Search Results (2,178)

To address the low application accuracy and poor spreading uniformity of conventional lime spreaders, an electromagnetic vibration-assisted variable-rate lime spreader integrating a shaftless screw metering mechanism was developed. The overall configuration and operating principle are presented. Considering the physicochemical characteristics of lime powder, including fine particle size, strong drift tendency, and poor flowability, a shaftless screw metering unit was designed to improve discharge stability and metering accuracy. To enhance dispersion uniformity, a vertical electromagnetic vibration device was developed, and its key parameters were determined through a theoretical analysis of vibration frequency and amplitude. In addition, the structure and kinematic parameters of the spreading disc were optimized by analyzing particle trajectories and outlet distribution patterns. A closed-loop feedback control strategy was implemented to enable precise variable-rate application. Static bench tests demonstrated a metering accuracy of 96.42%, and the dispersion uniformity was at least 84.14% at an electromagnetic vibration frequency of 10 to 18 Hz. Field evaluations further showed that the coefficient of variation for transverse uniformity was no more than 17.88%, while the maximum coefficient of variation for longitudinal stability was 18.09%. These results indicate that the proposed spreader satisfies the operational requirements for accurate and uniform variable-rate application of lime powder. Full article

Tissue-engineered vascular grafts (TEVGs) represent a promising alternative for coronary artery bypass grafting (CABG). However, replicating the mechanical and biological complexity of native vessels remains a major challenge. Compliance mismatch, local hemodynamics, and insufficient endothelialization are recognized as key contributors to maladaptive remodeling and graft failure. These limitations highlight the urgent need for advanced experimental platforms and standardized physical stimulation procedures to investigate these underlying biomechanisms and support the development of more effective TEVGs. In this work, we present an automated, modular platform designed to quantitatively characterize graft compliance and replicate coronary hemodynamics. The system integrates automated experimental procedures within a modular, incubator-compatible design, enabling an intuitive setup and real-time monitoring of physical parameters. Its modular architecture and dedicated control algorithms provide high adaptability, enabling its application across a broad range of experimental conditions. Bench testing demonstrates that the platform can automatically reproduce the pressure regimes defined by ISO standard and generate coronary-like flow-induced stimuli. These results confirm the innovative capability of the system to provide controlled and physiologically relevant conditions suitable for the investigation of key phenomena involved in CABG failure. In perspective, the platform offers a valuable tool for advanced mechanobiological studies in vascular tissue engineering. Full article

Patient-specific lattice implants (PSLIs) and modular porous scaffolds have emerged as promising solutions for treating diaphyseal segmental defects of the femur and tibia, particularly where conventional reconstruction methods fall short. This second part of our two-part review focuses on how current studies transform computed tomography (CT) and $\mathsf{\mu }$CT datasets into architected lattice implants, as well as how these constructs are fabricated and numerically, mechanically, biologically, and clinically verified. We outline imaging pipelines, including Digital Imaging and Communications in Medicine (DICOM) acquisition, segmentation, contralateral mirroring, and Hounsfield Units (HU)–density–elasticity mapping, and show how these choices impact finite element (FE) models and print-ready geometries. Next, lattice design strategies and mixed-material concepts are compared and linked to specific additive manufacturing routes in metals, polymers, and bioceramics, such as laser powder bed fusion (LPBF), electron beam melting (EBM), fused deposition modeling (FDM), material jetting, and extrusion-based bioprinting. Methodological overviews of linear–elastic models and homogenized finite element (FE) models, along with bench-top mechanical tests, in vitro cell assays, in vivo animal studies, and early clinical series, are utilized to categorize the studies into four pathways: simulation (S), mechanical (E_mech), biological (E_bio), and validation (V). Based on the reviewed literature, we establish a general workflow for CT implants. We identify common gaps in the process, observe insufficient reporting of imaging and modeling details, note a lack of data on fatigue and remodeling, and recognize the limited size of clinical cohorts. Additionally, we provide practical recommendations for developing more standardized and scalable planning pipelines. Part 1 of this two-part review studied defect patterns, anatomical location, and fixation strategies for patient-specific lattice implants used in femoral and tibial segmental reconstruction, with emphasis on how defect morphology and subregional anatomy influence construct selection and mechanical behavior. It established a defect- and fixation-centered review that provides the clinical and anatomical context for the workflow and validation analysis presented in Part 2. Full article

Variations in liner vibration among cylinders can lead to non-uniform lubrication, accelerated wear, and cavitation in multi-cylinder diesel engines. This study investigated the origin of these variations in a heavy-duty straight-six diesel engine using a transient dynamic model of the cylinder assembly, modal analysis, and VMD. An elastic transient model of the block, liner, and piston system was developed with measured cylinder pressure, cylinder head bolt preload, and piston thermal deformation applied as boundary conditions. The model was validated against modal testing and bench measurements of liner acceleration. Under nominally identical piston excitation across all six cylinders, the computed liner responses were decomposed using VMD to extract intrinsic mode components and dominant frequency bands. The results show that the primary vibration response is concentrated in the upper-middle region of the liner, while the end cylinders exhibit higher vibration levels than the central cylinders. A dominant component centred at approximately 1800 Hz is identified and linked to an engine block mode whose spatial deformation pattern matches the cylinder-to-cylinder distribution of liner vibration and cavitation risk. These findings indicate that the inter-cylinder discrepancy is linked to engine block modal and non-uniformity constraints. The proposed model provides a basis for reliability-oriented mitigation of vibration and cavitation in multi-cylinder diesel engines. Full article

Parameter estimation plays an important role in improving the accuracy, control, and diagnostic performance of mechanisms, particularly in parallel mechanisms such as the Stewart platform, which are increasingly used in high-precision automation, advanced manufacturing, and machine-centric applications. This paper presents a multibody–based framework for generalized dynamic modeling and inertial parameter estimation of parallel robotic manipulators, demonstrated on the DeltaLab-SMT EX800 Stewart platform. A systematic constrained multibody dynamic formulation is developed using an iterative kinematic–dynamic coupling scheme to compute generalized coordinates and their time derivatives under prescribed motion trajectories. The proposed identification manifold is experimentally validated on the physical test rig, in which the platform motion is executed via the control/DAQ system, while inertial measurements are acquired using an external 6-axis motion sensor to obtain direct acceleration data from the moving platform. Platform acceleration measurements are mapped through the inverse dynamics of the multibody model to derive the corresponding generalized forces, providing a practical and cost-effective alternative to direct force measurement with transducers. A Kalman filter is subsequently employed to combine the measured and the model-predicted data, yielding optimally filtered estimates of the inertial coordinates for accurate parameter identification. Inertial parameters are estimated using particle swarm optimization and bench marked against a gradient-based Levenberg–Marquardt approach, with comparison in terms of convergence behavior, robustness, and estimation accuracy. The results support the proposed framework as a measurement-informed benchmark methodology for parameter estimation of parallel manipulators. Full article

This study examined whether large language models (LLMs) can generate clinically realistic profiles of cognitive decline and whether simulated deficits reflect architectural constraints rather than superficial role-playing artifacts. Using GPT-4o-mini, we generated synthetic cohorts (n = 10 per group) representing healthy aging, mild cognitive impairment (MCI), and Alzheimer’s disease (AD), assessed through a conversational neuropsychological battery covering episodic memory, verbal fluency, narrative production, orientation, naming, and comprehension. Experiment 1 tested whether synthetic subjects exhibited graded cognitive profiles consistent with clinical progression (Control > MCI > AD). Experiment 2 systematically manipulated prompt context in AD subjects (short, rich biographical, and few-shot prompts) to dissociate robust from manipulable deficits. Significant cognitive gradients emerged (p < 0.001) across eight of thirteen domains. AD subjects showed impaired episodic memory (Cohen’s d = 4.71), increased memory intrusions, and reduced narrative length (d = 3.07). Critically, structurally constrained memory tasks (episodic recall, digit span) were invariant to prompting (p > 0.05), whereas generative tasks (narrative length, verbal fluency) showed high sensitivity (F > 100, p < 0.001). Rich biographical prompts paradoxically increased memory intrusions by 343%, indicating semantic interference rather than cognitive rescue. These results demonstrate that LLMs can serve as in silico test benches for exploring candidate digital biomarkers and clinical training protocols, while highlighting architectural constraints that may inform computational hypotheses about memory and language processing. Full article

The development of autonomous mobile robots or automated guided vehicles is consistently challenged by energy-storage constraints, and while batteries are the standard solution for mobile robots, dynamic wireless power transfer is an alternative way to supply power without reliance on chemical energy storage. For efficient dynamic wireless power transfer, transmitting coils should be energized as required, necessitating real-time position tracking of the receiving coil. Current prevalent techniques require complex modifications to existing systems and additional position sensors, which increase total costs. This article proposes a novel receiving coil position detection method for wireless power transfer systems without using external receiving coil position detection sensors and describes the application of the sensorless coil position detection method and its advantages compared to other methods. The proposed method was implemented on an existing low-power, miniaturized test bench. The described method was successfully validated and correctly switched transmitting coils, ensuring continuous movement of an electric vehicle, therefore proving its viability as a potential new approach for sensorless receiving-coil detection. Experimental results demonstrate that the prototype achieved a maximum power transfer efficiency of 53.8% while maintaining continuous transmitting coil switching operation at vehicle speeds up to 77 cm/s. Full article

Cost efficient, spatially resolved water quality monitoring is essential for managing pollution and protecting aquatic ecosystems. This study presents a low-cost (approximately USD 200), open-source, unmanned aerial vehicle (UAV)-deployable in situ sensor node for real-time assessment of surface-water conditions. The system integrates sensors for pH, turbidity, temperature, and total dissolved solids (TDSs), with onboard data logging and real-time clock (RTC) synchronization. Bench validation of the sensor package yielded mean absolute percentage errors of 1.34% for pH, 5.23% for TDS, and 0.81% for temperature, and the device operated continuously for 42 h. Field deployment demonstrated its ability to resolve spatial gradients, with observed ranges in the tested water body of pH 6.0–6.7, turbidity 11–18 NTU, TDS 44–51 ppm, and temperature 22.8–24.6 °C. Ordinary Kriging was used to interpolate measurements and generate continuous spatial maps. The open-source, UAV-deployable design provides an accessible platform for community-scale and research-oriented water quality mapping. Full article

In adaptive optics systems, high spatial resolution detection is a core prerequisite for achieving accurate wavefront correction. High spatial resolution wavefront measurement based on the traditional Shack-Hartmann technique is limited by the density of the microlens array. In contrast, off-axis digital holography technology is applied in wavefront measurement systems of adaptive optics systems due to its advantages of high spatial resolution, non-contact measurement, and full-field measurement. However, during the demodulation of its interference fringes, the accurate extraction of the complex amplitude of the +1st-order diffraction order directly determines the precision of wavefront reconstruction. Traditional frequency-domain filtering methods suffer from drawbacks such as reliance on manual threshold setting, poor adaptability to irregular spectra, and localization deviations caused by multi-region interference, making it difficult to meet the dynamic application requirements of adaptive optics. To address these issues, this study proposes a spectrum extraction method based on the Canny operator for adaptive edge extraction and centroid localization. The method first locks the rough range of the +1st-order spectrum through multi-stage peak screening, then achieves complete segmentation of spectrum spots by combining adaptive histogram equalization with edge closing and filling, resolves centroid indexing errors via maximum connected component screening, and ultimately accomplishes accurate extraction through Gaussian window filtering. Simulation experimental results show that, in comparison with two classical spectrum filtering methods, the centroid estimation error of the proposed method remains below 0.245 pixels under different noise intensity conditions. Moreover, the root mean square error of the residual wavefront corresponding to the reconstructed wavefront of the proposed method is reduced by 89.0% and 87.2% compared with those of the two classical methods, respectively. We further carried out measurement experiments based on a self-developed atmospheric turbulence test bench. The experimental results demonstrate that the proposed method exhibits higher-precision spectral centroid localization capability, which provides a reliable technical support for the high-precision measurement of dynamic distortion induced by atmospheric turbulence. Full article

This first part of a two-part review examines how Computed Tomography(CT)-based, additively manufactured (AM) porous implants are used to reconstruct large segmental defects of the femur and tibia. We focus on lightweight patient-specific lattice implants, architected cages, and modular porous constructs that incorporate engineered porosity into the load-bearing structure and are deployed with plate-, nail-, or external-fixator-based stabilization. We show how defects are described and classified by size, morphology, and anatomical subsegment; how these descriptors influence fixation choice and the resulting mechanical environment; and where along the femur and tibia porous implants have been applied in clinical and preclinical settings. Across the literature, outcomes appear to depend most strongly on defect morphology and local biology, while fixation feasibility and construct behavior vary by subregional anatomy. Most reported constructs use Ti6Al4V porous architectures intended to share load with fixation, reduce stress shielding, and provide a regenerative space for graft and tissue ingrowth. Finite element analyses (FEA) and bench-top studies consistently indicate that lattice architecture, relative density (RD), and fixation concept jointly control stiffness, micromotion, and fatigue-sensitive regions, whereas early animal and human reports describe promising incorporation and functional recovery in selected cases. However, defect descriptors, fixation reporting, boundary conditions, and outcome metrics remain diverse, and explicit quantitative validation of simulations against mechanical or in vivo measurements is uncommon. Most published work relies on simulation and bench testing, with limited reporting of biological endpoints, leaving a validation gap that prevents direct translation. We emphasize the need for standardized defect and fixation descriptors, harmonized mechanical and modeling protocols, and defect-centered datasets that integrate anatomy, mechanics, and longitudinal outcomes. Across the 27 included studies (may be counted in more than one group), simulation and mechanical testing are reported in 19/27 (70%) and 15/27 (56%), respectively, while in vivo studies (preclinical or clinical) account for 9/27 (33%), highlighting a validation gap that limits translation. Part 2 (under review); of these two series review paper; Patient-Specific Lattice Implants for Segmental Femoral and Tibial Reconstruction (Part 2): CT-Based Personalization, Design Workflows, and Validation-A Review; extends this work by detailing CT-to-implant workflows, lattice design strategies, and methodological validation. Full article

Clinical diagnostic laboratories continue to face growing pressure from rising test volumes, increasingly complex testing menus, significant workforce shortages, and expectations for faster turnaround times at sustainable cost. Total laboratory automation (TLA) has become a central strategy for improving efficiency in high-volume laboratories, where integrated systems from Abbott, Roche, Siemens Healthineers, and Beckman Coulter have demonstrated substantial reductions in turnaround time, error rates, and labor requirements. Evidence across multiple health systems shows that TLA improves performance and stabilizes laboratory operations even during workload peaks. Despite these gains, large segments of pre-analytical and post-analytical workflows remain manual, especially tasks related to specimen transportation, bench-level manipulation, instrument tending, and troubleshooting. Recent progress in collaborative robotics (cobots), autonomous mobile robots (AMRs), and hospital service robots demonstrates that these technologies can complement TLA by addressing not only the logistical and dexterous tasks that fixed automation lines cannot reach but also enabling robots that can work safely right alongside humans in a shared space. Cobots have shown sub-millimeter precision in colony picking and other fine-motor tasks, though typically at lower throughputs than dedicated track modules, and AMRs have demonstrated reliable transport of pathology carts and medical supplies through large clinical environments. Meanwhile, humanoid-capable mobile manipulators, like Moxi from Diligent Robotics, deployed in hospitals are already completing hundreds of thousands of supply deliveries, indicating real-world significance. Here, we integrate technical, regulatory, operational, and business perspectives on TLA, collaborative robotics, and mobile platforms. We discuss real-world efficiency gains, regulatory expectations under the CLIA and United States FDA, and the emerging case for hybrid automation ecosystems that combine TLA islands, cobotic workcells, AMRs, and AI-enabled orchestration. We argue that the next decade of laboratory automation will move beyond monolithic tracks with robots toward flexible, modular robotic systems designed to operate safely together with humans and to augment the increasingly strained laboratory workforce. This not only allows clinical staff to dedicate more time to patient care but also ensures greater reliability and scalability for essential services throughout demanding hospital environments. Full article

Background: The purpose of the study was to examine the effects of training volume in bench press (BP) on acute mechanical, metabolic, and cardiovascular responses, and the time course of recovery. Methods: Fourteen men with moderate resistance training experience performed, in randomized order and separated by one week, three BP protocols differing in volume: 3 (LOW), 15 (MOD), and 24 (HIG) repetitions. To isolate the effect of training volume by minimizing fatigue accumulation across repetitions, short rest periods were inserted between repetitions. The rest duration was individualized based on the performance impairment induced in each repetition. A battery of tests was performed at baseline (Pre) and post-exercise, in the following order: (a) heart rate (HR), blood systolic and diastolic pressure (SBP and DBP), and oxygen saturation (SpO2), (b) blood lactate, and (c) dynamic strength test, which was also conducted at 24 h-Post and 48 h-Post. Results: Performance within-session (best, average, and last velocity, as well as velocity loss) was similar for all protocols. A significant “protocol × time” interaction was observed for SBP, although no significant differences between protocols were found. No significant differences were observed for DBP or SpO2. All protocols showed similar lactate concentrations at Post and similarly increased velocity at 60% 1RM load at 24 h-Post and 48 h-Post. Conclusions: individualizing inter-repetition rest periods based on velocity loss allows matching fatigue across different bench press volumes, which produced similar mechanical, metabolic, and cardiovascular responses, indicating that volume alone does not determine acute physiological load. Full article

The high-speed rotor electric drive system in control moment gyroscopes (CMGs) is essential for precise spacecraft attitude control. Rigorous testing of this system is critical for ensuring reliability and longevity throughout orbital missions. However, conventional test bench methods exhibit numerous limitations. In contrast, the electric motor emulator (EME) provides a flexible and efficient alternative for power-level testing of the CMG high-speed rotor brushless DC motor drive system. To address the challenges of trapezoidal back-electromotive force (back-EMF) emulation and insufficient square-wave current tracking accuracy in existing brushless DC motor emulator (BLDCME) implementations, this paper proposes a sliding time window-based dynamic current compensation control (STW-DCCC) strategy for the CMG high-speed rotor BLDCME. First, based on the VSC single-conversion-circuit topology, the BLDCME basic control strategy based on the motor port current and the current change rate is implemented to achieve a tracking control of the square-wave current and emulation of the trapezoidal back-EMF. Building upon this foundation, a sliding time window-based RMS current compensation optimization strategy for the BLDCME is designed to provide dynamic compensation for system disturbances and thereby enhance the tracking accuracy of the square-wave current. Furthermore, by incorporating fault information, the proposed STW-DCCC strategy can also emulate the resistance unbalance fault of the brushless DC motor. Finally, through experiments, a comparative analysis is conducted between the basic control strategy and the proposed STW-DCCC strategy under normal operating conditions, parameter mismatch operating conditions, and resistance unbalance fault conditions, thereby validating the effectiveness of the proposed method. Full article

Background: Caffeine contributes to improvements in physical performance by enhancing muscular strength and endurance. However, it is necessary to evaluate the effects of different dosages on resistance training (RT) performance. Therefore, this study aimed to compare the effects of different caffeine doses (i.e., 3 mg·kg⁻¹ and 6 mg·kg⁻¹) on the maximum number of repetitions in a muscular endurance test. Methods: The study included 11 male participants (25.7 ± 5.9 years) who completed six in-person visits. During the first visit, a 24 h dietary recall (24HDR) was administered, anthropometric measurements were assessed, and one-repetition maximum (1RM) was determined in the flat bench press (BP). The second visit (baseline; BL) included a new 24HDR, assessment of muscle thickness using portable ultrasound (pre- and post-test), and a muscular endurance test in the BP at 80% of 1RM performed until concentric failure. The four subsequent visits followed the same protocol, with the administration of caffeine or placebo capsules 60 min before testing in a randomized, double-blind manner: low-dose caffeine (3 mg·kg⁻¹; LC), high-dose caffeine (6 mg·kg⁻¹; HC), low-dose placebo (3 mg·kg⁻¹; LP), and high-dose placebo (6 mg·kg⁻¹; HP). The first three interventions were conducted with 48 h intervals, and the remaining interventions were separated by a 7-day interval. Results: The number of repetitions and total workload (TWL) increased in all conditions compared with baseline; however, no significant differences were observed (p > 0.05). LC and HP achieved the highest repetition values (LC: 12.09 ± 3.33 reps; HP: 12.27 ± 2.72 reps). Muscle thickness was greater in all conditions in the post-test assessment, showing a significant increase (p < 0.05). Conclusions: Low- or high-dose caffeine supplementation appears to moderately influence responses in a muscular endurance test, suggesting that caffeine may be a potential supplement for resistance training. Full article

Aiming at the challenge of simultaneously optimizing ride comfort and wheel grounding performance for mining dump trucks under severe road conditions, this paper proposes a hydro-pneumatic suspension parameter design method based on an improved multi-objective particle swarm optimization (IMOPSO) algorithm. First, a dynamic model of the hydro-pneumatic suspension is established, incorporating the coupled nonlinear characteristics of the valve system and the gas chamber. The accuracy of the model is verified through bench tests. Subsequently, the influence of key parameters, including the damping orifice diameter, check valve seat hole diameter, and initial gas charging height, on the vertical dynamic performance of the vehicle, is systematically analyzed. On this basis, a multi-objective optimization model is constructed with the objective of minimizing the root mean square (RMS) values of both the sprung mass acceleration and the dynamic tire load. To enhance the global search capability and convergence performance of the MOPSO algorithm, adaptive inertia weighting, dynamic flight parameter update, and an enhanced mutation strategy are introduced. Simulation results demonstrate that the optimized suspension achieves significant improvements under various road conditions. On class-C roads, the RMS values of the sprung mass acceleration (SMA) and the dynamic tire load (DTL) are reduced by 37.6% and 15.8%, respectively, while the suspension rattle space (SRS) decreases by 10.2%. Under transient bump roads, the peak-to-peak (Pk-Pk) values of the same two indicators drop by 38.9% and 44.9%, respectively. Furthermore, compared to the NSGA-II algorithm, the proposed method demonstrates superior performance in terms of convergence stability and overall performance balance. These results indicate that the proposed design effectively balances ride comfort, wheel grounding performance, and driving safety. This study provides a theoretical foundation and an engineering-feasible method for the performance balancing and parameter co-design of suspension systems in heavy-duty engineering vehicles. Full article