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The unequal distribution of medical resources and scarcity of experienced practitioners confine access to bronchoscopy primarily to well-equipped hospitals in developed regions, contributing to the unavailability of bronchoscopic services in underdeveloped areas. Here, we present an artificial intelligence (AI) co-pilot bronchoscope robot that empowers novice doctors to conduct lung examinations as safely and adeptly as experienced colleagues. The system features a user-friendly, plug-and-play catheter, devised for robot-assisted steering, facilitating access to bronchi beyond the fifth generation in average adult patients. Drawing upon historical bronchoscopic videos and expert imitation, our AI–human shared control algorithm enables novice doctors to achieve safe steering in the lung, mitigating misoperations. Both in vitro and in vivo results underscore that our system equips novice doctors with the skills to perform lung examinations as expertly as seasoned practitioners. This study offers innovative strategies to address the pressing issue of medical resource disparities through AI assistance. The unequal distribution of medical resources means that bronchoscopic services are often unavailable in underdeveloped areas. Here, the authors present an AI co-pilot bronchoscope robot that features a user-friendly plug-and-play catheter and an AI-human shared control algorithm, to enable novice doctors to conduct lung examinations safely.

In this paper, we describe the advances in the design, actuation, modeling, and control field of continuum robots. After decades of pioneering research, many innovative structural design and actuation methods have arisen. Untethered magnetic robots are a good example; its external actuation characteristic allows for miniaturization, and they have gotten a lot of interest from academics. Furthermore, continuum robots with proprioceptive abilities are also studied. In modeling, modeling approaches based on continuum mechanics and geometric shaping hypothesis have made significant progress after years of research. Geometric exact continuum mechanics yields apparent computing efficiency via discrete modeling when combined with numerical analytic methods such that many effective model-based control methods have been realized. In the control, closed-loop and hybrid control methods offer great accuracy and resilience of motion control when combined with sensor feedback information. On the other hand, the advancement of machine learning has made modeling and control of continuum robots easier. The data-driven modeling technique simplifies modeling and improves anti-interference and generalization abilities. This paper discusses the current development and challenges of continuum robots in the above fields and provides prospects for the future.

Lung disease has become a leading cause of disease‐related death, making it one of the most serious health problems in the world. Due to the advantages of fast postoperative recovery and small trauma, transbronchoscopic biopsy has become the main method for the diagnosis of lung diseases. However, limited by the large outer diameter of the bronchoscope, insufficient flexibility of the biopsy needle, and lack of force sensing, traditional biopsy operation is simple and rough, and it is difficult to enter the deep narrow areas of the lung for examination. In this article, a flexible biopsy robot with force‐sensing ability is proposed. The robot is composed of a tendon‐actuated catheter and an inner sliding flexible needle as well as their driving systems. The experimental results demonstrate that the robot has good positioning accuracy of 0.72 mm and high flexibility and repeatability. With the cooperation of the commercial bronchoscope, the robot can reach various narrow areas of the lung to perform biopsy operations. The proposed robot has the potential to improve the diagnosis rate of lung diseases and reduce related deaths. Overview of the flexible biopsy robot for lung examination. After the bronchoscope is controlled to enter the bronchus near the tumor lesions by the surgeon, the flexible biopsy robot is inserted along its working channel and extends out. Then, the biopsy robot is controlled to near the lesion and perform biopsy sampling. The puncture force is monitored to ensure safety.

In the realm of underwater exploration and operations, soft robots exhibit considerable application potential due to their capacity for agile and complex deformations as well as their inherent compliance. These characteristics grant them excellent environmental adaptability and reduce damage to delicate samples and organisms. Nonetheless, existing underwater soft robots are primarily designed to mimic the movements of marine organisms or for specific functions, and little attention is paid to the camouflage ability. To address these challenges, in this study, a reconfigurable transparent soft robot with variable stiffness for underwater operations is presented. The design and fabrication methodology of the robot module is presented, followed by the kinematic analysis and stiffness characterization. Leveraging the proposed robot module, a soft manipulator and a soft gripper are designed for underwater operations. The soft manipulator excels in underwater pipeline detection and obstacle avoidance, while the soft gripper showcases considerable load‐bearing capacity (about 71 times its weight), making it suitable for tasks such as retrieving aquatic biological samples or garbage fishing. The proposed reconfigurable soft robot demonstrates robust camouflage capabilities, high environmental adaptability, and notable versatility, suggesting potential solutions to existing challenges in the field of underwater exploration. In this work, a reconfigurable transparent soft robot with variable stiffness capability for underwater operations is presented. Detailed design and fabrication methodology, kinematic analysis, and stiffness characterization of the robot are provided. Furthermore, a soft manipulator and a soft gripper are designed respectively for underwater exploration and grasping to demonstrate its potential for underwater operations.

Locating tumors during laparoscopic surgery for early gastric cancers poses an important challenge because they lack involvement with the serosal layer and remain invisible within the peritoneal cavity. To address this issue, various techniques such as preoperative dye injection and magnetic clip detection systems have been introduced to aid in intraoperative tumor localization. However, these existing techniques are often intricate and lack intuition and endurance. In this study, we propose a novel approach utilizing fluorescent soft robots to accurately locate tumors within the stomach. The methodology involved placing a metal clip at the tumor site, followed by administering several soft robots labeled with Cy5. These soft robots were designed to autonomously converge around the metal clip. To validate their efficacy, we conducted animal experiments by implanting clips into the stomachs of rats and subsequently administering capsules containing the soft robots. By detecting the resulting fluorescence, we successfully identified the location of the clips within the stomach. Our findings indicate that these soft robots hold great promise as a viable alternative for localizing gastric lesions during laparoscopic surgery, which has better persistence and intuitiveness than other markup methods. Their implementation could significantly enhance the accuracy and efficiency of tumor identification in a technologically advanced and clinically accessible manner.

Soft Underwater Robots Soft robots hold great significance for underwater operations due to their exceptional compliance and adaptability. In article number 2300688, Qin Fang, Zhefeng Gong, Haojian Lu, and co‐workers introduce a transparent reconfigurable soft underwater robot with variable stiffness capability. The cover image shows a soft gripper for delicate underwater grasping and a soft manipulator for exploration in confined underwater environments, highlighting the robot’s potential for future underwater applications.

Locating tumors during laparoscopic surgery for early gastric cancers poses an important challenge because they lack involvement with the serosal layer and remain invisible within the peritoneal cavity. To address this issue, various techniques such as preoperative dye injection and magnetic clip detection systems have been introduced to aid in intraoperative tumor localization. However, these existing techniques are often intricate and lack intuition and endurance. In this study, we propose a novel approach utilizing fluorescent soft robots to accurately locate tumors within the stomach. The methodology involved placing a metal clip at the tumor site, followed by administering several soft robots labeled with Cy5. These soft robots were designed to autonomously converge around the metal clip. To validate their efficacy, we conducted animal experiments by implanting clips into the stomachs of rats and subsequently administering capsules containing the soft robots. By detecting the resulting fluorescence, we successfully identified the location of the clips within the stomach. Our findings indicate that these soft robots hold great promise as a viable alternative for localizing gastric lesions during laparoscopic surgery, which has better persistence and intuitiveness than other markup methods. Their implementation could significantly enhance the accuracy and efficiency of tumor identification in a technologically advanced and clinically accessible manner.

With the increasing computing power, using data-driven approaches to co-design a robot's morphology and controller has become a promising way. However, most existing data-driven methods require training the controller for each morphology to calculate fitness, which is time-consuming. In contrast, the dual-network framework utilizes data collected by individual networks under a specific morphology to train a population network that provides a surrogate function for morphology optimization. This approach replaces the traditional evaluation of a diverse set of candidates, thereby speeding up the training. Despite considerable results, the online training of both networks impedes their performance. To address this issue, we propose a concurrent network framework that combines online and offline reinforcement learning (RL) methods. By leveraging the behavior cloning term in a flexible manner, we achieve an effective combination of both networks. We conducted multiple sets of comparative experiments in the simulator and found that the proposed method effectively addresses issues present in the dual-network framework, leading to overall algorithmic performance improvement. Furthermore, we validated the algorithm on a real robot, demonstrating its feasibility in a practical application.

A dielectric-barrier discharge (DBD) plasma technique has been successfully applied for template removal from ZSM-5 zeolite. The rate for template removal using DBD is about eight times higher than that using the conventional thermal calcination. During the template removal using DBD, the highest temperature of the sample is about 125 °C. As such, the thermal effect on the sample during the DBD template removal is not significant. This made the structure changes of ZSM-5 zeolite during the template removal less dramatic than that using thermal calcination. Graphical Abstract The dielectric-barrier discharge (DBD) plasma, initiated at ambient condition, has been successfully applied for removing template from ZSM-5 zeolite. The rate for the template removal using DBD is about eight times higher than that using the conventional thermal calcination. [graphic removed]

To the Editor: In their Perspective article, Tucker et al. (May 6 issue) 1 report that rapid increases in cases of congenital syphilis in China have generated great concern. Although sexually transmitted diseases (STDs) have become major notifiable diseases in China, 2 a review by an expert panel concluded in February 2008 that the rapid increase in reported cases of syphilis was primarily caused by systematic changes in diagnosis and reporting, because a nationwide, Web-based, real-time reporting system was introduced in 2004. 3 National surveillance of pregnant women with syphilis in China suggested that there was no significant change in the incidence between . . .