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Secure grasping of fragile fruits and other agricultural products without potential slip and damage is still a challenge due to the size and shape varying, bruise susceptible, as well as hardness changing during fruit and vegetable maturation. In the robotic grasping process, the mechanical damage mainly depends upon the aggressiveness of the gripper and the sensitivity of the product to the damage. In this study, a flexible gripper integrated with multi-sensor network is designed and tested. The network proposed includes three kinds of sensors that enable the gripper to grasp various products with the sense of touch and visual perception. Particular attention has been attached to the sensors applied between the fingers, and this makes sensing and grasping capabilities improved. To create an accurate grasping system, a grasping algorithm and the force control model are proposed for any bending state based on Cosserat theory. The boundary detection is included in the grasping algorithm, detecting the shape edge by some certain point calculation. The created grasping system guarantees mechanical compliance by evaluating and adjusting the finger status including force, angle, and direction. Multi-group tests have been done on grasping several objects of different sizes and materials in daily life. The relationship between force, bending, and surface material is also analyzed and compared under different conditions. The numerical comparisons related to the measurement error are analyzed based on their standard deviations. Experimental results indicate that this flexible manipulator with proposed system and strategy has better grasping ability for fragile fruits with its good flexibility and dexterity.

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Purpose: The relationship between contrast-enhanced ultrasound (CEUS) hemodynamics and the molecular biomarkers of adult-type diffuse gliomas, particularly isocitrate dehydrogenase (IDH), remains unclear. This study was conducted to provide a comprehensive description of the vascularization of adult-type diffuse gliomas using quantitative indicators. Additionally, it was designed to identify any variables with the potential to intraoperatively predict IDH mutation status.Methods: This prospective study enrolled patients with adult-type diffuse gliomas between November 2021 and September 2022. Intraoperative CEUS was performed, and CEUS videos were recorded for 90-second periods. Hemodynamic parameters, including the peak enhancement (PE) difference, were calculated based on the time-intensity curve of the region of interest. A differential analysis was performed on the CEUS parameters with respect to molecular biomarkers and grades. Receiver operating characteristic curves for various parameters were analyzed to evaluate the ability of those parameters to predict IDH mutation status.Results: Sixty patients with adult-type diffuse gliomas were evaluated. All hemodynamic parameters, apart from rising time, demonstrated significant differences between IDH-mutant and IDH-wildtype adult-type diffuse gliomas. The PE difference emerged as the optimal indicator for differentiating between IDH-wildtype and IDH-mutant gliomas, with an area under the curve of 0.958 (95% confidence interval, 0.406 to 0.785). Additionally, the hemodynamic parameters revealed significant differences across both grades and types of adult-type diffuse gliomas.Conclusion: Hemodynamic parameters can be used intraoperatively to effectively distinguish between IDHwildtype and IDH-mutant adult-type diffuse gliomas. Additionally, quantitative CEUS equips neurosurgeons with dynamic perfusion information for various types and grades of adult-type diffuse gliomas.

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