Search Results (40)

The amount of rod contour is a critical factor that influences sagittal and coronal alignment for posterior spinal fusion. Distraction techniques to correct spinal deformity, which are often three-dimensional (3D) in nature, are known to cause rod deformation from the ideal, planned rod curvature. Therefore, surgeons often overbend rods to account for this phenomenon. Currently, there is no agreed-upon method to scientifically quantify rod unbending, and no methods offer a 3D analysis. The proposed methodology addresses this gap. By aligning the 3D rod centerlines, the segmented area enclosed between the two lines serves as a measure of rod deformation. This paper presents the foundational principles and concepts for quantifying 3D rod deformation. With further research and clinical implementation, this methodology has the potential to provide valuable surgical insight, which could improve postoperative spinal alignment and outcomes. Full article

Accurate classification of pollen grains in microscopic images remains challenging because of noise, structural variability, background complexity, weak texture, and intra-class similarity. To address these issues, this study proposes a hybrid framework that integrates contour-signal modeling, spectral–wavelet analysis, and deep learning for robust microscopic pollen image recognition. In the proposed approach, microscopic pollen images are first converted into contour-based point-signal representations, allowing object boundaries to be analyzed as structured one-dimensional signals. To improve signal quality under real imaging conditions, the framework incorporates Gaussian, median, and contour-aware filtering together with defect-point detection and correction. The processed contour signals are then analyzed using Fourier transform, continuous wavelet transform, and discrete wavelet transform to extract complementary global and local descriptors. These enriched representations are provided to a convolutional neural network for final classification. Experiments conducted on a seven-class microscopic pollen-image dataset demonstrate that the proposed method outperforms conventional computer-vision and baseline deep-learning approaches. The best-performing hybrid configuration achieved an error rate of 6.4%, while the overall classification accuracy reached 0.977 with an F1-score of 0.966, compared with 0.837 for a traditional computer-vision pipeline. These results confirm that combining contour-based signal processing with hierarchical deep feature learning provides an effective and noise-robust strategy for microscopic pollen image recognition. However, the present validation is limited to pollen images, and further experiments on broader microscopic object datasets are required to assess generalization to other micro-object categories such as nanoparticles, fibers, rods, and synthetic microstructures. Full article

Adequate monitoring of flour storage bins in the food manufacturing industry can prevent profit loss from underproduction and overstocking. Manual volume measurement is labor-intensive and error-prone. With the need for efficient monitoring in mind, this study presents the design and development of volumetric measurement of the flour inside a storage bin using 2D-based rotating LiDAR to capture 3D point cloud data. The proposed system eliminates manual probing by fully automating the scanning and volumetric computation workflow. Instead of relying on discrete physical measurements inside the bin, the 2D rotating LiDAR continuously captures the interior walls and flour surface to generate a dense 3D point cloud. This removes the need for operators to insert rods or probes and thereby avoids human-induced measurement variability. Furthermore, because the system computes flour volume directly from geometric reconstruction rather than converting probe depths using a uniform surface assumption, it does not rely on a constant material density and is therefore more robust to compaction differences within the bin. The high-resolution point cloud also generates accurate mapping of non-uniform and irregular surface geometries, which captures true depressions, peaks, and sloped regions that manual methods typically miss. A dedicated web application was developed to send commands to the system for automated scanning and real-time volume computation. Successful real-world testing showed the system’s reliability, with an accuracy level of 1.013 ± 0.70% MAPE across varied flour quantities and surface contours. Full article

Fractional derivatives introduce an effective mathematical structure to describe memory effects, long-range interactions, and anomalous transport processes that are not well represented by the traditional integer-order models. This paper presents the unidirectional fractional longitudinal wave equation as a governing equation where a model is proposed to explain the steady wave propagation of solitary waves in a magneto-electro-elastic circular rod. Magneto-electro-elastic substances are a groundbreaking category of advanced functional materials with tremendous nanotechnology and biomedical engineering prospects because of their effective multi-field energy conversion and temperature responsiveness. In order to solve this complicated fractional nonlinear equation, we introduce a new computation-analysis approach: the Riccati subequation neural network method. This hybrid solution is a synergistic combination of an analytical solution structure and a neural network structure consisting of input, hidden, and output layers, with interconnection between neurons through weighted connections and activation functions. It is important to note that every neuron in the first hidden layer is coupled to the solutions of the Riccati equation, and this allows the systematic use of the new trial functions. With the suggested method, analytical solutions are obtained for the spacetime fractional partial differential equations of the unidirectional fractional longitudinal wave equation in the exact form of trigonometric, hyperbolic, and rational functions. This paper is the first attempt to combine the Riccati subequation method with a neural network model, which has given rise to new types of solitary wave solutions. The three-dimensional, two-dimensional, and contour plots are used to visualize the dynamic nature of these solutions and to display the rich nonlinear wave behavior. The effectiveness and the robustness of the implemented technique is not only proven through our findings but also provides more profound information about the nonlinear wave phenomena in the advanced multifunctional materials, which can inform future developments in energy harvesting and the design of biomedical devices. Full article

Alumina is a commonly used ceramic material known for high permittivity, low dielectric loss, good thermal conductivity, and low cost. In the development of electronic devices, the size effect of powdery materials is crucial, particularly in applications involving composite materials. This study introduces the field-enhancement method (FEM) to measure the resonant frequency ($f_0$) and the quality factor (Q) of alumina powders packed in a Teflon container and placed on top of the central rod in the proposed cavity. The measured resonant condition ($f_0$ and Q) is mapped to a contour plot and simulated using a high-frequency structure simulator (HFSS). The contour mapping technique allows the researchers to obtain the effective complex permittivity of alumina–air composites. The complex permittivity of the alumina powder is retrieved using a hybrid model and the effective medium theories (EMTs), respectively. The Landau–Lifshitz–Looyenga (LLL) model is compared with the results using the hybrid model for its applicability. The dielectric constant and the loss tangent of the alumina powder are found to increase as the powder size reduces. A power relation is found to fit the obtained permittivity, covering sizes ranging from nanometers to micrometers, and a surface-charge scaling argument is proposed to explain the observed trend. This finding opens a new avenue for manipulation of permittivity in composite materials and has potential applications in stealth/absorber technology and as a self-limiter for grain growth during sintering. Full article

Objective: Lumbar interbody fusion (LIF) is widely used to treat degenerative spinal disorders; however, both fixation strategies and interbody Cage designs still present biomechanical limitations. This study aimed to develop a posterior lumbar interbody fusion Cage using topology optimization and to compare the biomechanical performance of oblique pedicle screw fixation with conventional fixation. Methods: A validated three-dimensional nonlinear finite element model of the L1–L5 lumbar spine was established based on CT data. A two-step weighted topology optimization was applied to the L3–L4 interbody Cage to determine both the external contour and the internal bone graft window. Finite element models with oblique pedicle screw fixation and conventional pedicle screw–rod fixation were constructed and evaluated under static physiological loads and whole-body vibration conditions. Results: Compared with the conventional Cage, the topology-optimized Cage combined with oblique fixation significantly reduced the maximum von Mises stress on adjacent endplates and decreased Cage displacement under both static and dynamic loading. Although stresses in the Cage and screws increased relative to traditional fixation, all values remained well below material yield limits. Conclusions: The combination of a topology-optimized Cage and oblique pedicle screw fixation improves load transfer and structural stability while reducing the risk of endplate damage and Cage subsidence. This approach provides a promising alternative design strategy for posterior lumbar interbody fusion. Full article

Patient-specific technologies within the field of adult spinal deformity (ASD) aid surgeons in pre-surgical planning, accurately help identify anatomical landmarks, and can project optimal post-surgical sagittal alignment. This narrative review aims to discuss the current uses of patient-specific technologies in ASD and identify new innovations that may very soon be integrated into patient care. Pre-operatively, machine learning or artificial intelligence helps surgeons to simulate post-operative alignment and provide information for the 3D-printing of pre-contoured rods and patient-specific cages. Intraoperatively, robotic surgery and intraoperative guides allow for more accurate positioning of implants. Implant materials are being developed to allow for better osseointegration and patient outcome monitoring. Despite the significant promise of these technologies, work still needs to be performed to ensure their accuracy, safety, and cost efficacy. Full article

Prestressed concrete structures are facing serviceability challenges due to rising live loads, material degradation, and seismic demands. Retrofitting with carbon fiber-reinforced polymer (CFRP) offers a cost-effective alternative to full replacement. This study presents a finite element (FE) modeling framework to simulate the seismic performance of prestressed concrete T-beams retrofitted in the negative moment region using near-surface-mounted (NSM) CFRP rods and sheets. The model incorporates nonlinear material behavior and cohesive interaction at the CFRP–concrete interface and is validated against experimental benchmarks, with ultimate load prediction errors of 4.41% for RC T-beams, 0.49% for prestressed I-beams, and 1.30% for prestressed slabs. A parametric investigation was conducted to examine the influence of CFRP embedment depth and initial prestressing level under three seismic conditions. The results showed that fully embedded CFRP rods consistently improved the beams’ ultimate load capacity, with gains of up to 10.84%, 16.84%, and 14.91% under cyclic loading, near-fault ground motion, and far-field ground motion, respectively. Half-embedded CFRP rods also prove effective and offer comparable improvements where full-depth installation is impractical. The cyclic load–displacement histories, the time–load histories under near-fault and far-field excitations, stiffness degradation, and damage contour analysis further confirm that the synergy between full-depth CFRP retrofitting and optimized prestressing enhances structural resilience and energy dissipation under seismic excitation. Full article

This study proposes the use of a low-symmetry hexagonal photonic crystal (LSHPC) incorporating Kerr-type nonlinearity to enhance self-collimation. The equifrequency contours (EFCs) of a C₂-symmetric LSHPC composed of nonlinear LiNbO₃ rods are analyzed as a function of the nonlinear refractive index. The self-collimation characteristics, transmission spectrum, group velocity dispersion (GVD), and third-order dispersion (TOD) are investigated using the Plane Wave Expansion (PWE) and Finite Difference Time Domain (FDTD) methods. The results demonstrate that increasing the nonlinear index leads to a significant flattening of the EFCs, which enhances self-collimation performance. Furthermore, symmetry-lowering perturbations improve beam confinement and enable all-angle self-collimation. These findings highlight the potential of Kerr-type nonlinear photonic crystals for integrated photonic circuits requiring precise control over light propagation. Full article

Background/Objectives: Proximal junctional kyphosis (PJK) is one of the most frequently discussed complications following corrective surgery in patients with neuromuscular scoliosis (NMS). Despite its clinical relevance, the etiology of PJK remains incompletely understood and appears to be multifactorial. Biomechanical and limited clinical studies suggest that preoperative hyperkyphosis, resection of the spinous processes with consequent disruption of posterior ligamentous structures, and rod contouring parameters may contribute as risk factors. Methods: To validate these findings, we retrospectively analyzed 99 NMS patients who underwent posterior spinal fusion using a standardized screw-rod system between 2009 and 2017. Radiographic assessments were conducted at three time points: preoperatively (preOP), postoperatively (postOP), and at a mean follow-up (FU) of 29 months. Clinical variables collected included patient age, weight, height, sex, and Risser sign. Radiographic evaluations encompassed Cobb angles, thoracic kyphosis (TK), lumbar lordosis, the levels of the upper (UIV) and lower (LIV) instrumented vertebrae, the total number of fused segments, parameters of sagittal alignment, the rod contour angle (RCA), and the postoperative mismatch between RCA and the proximal junctional angle (PJA). Based on the development of proximal junctional kyphosis, patients were categorized into PJK and non-PJK groups. Results: The overall incidence of PJK was 23.2%. In line with previous biomechanical findings, spinous process resection was significantly associated with PJK development. Furthermore, the PJK group demonstrated significantly higher preoperative TK (59.3° ± 29.04° vs. 34.5° ± 26.76°, p < 0.001), greater RCA (10.2° ± 4.01° vs. 7.7° ± 4.34°, p = 0.021), and a larger postoperative mismatch between PJA and RCA (PJA−RCA: 3.8° ± 6.76° vs. −1.8° ± 6.55°, p < 0.001) compared to the non-PJK group. Conclusions: Spinous process resection, a pronounced mismatch between postoperative PJA and RCA (odds ratio [OR] = 1.19, p = 0.002), excessive rod bending (i.e., high RCA), and severe preoperative thoracic hyperkyphosis with an expected increase in the risk of PJK of approximately 6.5% per degree of increase in preoperative TK are significant risk factors for PJK. These variables should be carefully considered during the surgical planning and execution of deformity correction in NMS patients. Full article

Eccentric camshaft components serve as critical elements in emergency pump systems for commercial vehicle steering mechanisms. To optimize material utilization efficiency, reduce production costs, and enhance manufacturing throughput, this investigation implemented a vertical upsetting extrusion forming methodology for camshaft forging production. Initial trials revealed defect formation in forged components. By analyzing the causes of the defects, an improved process method was developed to eliminate them. The chemical composition, macroscopic and microscopic morphologies of defects, forging process, and metal streamlines were analyzed and studied by means of a direct reading spectrometer, high-resolution camera, metallographic microscope, DEFORM finite element analysis software, and chemical etching. Findings indicate that the observed defects constitute forging-induced cracks, with subsequent normalizing heat treatment exacerbating decarburization phenomena in defect-adjacent microstructures. During the forging process of the forgings, the metal continuously extruded into the die cavity, and the inflowing metal pulled the dead zone metal downward, causing the flow lines aligned with the contour to bend into S-shaped metal streamlines. Cracks formed when the tensile stress in the dead zone metal exceeded the material’s critical tensile stress. An improved process was proposed: adopting a vertical upsetting extrusion forming method with a 40° diversion angle at the junction between the first step and the thin rod in the die cavity. Numerical simulations confirmed complete elimination of deformation dead zones in the optimized process. Experimental verification demonstrated crack-free forgings. Therefore, the eccentric camshafts formed by the initial process exhibited forging cracks, and the proposed improved method of vertical upsetting extrusion forming with a diversion angle effectively eliminated the forging cracks. Full article

In the present work, the effect of different casting processes on the microstructure and creep properties of the second-generation single-crystal superalloy DD419 was investigated. Under conventional production conditions and a contour-suited thermal insulation method, single-crystal rods of types A and B were fabricated, respectively. In comparison to rod type A, the solidification process of rod type B featured a 1.6-fold increase in the temperature gradient and a 32% reduction in primary dendrite spacing. The γ/γ′ eutectic in the as-cast microstructure, the residual eutectic phase, and porosity after heat treatment were also significantly reduced, resulting in the improved homogeneity of the single crystal castings. Under the testing conditions of 850 °C/650 MPa and 1050 °C/190 MPa, the stress rupture life of sample B was enhanced by 25% and 5.2%, respectively, compared to sample A. Therefore, due to dendrite structure refinement, the stress rupture life of the superalloy was evidently improved, especially at medium temperatures. Full article

In order to improve the shelling efficiency of peanuts, the fracture mechanism of peanuts and the key components of the shelling test bench were studied. Firstly, the finite element method based on the cohesive element model was used to analyze the crack propagation of peanuts; the energy required for peanuts to crack was 0.06 J, and the maximum loading force was 30 N. Combined with the physical properties, mechanical properties, and shell-breaking energy of peanuts, the parameters of the two key components of the shell-breaking device and the adjustable grinding device were designed. The loading angle of the shell-breaking device was 30°, the mass of the rod was 1.5 kg, the mass of the hammer was 0.1 kg, the total length was 0.25 m, and the external contour of the grinding device was triangular. Through the field experiment, the single-factor test and the three-factor three-level regression test were designed, respectively, and the regression model of the removal rate and the damage rate was established. According to the response surface analysis of the regression model, when the feeding quantity is 12 pods/s, the speed of gear is 250 revolutions per minute, and the shelling clearance is 9.23 mm; the peanut removal rate reached 95.61%, and the kernel damage rate was 5.41%. However, the feeding amount was low and the damage rate was high, which could provide a reference for the future seed peanut sheller. Full article

This article presents the results of an experimental study of the coolant flow in a fuel rod bundle of a nuclear reactor fuel assembly of a small modular reactor for a small ground-based nuclear power plant. The aim of the work is to experimentally determine the hydrodynamic characteristics of the coolant flow in a fuel rod bundle of a fuel assembly. For this purpose, experimental studies were conducted in an aerodynamic model that included simulators of fuel elements, burnable absorber rods, spacer grids, a central displacer, and stiffening corners. During the experiments, the water coolant flow was modeled using airflow based on the theory of hydrodynamic similarity. The studies were conducted using the pneumometric method and the contrast agent injection method. The flow structure was visualized by contour plots of axial and tangential velocity, as well as the distribution of the contrast agent. During the experiments, the features of the axial flow were identified, and the structure of the cross-flows of the coolant was determined. The database obtained during the experiments can be used to validate CFD programs, refine the methods of thermal-hydraulic calculation of nuclear reactor cores, and also to justify the design of fuel assemblies. Full article

In order to improve the accuracy of a solar-powered punch card car’s movement on a designated route and reduce positional deviations during its operation, a solar-powered punch card car with a single cam as the steering guidance mechanism was designed. The car adopts a three-wheel structure. The transmission mechanism, steering mechanism, driving mechanism, and regulating mechanism of the car were analyzed. The kinematics model of the car was established and the motion characteristics of the car were obtained. By analyzing the relationship between the steering angle of the car and the curvature radius of its travel route, the front wheel angle of the car at each position was calculated using MATLAB R2020a. This allowed us to establish the relationship between the front wheel angle and the displacement of the steering push rod, which was further converted into the theoretical contour line of the cam. Subsequently, the theoretical contour line of the cam was completed and envelope correction was performed. Finally, through mechanical analysis and experimental verification using a prototype, the results indicated that the single-cam steering guidance mechanism calculated using this fast path fitting method exhibited excellent mechanical performance and a smooth and accurate trajectory, and the traveling path of the theoretical cam contour curve was basically consistent with the actual trajectory route. Full article