Automated Detection of Lunar Rockfalls Using a Convolutional Neural Network

This paper implements a novel approach to automatically detect and classify rockfalls in Lunar Reconnaissance Orbiter narrow angle camera (NAC) images using a single-stage dense object detector (RetinaNet). The convolutional neural network has been trained with a data set of 2932 original rockfall images. In order to avoid overfitting, the initial training data set has been augmented during training using random image rotation, scaling, and flipping. Testing images have been labelled by human operators and have been used for RetinaNet performance evaluation. Testing shows that RetinaNet is capable to reach recall values between 0.98 and 0.39, precision values between 1 and 0.25, and average precisions ranging from 0.89 to 0.69, depending on the used confidence threshold and intersection-over-union values. Mean processing time of a single NAC image in RetinaNet is around 10 s using a GeForce GTX 1080 Ti and GeForce Titan Xp, which is in orders of magnitudes faster than a human operator. The processing speed allows to efficiently exploit the currently available NAC data stack with more than 1 million images in a reasonable timeframe. The combination of speed and detection performance can be used to produce lunar rockfall distribution maps on large spatial scales for utilization by the scientific and engineering community

New incretin combination treatments under investigation in obesity and metabolism: A systematic review

The worldwide upward trend in obesity in adults and the increased incidence of overweight children suggests that the future risk of obesity-related illnesses will be increased. The existing anti-obesity drugs act either in the central nervous system (CNS) or in the peripheral tissues, controlling the appetite and metabolism. However, weight regain is a common homeostatic response; current anti-obesity medications show limited effectiveness in achieving long-term weight loss maintenance; in addition to being linked to various side effects. Combined anti-obesity medications (per os or injectable) target more than one of the molecular pathways involved in weight regulation, as well as structures in the CNS. In this systematic review, we conducted a search of PubMed and The ClinicalTrials.gov up to February 2021. We summarized the Food and Drug Administration (FDA)-approved medications, and we focused on the combined pharmacological treatments, related to the incretin hormones, currently in a clinical trial phase. We also assessed the mechanism of action and therapeutic utility of these novel hybrid peptides and potential interactions with other regulatory hormones that may have beneficial effects on obesity. As we improve our understanding of the pathophysiology of obesity, we hope to identify more novel treatment strategies. © 2021 by the authors. Licensee MDPI, Basel, Switzerland