cardiac Intensive Care Emory Heart & Vascular Center, Emory University School of Medicine, Atlanta, GA, USA.
Purpose Of Review: To explore the definitions of sepsis-induced cardiomyopathy and how that impacts interpretation of the available data and considerations of long-term prognosis and management.
Recent Findings: The field of sepsis-induced cardiomyopathy has been hampered by lack of consensus about its proper definition, with a great deal of heterogeneity in clinical trial data in both individual studies and meta-analyses and consequent disparity of estimates of incidence, prognosis, and clinical significance. New diagnostic techniques, while potentially shedding light on pathophysiology, have only exacerbated these challenges.
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