Technological breakthroughs in the past two decades have ushered in a new era of biomedical research, turning it into an information-rich and technology-driven science. This scientific revolution, though evident to the research community, remains opaque to nonacademic audiences. Such knowledge gaps are likely to persist without revised strategies for science education and public outreach. To address this challenge, we developed a unique outreach program to actively engage over 100 high-school students in the investigation of multidrug-resistant bacteria. Our program uses robotic automation and interactive web-based tools to bridge geographical distances, scale up the number of participants, and reduce overall cost. Students and teachers demonstrated high engagement and interest throughout the project and valued its unique approach. This educational model can be leveraged to advance the massive open online courses movement that is already transforming science education.
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http://dx.doi.org/10.1371/journal.pbio.3000348 | DOI Listing |
Arch Orthop Trauma Surg
January 2025
Centre Hospitalier Universitaire de Nîmes, Nîmes, France.
Purpose: The adoption of robotic-assisted total hip arthroplasty (THA) is increasingly widespread, yet its influence on outcomes in outpatient surgery remains uncertain. This study aimed to evaluate whether robotic assistance reduces the rate of 90-day postoperative events in patients undergoing outpatient THA, compared to those in inpatient procedures.
Methods: This historical-prospective cohort study analyzed 706 primary THA cases performed between January 2017 and January 2023 by three senior surgeons.
Am J Case Rep
January 2025
Department of Orthopedic Surgery, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
BACKGROUND The management of unstable atlas fractures remains a subject of ongoing debate and controversy. The conservative surgical treatment commonly involves fusion, resulting in severe loss of cervical spine mobility, and a large incisions and extensive tissue dissection are required. We aim to introduce a novel concept and surgical approach for treating atlas fracture, one that involves minimizing trauma while maintaining mobility of the upper cervical spine without resorting to fusion.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Department of Automation, "Dunarea de Jos" University of Galati, 800008 Galati, Romania.
This paper deals with a "digital twin" (DT) approach for processing, reprocessing, and scrapping (P/R/S) technology running on a modular production system (MPS) assisted by a mobile cyber-physical robotic system (MCPRS). The main hardware architecture consists of four line-shaped workstations (WSs), a wheeled mobile robot (WMR) equipped with a robotic manipulator (RM) and a mobile visual servoing system (MVSS) mounted on the end effector. The system architecture integrates a hierarchical control system where each of the four WSs, in the MPS, is controlled by a Programable Logic Controller (PLC), all connected via Profibus DP to a central PLC.
View Article and Find Full Text PDFSensors (Basel)
January 2025
State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China.
As advancements in autonomous underwater vehicle (AUV) technology unfold, the role of underwater wireless sensor networks (UWSNs) is becoming increasingly pivotal. However, the high energy consumption in these networks can significantly reduce their operational lifespan, while latency issues can impair overall network performance. To address these challenges, a novel mixed packet forwarding strategy is developed, which incorporates a wakeup threshold and a dynamically adjusted access probability for the cluster head (CH).
View Article and Find Full Text PDFSensors (Basel)
January 2025
Key Laboratory of Modern Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Nanjing Institute of Agricultural Mechanization, Nanjing 210014, China.
To address several challenges, including low efficiency, significant damage, and high costs, associated with the manual harvesting of , in this study, a machine vision-based intelligent harvesting device was designed according to its agronomic characteristics and morphological features. This device mainly comprised a frame, camera, truss-type robotic arm, flexible manipulator, and control system. The FES-YOLOv5s deep learning target detection model was used to accurately identify and locate .
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