RESUMEN
This research is dedicated to developing an automatic landing system for shipborne unmanned aerial vehicles (UAVs) based on wireless precise positioning technology. The application scenario is practical for specific challenging and complex environmental conditions, such as the Global Positioning System (GPS) being disabled during wartime. The primary objective is to establish a precise and real-time dynamic wireless positioning system, ensuring that the UAV can autonomously land on the shipborne platform without relying on GPS. This work addresses several key aspects, including the implementation of an ultra-wideband (UWB) circuit module with a specific antenna design and RF front-end chip to enhance wireless signal reception. These modules play a crucial role in achieving accurate positioning, mitigating the limitations caused by GPS inaccuracy, thereby enhancing the overall performance and reception range of the system. Additionally, the study develops a wireless positioning algorithm to validate the effectiveness of automatic landing on the shipborne platform. The platform's wave vibration is considered to provide a realistic landing system for shipborne UAVs. The UWB modules are practically installed on the shipborne platform, and the UAV and the autonomous three-body vessel are tested simultaneously in the outdoor open water space to verify the functionality, precision, and adaptability of the proposed UAV landing system. Results demonstrate that the UAV can autonomously fly from 200 m, approach, and automatically land on the moving shipborne platform without relying on GPS.
RESUMEN
Multiple myeloma (MM) was one of the hardest cancers to diagnose because of numerous nonspecific symptoms, leading to diagnostic delay. Proactive consultation of laboratory medicine (PCLM) could help timely diagnosis of blood cancers, avoiding diagnostic delay. This study aimed to evaluate the effect of PCLM on diagnosis and outcomes in MM. This retrospective study was conducted in newly diagnosed MM patients from 2011 to 2022. Implementation of PCLM initiated in 2015 with a laboratory-oriented algorithm. The annual diagnostic rate, patient demographics, the time intervals from symptom onset to diagnosis and to treatment, and clinical outcomes were analyzed. A total of 134 patients were newly diagnosed during the study interval. The diagnostic rate increased from 4.65â ±â 1.59 to 7.43â ±â 1.52 per million patient-visits after implementation of PCLM. The median time interval from symptom onset to diagnosis was significantly shortened after implementation of PCLM (50 days with interquartile range [IQR]: 24-136 days vs 150 days with IQR: 41-385 days, Pâ =â .003). Besides, the 1-year survival was significantly higher in patients diagnosed as MM after implementation of PCLM (72.4% vs 51.7%, Pâ =â .035). Implementation of PCLM not only increased diagnostic rate of MM and improved outcomes, but also raise awareness for MM and promote multidisciplinary collaboration in healthcare.