Kai-Jung Chen

Viscoelastic mechanical characteristics of the liver play a crucial role in fibrosis and cancer progression. Despite the evolution of liver fibrosis, as a pivotal step toward cirrhosis and hepatoma, originates from molecular dysfunctions and further extends to cellular and tissue levels, current clinical assessment is still largely based on tissue level stiffness. This study introduces a novel multiscale viscoelastic signature-based machine learning model for liver fibrosis evaluation. Utilizing a hybrid hierarchical theory-microrheology approach, we unveil a universal two-stage power-law rheology capturing dynamic mechanical variations in diverse liver conditions. Our analysis of multiscale viscoelastic disparities through a self-similar hierarchical theoretical framework enhances our understanding of fibrosis evolution. Distinct mechanical signatures observed across liver states provide valuable insights for assessing fibrotic individuals and treatment responses at different spatial scales. Furthermore, we propose a series of threshold values for each marker in the diagnosis of liver fibrosis. Notably, based on these new viscoelastic signatures, we eventually propose a Light Gradient Boosting Machine (LightGBM) diagnostic model that outperforms conventional stiffness-based classification, offering superior diagnostic precision for fibrotic treatment. This research contributes to the growing knowledge of viscoelastic characteristics in soft tissues and holds promise for innovative diagnostic strategies in various diseases and cancers.

Accurate diagnosis and treatment assessment of liver fibrosis face significant challenges, including inherent limitations in current techniques like sampling errors and inter-observer variability. Addressing this, our study introduces a novel machine learning (ML) framework, which integrates light gradient boosting machine and multivariate imputation by chained equations to enhance liver status assessment using biomechanical markers. Building upon our previously established multiscale mechanical characteristics in fibrotic and treated livers, this framework employs Gaussian Bayesian optimization for post-imputation, significantly improving classification performance. Our findings indicate a marked increase in the precision of liver fibrosis diagnosis and provide a novel, quantitative approach for assessing fibrosis treatment. This innovative combination of multiscale biomechanical markers with advanced ML algorithms represents a transformative step in liver disease diagnostics and treatment evaluation, with potential implications for other areas in medical diagnostics.

Three-dimensional printing is a non-conventional additive manufacturing process. It is different from the conventional subtractive manufacturing process. It offers exceptional rapid prototyping capabilities and results that conventional subtractive manufacturing methods cannot attain, especially in applications involving curved or intricately shaped components. Despite its advantages, metal 3D printing will face porosity, warpage, and surface roughness issues. These issues will affect the future practical application of the parts indirectly, for example, by affecting the structural strength and the parts’ assembly capability. Therefore, this study compares the qualities of the warpage, weight, and surface roughness after milling and grinding processes for the same material (316L stainless steel) between rolled steel and 3D-printed steel. The experimental results show that 3D-printed parts are approximately 13% to 14% lighter than rolled steel. The surface roughness performance of 3D-printed steel is better than that of rolled steel for the same material after milling or grinding processing. The hardness of the 3D-printed steel is better than that of the rolled steel. This research verifies that 3D additive manufacturing can use surface processing to optimize surface performance and achieve the functions of lightness and hardness.

3D printing is a non-traditional additive manufacturing process. It is different from the traditional subtractive manufacturing process. It offers exceptional rapid prototyping capabilities and results that traditional subtractive manufacturing methods cannot attain, especially in applications involving curved or intricately shaped components. Despite its advantages, metal 3D printing will face porosity, warpage, and surface roughness issues. These issues will affect the future practical application of the parts indirectly, for example, the structural strength and the parts assembly ca-pability. Therefore, this study compares the qualities of the warpage, weight, and surface rough-ness after milling and grinding processes under the same materials (316L stainless steel) between general rolled steel and 3D additive steel. Experimental results show that 3D printing parts are approximately 13% to 14% lighter than the general rolled steel. The surface roughness performance of 3D printing steel is better than general rolled steel under the same material after milling or grinding processing. The hardness of the 3D printing steel is better than that of the gen-eral rolled steel. The research verifies that 3D additive manufacturing can use surface processing to optimize surface performance and achieve the functions of lightness and hardness.

For heart disease patients with an implanted artificial pacemaker, monitoring the operational status of the pacemaker is a crucial and challenging issue. This study aims to design a transcutaneous optic telemetry (TOT) system that transmits light signals from a human body through the skin to a receiving circuit and carries pacemaker status information via the light signals to achieve transcutaneous telemetry. Petri net method is used to analyze the simulated pacemaker. Petri nets are constructed to illustrate the process of the pacemaker. Furthermore, the Petri nets for the process with four checkpoints (CPs) deployed on the pacemaker are also constructed. The TOT system uses near-infrared signals generated by a light-emitting diode as a transmission medium, and the pork skin animal model is used to validate the TOT system’s feasibility and efficiency. The correct sequence of CPs determines the normal state of the pacemaker, and the information from these CPs is transmitted in vitro for interpretation through the TOT system. This study designed and implemented the TOT system. Experiments showed that the TOT system’s design is effective in transmitting the CPs information through the pigskin layer without any significant interference. The results proved that the TOT system can transmit CPs information outside the body to achieve the transcutaneous telemetry diagnosis of the pacemaker. This study provides an alternative means to surgical operation for implanted pacemakers examination.

Tungsten carbide (WC) has been widely utilized in recent years in the hardware, mechanical, and chemical industries and in national defense because of its high hardness, anti-wear, low temperature, and anti-corrosion properties. However, using it for grinding is also challenging because the WC material has high hardness and brittle characteristics. The typical hub of a diamond wheel is made of steel. In high-speed grinding, the steel hub of the diamond wheel is subjected to gravity and centrifugal forces, which cause grinding wheel vibration, poor workpiece processing quality, and a short machine life. Therefore, this study used a carbon-fiber-reinforced thermoplastic (CFRP) hub to replace the steel hub when grinding the WC workpiece. It aimed to investigate methods to reduce oscillation, improve chip efficiency, and increase accuracy in the WC workpiece. The research results demonstrated that using a CFRP hub in the grinding wheel can reduce the oscillation when the peripheral speed of the grinding wheel is at 20–100 m/s. Additionally, the surface roughness average (Ra) of the workpiece can be reduced to 3.2–25.4% and the ten-point height of irregularities (Rz) can be reduced to 18.9–44% compared to using a steel hub in the grinding wheel.

This paper aims to design a one-wheeled robot as regards its pitch freedom and balance control on the one hand and to assess the application feasibility of the GM (1,1) swing estimation controller on the other. System control focuses mainly on one-wheeled robot stability, body swings in position, and speed control. Mathematical modeling and GM (1,1) prediction control are under investigation. The mathematical modeling is firstly conducted through referencing to the Newtonian mechanics and the Lagrange equation, from which the robot transfer function and state-space differential equation are derived. Next, the linear quadratic regulator is applied as the control rule at the balance point. Applying GM (1,1) to assess the robot gyro signal at a dynamic state is a discussion. Next, model reference estimation control is processed, and a mathematical model of the balance control method is completed. Finally, a simulation is conducted to verify the feasibility of the GM (1,1) estimation reference model. The linear quadratic regulator, which is credited with tenacity, can provide pitch swing and balance control of the one-wheeled robot.