Accurate three-dimensional (3D) localization is critical for robust human-robot collaboration (HRC) in dynamic indoor environments. However, realizing high-precision localization in complex scenarios still faces challenges such as multipath effects, field-of-view occlusion, etc. To address these limitations, we propose Geo-LSTM, a geometry-constrained long short-term memory (LSTM) framework that integrates ultra- wideband (UWB) sensors, inertial measurement unit (IMU), and barometric pressure (BMP) sensors. First, a Simplified Geometric Localization (SGL) algorithm is proposed, which uses dual-BMP sensors and IMU sensor to obtain precise height information and utilizes the geometric relationships between the UWB tag and anchors to compute an initial location estimate, serving as a priori input for the Geo-LSTM network. This Geo-LSTM algorithm then incorporates multi-source geometric information to extract time-series features from the UWB ranging data and the tag's a priori location, further enhancing 3D localization accuracy. The experimental results from the cluttered indoor environments, including real-world HRC tasks with occlusions, show that the Geo-LSTM algorithm achieves an average 3D localization root mean square error (RMSE) of 0.103 m, representing improvements of 38.60% and 31.20% over the weighted least squares (WLS) method and the range-based LSTM algorithm, respectively. These results demonstrate Geo-LSTM's potential for reliable multi-sensor 3D localization in HRC applications.

In this article, we introduce an assistive device for the elbow joint that is easily wearable, lightweight, and cable driven using a series elastic actuation principle implemented by an endless-shape elastic bungee element. This type of elastic element is selected due to its intrinsic damping, and compliant features similar to human muscles, which provide mechanical filtering against dynamic uncertainties such as impulsive forces, and oscillated movements because of possible controller issues. Furthermore, a spool system is designed targeting to maximize the transmission of the generated elastic force to the wearer while avoiding multiple coiling for the cable wrap/release operation. The design parameters of the device are selected through design and optimization studies. The manufactured actuator's performance is validated on a rigid link under position and force control modes. To demonstrate the effectiveness of the elastic element, we conducted actuator validation tests with and without bungee cases. The results show that while the bungee-integrated setup can transfer the generated elastic force to the link without oscillation at different frequency movements (0.05–0.16 Hz), the bungee-excluded setup performs unstable movements under the same control gains, producing 50.74% more vibrations detected through fast Fourier transform analysis. In addition, to test the system under aggressive conditions, we applied impacts to it, and the results indicate that the damping ratio index of the bungee incorporated system is 56.14% more than that of without bungee case, demonstrating the intrinsic safe behavior of the mechanism. Finally, the device is assessed on six human subjects (different arm weights and dimensions) in a simulated industrial painting task with 5 min duration, with an average <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$22.3^{\circ }/\text{s}$</tex-math></inline-formula> elbow velocity under force control. The average effort reduction on biceps muscle among the subjects is measured 64.42% with respect to the without assistance test.

Accurate three-dimensional (3D) localization is critical for robust human-robot collaboration (HRC) in dynamic indoor environments. However, realizing high-precision localization in complex scenarios still faces challenges such as multipath effects, field-of-view occlusion, etc. To address these limitations, we propose Geo-LSTM, a geometry-constrained long short-term memory (LSTM) framework that integrates ultra- wideband (UWB) sensors, inertial measurement unit (IMU), and barometric pressure (BMP) sensors. First, a Simplified Geometric Localization (SGL) algorithm is proposed, which uses dual-BMP sensors and IMU sensor to obtain precise height information and utilizes the geometric relationships between the UWB tag and anchors to compute an initial location estimate, serving as a priori input for the Geo-LSTM network. This Geo-LSTM algorithm then incorporates multi-source geometric information to extract time-series features from the UWB ranging data and the tag's a priori location, further enhancing 3D localization accuracy. The experimental results from the cluttered indoor environments, including real-world HRC tasks with occlusions, show that the Geo-LSTM algorithm achieves an average 3D localization root mean square error (RMSE) of 0.103 m, representing improvements of 38.60% and 31.20% over the weighted least squares (WLS) method and the range-based LSTM algorithm, respectively. These results demonstrate Geo-LSTM's potential for reliable multi-sensor 3D localization in HRC applications.

In this article, we introduce an assistive device for the elbow joint that is easily wearable, lightweight, and cable driven using a series elastic actuation principle implemented by an endless-shape elastic bungee element. This type of elastic element is selected due to its intrinsic damping, and compliant features similar to human muscles, which provide mechanical filtering against dynamic uncertainties such as impulsive forces, and oscillated movements because of possible controller issues. Furthermore, a spool system is designed targeting to maximize the transmission of the generated elastic force to the wearer while avoiding multiple coiling for the cable wrap/release operation. The design parameters of the device are selected through design and optimization studies. The manufactured actuator's performance is validated on a rigid link under position and force control modes. To demonstrate the effectiveness of the elastic element, we conducted actuator validation tests with and without bungee cases. The results show that while the bungee-integrated setup can transfer the generated elastic force to the link without oscillation at different frequency movements (0.05–0.16 Hz), the bungee-excluded setup performs unstable movements under the same control gains, producing 50.74% more vibrations detected through fast Fourier transform analysis. In addition, to test the system under aggressive conditions, we applied impacts to it, and the results indicate that the damping ratio index of the bungee incorporated system is 56.14% more than that of without bungee case, demonstrating the intrinsic safe behavior of the mechanism. Finally, the device is assessed on six human subjects (different arm weights and dimensions) in a simulated industrial painting task with 5 min duration, with an average <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$22.3^{\circ }/\text{s}$</tex-math></inline-formula> elbow velocity under force control. The average effort reduction on biceps muscle among the subjects is measured 64.42% with respect to the without assistance test.

Prostate cancer (PC) is the second leading cause of cancer-related death among men. Treatment of PC becomes difficult after progression because PC that used to be androgen-dependent becomes androgen-independent prostate cancer (AIPC). Veratramine, an alkaloid extracted from the root of the <i>Veratrum</i> genus, has recently been reported to have anticancer effects that work against various cancers; however, its anticancer effects and the underlying mechanism of action in PC remain unknown. We investigated the anticancer effects of veratramine on AIPC using PC3 and DU145 cell lines, as well as a xenograft mouse model. The antitumor effects of veratramine were evaluated using the CCK-8, anchorage-independent colony formation, trans-well, wound healing assays, and flow cytometry in AIPC cell lines. Microarray and proteomics analyses were performed to investigate the differentially expressed genes and proteins induced by veratramine in AIPC cells. A xenograft mouse model was used to confirm the therapeutic response and <i>in vivo</i> efficacy of veratramine. Veratramine dose dependently reduced the proliferation of cancer cells both <i>in vitro</i> and <i>in vivo</i>. Moreover, veratramine treatment effectively suppressed the migration and invasion of PC cells. The immunoblot analysis revealed that veratramine significantly downregulated Cdk4/6 and cyclin D1 via the ATM/ATR and Akt pathways, both of which induce a DNA damage response that eventually leads to G1 phase arrest. In this study, we discovered that veratramine exerted antitumor effects on AIPC cells. We demonstrated that veratramine significantly inhibited the proliferation of cancer cells via G0/G1 phase arrest induced by the ATM/ATR and Akt pathways. These results suggest that veratramine is a promising natural therapeutic agent for AIPC.

Immortalized EF-MSCs exhibited significantly enhanced proliferative capacity, retained adipogenic potential, and upregulated the expression of DNA replication pathway components.

Variable impedance control is a control strategy widely used in physical human-robot collaboration (pHRC) and physical human-robot interaction (pHRI). Variable stiffness and damping parameters improve adaptability to changing environments and enhance safety in human-robot interaction. However, these adaptive parameters can compromise the stability of the system without proper management, particularly in dynamic environments. To address this, we propose a real-time parameter prediction method for variable impedance control using model predictive control (MPC) with Control Lyapunov Function (CLF). Unlike the method that sets the terminal constraint as the equilibrium position, the proposed method guarantees system stability even when parameters change or external disturbances occur, ensuring safe and adaptive robot behavior. Moreover, the infeasibility issue is resolved by applying CLF instead of relying on the equilibrium position. Furthermore, considering stability throughout the prediction horizon, the stability of the system is strictly guaranteed. The proposed method was validated through comparative experiments with the method that sets the terminal constraint as the equilibrium position in both simulations and real-world environments using the Franka Emika Panda robot. Through these experiments, the proposed controller demonstrated a significant reduction in parameter computation time, achieving approximately 97.13% and 96.20% faster computation in simulation tests compared to conventional method, while consistently ensuring stability under various disturbances including human interaction, tool vibration, and contact loss scenarios.

This paper presents a human-centric proactive ergonomic safety framework for humanhumanoid collaboration, aiming to ensure that human motion remains physically safe and ergonomically compliant throughout cooperative tasks. A vector auto-regressive model predicts short-term human joint trajectories based on repetitive task data, and the predicted motion is tracked by a virtual human model. Control Barrier Functions enforce ergonomic constraints in real time, including stance stability via the Center of Pressure and effort alignment via the force manipulability ellipsoid. Simulations of collaborative lifting tasks demonstrate that the framework effectively constrains predicted motions within an ergonomic safety set. Quantitative results show that average overloading joint torque was reduced by 24.6 % at the shoulder, and total biomechanical effort decreased by 48.1 % and 60.8 % at the shoulder and elbow, respectively. These reductions highlight the potential of our framework to enable humanoid systems that proactively adapt to human motion while maintaining ergonomic safety in physically collaborative tasks.

PRPF4 knockdown inhibits GBM progression by reducing p38 MAPK and ERK signaling cascade with metabolic alterations. Targeting PRPF4 may offer novel therapeutic strategies for GBM treatment.