The History of the Mexican Contract Labor Program, 1942-1966

This thesis examines the history of the Mexican contract labor program from the World War II program in 1942 to the post-bracero era in 1964-66

Late Pleistocene human genome suggests a local origin for the first farmers of central Anatolia

Anatolia was home to some of the earliest farming communities. It has been long debated whether a migration of farming groups introduced agriculture to central Anatolia. Here, we report the first genome-wide data from a 15,000-year-old Anatolian hunter-gatherer and from seven Anatolian and Levantine early farmers. We find high genetic continuity (~80–90%) between the hunter-gatherers and early farmers of Anatolia and detect two distinct incoming ancestries: an early Iranian/Caucasus related one and a later one linked to the ancient Levant. Finally, we observe a genetic link between southern Europe and the Near East predating 15,000 years ago. Our results suggest a limited role of human migration in the emergence of agriculture in central Anatolia

PREDICTING 3D GROUND REACTION FORCE FROM 2D VIDEO VIA NEURAL NETWORKS IN SIDESTEPPING TASKS

Sports science practitioners often measure ground reaction forces (GRFs) to assess performance, rehabilitation and injury risk. However, recording of GRFs during dynamic tasks has historically been limited to lab settings. This work aims to use neural networks (NN) to predict three-dimensional (3D) GRF via pose estimation keypoints as inputs, determined from 2D video data. Two different NN were trained on a dataset containing 1474 samples from 14 participants and their prediction accuracy compared with ground truth force data. Results for both NN showed correlation coefficients ranging from 0.936 to 0.954 and normalised root mean square errors from 11.05% to 13.11% for anterior-posterior and vertical GRFs, with poorer results found in the medio-lateral direction. This study demonstrates the feasibility and utility of predicting GRFs from 2D video footage

NO DATASET TOO SMALL! ANIMATING 3D MOTION DATA TO ENLARGE 2D VIDEO DATABASES

This study outlines a technique to leverage the wide availability of high resolution three-dimensional (3D) motion capture data for the purpose of synthesising two-dimensional (2D) video camera views, thereby increasing the availability of 2D video image databases for training machine learning models requiring large datasets. We register 3D marker trajectories to generic 3D body-shapes (hulls) and use a 2D pose estimation algorithm to predict joint centre and anatomical landmark keypoints in the synthesised 2D video views – a novel approach that addresses the limited data available in elite sport settings. We use 3D long jump data as an exemplar use case and investigate the influence of; 1) varying anthropometrics, and 2) the 2D camera view, on keypoint estimation accuracy. The results indicated that 2D keypoint determination accuracy is affected by body-shape. Frontal plane camera views result in lower accuracy than sagittal plane camera views

A randomised controlled trial of the clinical effectiveness and cost-effectiveness of different knee prostheses : the Knee Arthroplasty Trial (KAT)

Peer reviewedPublisher PD