Resistance training effects on healthy postmenopausal women: a systematic review with meta-analysis.

The aim of this systematic review with meta-analysis was to evaluate the effects of resistance training on physical fitness, physiological variables and body composition of postmenopausal women. The present systematic review was performed in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement and was registered in PROSPERO. A total of 12 studies were included.

A Deep Neural Network Based Model for a Kind of Magnetorheological Dampers.

In this paper, a deep neural network based model for a set of small-scale magnetorheological dampers (MRD) is developed where relevant parameters that have a physical meaning are inputs to the model. An experimental platform and a 3D-printing rapid prototyping facility provided a set of different conditions including MRD filled with two different MR fluids, which were used to train a Deep Neural Network (DNN), which is the core of the proposed model. Testing results indicate the model could forecast the hysteretic response of magnetorheological dampers for different load conditions and various physical configurations.

Study on the impact of partition-induced dataset shift on k-fold cross-validation.

Cross-validation is a very commonly employed technique used to evaluate classifier performance. However, it can potentially introduce dataset shift, a harmful factor that is often not taken into account and can result in inaccurate performance estimation. This paper analyzes the prevalence and impact of partition-induced covariate shift on different k-fold cross-validation schemes.