Search Results (604)

Background and Objectives: Because of its consistently high stone-free rates (SFRs), percutaneous nephrolithotomy (PCNL) continues to be the first-line treatment for renal stones larger than 20 mm. Standard 24 to 30 Fr access tracts, however, are linked to access-related morbidity, such as bleeding, pain, and extended hospital stays. These restrictions have led to progressive tract miniaturization and the development of mini-PCNL, ultra-mini PCNL, and micro-PCN techniques. Materials and Methods: We performed a narrative review of studies published through January 2026 using PubMed and Google Scholar. Search terms included percutaneous nephrolithotomy, mini-PCNL, ultra-mini PCNL, micro-PCNL, and vacuum-assisted PCNL. Original studies, systematic reviews, and meta-analyses reporting clinical outcomes, complications, and advancements were selected, whereas conference abstracts, non-English papers, and articles without accessible full text were excluded. Results: Across randomized trials, miniaturized PCNL generally preserves efficacy when patients are selected appropriately. Across randomized trials and meta-analyses, miniaturized PCNL achieved stone-free rates comparable to standard PCNL (typically ~80–90% for stones ≤20 mm and similar rates in selected stones >2 cm), while demonstrating lower hemoglobin decrease (mean difference approximately −0.6 to −1.0 g/dL), reduced transfusion rates, and shorter hospital stays, at the cost of longer operative time (mean difference ~8–12 min). On the other hand, operative time may increase, and smaller working channels can make visualization and fragment evacuation more demanding as stone burden rises. Raised intrarenal pressure is a recurring safety issue because it may increase infectious risk unless drainage is actively managed. Recent innovations aim to address these limitations, including vacuum-assisted access sheaths, pressure-controlled irrigation, improved laser and lithotripsy platforms, image-fusion guidance, navigation systems, and robotic assistance. Conclusions: PCNL now spans a spectrum of tract sizes rather than a single standard approach. When chosen appropriately and performed with attention to pressure control and fragment evacuation, miniaturized PCNL can reduce morbidity without sacrificing stone clearance. Future advancements in percutaneous stone surgery are more likely to rely on integrated technological solutions that improve accuracy, safety, and repeatability than on additional tract size reduction. Full article

This paper presents initial developments towards a high-frequency condition monitoring framework designed for Autonomous Mobile Robots (AMRs) in Smart Factory environments. The proposed approach focuses on data acquisition and edge-level processing at the ultrasound range specifically (>20 kHz), using Micro-Electro-Mechanical System (MEMS) sensors. The system integrates real-time data acquisition, embedded fixed-point frequency-domain processing via a 1024-point FFT, and the integration of Industrial Internet-of-Things (IIoT) infrastructure based on the TIG (Telegraf, InfluxDB, and Grafana) stack, for data aggregation and remote visualization. To ensure timing precision at a sampling rate of 160 kHz, a software-based calibration routine is implemented to compensate for microcontroller overhead. Furthermore, the architecture’s alignment with IEEE 1451 principles is discussed to support interoperable and scalable sensor integration. Experimental results validate the reliable acquisition and processing of ultrasonic signals up to 80 kHz using controlled acoustic sources. This work provides a foundational infrastructure for condition-based monitoring, enabling future development of automated anomaly detection for mechanical components, such as bearings, which exhibit early-stage fault signatures in the ultrasonic spectrum. Full article

Underground wine cellars represent a fragile form of cultural heritage, where long-term microclimatic imbalance can lead to material degradation, structural instability, and internal collapses. High humidity, limited ventilation, and the difficulty of access complicate both diagnosis and conservation. This study presents preliminary results from a preventive monitoring strategy applied to the underground wine cellars of Baltanás (Palencia, Spain), focusing on temperature, relative humidity, wall moisture content, and ventilation as key drivers of deterioration. A wireless network of commercial temperature–humidity sensors, wall moisture probes, and airflow sensors was deployed in four sections of a representative cellar over a monitoring period exceeding two years. In addition, mobile monitoring was performed using a quadruped robot equipped with a rotating environmental sensing module, enabling measurements in confined and unstable areas. Results reveal strong thermal inertia, persistently high relative humidity frequently approaching saturation, low and intermittent natural ventilation, and sustained internal wall moisture. These conditions are consistent with observed material decay and internal landslides. The monitoring with quadruped robot proved particularly valuable for identifying localized humidity pockets and stagnant air zones beyond the reach of fixed sensors. The study demonstrates how different solutions for monitoring can support preventive conservation strategies for subterranean heritage, providing a scalable framework for early risk detection and informed management decisions. Full article

Interface interaction mechanics analysis is of great significance for robot-assisted insertion surgery in minimally invasive surgery and therapy. Previous work indicates that the accurate modeling of soft tissue puncture forces plays a crucial role in surgical planning, robotic needle insertion, and biomechanical simulation, which can give insights useful for physicians to guide and operate assisted robots. The objective of this study is to develop a dynamic multi-component force model that integrates cutting force, stiffness resistance, and frictional interaction to characterize needle–soft tissue interaction during puncture. A dynamic force model is proposed, and a lateral periodic disturbance mechanism is introduced into the simulation framework in order to enhance the robustness and realism of the model under micro-manipulation scenarios. The model has been validated using a series of controlled puncture experiments on porcine liver and renal tissues under varying insertion angles (15°, 30°, 45°) and speeds (0.5 mm/s, 1.5 mm/s, 2.5 mm/s). Corresponding finite element simulations were also conducted using ANSYS software. The agreement between simulation and experiment has been quantitatively evaluated by comparing force–depth and force–time curves, and the statistical significance of the impact of angle and speed on puncture forces has been assessed using ANOVA and Tukey’s HSD tests. Quantitative comparison demonstrated strong consistency, with the optimal case reaching a coefficient of determination (R²) value of 0.96 and Root Mean Square Error (RMSE) below 0.13 N after incorporating a 0.05 mm lateral perturbation. Statistical analysis confirmed the impact of angle and speed on puncture force responses (p < 0.05). Furthermore, comparative analysis revealed that porcine liver exhibits more consistent biomechanical behavior than renal tissue, particularly under perturbation-enhanced simulation. This study successfully establishes a dynamic multi-component force model for soft tissue puncture, validated with high fidelity against experimental data. The incorporated lateral disturbance mechanism enhanced the model’s realism. This work can provide a reliable foundation for the future design of intelligent robot-assisted puncture systems and high-fidelity simulation-based training platforms. Full article

Developing new quality productive forces represents a core strategy for steering China’s path to modernization and shaping new competitive advantages for the nation. As a leading technology in the new round of technological revolution and industrial transformation, artificial intelligence (AI) serves as a key engine for fostering new quality productive forces. Utilizing panel data from China’s A-share listed manufacturing firms (2012–2024), this study employs the penetration rate of industrial robots to proxy for AI development levels and the entropy method to measure new quality productive forces. From the perspective of supply chain resilience, ordinary least squares (OLS) and instrumental variable (IV) methods are employed to examine the impact of AI on enterprise new quality productive forces and its underlying mechanisms. The findings indicate that AI significantly enhances corporate new quality productive forces, a conclusion that remains robust after addressing potential endogeneity and conducting robustness checks. Mediation analysis reveals that AI reinforces corporate supply chain resilience by improving supply chain efficiency and strengthening supply chain discourse power, which in turn drives the enhancement of corporate new quality productive forces. Heterogeneity analysis indicates that the impact of AI on corporate new quality productive forces is heterogeneous, with particularly pronounced effects observed in firms with higher innovation levels, state-owned enterprises, and firms located in western China. This study contributes new evidence from a supply chain resilience perspective to understand the micro-level pathways through which AI empowers new quality productive forces, and offers targeted policy and managerial recommendations to foster the sustainable development of the manufacturing sector. Full article

Flapping-wing micro air vehicles (FWMAVs) have gained increasing attention due to their manoeuvrability, low acoustic signature, and suitability for confined or cluttered environments. Despite considerable progress, existing reviews treat actuation mechanisms and mechanical transmissions in isolation, leaving a gap in the comparative assessment of pulley-based and alternative flapping systems. This study provides a comprehensive and quantitative synthesis of the literature on FWMAV mechanical architectures, with particular emphasis on pulley-driven transmissions used in platforms such as the Nano Hummingbird and the Robotic Hummingbird. A structured review methodology was applied, incorporating a systematic database search, extraction of performance parameters, and cross-platform comparison of flapping frequency, lift generation, power consumption, lift-to-weight ratio, and material choices. The analysis identifies consistent scaling trends across motor-driven, piezoelectric, and hybrid actuation families and highlights the efficiency and stroke-amplification advantages of pulley-based mechanisms for centimetre-scale hovering MAVs. The review also identifies unresolved challenges, including durability of transmission materials, standardisation of performance metrics, and the need for high-fidelity aerodynamic characterisation. Overall, this work offers an integrated framework for understanding the trade-offs among actuation and transmission strategies and provides a roadmap to guide future research and the practical development of next-generation FWMAVs. Full article

In this research, an innovative scheme to generate heterogeneous acoustofluidic distributions in various pseudo-Sierpiński-carpet-shaped chambers with different filling fractions and cross-sectional configurations has been proposed and calculated for topographical manipulation of large-scale micro-particles. All of the structural components positioned in the pseudo-fractal chambers are symmetrically distributed in space, and all ultrasonic radiation surfaces hold the unified settings of input frequency point, oscillation amplitude, and initial phase distribution along their respective normal directions. A large number of fascinating acoustofluidic patterns can be generated in the originally-static pseudo-Sierpiński-carpet-shaped chambers at different recursion levels without complicated vibration parameter modulation. The simulation results of acoustofluidic distributions and particle motion trajectories under different radiation surface arrangements further demonstrate the manipulation performance of these specially designed devices, and indicate that controllable spatial partitioning and intensity modulation of the acoustofluidic field can be achieved by adjusting the hierarchical order, cross-sectional configuration and combination mode of the radiation surfaces. Unlike the existing device construction method of miniaturized microfluidic systems, the artificial introduction of fractal elements like Sierpiński carpet/triangle, Koch snowflake, Mandelbrot set, Pythagoras tree, etc., can provide extraordinary perspectives and expand the application range of the acoustofluidic effect, which also makes ultrasonic micro/nano-scale manipulation technology more abundant and diversified. This exploratory research indicates the potential possibility of applying fractal structures as alternative component parts to purposefully customize acoustofluidic distributions for the further research of patterned manipulation of bio-organisms and navigation of micro-robot swarms in brand new ways that cannot be achieved through traditional methods. Full article

Accurate braking-distance prediction for heavy-duty multi-axle trucks remains challenging due to the large gross vehicle weight, tandem-axle interactions, and strong transient load transfer during emergency braking. Recent studies on tire–road friction estimation, commercial-vehicle braking control (EBS/AEBS), and weigh-in-motion (WIM) sensing have highlighted that unmeasured vertical-load dynamics and time-varying friction are key sources of prediction uncertainty. To address these limitations, this study proposes an integrated sensing–simulation–AI framework that combines real-time axle-load estimation, full-scale robotic braking tests, fused road-friction sensing, and physics-consistent machine-learning modeling. A micro-electro-mechanical systems (MEMS)-based load-angle sensor was installed on the leaf-spring panel linking tandem axles, enabling the continuous estimation of dynamic vertical loads via a polynomial calibration model. Full-scale on-road braking tests were conducted at 40–60 km/h under systematically varied payloads (0–15.5 t) using an actuator-based braking robot to eliminate driver variability. A forward-looking optical friction module was synchronized with dynamic axle-load estimates and deceleration signals, and additional scenarios generated in a commercial ASM environment expanded the operational domain across a broader range of friction, grade, and loading conditions. A gradient-boosting regression model trained on the hybrid dataset reproduced measured stopping distances with a mean absolute error (MAE) of 1.58 m and a mean absolute percentage error (MAPE) of 2.46%, with most predictions falling within ±5 m across all test conditions. The results indicate that incorporating real-time dynamic axle-load sensing together with fused friction estimation improves braking-distance prediction compared with static-load assumptions and purely kinematic formulations. The proposed load-aware framework provides a scalable basis for advanced driver-assistance functions, autonomous emergency braking for heavy trucks, and infrastructure-integrated freight safety management. All full-scale braking tests were carried out at approximately 60% of the nominal service-brake pressure, representing non-panic but moderately severe braking conditions, and the proposed model is designed to accurately predict the resulting stopping distance under this prescribed braking regime rather than to minimize the absolute stopping distance itself. Full article

The escalating incidence of knee cartilage damage underscores the need for improved treatment approaches, while the present modalities are constrained by limitations. This paper presents a novel mobile device for manipulating microrobots to deliver therapeutic agents to damaged knee cartilage areas using external magnetic fields. A curved telescopic mechanism, proposed for the first time, enables effective navigation along complex human body contours, thereby overcoming the limitations of conventional linear approaches. The device is equipped with a precise closed-loop controller. A model-based optimization of magnetic end-effector position and orientation is developed to ensure high targeting efficiency and repeatability. The system performances are verified in a human-sized phantom model, demonstrating the superior targeting accuracy, and achieving outcomes exceeding those of conventional systems. These findings underscore the system’s strong potential for clinical translation in regenerative knee therapies, offering a portable, low-cost, and effective alternative to existing methods. Full article

Fiber actuators underpin soft robots, artificial muscles, and smart textiles. A persistent bottleneck is the fabrication of monodomain liquid crystal elastomer (LCE) microfibers with narrow size distributions while preserving axial alignment. This work establishes a melt-centrifugal spinning (MCS) route with two-step UV fixation that separates flow-induced alignment from network crosslinking. High-speed rotation creates a long extensional jet; an obliquely incident, on-the-fly UV dose at touchdown locks the director, and a post-cure consolidates the network. The obtained LCE microfiber can achieve large reversible contraction (L/L₀ = 0.56), lift a weight, and trigger the tweezers. The method produces a new approach for the fabrication of device-ready LCE actuators, establishes a general design principle for diameter control via curing sequence, and opens a practical path toward artificial muscles and flexible micro robotics. Full article

Underwater optical images often exhibit severe color distortion, weak texture, and uneven illumination due to light absorption and scattering in water. These issues result in unstable feature detection and inaccurate image registration. To address these challenges, this paper proposes an underwater image stitching method that integrates ORB (Oriented FAST and Rotated BRIEF) feature extraction with a fixed-ratio constraint matching strategy. First, lightweight color and contrast enhancement techniques are employed to restore color balance and improve local texture visibility. Then, ORB descriptors are extracted and matched via a KNN (K-Nearest Neighbors) nearest-neighbor search, and Lowe’s ratio test is applied to eliminate false matches caused by weak texture similarity. Finally, the geometric transformation between image frames is estimated by incorporating robust optimization, ensuring stable homography computation. Experimental results on real underwater datasets show that the proposed method significantly improves stitching continuity and structural consistency, achieving 40–120% improvements in SSIM (Structural Similarity Index) and PSNR (peak signal-to-noise ratio) over conventional Harris–ORB + KNN, SIFT (scale-invariant feature transform) + BF (brute force), SIFT + KNN, and AKAZE (accelerated KAZE) + BF methods while maintaining processing times within one second. These results indicate that the proposed method is well-suited for real-time underwater environment perception and panoramic mapping on low-cost, micro-sized underwater robotic platforms. Full article

Hair loss disorders, particularly androgenetic alopecia (AGA), are common conditions that carry significant psychosocial impact. Current standard therapies, including minoxidil, finasteride, and hair transplantation, primarily slow progression or re-distribute existing follicles and do not regenerate lost follicular structures. In recent years, regenerative medicine has been associated with a gradual shift toward approaches that aim to restore follicular function and architecture. Stem cell-derived conditioned media and exosomes have shown the ability to activate Wnt/β-catenin signaling, enhance angiogenesis, modulate inflammation, and promote dermal papilla cell survival, resulting in improved hair density and shaft thickness with favorable safety profiles. Autologous cell-based therapies, including adipose-derived stem cells and dermal sheath cup cells, have demonstrated the potential to rescue miniaturized follicles, although durability and standardization remain challenges. Adjunctive interventions such as microneedling and platelet-rich plasma (PRP) further augment follicular regeneration by inducing controlled micro-injury and releasing growth and neurotrophic factors. In parallel, machine learning-based diagnostic tools and deep hair phenotyping offer improved severity scoring, treatment monitoring, and personalized therapeutic planning, while robotic Follicular Unit Excision (FUE) platforms enhance surgical precision and graft preservation. Advances in tissue engineering and 3D follicle organoid culture suggest progress toward producing transplantable follicle units, though large-scale clinical translation is still in early development. Collectively, these emerging biological and technological strategies indicate movement beyond symptomatic management toward more targeted, multimodal approaches. Future progress will depend on standardized protocols, regulatory clarity, and long-term clinical trials to define which regenerative approaches can reliably achieve sustainable follicle renewal in routine cosmetic dermatology practice. Full article

The deterioration of civil infrastructure poses a significant threat to public safety, yet conventional manual inspections remain subjective, labor-intensive, and constrained by accessibility. To address these challenges, this paper presents a real-time robotic inspection system that integrates deep learning perception and autonomous navigation. The proposed framework employs a two-stage neural network: a U-Net for initial segmentation followed by a Pix2Pix conditional generative adversarial network (GAN) that utilizes adversarial residual learning to refine boundary accuracy and suppress false positives. When deployed on an Unmanned Ground Vehicle (UGV) equipped with an RGB-D camera and LiDAR, this framework enables simultaneous automated crack detection and collision-free autonomous navigation. Evaluated on the CrackSeg9k dataset, the two-stage model achieved a mean Intersection over Union (mIoU) of 73.9 ± 0.6% and an F1-score of 76.4 ± 0.3%. Beyond benchmark testing, the robotic system was further validated through simulation, laboratory experiments, and real-world campus hallway tests, successfully detecting micro-cracks as narrow as 0.3 mm. Collectively, these results demonstrate the system’s potential for robust, autonomous, and field-deployable infrastructure inspection. Full article

Flexible sensors have emerged as critical interfaces for information exchange between soft biological tissues and machines. Here, we present a dual-mode stretchable sensor system capable of synchronous strain and electromyography (EMG) signal detection, integrated with wireless WIFI transmission for real-time joint movement monitoring. The system consists of two key components: (1) A multi-channel gel electrode array for high-fidelity EMG signal acquisition from target muscle groups, and (2) a novel capacitive strain sensor made of stretchable micro-cracked gold film based on Styrene Ethylene Butylene Styrene (SEBS) that exhibits exceptional performance, including >80% stretchability, >4000-cycle durability, and fast response time (<100 ms). The strain sensor demonstrates position-independent measurement accuracy, enabling robust joint angle detection regardless of placement variations. Through synchronized mechanical deformation and electrophysiological monitoring, this platform provides comprehensive movement quantification, with data visualization interfaces compatible with mobile and desktop applications. The proposed technology establishes a generalizable framework for multimodal biosensing in human motion analysis, robotics, and human–machine interaction systems. Full article

Over the past three decades, cardiac surgery has undergone a deep transformation, shifting from full median sternotomy to minimally invasive (MICS) and micro-invasive techniques. These approaches aim to achieve equivalent therapeutic outcomes while reducing surgical trauma, postoperative pain, hospitalization time, and healthcare costs. Minimally invasive strategies are now widely applied to aortic and mitral valve surgery, coronary artery bypass grafting, atrial fibrillation ablation, and combined procedures. Key advancements such as sutureless prostheses, video- and robotic-assisted systems, and enhanced imaging technologies have improved surgical precision and clinical outcomes while promoting faster recovery and superior cosmetic results. Evidence from randomized trials and observational studies demonstrates that MICS provides mortality and morbidity rates comparable to conventional surgery, with additional benefits in high-risk, elderly, and frail patients. Micro-invasive transcatheter interventions, particularly transcatheter aortic valve implantation (TAVI) and transcatheter mitral repair or replacement, have further expanded therapeutic options for patients unsuitable for open-heart surgery. Their success has fostered debate not between conventional and minimally invasive surgery, but between minimally invasive and micro-invasive approaches. Hybrid procedures—combining surgical and percutaneous techniques—exemplify a multidisciplinary evolution aimed at tailoring treatment to patient-specific anatomy, comorbidities, and risk profiles. Despite clear advantages, these techniques present challenges, including a steep learning curve, increased procedural costs, and the requirement for specialized equipment and institutional expertise. Optimal patient selection based on clinical risk assessment and advanced imaging remains essential. Future directions include refinement of robotic platforms, artificial intelligence-based decision support, miniaturization of instruments, and broader validation of emerging technologies in younger and low-risk populations. Minimally and micro-invasive cardiac surgery represent a paradigm shift toward patient-centered care, offering reduced physiological burden, improved functional recovery, and long-term outcomes comparable to conventional techniques. As innovation continues, these approaches are poised to become integral to modern cardiac surgical practice. Full article