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- 31P magnetic resonance spectroscopy (1)
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Articles 1 - 4 of 4
Full-Text Articles in Physiology
Mitochondrial Function Assessed By 31p Mrs And Bold Mri In Non-Obese Type 2 Diabetic Rats, Yuchi Liu, Xunbai Mei, Jielei Li, Nicola Lai, Xin Yu
Mitochondrial Function Assessed By 31p Mrs And Bold Mri In Non-Obese Type 2 Diabetic Rats, Yuchi Liu, Xunbai Mei, Jielei Li, Nicola Lai, Xin Yu
Electrical & Computer Engineering Faculty Publications
The study aims to characterize age-associated changes in skeletal muscle bioenergetics by evaluating the response to ischemia-reperfusion in the skeletal muscle of the Goto-Kakizaki (GK) rats, a rat model of non-obese type 2 diabetes (T2D). 31P magnetic resonance spectroscopy (MRS) and blood oxygen level-dependent (BOLD) MRI was performed on the hindlimb of young (12 weeks) and adult (20 weeks) GK and Wistar (control) rats. 31P-MRS and BOLD-MRI data were acquired continuously during an ischemia and reperfusion protocol to quantify changes in phosphate metabolites and muscle oxygenation. The time constant of phosphocreatine recovery, an index of mitochondrial oxidative capacity, …
Gender Differences In Vo2 And Hr Kinetics At The Onset Of Moderate And Heavy Exercise Intensity In Adolescents, Nicola Lai, Alessandro Martis, Alfredo Belfiori, Fatima Tolentino-Silva, Melita M. Nasca, James Strainic, Marco E. Cabrera
Gender Differences In Vo2 And Hr Kinetics At The Onset Of Moderate And Heavy Exercise Intensity In Adolescents, Nicola Lai, Alessandro Martis, Alfredo Belfiori, Fatima Tolentino-Silva, Melita M. Nasca, James Strainic, Marco E. Cabrera
Electrical & Computer Engineering Faculty Publications
The majority of the studies on VO2 kinetics in pediatric populations investigated gender differences in prepubertal children during submaximal intensity exercise, but studies are lacking in adolescents. The purpose of this study was to test the hypothesis that gender differences exist in the VO2 and heart rate (HR) kinetic responses to moderate (M) and heavy (H) intensity exercise in adolescents. Twenty-one healthy African-American adolescents (9 males, 15.8 ± 1.1 year; 12 females, 15.7 ± 1 year) performed constant work load exercise on a cycle ergometer at M and H. The VO2 kinetics of the male group was …
A Systematic Approach For Engagement Analysis Under Multitasking Environments, Guangfan Zhang, John Leddo, Roger Xu, Carl Richey, Tom Schnell, Frederick Mckenzie, Jiang Li, Thomas E. Pinelli (Ed.)
A Systematic Approach For Engagement Analysis Under Multitasking Environments, Guangfan Zhang, John Leddo, Roger Xu, Carl Richey, Tom Schnell, Frederick Mckenzie, Jiang Li, Thomas E. Pinelli (Ed.)
Electrical & Computer Engineering Faculty Publications
An overload condition can lead to high stress for an operator and further cause substantial drops in performance. On the other extreme, in automated systems, an operator may become underloaded; in which case, it is difficult for the operator to maintain sustained attention. When an unexpected event occurs, either internal or external to the automated system, a disengaged operation may neglect, misunderstand, or respond slowly/inappropriately to the situation. In this paper, we discuss a systematic approach monitor for extremes of cognitive workload and engagement in multitasking environments. Inferences of cognitive workload and engagement are based on subjective evaluations, objective performance …
Imbalanced Learning For Functional State Assessment, Feng Li, Frederick Mckenzie, Jiang Li, Guanfan Zhang, Roger Xu, Carl Richey, Tom Schnell, Thomas E. Pinelli (Ed.)
Imbalanced Learning For Functional State Assessment, Feng Li, Frederick Mckenzie, Jiang Li, Guanfan Zhang, Roger Xu, Carl Richey, Tom Schnell, Thomas E. Pinelli (Ed.)
Electrical & Computer Engineering Faculty Publications
This paper presents results of several imbalanced learning techniques applied to operator functional state assessment where the data is highly imbalanced, i.e., some function states (majority classes) have much more training samples than other states (minority classes). Conventional machine learning techniques usually tend to classify all data samples into majority classis and perform poorly for minority classes. In this study, we implemented five imbalanced learning techniques, including random under-sampling, random over-sampling, synthetic minority over-sampling technique (SMOTE), borderline-SMOTE and adaptive synthetic sampling (ADASYN) to solve this problem. Experimental results on a benchmark driving test dataset show that accuracies for minority classes …