Video-Based Lifting Action Recognition Using Rank-Altered Kinematic Feature Pairs.

Objective: To identify lifting actions and count the number of lifts performed in videos based on robust class prediction and a streamlined process for reliable real-time monitoring of lifting tasks.

Background: Traditional methods for recognizing lifting actions often rely on deep learning classifiers applied to human motion data collected from wearable sensors. Despite their high performance, these methods can be difficult to implement on systems with limited hardware resources.

Artificial Cascade Transformation Biosystem for One-Pot Biomanufacturing of Odd-Numbered Neoagarooligosaccharides and d-Tagatose through Wiser Agarose Utilization.

The application of agarose oligosaccharides has garnered great attention, with their biological activities varying among different structures. However, it still meets a great bottleneck for the targeted production of odd-numbered neoagarooligosaccharides (NAOSs), such as neoagarotriose (NA3), due to the lack of one-step hydrolases. In this work, the α-agarase AgaA33 and β-galactosidase BgaD were synergistically used to prepare NA3 with agarose as a substrate.

Chitinase and Deacetylase-Based Chitin-Degrading Bacteria: One-Pot Cascade Bioconversion of Chitin to Chitooligosaccharides.

Cascade conversion of chitin into soluble and functional chitooligosaccharides has gained great attention. However, the biotransformation route is still limited to the low catalytic performances of chitin deacetylases (CDAs) and complicated procedures. In this study, a CDA from sp.

Markerless gait analysis through a single camera and computer vision.

The assessment of gait performance using quantitative measures can yield crucial insights into an individual's health status. Recently, computer vision-based human pose estimation has emerged as a promising solution for markerless gait analysis, as it allows for the direct extraction of gait parameters from videos. This study aimed to compare the lower extremity kinematics and spatiotemporal gait parameters obtained from a single-camera-based markerless method with those acquired from a marker-based motion tracking system across a healthy population.

Exploring the impact of human-robot interaction on workers' mental stress in collaborative assembly tasks.

Advances in robotics have contributed to the prevalence of human-robot collaboration (HRC). However, working and interacting with collaborative robots in close proximity can be psychologically stressful. Therefore, understanding the impacts of human-robot interaction (HRI) on mental stress is crucial for enhancing workplace well-being.

Hyperspectral imaging in combination with data fusion for rapid evaluation of tilapia fillet freshness.

The potential of two different hyperspectral imaging systems (visible near infrared spectroscopy (Vis-NIR) and NIR) was investigated to determine TVB-N contents in tilapia fillets during cold storage. With Vis-NIR and NIR data, calibration models were established between the average spectra of tilapia fillets in the hyperspectral image and their corresponding TVB-N contents and optimized with various variable selection and data fusion methods. Superior models were obtained with variable selection methods based on low-level fusion data when compared with the corresponding methods based on single data blocks.