Matthew Buell, Brian Hu

Canadian Journal of Urology, Vol.31, No.5, pp. 12026-12029, 2024

Abstract Radical cystectomy is a preferred treatment for muscle invasive bladder cancer. Despite known complications, rapid onset, severe hyperkalemia necessitating abortion of surgery has not been reported. In this case report, a patient with end stage renal disease (ESRD) undergoing attempted cystectomy developed severe intraoperative hyperkalemia and acidosis that led to abortion of surgery and transfer to the medical intensive care unit for emergent hemodialysis. The multifactorial etiology was related to respiratory acidosis, ESRD, patient positioning, clipping of ureters, and body habitus, as well as an idiopathic element. Knowledge of hyperkalemia etiologies can assist in diagnosis More >

Braden Rolig¹, James A. Brown²

Canadian Journal of Urology, Vol.31, No.5, pp. 12019-12021, 2024

Abstract The Hem-o-lok Weck clip is part of a polymer locking ligation system often employed for hemostasis in surgical practices. Its use is routine in a wide array of surgical subspecialties. Surgeons have limited options in removing these clips when they are aberrantly positioned.
Herein, we describe a novel, cost-effective approach for removing a Hem-o-lok clip using standard robotic instruments. This simple approach will allow surgeons to remove a Hem-o-lok clip precisely and quickly if it is not adequately placed.
During a routine robotic-assisted laparoscopic prostatectomy a Hem-o-lok Weck clip was noted to be in juxtaposition to… More >

Stephanie Aron, Anthony Galvez, Ryan Nasseri, Susana Berrios, Tyler Sheetz

Canadian Journal of Urology, Vol.31, No.6, pp. 12077-12080, 2024

Abstract Nephrolithiasis is one of the most common indications for surgery in patients with a horseshoe kidney. Robotic assisted surgery has become a staple in urologic practice, yet its application in stone management is largely undefined. We present a patient with a horseshoe kidney, who underwent a robotic-assisted laparoscopic pyelolithotomy (RPL) to treat a 3 cm stone burden. This procedure allowed for safe access that could not be obtained with percutaneous nephrolithotomy (PCNL) and stone removal without fragmentation, which would have been challenging with traditional laparoscopy. We advocate for the use of robotic-assisted laparoscopic pyelolithotomy in More >

Alex J. Xu¹, Jeffery S. Lin¹, Po Yen Chen², Samuel Carbunaru¹, Yeonsoo S. Lee³, Lee C. Zhao¹

Canadian Journal of Urology, Vol.31, No.6, pp. 12072-12076, 2024

Abstract Introduction: We describe a method of robotic ureterocalicostomy (RALUC) with the Da Vinci Single Port (SP) platform and present clinical outcomes in our cohort of patients.
Materials and methods: We retrospectively reviewed all patients undergoing RALUC with the SP platform in a single-institution, IRB-approved database between 2020 2023. Demographics, preoperative, intraoperative, and postoperative outcomes were collated. Surgical success was defined as freedom from hardware, avoidance of additional surgical reconstruction, and no obstruction on follow up imaging/ureteroscopy.
An incision is made 1/3rd the distance from anterior superior iliac spine to the umbilicus. The retroperitoneal space is entered and SP… More >

Tianyu Chen¹, Yifan Wang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.31, No.4, pp. 1-1, 2024, DOI:10.32604/icces.2024.011272

Abstract Biological organisms often possess remarkable multifunctionality through intricate structures, such as the concurrent shape-morphing and stiffness-variation in octopus. Soft robots, which are inspired by natural creatures, usually require the integration of separate modules to achieve these various functions. As a result, the whole structure is cumbersome and the control system is complex, often involving multiple control loops to finish the required task. Here, inspired by the scaly creatures in nature such as pangolins and fish, we develop a robotic structure that can vary stiffness and change shape simultaneously in a highly-integrated compact body. The scale-inspired… More >

Jungyeon Kim¹, Lequn Chen¹, Seung Ki Moon^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.31, No.3, pp. 1-1, 2024, DOI:10.32604/icces.2024.012511

Abstract Robotic Laser-Directed Energy Deposition (L-DED) offers significant advantages in terms of workplace size and kinematic flexibility for part fabrication. However, its potential is hindered by challenges such as toolpath precision and speed inconsistency compared to traditional CNC machines. These limitations critically affect melt pool dynamics, temperature consistency, and ultimately, the geometric integrity of fabricated parts, areas that are still not thoroughly understood or quantified.
This preliminary research aims to investigate the impact of these inaccuracies on melt pool morphology and part quality, utilizing in-situ collected speed/position data with a digital twin model, notably the Eagar-Tsai… More >

Jiacheng Ji¹, Boyu Zhang¹, Hongying Zhang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.31, No.3, pp. 1-3, 2024, DOI:10.32604/icces.2024.012193

Abstract Tensegrity metamaterial, well-known for its unique synergy between compressed bars and tensile strings, enable a remarkable deformation and distinctive vibration characteristic [1]. These materials are increasingly recognized for their potential to facilitate advanced locomotion in soft robots. Tensegrity metamaterials, primarily constructed manually, have found applications in large-scale sectors like architecture and aerospace engineering [2]. However, their integration into soft robots necessitates scaling down to a centimeter scale, presenting challenges in automatic prototyping and kinematic simulation to guide the design process [3].
Recent advancements advocate for 3D-printed tensegrity structures to achieve integrated, one-piece systems [3,4]. Yet,… More >

Jiazhao Huang¹, Xiaoying Qi¹, Chu Long Tham¹, Hang Li Seet¹, Sharon Mui Ling Nai¹, David William Rosen^1,2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.31, No.3, pp. 1-2, 2024, DOI:10.32604/icces.2024.012040

Abstract The emergence of 4D printing introduces stimuli-responsive, shape-changing capabilities through additive manufacturing (AM) and smart materials, has advanced the field of soft robotics. However, there are currently lack of methods or tools that capable of aiding in the generative design of 4D AM structures. The current generative design procedure for 4D AM structures often lacks transferability among various structures due to limited understanding of shape memory material behaviors for soft robotics. To develop such a digital library, investigation of fundamental elements, such as material properties of shape memory materials, geometry parameters of design primitives, and… More >

J. M. Tan¹, A. Chooi², C. Chen¹, A. Castillo Ugalde², T. Stalin², T. Calais², P. Valdivia y Alvarado^1,2,3,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.31, No.3, pp. 1-1, 2024, DOI:10.32604/icces.2024.011827

Abstract In this study two novel forms of textile-assisted direct ink writing (DIW) of room temperature vulcanised (RTV) silicones were explored: Silicone DIW on spandex fabric, and Silicone DIW on dissolvable fabrics. These processes were evaluated by incorporating resulting components into 4 soft robotic devices: impact resistant elbow pads, a soft passive suction cup gripper, and two fiber embedded inflatable tendril-like soft grippers. More >

Yameng Yin¹, Lieping Zhang^2,*, Xiaoxu Shi¹, Yilin Wang³, Jiansheng Peng⁴, Jianchu Zou⁴

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2769-2790, 2024, DOI:10.32604/cmc.2024.056791 - 18 November 2024

Abstract By integrating deep neural networks with reinforcement learning, the Double Deep Q Network (DDQN) algorithm overcomes the limitations of Q-learning in handling continuous spaces and is widely applied in the path planning of mobile robots. However, the traditional DDQN algorithm suffers from sparse rewards and inefficient utilization of high-quality data. Targeting those problems, an improved DDQN algorithm based on average Q-value estimation and reward redistribution was proposed. First, to enhance the precision of the target Q-value, the average of multiple previously learned Q-values from the target Q network is used to replace the single Q-value… More >