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This study presents a field-programmable gate array (FPGA)-based mechatronic design and real-time fuzzy control method with computational intelligence optimization for omni-Mecanum-wheeled autonomous vehicles. With the advantages of cuckoo search (CS), an evolutionary CS-based fuzzy system is proposed, called CS-fuzzy. The CS&rsquo, s computational intelligence was employed to optimize the structure of fuzzy systems. The proposed CS-fuzzy computing scheme was then applied to design an optimal real-time control method for omni-Mecanum-wheeled autonomous vehicles with four wheels. Both vehicle model and CS-fuzzy optimization are considered to achieve intelligent tracking control of Mecanum mobile vehicles. The control parameters of the Mecanum fuzzy controller are online-adjusted to provide real-time capability. This methodology outperforms the traditional offline-tuned controllers without computational intelligences in terms of real-time control, performance, intelligent control and evolutionary optimization. The mechatronic design of the experimental CS-fuzzy based autonomous mobile vehicle was developed using FPGA realization. Some experimental results and comparative analysis are discussed to examine the effectiveness, performance, and merit of the proposed methods against other existing approaches.

The nasopharyngeal tract traps mainly coarse particles in inhaled air. Soluble carcinogenic compounds, endotoxins, and trace metals contained in these particles are potential causes of inflammation and oxidative stress which could enhance carcinogenesis. The aim of this study was to determine the association between coarse particulate matter (PM10-2.5) and nasopharyngeal cancer (NPC). A total of 521,098 men (355 cases and 520,743 non-cases), aged ≥40 years were included in this study. Data were retrieved from the Taiwan Cancer Registry, the Adult Preventive Medical Services Database, and the Air Quality Monitoring Database. PM10-2.5 was significantly associated with a higher risk of NPC after adjusting for SO2, NOx, O3, age, body mass index, smoking, alcohol drinking, betel nut chewing, exercise, hypertension, diabetes, and hyperlipidemia. With PM10-2.5

This paper presents a backstepping holonomic tracking control method of embedded wheeled robots using an evolutionary fuzzy system with qualified ant colony optimization (ACO). The Taguchi method is applied to design an optimal ACO via an orthogonal array. This qualified ACO is then employed to develop an evolutionary fuzzy system, called FS-TACO. The proposed hybrid intelligent fuzzy system FS-TACO is realized in a field-programmable gate array (FPGA) to dynamic tracking control of three-wheeled holonomic mobile robots. In comparison with conventional control systems, this approach takes the advantages of Taguchi quality method, fuzzy system, ACO and FPGA technique, thereby obtaining better population diversity, avoiding premature convergence, and achieving self-adaptive holonomic control. The FPGA realization using system-on-a-programmable chip methodology of the proposed FS-TACO is more effective in practice for real-world embedded applications. Experimental results and comparative works are conducted to exhibit the merits of the proposed FPGA-based FS-TACO controller for three-wheeled holonomic mobile robots.

This paper presents an evolutionary radial basis function neural network with genetic algorithm and artificial immune system (GAAIS-RBFNN) for tracking control of autonomous robots. Both the GAAIS-RBFNN computational intelligence and online tracking controller are implemented in one field-programmable gate array (FPGA) chip to cope with the optimal control problem of real-world mobile robotics. The hybrid GAAIS paradigm incorporated with Taguchi quality method is employed to determine the optimal structure of RBFNN. The control parameters of tracking controller are online tuned by minimizing the performance index using the proposed GAAIS-RBFNN to achieve trajectory tracking. Experimental results and comparative works are conducted to show the effectiveness and merit of the proposed FPGA-based GAAIS-RBFNN tracking controller using system-on-a-programmable-chip technology. This FPGA-based online hybrid GAAIS-RBFNN intelligent controller outperforms the existing bio-inspired RBFNN controllers using individual GA and AIS algorithms.

Pneumocytoma, former known as sclerosing hemangioma, is a rare and benign tumor in lung which derived from primitive respiratory epithelium. It’s usually a single tumor, size from 0.3–7 cm (70% of patient

This paper presents a self-tuning proportional-integral-derivative (PID) leader-follower control method of autonomous robots. Simulation result demonstrates the effectiveness and merit of the proposed methods.

This paper presents a biologically inspired deoxyribonucleic acid (DNA) algorithm for solving the inverse kinematics of five degree-of-freedom (DOF) robotic manipulators. Although the 5-DOF robotic manipulator agilely maneuvers from one pose to another and easily performs some tasks, the inverse kinematics problem of the system is redundant. This problem has no general closed-form solutions or analytical solutions for the 5-DOF manipulator. The DNA soft computing is proposed to solve the redundant inverse kinematics problem of the 5-DOF robotic manipulators more efficiently. Simulation results are conducted to illustrate the effectiveness and merit of the proposed methods in comparison with conventional genetic algorithm (GA) and particle swarm optimization.

This paper presents a field-programmable gate array (FPGA)-based parallel metaheuristic particle swarm optimization algorithm (PPSO) and its application to global path planning for autonomous robot navigating in structured environments with obstacles. This PPSO consists of three parallel PSOs along with a communication operator in one FPGA chip. The parallel computing architecture takes advantages of maintaining better population diversity and inhibiting premature convergence in comparison with conventional PSOs. The collision-free discontinuous path generated from the PPSO planner is then smoothed using the cubic B-spline and system-on-a-programmable-chip (SoPC) technology. Experimental results are conducted to show the merit of the proposed FPGA-based PPSO path planner and smoother for global path planning of autonomous mobile robot navigation.

This paper presents a parallel elite genetic algorithm (PEGA) and its application to global path planning for autonomous mobile robots navigating in structured environments. This PEGA, consisting of two parallel EGAs along with a migration operator, takes advantages of maintaining better population diversity, inhibiting premature convergence, and keeping parallelism in comparison with conventional GAs. This initial feasible path generated from the PEGA planner is then smoothed using the cubic B-spline technique, in order to construct a near-optimal collision-free continuous path. Both global path planner and smoother are implemented in one field-programmable gate array chip utilizing the system-on-a-programmable-chip technology and the pipelined hardware implementation scheme, thus significantly expediting computation speed. Simulations and experimental results are conducted to show the merit of the proposed PEGA path planner and smoother for global path planning of autonomous mobile robots.

This paper presents adaptive robust regulation methods for self-balancing and yaw motion of a two-wheeled human transportation vehicle (HTV) with varying payload and system uncertainties. The proposed regulators are aimed at providing consistent driving performance for the HTV with system uncertainties and parameter variations caused by different drivers. By decomposing the overall system into the yaw motion subsystems and the wheeled inverted pendulum, two proposed adaptive robust regulators are synthesized to achieve self-balancing and yaw motion control. Numerical simulations and experimental results on different terrains show that the proposed adaptive robust controllers are capable of achieving satisfactory control actions to steer the vehicle.

This paper presents an adaptive polar-space motion controller for trajectory tracking and stabilization of a three-wheeled, embedded omnidirectional mobile robot with parameter variations and uncertainties caused by friction, slip and payloads. With the derived dynamic model in polar coordinates, an adaptive motion controller is synthesized via the adaptive backstepping approach. This proposed polar-space robust adaptive motion controller was implemented into an embedded processor using a field-programmable gate array (FPGA) chip. Furthermore, the embedded adaptive motion controller works with a reusable user IP (Intellectual Property) core library and an embedded real-time operating system (RTOS) in the same chip to steer the mobile robot to track the desired trajectory by using hardware/software co-design technique and SoPC (system-on-a-programmable-chip) technology. Simulation results are conducted to show the merit of the proposed polar-space control method in comparison with a conventional proportional-integral (PI) feedback controller and a non-adaptive polar-space kinematic controller. Finally, the effectiveness and performance of the proposed embedded adaptive motion controller are exemplified by conducting several experiments on steering an embedded omnidirectional mobile robot.

This paper presents polar‐space kinematic and dynamic control methods to achieve both trajectory tracking and stabilization for an omnidirectional wheeled mobile robot with three independent, omnidirectional, driving wheels equally spaced at 120 degrees from one another. Both kinematic and dynamic models of the robot in polar coordinates are presented. A kinematic control method is proposed based on feedback linearization and the kinematic model, whereas a dynamic controller is synthesized using backstepping and the dynamic model. Experimental results are presented to show the efficacy and usefulness of the proposed control methods.

SUMMARYThis paper presents a polar-space kinematics control method to achieve simultaneous tracking and stabilization for an omnidirectional wheeled mobile robot with three independent driving omnidirectional wheels equally spaced at 120° from one another. The kinematic model of the robot in polar coordinates is presented. With the kinematic model, a kinematic control method based on feedback linearization is proposed in order to achieve simultaneous tracking and stabilization. The proposed method is easily extended to address the path following problem. Computer simulations and experimental results are presented to show the effectiveness and usefulness of the proposed control method at slow speeds.

This paper presents an embedded adaptive robust controller for trajectory tracking and stabilization of an omnidirectional mobile platform with parameter variations and uncertainties caused by friction and slip. Based on a dynamic model of the platform, the adaptive controller to achieve point stabilization, trajectory tracking, and path following is synthesized via the adaptive backstepping approach. This robust adaptive controller is then implemented into a high-performance field-programmable gate array chip using hardware/software codesign technique and system-on-a-programmable-chip design concept with a reusable user intellectual property core library. Furthermore, a soft-core processor and a real-time operating system are embedded into the same chip for realizing the control law to steer the mobile platform. Simulation results are conducted to show the effectiveness and merit of the proposed control method in comparison with a conventional proportional-integral feedback controller. The performance and applicability of the proposed embedded adaptive controller are exemplified by conducting several experiments on an autonomous omnidirectional mobile robot.

This paper presents techniques for design and control of a brushless direct-current (DC) limited-angle torque motor (LATM) with its application to fuel control of gas turbine engines. Given the desired specifications, a two-pole brushless DC LATM with a toroidally wound armature is designed using selected ferromagnetic material and rare-earth permanent magnets; its electromagnetic characteristics is then computationally found and well tuned using the finite element method (FEM) in order to ensure whether the design meets the performance specifications. To achieve the simple and inexpensive semi-closed-loop fuel control, a robust position controller (including a proportional-integral-derivative (PID) controller with a prefilter) is synthesized for providing the required positioning performance for the developed motor, thereby achieving an inexpensive semi-closed-loop fuel control. A closed-loop fuel controller associated with the proposed position controller and a flow meter is then proposed based on multi-loop control structure in order to achieve required linear input–output relationship. All the proposed fuel control laws were implemented using a stand-alone single-chip digital signal processor (DSP). Experimental results are conducted to show the efficacy and usefulness of the developed limited-angle torque motor with its application to an experimental gas turbine fuel control test platform.

This paper presents an adaptive robust control method for trajectory tracking and path following of an omni-directional wheeled mobile platform with actuators' uncertainties. The polar-space kinematic model of the platform with three independent driving omnidirectional wheels equally spaced at 120 from one another is briefly introduced, and the dynamic models of the three uncertain servomotors mounted on the driving wheels are also described. With the platform's kinematic model and the motors' dynamic model associated two unknown parameters, the adaptive robust controller is synthesized via the integral backstepping approach. Computer simulations and experimental results are conducted to show the effectiveness and merits of the proposed control method in comparison with a conventional PI feedback control method.

This paper presents an adaptive backstepping control method for trajectory tracking and stabilization of an omnidirectional wheeled mobile robot with parameter variations and uncertainties caused by friction and slip. The dynamic model of the robot with three independent driving omnidirectional wheels equally spaced at 120 degrees from one another is briefly introduced. With the dynamic model, the adaptive controller to achieve both trajectory tracking and stabilization is synthesized via adaptive backstepping approach. Experimental results are conducted to show the merit of the proposed control method.

This paper presents an optimal fuzzy controller design method using Taguchi theory based particle swarm optimization (TPSO) to four-wheeled redundant mobile robots, called TPSO. In comparison with conventional fuzzy controllers, this approach takes the advantages of Taguchi method, fuzzy control and PSO, thereby obtaining better population diversity, avoiding premature convergence and achieving self-adaptive redundant control. This hybrid computing is then applied to develop an optimal fuzzy controller of redundant autonomous wheeled robots. The optimal parameters of the dynamic controller are self-adaptive via the proposed TPSO to resolve trajectory tracking problem. Simulation results are given to exhibit the merits of the proposed TPSO for redundant wheeled robots.

This work presents an adaptive fuzzy cerebellar model articulation controller (AFCMAC) for solving the tracking control problem for an omni-directional mobile robot. First, fuzzy logic and CMAC are combined, coupled with a triangular basis function that is embedded in the hypercube receptive-field space to yield non-constant differentiable basis functions, which simplify the complex structure and reduce the number of input space dimensions of CMAC. Both adaptive and control laws are developed to tune all of the control parameters online, accommodating uncertainty in tracking control for an omni-directional mobile robot. Hardware agencies and drive circuits are developed. This proposed AFCMAC is implemented in a high-performance field-programmable gate array (FPGA) chip using a hardware/software co-design method and the Qsys design concept with a reusable user IP (Intellectual Property) core library. An omni-directional mobile robot is thus produced. Finally, the trajectory tracking controllability of the robot along an elliptical path is experimented to evaluate the effectiveness of the proposed AFCMAC control scheme.

This paper presents a metaheuristic artificial immune system (AIS) algorithm for mobile robot navigation in a structured environment with obstacles. The generated collision-free path is optimal in the sense of the shortest distance by defining the performance index. The initial feasible path generated from the AIS planner is then smoothed using the cubic B-spline technique, in order to construct a near-optimal collision-free continuous path. Simulations results are conducted to show the merit of the proposed AIS path planner and smoother for global path planning of autonomous robot navigation.

Video-assisted thoracoscopic surgery (VATS) is a minimally invasive alternative to conventional surgery (CS). We aimed to estimate the short-term cost-effectiveness of VATS vs. CS for clinical stage I non-small cell lung cancer (NSCLC-c-stage-I) patients from the payer's perspective (National Health Insurance).We identified NSCLC-c-stage-I patients diagnosed and received surgery within 2007-2009 through a comprehensive population-based database containing cancer and death registries, and reimbursement data. The duration of interest was 1 year. We included potential confounding covariables through literature searching and our own experience, and used a propensity score to construct a 1:1 population for adjustment.Our study population constituted 966 patients. The mean hospital stay [days, standard deviation (SD)] were 14.4 [7] and 16.1 (7.7) for VATS and CS respectively (P=0.002). The mean cost (2013 USD) and survival (year) was $22,316 vs. $21,976 and 0.98 vs. 0.974 for VATS vs. CS. The probability for VATS to be cost-effective (i.e., positive net benefit) was 0.490.56 at willingness-to-pay (WTP) 50,000100,000 USD/life-year, respectively.We provide the first empirical evidence that when compared to CS, VATS was potentially cost-effective in the short term (1 year) within the common WTP levels in Taiwan.

Background: Although blebs and bullae are frequently found in the apexes of lungs of patients with primary spontaneous pneumothorax (PSP), its pathogens remain unclear. Objectives: To examine the role of proteases [matrix metalloproteinase (MMP)-2, MMP-7 and MMP-9] and antiproteases [tissue inhibitors of metalloproteinase (TIMP)-1, TIMP-2, TIMP-3 and TIMP-4] in the pathogenesis of PSP. Method: Fifty consecutive PSP patients who received standard surgical care were enrolled in the study. Lung tissues from 20 patients with stage I non-small cell lung cancer were used as a control. Immunohistochemistry (IHC), reverse transcription-polymerase chain reaction (RT-PCR) and gelatin zymography were used to evaluate the expression of MMP and TIMP in the lung tissue of patients with PSP. Results: Overexpression of MMP-2, MMP-7 and MMP-9 was found in the afflicted lung by IHC, zymography and RT-PCR. By IHC, higher expression of MMP-2 and MMP-9 in PSP patients was identified in alveolar macrophages and type II pneumocytes (88 and 92% of patients in macrophages, and 72 and 70% of patients in type II pneumocytes, respectively). MMP-2, MMP-7 and MMP-9 expression in patients was higher in mesothelial cells (66, 76 and 76%). Overexpression of TIMP-2 was detected in the extracellular matrix around bullae and blebs. Expression levels of TIMP-1, TIMP-3 and TIMP-4 were negligible (Conclusions: MMP-2, MMP-9, MMP-7 and TIMP-2 were upregulated in PSP lesions. These results suggest that an imbalance between the expression of proteases and antiproteases may be involved in the pathogeneses of PSP.

This paper presents a hybrid Taguchi deoxyribonucleic acid (DNA) swarm intelligence for solving the inverse kinematics redundancy problem of six degree-of-freedom (DOF) humanoid robot arms. The inverse kinematics problem of the multi-DOF humanoid robot arm is redundant and has no general closed-form solutions or analytical solutions. The optimal joint configurations are obtained by minimizing the predefined performance index in DNA algorithm for real-world humanoid robotics application. The Taguchi method is employed to determine the DNA parameters to search for the joint solutions of the six-DOF robot arms more efficiently. This approach circumvents the disadvantage of time-consuming tuning procedure in conventional DNA computing. Simulation results are conducted to illustrate the effectiveness and merit of the proposed methods. This Taguchi-based DNA (TDNA) solver outperforms the conventional solvers, such as geometric solver, Jacobian-based solver, genetic algorithm (GA) solver and ant, colony optimization (ACO) solver.

This paper presents an intelligent fuzzy motion controller for three-wheeled omnidirectional mobile robots to achieve trajectory tracking and stabilization. The controller parameters of motion controller are on-line tuned using the fuzzy theory. These optimized parameters are employed in the intelligent motion controller to obtain optimal performance for three-wheeled omnidirectional mobile robots. This approach outperforms the conventional trial-and-error approaches and the off-line tuning methods. Simulation results are conducted to show the effectiveness and merit of the proposed intelligent fuzzy motion controller for three-wheeled omnidirectional mobile robots.

This paper presents a particle swarm optimization algorithm (PSO) for solving the inverse kinematics of 7 degree-of-freedom (DOF) robotic manipulators. Although the 7-DOF robotic manipulator agilely maneuvers from one pose to another and easily performs some tasks, the inverse kinematics problem of the system is redundant. This problem has no general closed-form solutions or analytical solutions for the 7-DOF manipulator. The PSO algorithm is proposed to solve the redundant inverse kinematics problem of the 7-DOF robotic manipulators more efficiently. This PSO algorithm is shown to take advantage of powerful intelligent background and constructive cooperation between particles. Simulation results are conducted to illustrate the effectiveness and merit of the proposed methods.

This paper presents a parallel ACO (ant colony optimization) algorithm and its application to optimal motion controller design for omnidirectional mobile robots. Both parallel ACO (PACO) parameter tuner and motion controller are integrated in one FPGA (field programmable gate arrays) chip to efficiently construct an experimental omnidirectional mobile robot. The optimal parameters of the motion controller are obtained by minimizing the performance index using the proposed PACO algorithm. These optimal parameters are then employed in the PACO-based embedded motion controller to achieve trajectory tracking and stabilization with better performance. Experimental results are conducted to show the effectiveness and merit of the proposed PACO algorithm for omnidirectional mobile robots.

A 45-year-old man presented with a six-month history of progressive dyspnea with productive cough and wheezing. The patient was a heavy smoker and had a history of tongue cancer, hypertension, and asthma. Chest X-ray and computed tomography showed a mass lesion in the left hilar region and total collapse of the upper left lobe of the lung. Bronchoscopy revealed a whitish solid tumor obstructing the left upper lobe bronchus. Positron emission tomography showed increased tracer uptake in the lesion. A thoracoscopic lobectomy of the left upper lobe of the lung was performed. The final pathologic diagnosis was inflammatory myofibroblastic tumor.

This paper presents a polar-space optimal kinematic controller design based on ant colony optimization (ACO) computing method for omnidirectional mobile robots with three independent driving wheels equally spaced at 120 degrees from one another. The optimal control parameters are obtained by minimizing the performance index using the proposed ACO computing method. These optimal parameters are used in the ACO-based polar-space kinematic controller to obtain better performance for omnidirectional mobile robots to achieve both trajectory tracking and stabilization. Simulation results are conducted to show the effectiveness and merit of the proposed ACO-based polar-space kinematic controller for omnidirectional mobile robots.

This paper presents an optimal kinematic controller design based on ant colony optimization (ACO) computing method for omnidirectional mobile robots with three independent driving wheels equally spaced at 120 degrees from one another. The optimal control parameters are obtained by minimizing the performance index using the proposed ACO computing method. These optimal parameters are used in the ACO-based kinematic controller to obtain better performance for omnidirectional mobile robots to achieve both trajectory tracking and stabilization. Simulation results are conducted to show the effectiveness and merit of the proposed ACO-based kinematic controller for omnidirectional mobile robots.

This paper presents an efficient parallel elite genetic algorithm (PEGA) for global path planning of an omnidirectional mobile robot moving in a static environment expressed by a grid-based map. This efficient PEGA, consisting of two parallel EGAs along with a migration operator, is proposed for global path planning of the mobile robots. The PEGA takes advantages of maintaining better population diversity, inhibiting premature convergence and keeping parallelism than conventional GAs do. The generated collision-free path is optimal in the sense of the shortest distance. The pipelined hardware implementation of IP (Intellectual Property) core library on a field-programmable gate array (FPGA) chip is employed to significantly speedup the processing time. Furthermore, a soft-core processor and a real-time operating system (RTOS) are embedded into the same chip to perform the global path planning using hardware/software co-design technique and SoPC (System-on-a-Programmable-Chip) concept. The merit and performance of the proposed SoPC-based PEGA are illustrated by conducting several simulations and experiments.

This paper presents adaptive sliding-mode control methods for self-balancing and yaw rate control of a dynamically two-wheeled human transportation vehicle (HTV) with mass variations and system uncertainties. The proposed controllers aim to provide consistent driving performance for system uncertainties and different drivers whose weights cause parameter variations of the HTV. By decomposing the overall system into the yaw subsystems and the self-balancing subsystems with parameters variations with respect to different riders, two adaptive sliding mode controls are proposed to achieve self-balancing and yaw control. Numerical simulations and experimental results on different terrains show that the proposed adaptive sliding mode controllers are capable of achieving satisfactory control actions to steer the vehicle.

This paper develops methodologies and techniques for autonomous navigation of a tour-guide robot with a human-robot interaction system. The designed navigation system includes global localization, dynamic path planning, local goal-seeking, safe obstacle-avoidance, behavior fusion, and autonomous robot control. The RFID module for global pose initialization is presented based on the RSSI measurements, the proposed calibration method and least square method. With the gross initial robot pose, accurate robot pose tracking are achieved by fusing the RFID data and laser scanning measurements utilizing an extended Kalman filter. The global path is generated by dynamic programming method. The Petri-net model is employed to construct the event-driven logic control sequence from the present states of the robot and assigned tour missions. An operational scenario is used to show the effectiveness of the proposed autonomous navigation method.

This paper presents methodologies and techniques for multi-sensory fuzzy hybrid navigation of an active mobile robot assistant for the elderly people in known, cluttered and dynamic indoor environments. For self-localization, the geometric and topological representations are combined together to maintain the advantages of them and counteract their disadvantages. By using RFID system, the estimation of position hypothesis for similar regions in a known environment can be reduced. The global optimal path composed of via points is determined by using Dijkstra's dynamic programming approach. Fuzzy adaptive speed control law is designed to make the robot adapt to various users' speeds. Safe fuzzy hybrid navigation is achieved by fusing adaptive speed, goal-seeking and obstacle- avoidance from the sensing data of laser scanner and ultrasonic rangers. In addition, Experimental results are conducted to show the effectiveness and merits of the proposed methods.

This paper presents a kinematics trajectory planning of an omnidirectional mobile manipulator using DNA algorithm. Combining an omnidirectional mobile platform and an onboard object recognition device makes this manipulator can move to any desired posture and then catch the desired object easily. A DNA (Deoxyribonucleic acid) algorithm is proposed to find the near optimal point-to-point configuration of the mobile manipulator moving from one pose to another, and an integrated trajectory planning method is presented to obtain the motion trajectories for the mobile platform and all the joints of the manipulator. Computer simulations are conducted to show the feasibility of the proposed method. Experimental results are performed to verify the efficacy of the proposed methods.

Tumor size is an important prognostic factor in non-small cell lung cancer (NSCLC), but the American Joint Committee on Cancer staging system does not mandate a specific measurement method. Moreover, measuring fresh specimens and formalin-fixed specimens may yield disparate results. Our goal was to evaluate this disparity for stage I NSCLC.We enrolled 401 patients with stage I NSCLC who underwent surgical interventions and follow-up in our hospital between 1993 and 2002. Tumors invading visceral pleura, involving the main bronchus, or associated with atelectasis or obstructive pneumonitis were excluded. Tumor size was measured immediately after resection by surgeons and after formalin fixation by pathologists. Patients were assigned to one of three groups. Group 1 included 201 patients with tumors of 3 cm or less as indicated by both operation notes and pathology reports. Group 2 included 160 patients with tumors larger than 3 cm by both records. Group 3 included 40 patients with tumors larger than 3 cm according to operation notes but 3 cm or less according to pathology reports. Survival rates were compared.Mean follow-up was 58 months. Five-year survival was 70.1% in group 1, 49.1% in group 2, and 51.1% in group 3. As expected, there was a significant survival difference between groups 1 and 2 (p0.001); however, there was also a difference between groups 1 and 3 (p = 0.006).Formalin fixation may cause tumor shrinkage and migration from T2 to T1. For accurate tumor staging, size measurements should be performed immediately after resection instead of after formalin fixation. TNM staging should specify how to measure tumor size and the specimen status to be measured.

Objective Single-incision laparoscopic surgery had been proven effective for appendectomy, cholecystectomy, and inguinal hernia repair. However, single-incision thoracoscopic surgery (SITS) in primary spontaneous pneumothorax (PSP) has not been reported. Methods We prospectively enrolled 30 PSP patients who received thoracoscopic surgery in the division of Thoracic Surgery of China Medical University Hospital. Ten patients received SITS and 20 patients received traditional three-port thoracoscopic surgery. The operative time, blood loss, wound size, visual analog scale (VAS) pain score, and patient satisfaction score were compared. Results There was no significant difference in the operative time and blood loss between the two groups. However, the VAS pain scores were significantly better in the SITS group in first 24 hours after surgery. Patient satisfaction scores in the SITS group were also significantly better in the first 24 and 48 hours after operation. Conclusion Although three-port thoracoscopic surgery for PSP is well established, SITS results in better patient satisfaction and decreased postoperative pain in the treatment of PSP.