Investigative trends in understanding penalty-kick performance in association football: An ecological dynamics perspective

There have been different approaches to studying penalty-kick performance in association football. In this paper, the authors synthesize key findings within an ecological dynamics theoretical framework. According to this theoretical perspective, information is the cornerstone for understanding the dynamics of action regulation in penalty-kick performance. Research suggests that investigators need to identify the information sources that are most relevant to penalty-kick performance. An important task is to understand how constraints can channel (i.e. change, emphasize or mask) information sources used to regulate upcoming actions and how the influence of these constraints is expressed in players' behavioural dynamics. Due to the broad range of constraints influencing penalty-kick performance, it is recommended that future research adopts an interdisciplinary focus on performance assessment to overcome the current lack of representativeness in penalty-kick experimental designs. Such an approach would serve to capture the information-based control of action of both players as components of this dyadic system in competitive sport.

A high performance liquid chromatography and electrospray ionization mass spectrometry method for the analysis of the natural medicine, Forsythia suspensa

Samples of Forsythia suspensa from raw (Laoqiao) and ripe (Qingqiao) fruit were analyzed with the use of HPLC-DAD and the EIS-MS techniques. Seventeen peaks were detected, and of these, twelve were identified. Most were related to the glucopyranoside molecular fragment. Samples collected from three geographical areas (Shanxi, Henan and Shandong Provinces), were discriminated with the use of hierarchical clustering analysis (HCA), discriminant analysis (DA), and principal component analysis (PCA) models, but only PCA was able to provide further information about the relationships between objects and loadings; eight peaks were related to the provinces of sample origin. The supervised classification models-K-nearest neighbor (KNN), least squares support vector machines (LS-SVM), and counter propagation artificial neural network (CP-ANN) methods, indicated successful classification but KNN produced 100% classification rate. Thus, the fruit were discriminated on the basis of their places of origin.

Methodology to predict the safety performance of rural multilane highways [Final Report for NCHRP Project 17-29]

The objective of this research is to develop a methodology that predicts the safety performance of various elements considered in the planning, design, and operation of nonlimited- access rural multilane highways.