Modelling Age Differences in Isometric Elbow Flexion Using Hill's Three-Element Visco-Elastic Model

1993 ◽  
Vol 37 (2) ◽  
pp. 202-205
Author(s):  
R. Darin Ellis ◽  
Kentaro Kotani
Keyword(s):  
Mechanical Properties ◽  
Steady State ◽  
Age Differences ◽  
Elbow Flexion ◽  
Model Parameters ◽  
Elastic Model ◽  
Tissue Elasticity ◽  
Age Related ◽  
Complex Models ◽  
State Force

A visco-elastic model of the mechanical properties of muscle was used to describe age-differences in the buildup of force in isometric elbow flexion. Given information from the literature on age-related physiological changes, such as decreasing connective-tissue elasticity, one would expect changes in the mechanical properties of skeletal muscle and their related model parameters. Force vs. time curves were obtained for 7 young (aged 21–27) and 7 old (aged 69–83) female subject. There were significant age group differences in steady-state force level and the best fitting model parameters. In particular, the viscous damping element of the model plays a large role in describing the increased time to reach steady-state force levels in the older subject group. Implications of this research include incorporating parameter differences into more complex models, such as crash impact models.

scholarly journals Disentangling the Effects of Processing Speed on the Association between Age Differences and Fluid Intelligence

2019 ◽  
Vol 8 (1) ◽  
pp. 1 ◽  
Author(s):  
Anna-Lena Schubert ◽  
Dirk Hagemann ◽  
Christoph Löffler ◽  
Gidon T. Frischkorn
Keyword(s):  
Individual Differences ◽  
Age Differences ◽  
Processing Speed ◽  
Cognitive Aging ◽  
Fluid Intelligence ◽  
Higher Order ◽  
Mediation Effect ◽  
Model Parameters ◽  
Response Planning ◽  
Age Related

Several studies have demonstrated that individual differences in processing speed fully mediate the association between age and intelligence, whereas the association between processing speed and intelligence cannot be explained by age differences. Because measures of processing speed reflect a plethora of cognitive and motivational processes, it cannot be determined which specific processes give rise to this mediation effect. This makes it hard to decide whether these processes should be conceived of as a cause or an indicator of cognitive aging. In the present study, we addressed this question by using a neurocognitive psychometrics approach to decompose the association between age differences and fluid intelligence. Reanalyzing data from two previously published datasets containing 223 participants between 18 and 61 years, we investigated whether individual differences in diffusion model parameters and in ERP latencies associated with higher-order attentional processing explained the association between age differences and fluid intelligence. We demonstrate that individual differences in the speed of non-decisional processes such as encoding, response preparation, and response execution, and individual differences in latencies of ERP components associated with higher-order cognitive processes explained the negative association between age differences and fluid intelligence. Because both parameters jointly accounted for the association between age differences and fluid intelligence, age-related differences in both parameters may reflect age-related differences in anterior brain regions associated with response planning that are prone to be affected by age-related changes. Conversely, age differences did not account for the association between processing speed and fluid intelligence. Our results suggest that the relationship between age differences and fluid intelligence is multifactorially determined.

scholarly journals Disentangling the Effects of Processing Speed on the Association between Age Differences and Fluid Intelligence

2019 ◽  
Author(s):  
Anna-Lena Schubert ◽  
Dirk Hagemann ◽  
Christoph Löffler ◽  
Gidon T. Frischkorn
Keyword(s):  
Individual Differences ◽  
Age Differences ◽  
Processing Speed ◽  
Cognitive Aging ◽  
Fluid Intelligence ◽  
Higher Order ◽  
Mediation Effect ◽  
Model Parameters ◽  
Response Planning ◽  
Age Related

Several studies have demonstrated that individual differences in processing speed fully mediate the association between age and intelligence, whereas the association between processing speed and intelligence cannot be explained by age differences. Because measures of processing speed reflect a plethora of cognitive and motivational processes, it cannot be determined which specific processes give rise to this mediation effect. This makes it hard to decide whether these processes should be conceived of as a cause or an indicator of cognitive aging. In the present study, we addressed this question by using a neurocognitive psychometrics approach to decompose the association between age differences and fluid intelligence. Reanalyzing data from two previously published datasets containing 223 participants between 18 and 61 years, we investigated whether individual differences in diffusion model parameters and in ERP latencies associated with higher-order attentional processing explained the association between age differences and fluid intelligence. We demonstrate that individual differences in the speed of non-decisional processes such as encoding, response preparation, and response execution, and individual differences in latencies of ERP components associated with higher-order cognitive processes explained the negative association between age differences and fluid intelligence. Because both parameters jointly accounted for the association between age differences and fluid intelligence, age-related differences in both parameters may reflect age-related differences in anterior brain regions associated with response planning that are prone to be affected by age-related changes. Conversely, age differences did not account for the association between processing speed and fluid intelligence. Our results suggest that the relationship between age differences and fluid intelligence is multifactorially determined. Data and analysis code are available at https://osf.io/hy5fw/.

Holdup and holdup profiles in the reciprocating plate extractor VPE

1990 ◽  
Vol 55 (11) ◽  
pp. 2648-2661 ◽  
Author(s):  
Helena Sovová ◽  
Vladislav Bízek ◽  
Jaroslav Procházka
Keyword(s):  
Steady State ◽  
Experimental Results ◽  
Model Parameters ◽  
Dispersed Phase ◽  
Pulse Form ◽  
Sieve Plates

In this work measurements of mean holdup of dispersed phase, of axial holdup profiles and of flooding points in a reciprocating plate contactor with both the VPE-type plates and the sieve plates were carried out. The experimental results were compared with a monodisperse model of steady-state column hydrodynamics and the model parameters were evaluated. Important differences in the behaviour of the two plate types could be identified. Comparison was also made between two reciprocating drives of different pulse form.

scholarly journals Age related extracellular matrix and interstitial cell phenotype in pulmonary valves

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Shaohua Wu ◽  
Vikas Kumar ◽  
Peng Xiao ◽  
Mitchell Kuss ◽  
Jung Yul Lim ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Extracellular Matrix ◽  
Heart Valve ◽  
Cell Phenotype ◽  
Primary Concern ◽  
Ross Operation ◽  
Age Related ◽  
Cardiovascular Morbidity And Mortality ◽  
Extracellular Matrix Components ◽  
Matrix Components

AbstractHeart valve disease is a common manifestation of cardiovascular disease and is a significant cause of cardiovascular morbidity and mortality worldwide. The pulmonary valve (PV) is of primary concern because of its involvement in common congenital heart defects, and the PV is usually the site for prosthetic replacement following a Ross operation. Although effects of age on valve matrix components and mechanical properties for aortic and mitral valves have been studied, very little is known about the age-related alterations that occur in the PV. In this study, we isolated PV leaflets from porcine hearts in different age groups (~ 4–6 months, denoted as young versus ~ 2 years, denoted as adult) and studied the effects of age on PV leaflet thickness, extracellular matrix components, and mechanical properties. We also conducted proteomics and RNA sequencing to investigate the global changes of PV leaflets and passage zero PV interstitial cells in their protein and gene levels. We found that the size, thickness, elastic modulus, and ultimate stress in both the radial and circumferential directions and the collagen of PV leaflets increased from young to adult age, while the ultimate strain and amount of glycosaminoglycans decreased when age increased. Young and adult PV had both similar and distinct protein and gene expression patterns that are related to their inherent physiological properties. These findings are important for us to better understand the physiological microenvironments of PV leaflet and valve cells for correctively engineering age-specific heart valve tissues.

Ageing Changes in the Tensile Properties of Tendons: Influence of Collagen Fibril Volume Fraction

2008 ◽  
Vol 130 (2) ◽  
Author(s):  
K. L. Goh ◽  
D. F. Holmes ◽  
H.-Y. Lu ◽  
S. Richardson ◽  
K. E. Kadler ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Collagen Fibril ◽  
Volume Fraction ◽  
Area Fraction ◽  
Sectional Area ◽  
Cross Sectional ◽  
P Values ◽  
Age Related ◽  
Fibril Diameter ◽  
Age Related Changes

Connective tissues are biological composites comprising of collagen fibrils embedded in (and reinforcing) the hydrated proteoglycan-rich (PG) gel within the extracellular matrices (ECMs). Age-related changes to the mechanical properties of tissues are often associated with changes to the structure of the ECM, namely, fibril diameter. However, quantitative attempts to correlate fibril diameter to mechanical properties have yielded inconclusive evidence. Here, we described a novel approach that was based on the rule of mixtures for fiber composites to evaluate the dependence of age-related changes in tendon tensile strength (σ) and stiffness (E) on the collagen fibril cross-sectional area fraction (ρ), which is related to the fibril volume fraction. Tail tendons from C57BL6 mice from age groups 1.6–35.3months old were stretched to failure to determine σ and E. Parallel measurements of ρ as a function of age were made using transmission electron microscopy. Mathematical models (rule of mixtures) of fibrils reinforcing a PG gel in tendons were used to investigate the influence of ρ on ageing changes in σ and E. The magnitudes of σ, E, and ρ increased rapidly from 1.6monthsto4.0months (P-values <0.05) before reaching a constant (age independent) from 4.0monthsto29.0months (P-values >0.05); this trend continued for E and ρ (P-values >0.05) from 29.0monthsto35.3months, but not for σ, which decreased gradually (P-values <0.05). Linear regression analysis revealed that age-related changes in σ and E correlated positively to ρ (P-values <0.05). Collagen fibril cross-sectional area fraction ρ is a significant predictor of ageing changes in σ and E in the tail tendons of C57BL6 mice.

Study on Multi-Axial Mechanical Properties of a Polyurethane Foam and Experimental Verification

2011 ◽  
Vol 311-313 ◽  
pp. 301-308
Author(s):  
Shou Hong Han ◽  
Zhen Hua Lu ◽  
Yong Jin Liu
Keyword(s):  
Mechanical Properties ◽  
Constitutive Model ◽  
Polyurethane Foam ◽  
Axial Compression ◽  
Axial Loading ◽  
Hydrostatic Compression ◽  
Model Parameters ◽  
Loading Conditions ◽  
Three Point Bending ◽  
Pu Foam

In order to investigate the multi-axial mechanical properties of a kind of PU (polyurethane) foam, some experiments in different loading conditions including uni-axial tension, uni-axial compression, hydrostatic compression and three-point bending were conducted. It is shown that the hydrostatic component influences yield behavior of PU foam, the yield strength and degree of strain hardening in hydrostatic compression exceed those for uni-axial compression. In terms of the differential hardening constitutive model, the evolution of PU foam yield surface and plastic hardening laws were fitted from experimental data. A finite element method was applied to analyze the quasi-static responses of the PU foam sandwich beam subjected to three-point bending, and good agreement was observed between experimental load-displacement responses and computational predictions, which validated the multi-axial loading methods and stress-strain constitutive model parameters. Moreover, effects of two foam models applied to uni-axial loading and multi-axial loading conditions were analyzed and compared with three-point bending tests and simulations. It is found that the multi-axial constitutive model can bring more accurate prediction whose parameters are obtained from the tests above mentioned.

Age Differences in the Social Associative Learning of Trust Information

2022 ◽  
Author(s):  
Kendra Leigh Seaman ◽  
Alexander P. Christensen ◽  
Katherine Senn ◽  
Jessica Cooper ◽  
Brittany Shane Cassidy
Keyword(s):  
Older Adults ◽  
Age Differences ◽  
Social Cues ◽  
Trust Game ◽  
Time Model ◽  
Younger Adults ◽  
Cortical Areas ◽  
Age Related ◽  
The Social ◽  
Over Time

Trust is a key component of social interaction. Older adults, however, often exhibit excessive trust relative to younger adults. One explanation is that older adults may learn to trust differently than younger adults. Here, we examine how younger (N=33) and older adults (N=30) learn to trust over time. Participants completed a classic iterative trust game with three partners. Younger and older adults shared similar amounts but differed in how they shared money. Compared to younger adults, older adults invested more with untrustworthy partners and less with trustworthy partners. As a group, older adults displayed less learning than younger adults. However, computational modeling shows that this is because older adults are more likely to forget what they have learned over time. Model-based fMRI analyses revealed several age-related differences in neural processing. Younger adults showed prediction error signals in social processing areas while older adults showed over-recruitment of several cortical areas. Collectively, these findings suggest that older adults attend to and learn from social cues differently from younger adults.

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