The evidence presented in this study suggests that the Corin C-Fit uncemented total hip arthroplasty has one of the highest mid- and long-term failure rates for both femoral and acetabular components in the literature. We believe this implant should not be used and patients who have had this form of total hip arthroplasty should be kept under regular review.
diman (dimensional analysis) is a Clojure based scientific software package with the ability to: create dimensional formulas, create dimensional equations, check dimensional homogeneity (consistency), and derive dimensionless products.diman provides functions for each step of the analytic process for checking dimensional homogeneity or deriving dimensionless products; the repetitive operations (computational) are hidden. Users can write compound functions that perform a desired process. Thus, not only is the computational labor saved, but also introspection of the analysis is possible; the analyst is able to go through the steps of dimensional analysis.
How can one design an adaptive pulsed neural network that is based on psycho-phenomenological foundations? In other words, how can one migrate the adaptive capability of a psychologically modeled neural network to a pulsed network? Neural networks that model psychological phenomena are at a larger scale than physiological models. There is a common presumption that pulse-coded neural network analogs to non-pulsing networks can be obtained by a simple mapping and scaling process of some sort. But the actual in vivo environment of pulse-coded neural network systems produces a much more diverse set of firing patterns. Thus, functional mapping from traditional neural network systems to pulse-coded neural network systems is much more challenging than has been presumed. This paper demonstrates that the employment of model reference adaptation as a method for applying scientific reduction is a powerful design tool for the development of a function-oriented adaptive pulse-coded neural network. The performance surface is empirically obtained by comparing the performance of the pulsed network to the non-pulsing network. Based on this surface, the adaptive algorithm is a combination of gain scheduling and steepest-descent method. Therefore, the adaptive property of the pulse-coded neural network is built upon a psycho-physiological foundation.
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