A fast-modeling framework for personalized human body models based on a single image.

Finite element human body models (HBMs) are the primary method for predicting human biological responses in vehicle collisions, especially personalized HBMs that allow accounting for diverse populations. Yet, creating personalized HBMs from a single image is a challenging task. This study addresses this challenge by providing a framework for HBM personalization, starting from a single image used to estimate the subject's skin point cloud, the skeletal point cloud, and the relative positions of the skeletons.

A data-mining study on the prediction of head injury in traffic accidents among vulnerable road users with varying body sizes and head anatomical characteristics.

Body sizes and head anatomical characteristics play the major role in the head injuries sustained by vulnerable road users (VRU) in traffic accidents. In this study, in order to study the influence mechanism of body sizes and head anatomical characteristics on head injury, we used age, gender, height, and Body Mass Index (BMI) as characteristic parameters to develop the personalized human body multi-rigid body (MB) models and head finite element (FE) models. Next, using simulation calculations, we developed the VRU head injury dataset based on the personalized models.

A fast methodology for generating skeletal FEM with detailed human geometric features based on CPD and RBF algorithms.

Due to the significant effects of the human anatomical characteristics on the injury mechanism of passenger in traffic accidents, it is necessary to develop human body FEM (Finite Element Model) with detailed anatomical characteristics. However, traditional development of a human body FEM is an extremely complicated process. In particular, the meshing of human body is a huge and time-consuming project.

Combinatorial Antitumor Effect of Rapamycin and β-Elemene in Follicular Thyroid Cancer Cells.

Background. mTOR signaling would be a promising target for thyroid cancer therapy. However, in clinical trials, objective response rate with mTOR inhibitor monotherapy in most cancer types was modest.