Search Results (765)

In children under 4, septic arthritis of the hip (SAH) caused by Kingella kingae (SAH-KK) can be misdiagnosed, as it does not meet classic septic joint criteria (fever > 38.5°, pain, limited range of motion, and inability to bear weight). The objective of this study was to report clinical and paraclinical characteristics in a large cohort of children with confirmed SAH-KK and to evaluate the reliability of the Kocher (KC) and Caird criteria (CC) in predicting SAH-KK. Medical records of 140 children with confirmed SAH-KK were collected. Data on sex, age, temperature on admission, weight-bearing status, white blood cell (WBC) count, platelet count, C-reactive protein (CRP) value, and erythrocyte sedimentation rate (ESR) were extracted. The study focused on the sensitivity of KC (body temperature, refusal to bear weight, leukocytosis, and ESR) and CC (KC criteria plus CRP level). All patients had bacteriologically confirmed SAH-KK; most had mild symptoms and near-normal inflammatory markers. CRP (76.2%) had the highest sensitivity, followed by weight-bearing status (73.8%) and WBC count (69.6%). Body temperature and ESR exceeded cutoff values in less than 50% of cases. Among 77 patients fulfilling all KC, 49 (63.5%) had less than a 40% probability of SAH. Of 50 children with complete CC, 20 (40%) had a 62.4% or lower probability of SAH. KC and CC are not sufficiently accurate to confidently exclude SAH-KK in preschool-aged children due to heterogeneous clinical presentations. Further studies are needed to redefine diagnostic criteria based on patient age and causative pathogens. Full article

MXenes, a rapidly emerging family of two-dimensional transition metal carbides and nitrides, have attracted considerable attention in recent years for their potential in next-generation energy storage technologies. In solid-state batteries (SSBs), they combine metallic-level conductivity (>10³ S cm⁻¹), adjustable surface terminations, and mechanical resilience, which makes them suitable for diverse functions within the cell architecture. Current studies have shown that MXene-based anodes can deliver reversible lithium storage with Coulombic efficiencies approaching ~98% over 500 cycles, while their use as conductive additives in cathodes significantly improves electron transport and rate capability. As interfacial layers or structural scaffolds, MXenes effectively buffer volume fluctuations and suppress lithium dendrite growth, contributing to extended cycle life. In solid polymer and composite electrolytes, MXene fillers have been reported to increase Li⁺ conductivity to the 10⁻³–10⁻² S cm⁻¹ range and enhance Li⁺ transference numbers (up to ~0.76), thereby improving both ionic transport and mechanical stability. Beyond established Ti-based systems, double transition metal MXenes (e.g., Mo₂TiC₂, Mo₂Ti₂C₃) and hybrid heterostructures offer expanded opportunities for tailoring interfacial chemistry and optimizing energy density. Despite these advances, large-scale deployment remains constrained by high synthesis costs (often exceeding USD 200–400 kg⁻¹ for Ti₃C₂T_x at lab scale), restacking effects, and stability concerns, highlighting the need for greener etching processes, robust quality control, and integration with existing gigafactory production lines. Addressing these challenges will be crucial for enabling MXene-based SSBs to transition from laboratory prototypes to commercially viable, safe, and high-performance energy storage systems. Beyond summarizing performance, this review elucidates the mechanistic roles of MXenes in SSBs—linking lithiophilicity, field homogenization, and interphase formation to dendrite suppression at Li|SSE interfaces, and termination-assisted salt dissociation, segmental-motion facilitation, and MWS polarization to enhanced electrolyte conductivity—thereby providing a clear design rationale for practical implementation. Full article

This study investigates the 3RPUR (3-Revolute–Prismatic–Universal–Revolute) variable parallel mechanism, employing screw theory and linear geometry to analyze the geometric relationships and constraint characteristics of the RPUR (Revolute–Prismatic–Universal–Revolute) limb kinematic pairs. The findings reveal that the constraint moment in the always remains perpendicular to the two axes of the U pair, forming an equivalent plane. Through the locking/unlocking mechanism of universal joints (U pair), the mechanism achieves dynamic degree-of-freedom reconstruction, enabling seamless switching between three translational (3T) and three translational-one-rotation (3T1R) motion modes. The continuity between motion and degrees of freedom during the variable cell process is demonstrated. This research reveals a strict 1:1 linear coupling between the rotational angle of the moving platform around the Z-axis and the U pair’s rotation angle under 3T1R mode. Simulation experiments validate the feasibility and coupling characteristics of both motion modes, providing theoretical and technical support for this mechanism’s adaptation to complex working conditions in mobile robotics applications, particularly where reconfigurable parallel mechanisms are required for multi-task flexibility. Full article

We present three dimensional particle-in-cell simulations of current-voltage characteristics of the hemispherical Langmuir probe (LAP), onboard the China Seismo-Electromagnetic Satellite (CSES). Using realistic plasma parameters and background magnetic fields obtained from the International Reference Ionosphere (IRI) and International Geomagnetic Reference Field (IGRF) models, we simulate probe–plasma interactions at three locations: the equatorial region and two magnetically conjugate mid-latitude sites: Millstone Hill (Northern Hemisphere) and Rothera (Southern Hemisphere). The simulations, performed using the PTetra PIC code, incorporate realistic LAP geometry and spacecraft motion in the ionospheric plasma. Simulated current voltage characteristics or I–V curves are compared against in-situ LAP measurements from CSES Orbit-026610, with Pearson’s correlation coefficients used to assess agreement. Our findings indicate how plasma temperature, density, and magnetization affect sheath structure and probe floating potential. The study highlights the significance of kinetic modeling in enhancing diagnostic accuracy, particularly in variable sheath regimes where classic analytical models such as the Orbital-Motion-Limited (OML) theory may be inadequate. Full article

Motion of dislocations is a common mechanism of plasticity in many materials. Dislocation-mediated deformation is essentially an inhomogeneous process, which is manifest in the formation of slip lines and complicated cell wall structures. An adequate description of these processes is an important goal of Materials Theory, which aims to describe the mechanical properties of materials and their reliability in service. This publication advances the thermodynamically consistent theory of dislocation-mediated plasticity to include the spatial gradients of the independent variables. We conducted the renormalization group scaling analysis of deformation and obtained the low-energy dislocation structures as ordinary solutions of the equilibrium equations without any arbitrary assumptions. We matched the emerging theoretical structures with the experimentally observed and made several predictions regarding possible experiments. Full article

This paper introduces a new quadruped spider robot platform specializing in environmental reconnaissance and mapping. The robot measures 180 mm × 180 mm × 95 mm and weighs 385 g, including the battery, providing a compact yet capable platform for reconnaissance missions. The robot consists of an ESP32 microcontroller and eight servos that are disposed in a biomimetic layout to achieve the biological gait of an arachnid. One of the major design revolutions is in the power distribution network (PDN) of the robot, in which two DC-DC buck converters (LM2596M) are used to isolate the power domains of the computation and the mechanical subsystems, thereby enhancing reliability and the lifespan of the robot. The theoretical analysis demonstrates that this dual-domain architecture reduces computational-domain voltage fluctuations by 85.9% compared to single-converter designs, with a measured voltage stability improving from 0.87 V to 0.12 V under servo load spikes. Its proprietary Bluetooth protocol allows for both the sending and receiving of controls and environmental data with fewer than 120 ms of latency at up to 12 m of distance. The robot’s mapping system employs a novel motion-compensated probabilistic algorithm that integrates ultrasonic sensor data with IMU-based motion estimation using recursive Bayesian updates. The occupancy grid uses 5 cm × 5 cm cells with confidence tracking, where each cell’s probability is updated using recursive Bayesian inference with confidence weighting to guide data fusion. Experimental verification in different environments indicates that the mapping accuracy (92.7% to ground-truth measurements) and stable pattern of the sensor reading remain, even when measuring the complex gait transition. Long-range field tests conducted over 100 m traversals in challenging outdoor environments with slopes of up to 15° and obstacle densities of 0.3 objects/m² demonstrate sustained performance, with 89.2% mapping accuracy. The energy saving of the robot was an 86.4% operating-time improvement over the single-regulator designs. This work contributes to the championing of low-cost, high-performance robotic platforms for reconnaissance tasks, especially in search and rescue, the exploration of hazardous environments, and educational robotics. Full article

Ultra-high-resolution synthetic aperture radar (SAR) has important applications in military and civilian fields. However, the acquisition of high-resolution SAR imagery poses considerable processing challenges, including limitations in traditional slant range model precision, the spatial variation in equivalent velocity, spectral aliasing, and non-negligible error introduced by stop-and-go assumption. To this end, this paper proposes an improved extended wavenumber domain imaging algorithm for ultra-high-resolution SAR to systematically address the imaging quality degradation caused by these challenges. In the proposed algorithm, the one-step motion compensation method is employed to compensate for the errors caused by orbital curvature through range-dependent envelope shift interpolation and phase function correction. Then, the interpolation based on modified Stolt mapping is performed, thereby facilitating effective separation of the range and azimuth focusing. Finally, the residual range cell migration correction is applied to eliminate range position errors, followed by azimuth compression to achieve high-precision focusing. Both simulation and spaceborne data experiments are performed to verify the effectiveness of the proposed algorithm. Full article

S-adenosylmethionine decarboxylase (AdoMetDC) is an essential enzyme in the polyamine biosynthesis pathway and plays a key role in the synthesis of the polyamines spermidine and spermine, polycationic alkylamines that are present in millimolar levels in mammalian cells. Polyamines are metabolic molecules that are involved in many fundamental processes, including regulation of protein and nucleic acid synthesis, stabilization of chromatin, differentiation, apoptosis, protection from oxidation, and regulation of ion channels. Multiple oncogenic pathways lead to dysregulation of polyamines, making polyamines a potential biomarker for cancer and polyamine biosynthesis a target for therapeutic intervention. This study uses multi-temperature crystallography to probe the structure and dynamics of AdoMetDC by collecting diffraction data at 100 K, 273 K, and 293 K. Differential loop behavior is observed across the collected datasets, with dramatic residue rearrangements. In the loop containing residues 20–28, the ambient temperature datasets show a large motion relative to the cryo structure. In a second loop containing residues 164–174, previous cryo structures do not report ordered positions. This loop is ordered in our 100 K structure, while assuming different conformations in the 273 K and 293 K data. These results further illustrate the usefulness of ambient data collection for understanding the structure and dynamics of proteins, especially in loop regions which are less restrained than protein cores. Full article

Cell detection-tracking tasks are vital for biomedical image analysis with potential applications in clinical diagnosis and treatment. However, it poses challenges such as ambiguous boundaries and complex backgrounds in microscopic video sequences, leading to missed detection, false detection, and loss of tracking. Therefore, we propose an enhanced multiple object tracking algorithm IEGS-YOLO + BoT-SORT, named IEGS-BoT, to address these issues. Firstly, the IEGS-YOLO detector is developed for cell detection tasks. It uses the iEMA module, which effectively combines the global information to enhance the local information. Then, we replace the traditional convolutional network in the neck of the YOLO11n with GSConv to reduce the computational complexity while maintaining accuracy. Finally, the BoT-SORT tracker is selected to enhance the accuracy of bounding box positioning through camera motion compensation and Kalman filter. We conduct experiments on the CTMC dataset, and the results show that in the detection phase, the map50 (mean Average Precision) and map50–95 values are 73.2% and 32.6%, outperforming the YOLO11n detector by 1.1% and 0.6%, respectively. In the tracking phase, using the IEGS-BoT method, the multiple objects tracking accuracy (MOTA), higher order tracking accuracy (HOTA), and identification F1 (IDF1) reach 53.97%, 51.30%, and 67.52%, respectively. Compared with the base BoT-SORT, the proposed method achieves improvements of 1.19%, 0.23%, and 1.29% in MOTA, HOTA, and IDF1, respectively. ID switch (IDSW) decreases from 1170 to 894, which demonstrates significant mitigation of identity confusion. This approach effectively addresses the challenges posed by object loss and identity switching in cell tracking, providing a more reliable solution for medical image analysis. Full article

Cancer cells can adapt to their surrounding microenvironment by upregulating glucose-regulated protein 78 kDa (GRP78) and vacuolar-type ATPase (V-ATPase) proteins to increase their proliferation and resilience to anticancer therapy. Therefore, targeting these proteins can obstruct cancer progression. A comprehensive computational study was conducted to investigate the inhibitory potential of four proton pump inhibitors (PPIs), dexlasnoprazole (DEX), esomeprazole (ESO), pantoprazole (PAN), and rabeprazole (RAB), against GRP78 and V-ATPase. Molecular docking revealed high-affinity scores for PPIs against both proteins. Moreover, molecular dynamics showed favorable root mean square deviation values for GRP78 and V-ATPase complexes, whereas root mean square fluctuations were high at the substrate-binding subdomains of GRP78 complexes and the α-helices of V-ATPase. Meanwhile, the radius of gyration and the surface-accessible surface area of the complexes were not significantly affected by ligand binding. Trajectory projections of the first two principal components showed similar motions of GRP78 structures and the fluctuating nature of V-ATPase structures, while the free-energy landscape revealed the thermodynamically favored GRP78-RAB and V-ATPase-DEX conformations. Furthermore, the binding free energy was −16.59 and −18.97 kcal/mol for GRP78-RAB and V-ATPase-DEX, respectively, indicating their stability. According to our findings, RAB and DEX are promising candidates for GRP78 and V-ATPase inhibition experiments, respectively. Full article

This study presents a simulation-based feasibility analysis of a beam steering metasurface, theoretically driven by mechanical energy harvested from human motion via a triboelectric nanogenerator (TENG). In the proposed model, the TENG converts biomechanical motion into alternating current (AC), which is rectified into direct current (DC) to bias varactor diodes integrated into each metasurface unit cell. These bias voltages are numerically applied to dynamically modulate the local reflection phase, enabling beam steering without external power. Full-wave electromagnetic simulations were conducted to confirm the feasibility of beam manipulation under TENG-generated voltage levels. The proposed simulation-driven design offers a promising framework for battery-free, adaptive electromagnetic control with potential applications in wearable electronics, intelligent sensing, and energy-autonomous radar systems. Full article

Road accidents could result in severe or fatal neck injuries. A few surrogate necks are available to develop and test neck protectors as countermeasures, but each has its own limitations. The objective of this study was to develop a surrogate neck compatible with the Hybrid III dummy, focused on tunable flexural stiffness and integrated angular sensors for kinematic feedback during impact tests. The neck features six 3D-printed surrogate vertebral bodies interconnected by rubber surrogate discs, providing a baseline flexibility to the surrogate fundamental spinal units. An adjustable inner cable and elastic elements hooked on the sides of vertebral elements allow to increase the flexural stiffness of the surrogate and to simulate the asymmetric behavior of the human neck. Neck flexural angles and axial compression are measured using a novel system made of wires, pulleys, and rotary potentiometers embedded in the neck base. A motion capture system and a load cell were used to determine the bending and torsional stiffness of the neck and to calibrate the sensors. Results showed that the neck flexural stiffness can be tuned between 3.29 and 5.76 Nm/rad. Torsional stiffness was 1.01 Nm/rad and compression stiffness can be tuned from 39 to 193 N/mm. Sensor flexural angles were compared with motion capture angles, showing an RMSE error of 1.35° during static testing and of 3° during dynamic testing. The developed neck could be a viable tool for investigating neck braces from a kinematic and kinetic perspective due to its inbuilt sensing ability and its tunable stiffness. Full article

This paper presents the development, modeling, and analysis of an autonomous active ankle prosthesis with two degrees of freedom (2-DoF), designed to reproduce movements in the sagittal (dorsiflexion/plantarflexion) and frontal (inversion/eversion) planes in order to enhance the stability and naturalness of the user’s gait. Unlike most commercial prostheses, which typically feature only one active degree of freedom, the proposed device combines a lightweight mechanical design, a screw drive with a stepper motor, and a microcontroller-based control system. The prototype was developed using CAD modeling in SolidWorks 2024, followed by dynamic modeling and finite element analysis (FEA). The simulation results confirmed the achievement of physiological angular ranges of ±20–22 deg. in both planes, with stable kinematic behavior and minimal vertical displacements. According to the FEA data, the maximum von Mises stress (1.49 × 10⁸ N/m²) and deformation values remained within elastic limits under typical loading conditions, though cyclic fatigue and impact energy absorption were not experimentally validated and are planned for future work. The safety factor was estimated at ~3.3, indicating structural robustness. While sensor feedback and motor dynamics were idealized in the simulation, future work will address real-time uncertainties such as sensor noise and ground contact variability. The developed design enables precise, energy-efficient, and adaptive motion control, with an estimated average power consumption in the range of 7–9 W and an operational runtime exceeding 3 h per charge using a standard 18,650 cell pack. These results highlight the system’s potential for real-world locomotion on uneven surfaces. This research contributes to the advancement of affordable and functionally autonomous prostheses for individuals with transtibial amputation. Full article

Background/Objectives: This study investigates the benefits of incorporating stem cell therapy into arthroscopic rotator cuff repair by evaluating its impact on postoperative pain and functional recovery. Methods: A retrospective, comparative analysis was conducted with a small cohort of patients undergoing rotator cuff surgery, divided into two groups: one receiving adjunctive combined PRP and bursal stem cell therapy and the other undergoing standard arthroscopic repair alone. The outcomes were assessed using visual analog scale (VAS) scores for pain and the Constant–Murley score (CMS), which includes strength of abduction, VAS pain, limitation and range of motion, evaluated at baseline, 1, 2, 3 and 6 months postoperatively. Results: Patients in the stem cell group experienced significantly greater reductions in pain scores and more substantial improvements in functional scores at the follow-up points compared to the control group. A linear mixed-effects analysis showed that in the early postoperative period, the use of PRP and bursal stem cell therapy was associated with significantly reduced postoperative VAS pain scores (F 4.8, p = 0.045) and an increased CMS regarding postoperative pain (F 8.6, p = 0.01), alongside painless elevation level (F 6.5, p = 0.022), forward flexion (F 8.5, p = 0.01) and abduction scores (F 8.3, p = 0.011). The effect of PRP and bursal stem cell therapy remains constant during late follow-up, from the fourth to sixth postoperative month, with postoperative CMS regarding pain remaining statistically significantly higher in the stem cell therapy group (F 4.8, p = 0.008), alongside reduced night-time pain (F 7.4, p = 0.015), improved recreation ability (F 4.8, p = 0.044) and reduced activity restriction (F 5.8, p = 0.028). Conclusions: The findings suggest that the addition of stem cell therapy to arthroscopic rotator cuff repair may enhance postoperative recovery by alleviating pain and promoting functional gains. Full article

Digital Twins (DTs) are transforming manufacturing by bridging the physical and digital worlds, enabling real-time insights, predictive analytics, and enhanced decision making. In Industry 4.0, DTs facilitate automation and data integration, while Industry 5.0 emphasizes human-centric, resilient, and sustainable production. However, implementing DTs in robotic metal additive manufacturing (AM) remains challenging because of the complexity of the wire-based laser metal deposition (LMD) process, the need for real-time monitoring, and the demand for advanced defect detection to ensure high-quality prints. This work proposes a structured DT architecture for a robotic wire-based LMD cell, following a standard framework. Three DT implementations were developed. First, a real-time 3D simulation in RoboDK, integrated with a 2D Node-RED dashboard, enabled motion validation and live process monitoring via MQTT (message queuing telemetry transport) telemetry, minimizing toolpath errors and collisions. Second, an Industrial IoT-based system using KUKA iiQoT (Industrial Internet of Things Quality of Things) facilitated predictive maintenance by analyzing motor loads, joint temperatures, and energy consumption, allowing early anomaly detection and reducing unplanned downtime. Third, the Meltio dashboard provided real-time insights into the laser temperature, wire tension, and deposition accuracy, ensuring adaptive control based on live telemetry. Additionally, a prescriptive analytics layer leveraging historical data in FireStore was integrated to optimize the process performance, enabling data-driven decision making. Full article