Matching Items (407)

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Effects of Aerobic Fitness on Aging-Related Changes of Interhemispheric Inhibition and Motor Performance

Description

Physical fitness has been long associated with maintenance and improvement of motor performance as we age. In particular, measures of psychomotor speed and motor dexterity tend to be higher in

Physical fitness has been long associated with maintenance and improvement of motor performance as we age. In particular, measures of psychomotor speed and motor dexterity tend to be higher in physically fit aging adults as compared to their sedentary counterparts. Using functional magnetic resonance imaging (fMRI) and transcranial magnetic stimulation (TMS), we explored the patterns of neural activity that may, in part, account for differences between individuals of varying physical fitness levels. In this study, we enrolled both sedentary and physically fit middle age (40–60) and younger (18–30) adults and measured upper extremity motor performance during behavioral testing. In a follow-up session, we employed TMS and fMRI to assess levels of interhemispheric communication during unimanual tasks. Results show that increased physical fitness is associated with better upper extremity motor performance on distal dexterity assessments and increased levels of interhemispheric inhibition in middle age adults. Further, the functional correlates of changes of ipsilateral activity appears to be restricted to the aging process as younger adults of varying fitness levels do not differ in hemispheric patterns of activity or motor performance. We conclude that sedentary aging confers a loss of interhemispheric inhibition that is deleterious to some aspects of motor function, as early as midlife, but these changes can be mediated by chronic engagement in aerobic exercise.

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Created

Date Created
  • 2013-10-30

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The Effect of Applying 2D Enhancement Algorithms on 3D Video Content

Description

Enhancement algorithms are typically applied to video content to increase their appeal to viewers. Such algorithms are readily available in the literature and are already widely applied in, for example,

Enhancement algorithms are typically applied to video content to increase their appeal to viewers. Such algorithms are readily available in the literature and are already widely applied in, for example, commercially available TVs. On the contrary, not much research has been done on enhancing stereoscopic 3D video content. In this paper, we present research focused on the effect of applying enhancement algorithms used for 2D content on 3D side-by-side content. We evaluate both offline enhancement of video content based on proprietary enhancement algorithms and real-time enhancement in the TVs. This is done using stereoscopic TVs with active shutter glasses, viewed both in their 2D and 3D viewing mode. The results of this research show that 2D enhancement algorithms are a viable first approach to enhance 3D content. In addition to video quality degradation due to the loss of spatial resolution as a consequence of the 3D video format, brightness reduction inherent to polarized or shutter glasses similarly degrades video quality. We illustrate the benefit of providing brightness enhancement for stereoscopic displays.

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Created

Date Created
  • 2014-06-19

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DTALite: A Queue-Based Mesoscopic Traffic Simulator for Fast Model Evaluation and Calibration

Description

A number of emerging dynamic traffic analysis applications, such as regional or statewide traffic assignment, require a theoretically rigorous and computationally efficient model to describe the propagation and dissipation of

A number of emerging dynamic traffic analysis applications, such as regional or statewide traffic assignment, require a theoretically rigorous and computationally efficient model to describe the propagation and dissipation of system congestion with bottleneck capacity constraints. An open-source light-weight dynamic traffic assignment (DTA) package, namely DTALite, has been developed to allow a rapid utilization of advanced dynamic traffic analysis capabilities. This paper describes its three major modeling components: (1) a light-weight dynamic network loading simulator that embeds Newell’s simplified kinematic wave model; (2) a mesoscopic agent-based DTA procedure to incorporate driver’s heterogeneity; and (3) an integrated traffic assignment and origin–destination demand calibration system that can iteratively adjust path flow volume and distribution to match the observed traffic counts. A number of real-world test cases are described to demonstrate the effectiveness and performance of the proposed models under different network and data availability conditions.

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Created

Date Created
  • 2014-10-01

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Digit Position and Forces Covary During Anticipatory Control of Whole-Hand Manipulation

Description

Theoretical perspectives on anticipatory planning of object manipulation have traditionally been informed by studies that have investigated kinematics (hand shaping and digit position) and kinetics (forces) in isolation. This poses

Theoretical perspectives on anticipatory planning of object manipulation have traditionally been informed by studies that have investigated kinematics (hand shaping and digit position) and kinetics (forces) in isolation. This poses limitations on our understanding of the integration of such domains, which have recently been shown to be strongly interdependent. Specifically, recent studies revealed strong covariation of digit position and load force during the loading phase of two-digit grasping. Here, we determined whether such digit force-position covariation is a general feature of grasping. We investigated the coordination of digit position and forces during five-digit whole-hand manipulation of an object with a variable mass distribution. Subjects were instructed to prevent object roll during the lift. As found in precision grasping, there was strong trial-to-trial covariation of digit position and force. This suggests that the natural variation of digit position that is compensated for by trial-to-trial variation in digit forces is a fundamental feature of grasp control, and not only specific to precision grasp. However, a main difference with precision grasping was that modulation of digit position to the object’s mass distribution was driven predominantly by the thumb, with little to no modulation of finger position. Modulation of thumb position rather than fingers is likely due to its greater range of motion and therefore adaptability to object properties. Our results underscore the flexibility of the central nervous system in implementing a range of solutions along the digit force-to-position continuum for dexterous manipulation.

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Created

Date Created
  • 2016-09-15

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Design, Construction, and Modeling of a 252Cf Neutron Irradiator

Description

Neutron production methods are an integral part of research and analysis for an array of applications. This paper examines methods of neutron production, and the advantages of constructing a radioisotopic

Neutron production methods are an integral part of research and analysis for an array of applications. This paper examines methods of neutron production, and the advantages of constructing a radioisotopic neutron irradiator assembly using 252Cf. Characteristic neutron behavior and cost-benefit comparative analysis between alternative modes of neutron production are also examined. The irradiator is described from initial conception to the finished design. MCNP modeling shows a total neutron flux of 3 × 105 n/(cm2·s) in the irradiation chamber for a 25 μg source. Measurements of the gamma-ray and neutron dose rates near the external surface of the irradiator assembly are 120 μGy/h and 30 μSv/h, respectively, during irradiation. At completion of the project, total material, and labor costs remained below $50,000.

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Created

Date Created
  • 2016-07-31

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Design of Miniaturized Multiband Filters Using Zero Order Resonators for WLAN Applications

Description

The objective of this paper is to design miniaturized narrow- and dual-band filters for WLAN application using zero order resonators by the method of least squares. The miniaturization of the

The objective of this paper is to design miniaturized narrow- and dual-band filters for WLAN application using zero order resonators by the method of least squares. The miniaturization of the narrow-band filter is up to 70% and that of the dual-band filter is up to 64% compared to the available models in the literature. Two prototype models of the narrow-band and dual-band filters are fabricated and measured, which verify the proposed structure for the filter and its design by the presented method, using an equivalent circuit model.

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Created

Date Created
  • 2015-02-18

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Comparative Study on Theoretical and Machine Learning Methods for Acquiring Compressed Liquid Densities of 1,1,1,2,3,3,3-Heptafluoropropane (R227ea) Via Song and Mason Equation, Support Vector Machine, and Artificial Neural Networks

Description

1,1,1,2,3,3,3-Heptafluoropropane (R227ea) is a good refrigerant that reduces greenhouse effects and ozone depletion. In practical applications, we usually have to know the compressed liquid densities at different temperatures and pressures.

1,1,1,2,3,3,3-Heptafluoropropane (R227ea) is a good refrigerant that reduces greenhouse effects and ozone depletion. In practical applications, we usually have to know the compressed liquid densities at different temperatures and pressures. However, the measurement requires a series of complex apparatus and operations, wasting too much manpower and resources. To solve these problems, here, Song and Mason equation, support vector machine (SVM), and artificial neural networks (ANNs) were used to develop theoretical and machine learning models, respectively, in order to predict the compressed liquid densities of R227ea with only the inputs of temperatures and pressures. Results show that compared with the Song and Mason equation, appropriate machine learning models trained with precise experimental samples have better predicted results, with lower root mean square errors (RMSEs) (e.g., the RMSE of the SVM trained with data provided by Fedele et al. [1] is 0.11, while the RMSE of the Song and Mason equation is 196.26). Compared to advanced conventional measurements, knowledge-based machine learning models are proved to be more time-saving and user-friendly.

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Created

Date Created
  • 2016-01-19

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Compaction of Granular HMX: P-α Porosity Model in CTH Hydrocode

Description

Compaction waves traveling through porous cyclotetramethylene-tetranitramine (HMX) are computationally modeled using the Eulerian hydrocode CTH and validated with gas gun experimental data. The method employed use of a newly generated

Compaction waves traveling through porous cyclotetramethylene-tetranitramine (HMX) are computationally modeled using the Eulerian hydrocode CTH and validated with gas gun experimental data. The method employed use of a newly generated set of P-α parameters for granular HMX in a Mie-Gruneisen equation of state. The P-α model adds a separate parameter to differentiate between the volume changes of a solid material due to compression from the volume change due to compaction, void collapse in a granular material. Computational results are compared via five validation schema for two different initial-porosity experiments. These schema include stress measurements, velocity rise times and arrival times, elastic sound speeds though the material and final compaction densities for a series of two different percent Theoretical Maximum Density (TMD) HMX sets of experimental data. There is a good agreement between the simulations and the experimental gas gun data with the largest source of error being an 11% overestimate of the peak stress which may be due to impedance mismatch on the experimental gauge interface. Determination of these P-α parameters are important as they enable modeling of porosity and are a vital first step in modeling of precursory hotspots, caused by hydrodynamic collapse of void regions or grain interactions, prior to deflagration to detonation transition of granular explosives.

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Created

Date Created
  • 2015-12-17

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Climate Modeling for Renewable Energy Applications

Description

The exploration of environmentally friendly energy resources is one of the major challenges facing society today. The last decade has witnessed rapid developments in renewable energy engineering. Wind and solar

The exploration of environmentally friendly energy resources is one of the major challenges facing society today. The last decade has witnessed rapid developments in renewable energy engineering. Wind and solar power plants with increasing sizes and technological sophistication have been built. Amid this development, meteorological modeling plays an increasingly important role, not only in selecting the sites of wind and solar power plants but also in assessing the environmental impacts of those plants. The permanent land-use changes as a result of the construction of wind farms can potentially alter local climate (Keith et al. [1], Roy and Traiteur [2]). The reduction of wind speed by the presence of wind turbines could affect the preconstruction estimate of wind power potential (e.g., Adams and Keith [3]). Future anthropogenic greenhouse gas emissions are expected to induce changes in the surface wind and cloudiness, which would affect the power production of wind and solar power plants. To quantify these two-way relations between renewable energy production and regional climate change, mesoscale meteorological modeling remains one of the most efficient approaches for research and applications.

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Created

Date Created
  • 2014-12-22

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Characterizing Corridor-Level Travel Time Distributions Based on Stochastic Flows and Segment Capacities

Description

Trip travel time reliability is an important measure of transportation system performance and a key factor affecting travelers’ choices. This paper explores a method for estimating travel time distributions for

Trip travel time reliability is an important measure of transportation system performance and a key factor affecting travelers’ choices. This paper explores a method for estimating travel time distributions for corridors that contain multiple bottlenecks. A set of analytical equations are used to calculate the number of queued vehicles ahead of a probe vehicle and further capture many important factors affecting travel times: the prevailing congestion level, queue discharge rates at the bottlenecks, and flow rates associated with merges and diverges. Based on multiple random scenarios and a vector of arrival times, the lane-by-lane delay at each bottleneck along the corridor is recursively estimated to produce a route-level travel time distribution. The model incorporates stochastic variations of bottleneck capacity and demand and explains the travel time correlations between sequential links. Its data needs are the entering and exiting flow rates and a sense of the lane-by-lane distribution of traffic at each bottleneck. A detailed vehicle trajectory data-set from the Next Generation SIMulation (NGSIM) project has been used to verify that the estimated distributions are valid, and the sources of estimation error are examined.

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Created

Date Created
  • 2015-01-09