A Neuro-Muscular Elasto-Dynamic Model of the Human Arm Part 2:Musculotendon Dynamics and Related Stress Effects

In this paper we develop an elasto-dynamic model of the human arm that includes effects of neuro-muscular control upon elastic deformation in the limb.The elasto-dynamic model of the arm is based on hybrid parameter multiple body system variational projection principles presented in the companion paper.Though the technique is suitable for detailed bone and joint modeling,we present simulations for simplified geometry of the bones,discretized as Rayleigh beams with elongation,while allowing for large deflections.Motion of the upper extremity is simulated by incorporating muscle forces derived from a Hill-type model of musculotendon dynamics.The effects of muscle force are modeled in two ways.In one approach,an effective joint torque is calculated by multiplying the muscle force by a joint moment ann.A second approach models the muscle as acting along a straight line between the origin and insertion sites of the tendon.Simple arm motion is simulated by utilizing neural feedback and feedforward control.Simulations illustrate the combined effects of neural control strategies, models of muscle force inclusion,and elastic assumptions on joint trajectories and stress and strain development in the bone and tendon.

A polynomial hybrid reflection model and measurement of its parameters based on images of sample

Reflectance model is a basic concept in computer vision. Some existing models combining the classical diffuse reflectance model and those for surfaces containing specular components can approximately describe real reflectance. But the ratio of diffuse and specular reflection decided manually has no clear meaning. We propose a new polynomial hybrid reflectance model. The reflectance map equation with a known shape （for example cylinder） as a sample is used to estimate parameters of the proposed reflectance model by least square regression algorithm. Then the reflectance parameters for surfaces of the same class of materials can be determined. Experiments are performed for a metal surface. The synthesis images produced by the proposed method and existing ones are compared with the real acquired image, and the results show that the proposed reflectance model is suitable for describing real reflectance.

A Neuro-Muscular Elasto-Dynamic Model of the Human Arm Part 1:Model Development

In this paper we develop an elasto-dynamic model of the human arm for use in neuro-muscular control and dynamic interaction studies.The motivation for this work is to present a case for developing and using non-quasistatic models of human musculo-skeletal biomechanics.The model is based on hybrid parameter multiple body system(HPMBS)variational projection principles.In this paper,we present an overview of the HPMBS variational principle applied to the full elasto-dynamic model of the arm.The generality of the model allows one to incorporate muscle effects as either loads transmitted through the tendon at points of origin and insertion or as an effective torque at a joint.Though the technique is suitable for detailed bone and joint modeling,we present in this initial effort only simple geometry with the bones discretized as Rayleigh beams with elongation, while allowing for large deflections.Simulations demonstrate the viability of the mcthod for use in the companion paper and in future studies.

Real-Time Automatic Scaling Method of Oblique Ionogram Parameters Based on Morphological Operator and Inversion Technique

Automatic scaling ionogram can get the parameters of ionogram which are vital to ionosphere detecting. In this paper, a new method is proposed to scale F2 layer trace automatically from oblique ionogram based on morphological operator and inversion technique. This method is verified through the comparison of actual detecting data with statistical analysis. The results show that the proposed automatic scaling method has high acceptable rate and is suitable for scaling oblique ionogram with different high angle wave states. It is fast and precise to fit O-mode echoes in F2 layer without the influence from F1 layer. This method could be applied in real-time ionospheric oblique sounding research with high reliability and versatility.

Advancing from unimechanism polymerization to multimechanism polymerization: binary polymerization

Polymerizations with multiple mechanisms performed simultaneously are promising but very challenging. As the key limitation,the complicated mutual influence between different mechanisms can be hardly defined and measured. Herein we establish a universal framework for the assessment of mutual influence between different mechanisms using binary polymerization for demonstration. The kinetics and thermodynamics of polymerization with two mechanisms are compared with the corresponding homopolymerization and the difference is expressed by a hybrid function. The hybrid function is composed of a hybrid parameter that describes the extent of mutual influence and a function that describes necessary conditions for mutual influence to occur. The extent of mutual influence can be calculated using kinetic and thermodynamic data without details of reaction mechanisms, for the first time providing a straightforward method to assess the mutual influence between different polymerization mechanisms.We envision that the method has potential in more complex systems with multiple mechanisms/monomers with mutual influence.