PubMed HealthSearch

PubMed · 8146754

[Cushioning versus stability].

Abstract

Cushioning and stability are still key words for functionally constructed sport shoes. The goal of this investigation is to present and discuss the possibilities and limits of these shoe properties. Here, stability is not regarded as rigidity (like in a ski boot), but as a "dynamic stability" in the sense of functionality which supports the foot under load in such a manner that no unphysiological movements are provoked. Cushioning (in physics terminology: "damping") is defined to reduce and eliminate (kinetic) energy. When considering the impact peak in running, this peak can be reduced by using hard shoe soles with large heel flares. However, by doing that, large levers are introduced which produce an increased distance to decelerate the touchdown. This is basically the opposite of dynamic stability. Current shoe sole materials (homogeneous/isotropic) improve the "cushioning" but enhance the instability. New ways of shoe construction using more sophisticated anisotropic materials may lead out of this dichotomy.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

E Stüssi, A Stacoff, E Lucchinetti. 1993. [Cushioning versus stability].. https://doi.org/10.1055/s-2007-993501

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Generating correlated data for omics simulation.

Simulation of realistic omics data is a key input for benchmarking studies that help users obtain optimal computational pipelines. Omics data involves large numbers of measured features on each sample and these measures are generally correlated with each other. However, simulation too often ignores these correlations, perhaps due to computational and statistical hurdles of doing so. To alleviate this, we describe three approaches for generating omics-scale data with correlated measures which mimic real datasets. These approaches are all based on a Gaussian copula approach with a covariance matrix that decomposes into a diagonal part and a low-rank part. This decomposition allows for extremely efficient simulation, overcoming a hurdle for adoption of past methods. We use these approaches to demonstrate the importance of including correlation in two benchmarking applications. First, we show that variance of results from the popular DESeq2 method increases when dependence is included. Second, we demonstrate that CYCLOPS, a method for inferring circadian time of collection from transcriptomics, improves in performance when given gene-gene dependencies in some circumstances. We provide an R package, dependentsimr, that has efficient implementations of these methods and can generate dependent data with arbitrary marginal distributions, including discrete (binary, ordered categorical, Poisson, negative binomial), continuous (normal), or with an empirical distribution.

Computer Simulation

Addressing current challenges in cancer immunotherapy with mathematical and computational modelling.

The goal of cancer immunotherapy is to boost a patient's immune response to a tumour. Yet, the design of an effective immunotherapy is complicated by various factors, including a potentially immunosuppressive tumour microenvironment, immune-modulating effects of conventional treatments and therapy-related toxicities. These complexities can be incorporated into mathematical and computational models of cancer immunotherapy that can then be used to aid in rational therapy design. In this review, we survey modelling approaches under the umbrella of the major challenges facing immunotherapy development, which encompass tumour classification, optimal treatment scheduling and combination therapy design. Although overlapping, each challenge has presented unique opportunities for modellers to make contributions using analytical and numerical analysis of model outcomes, as well as optimization algorithms. We discuss several examples of models that have grown in complexity as more biological information has become available, showcasing how model development is a dynamic process interlinked with the rapid advances in tumour-immune biology. We conclude the review with recommendations for modellers both with respect to methodology and biological direction that might help keep modellers at the forefront of cancer immunotherapy development.

Computer Simulation

Review of ionic models of vagal-cardiac pacemaker control.

Mathematical models of ion currents in pacemaker cells of the heart and their associated modulation by vagal stimulation have provided numerous insights into the ionic mechanisms underlying parasympathetic control of heart rate. In this article, ionic models described in the literature are reviewed and compared, with a view to examining their effectiveness in reproducing known chronotropic responses to vagal stimulation.

Computer Simulation