The application of machine learning techniques has facilitated the automatic annotation of behavior in video sequences, offering a promising approach for ethological studies by reducing the manual effort required for annotating each video frame. Nevertheless, before solely relying on machine-generated annotations, it is essential to evaluate the accuracy of these annotations to ensure their reliability and applicability. While it is conventionally accepted that there cannot be a perfect annotation, the degree of error associated with machine-generated annotations should be commensurate with the error between different human annotators. We hypothesized that machine learning supervised with adequate human annotations would be able to accurately predict body parts from video sequences. Here, we conducted a comparative analysis of the quality of annotations generated by humans and machines for the body parts of sheep during treadmill walking. For human annotation, two annotators manually labeled six body parts of sheep in 300 frames. To generate machine annotations, we employed the state-of-the-art pose-estimating library, DeepLabCut, which was trained using the frames annotated by human annotators. As expected, the human annotations demonstrated high consistency between annotators. Notably, the machine learning algorithm also generated accurate predictions, with errors comparable to those between humans. We also observed that abnormal annotations with a high error could be revised by introducing Kalman Filtering, which interpolates the trajectory of body parts over the time series, enhancing robustness. Our results suggest that conventional transfer learning methods can generate behavior annotations as accurate as those made by humans, presenting great potential for further research.

This article investigates differences in gene expression in the brains of patients with and without Parkinson's disease. The authors identify a crucial transcriptional regulator may be a relevant target for future therapeutic treatment for Parkinson's disease.

This study compares the voltage output of two potential alternative energy sources: water drops hitting a piezoelectric surface and water flowing through a hydroelectric turbine. The findings of this study suggest that harnessing kinetic energy from falling raindrops may be a viable alternative energy source.

Vibrio fischeri is an amazing species of bacteria that lives symbiotically in the light organ of luminescent bobtail squid. In this study, authors study the strength and optimal conditions for V. fischeri light production, and assess whether this luminescence could be a natural light source comparable to manmade lighting.

Here, the authors investigated the most efficient way to position magnets to hold the most pieces of paper on the surface of a refrigerator. They used a regression model along with an artificial neural network to identify the most efficient positions of four magnets to be at the vertices of a rectangle.

Here the authors investigated the role of agricultural fertilizers as potential contributors to greenhouse gas emissions. In contrast to the typical investigations that consider microbiological processes, the authors considered purely chemical processes. Based on their results they found that as much as 20.41% of all CO₂ emission from land-based activities could be a result of mineral nitrogen fertilizers.

In this report, Bhardwaj and Sharma tested whether placing specific plants indoors can reduce levels of indoor air pollution that can lead to lung-related illnesses. Using machine learning, they show that plants improved overall indoor air quality and reduced levels of particulate matter. They suggest that plant-based interventions coupled with sensors may be a useful long-term solution to reducing and maintaining indoor air pollution.

Dental resins can be a source of reactive oxygen species (ROS) which in unruly amounts can be toxic to cellular and overall health. In this report, the authors test whether the consumption of antioxidant rich foods like avocado and asparagus can protect against the effect of dental resin-derived ROS. However, rather than testing humans, they use fruit flies and their climbing abilities as an experimental readout.

Ecological corridors are geographic features designated to allow the movement of wildlife populations between habitats that have been fragmented by human landscapes. Corridors can be a pivotal aspect in wildlife conservation because they preserve a suitable habitat for isolated populations to live and intermingle. Here, two students simulate the effect of introducing a safety corridor for cheetahs, based on real tracking data on cheetahs in Namibia.

Amyotrophic lateral sclerosis (ALS) affects nearly 200,000 people worldwide and there is currently no cure. The purpose of the study was to determine if Helianthus annuus seeds helped reduce nerve degeneration and increase locomotion using Drosophila melanogaster as the model organism. Through this experiment, we found a general trend suggesting that H. annuus helped increase the mobility of the D. melanogaster suggesting it could be a viable supplement for patients with ALS.