Multi-function Robotized Surgical Dissector for Endoscopic Pulmonary Thromboendarterectomy: Preclinical Study and Evaluation

Patients suffering chronic severe pulmonary thromboembolism need Pulmonary Thromboendarterectomy (PTE) to remove the thromb and intima located inside pulmonary artery (PA). During the surgery, a surgeon holds tweezers and a dissector to delicately strip the blockage, but available tools for this surgery are rigid and straight, lacking distal dexterity to access into thin branches of PA. Therefore, this work presents a novel robotized dissector based on concentric push/pull robot (CPPR) structure, enabling entering deep thin branch of tortuous PA. Compared with conventional rigid dissectors, our design characterizes slenderness and dual-segment-bending dexterity. Owing to the hollow and thin-walled structure of the CPPR-based dissector as it has a slender body of 3.5mm in diameter, the central lumen accommodates two channels for irrigation and tip tool, and space for endoscopic camera's signal wire. To provide accurate surgical manipulation, optimization-based kinematics model was established, realizing a 2mm accuracy in positioning the tip tool (60mm length) under open-loop control strategy. As such, with the endoscopic camera, traditional PTE is possible to be upgraded as endoscopic PTE. Basic physic performance of the robotized dissector including stiffness, motion accuracy and maneuverability was evaluated through experiments. Surgery simulation on ex vivo porcine lung also demonstrates its dexterity and notable advantages in PTE.

SimGym: Traffic-Grounded Browser Agents for Offline A/B Testing in E-Commerce

A/B testing remains the gold standard for evaluating e-commerce UI changes, yet it diverts traffic, takes weeks to reach significance, and risks harming user experience. We introduce SimGym, a scalable system for rapid offline A/B testing using traffic-grounded synthetic buyers powered by Large Language Model agents operating in a live browser. SimGym extracts per-shop buyer profiles and intents from production interaction data, identifies distinct behavioral archetypes, and simulates cohort-weighted sessions across control and treatment storefronts. We validate SimGym against real human outcomes from real UI changes on a major e-commerce platform under confounder control. Even without alignment post training, SimGym agents achieve state of the art alignment with observed outcome shifts and reduces experiment cycles from weeks to under an hour , enabling rapid experimentation without exposure to real buyers.