Designing a Web-Based Knowledge Repository in A Virtual Team and Exploring Its Usefulness

By using a computer network, geographically distributed people with common goals can communicate and collaborate their work efforts across time and space barriers. These groups has been called virtual teams (Geber, 1995). The virtual teams are used to support various kinds of collaborative efforts ranging from routine, mundane works to complex, creative works (Geber, 1995; Snizek, 1995). Because the virtual teams can bring together the right mix of people who have the appropriate set of knowledge, skills, information, and authority to solve difficult problems quickly and easily, they are receiving considerable attention from knowledge workers (Boldyreff et al., 1996; McGuire, 1996). These knowledge workers are characterized as highly qualified individuals who need to make decisions under non- routine, unstructured, and uncertain environments (Knight et al., 1993). As the numerous benefits and advantages of the virtual teams in increasing effectiveness and efficiency of knowledge workers becomes widely recognized, organizations face a new challenge in coping with their new organizational structure (Davidow & Malone, 1993). The challenge is to turn the scattered, diverse knowledge of their knowledge workers who are working in a virtual team into a well-structured knowledge repository (Spek & Spijkervet, 1996; Wiig, 1993)

Growth-profile configuration for specific deformations of tubular organs: A study of growth-induced thinning and dilation of the human cervix

Growth is a significant factor that results in deformations of tubular organs, and particular deformations associated with growth enable tubular organs to perform certain physiological functions. Configuring growth profiles that achieve particular deformation patterns is critical for analyzing potential pathological conditions and for developing corresponding clinical treatments for tubular organ dysfunctions. However, deformation-targeted growth is rarely studied. In this article, the human cervix during pregnancy is studied as an example to show how cervical thinning and dilation are generated by growth. An advanced hyperelasticity theory called morphoelasticity is employed to model the deformations, and a growth tensor is used to represent growth in three principle directions. The computational results demonstrate that both negative radial growth and positive circumferential growth facilitate thinning and dilation. Modeling such mixed growth represents an advancement beyond commonly used uniform growth inside tissues to study tubular deformations. The results reveal that complex growth may occur inside tissues to achieve certain tubular deformations. Integration of further biochemical and cellular activities that initiate and mediate such complex growth remains to be explored

Rapid Estimation of Left Ventricular Contractility with a Physics-Informed Neural Network Inverse Modeling Approach

Physics-based computer models based on numerical solution of the governing equations generally cannot make rapid predictions, which in turn, limits their applications in the clinic. To address this issue, we developed a physics-informed neural network (PINN) model that encodes the physics of a closed-loop blood circulation system embedding a left ventricle (LV). The PINN model is trained to satisfy a system of ordinary differential equations (ODEs) associated with a lumped parameter description of the circulatory system. The model predictions have a maximum error of less than 5% when compared to those obtained by solving the ODEs numerically. An inverse modeling approach using the PINN model is also developed to rapidly estimate model parameters (in $\sim$ 3 mins) from single-beat LV pressure and volume waveforms. Using synthetic LV pressure and volume waveforms generated by the PINN model with different model parameter values, we show that the inverse modeling approach can recover the corresponding ground truth values, which suggests that the model parameters are unique. The PINN inverse modeling approach is then applied to estimate LV contractility indexed by the end-systolic elastance $E_{es}$ using waveforms acquired from 11 swine models, including waveforms acquired before and after administration of dobutamine (an inotropic agent) in 3 animals. The estimated $E_{es}$ is about 58% to 284% higher for the data associated with dobutamine compared to those without, which implies that this approach can be used to estimate LV contractility using single-beat measurements. The PINN inverse modeling can potentially be used in the clinic to simultaneously estimate LV contractility and other physiological parameters from single-beat measurements

The treatment of pathologies, biotransport, and fluid–structure interaction problems in biomechanics

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