Financial incentives for COVID-19 vaccines in a rural low-resource setting: a cluster-randomized trial.

We implemented a clustered randomized controlled trial with 6,963 residents in six rural Ghana districts to estimate the causal impact of financial incentives on coronavirus disease 2019 (COVID-19) vaccination uptake. Villages randomly received one of four video treatment arms: a placebo, a standard health message, a high cash incentive (60 Ghana cedis) and a low cash incentive (20 Ghana cedis). For the first co-primary outcome-COVID-19 vaccination intentions-non-vaccinated participants assigned to the cash incentive treatments had an average rate of 81% (1,733 of 2,168) compared to 71% (1,895 of 2,669) for those in the placebo treatment arm.

Traditional Artificial Neural Networks Versus Deep Learning in Optimization of Material Aspects of 3D Printing.

3D printing of assistive devices requires optimization of material selection, raw materials formulas, and complex printing processes that have to balance a high number of variable but highly correlated variables. The performance of patient-specific 3D printed solutions is still limited by both the increasing number of available materials with different properties (including multi-material printing) and the large number of process features that need to be optimized. The main purpose of this study is to compare the optimization of 3D printing properties toward the maximum tensile force of an exoskeleton sample based on two different approaches: traditional artificial neural networks (ANNs) and a deep learning (DL) approach based on convolutional neural networks (CNNs).

Reducing Waste in 3D Printing Using a Neural Network Based on an Own Elbow Exoskeleton.

Traditional rehabilitation systems are evolving into advanced systems that enhance and improve rehabilitation techniques and physical exercise. The reliable assessment and robotic support of the upper limb joints provided by the presented elbow exoskeleton are important clinical goals in early rehabilitation after stroke and other neurological disorders. This allows for not only the support of activities of daily living, but also prevention of the progression neuromuscular pathology through proactive physiotherapy toward functional recovery.

The Applicability of Self-Play Algorithms to Trading and Forecasting Financial Markets.

The central research question to answer in this study is whether the AI methodology of Self-Play can be applied to financial markets. In typical use-cases of Self-Play, two AI agents play against each other in a particular game, e.g.