Vertical Axis Research Articles

Automated spinopelvic measurements on radiographs with artificial intelligence: a multi-reader study.

To develop an artificial intelligence (AI) algorithm for automated measurements of spinopelvic parameters on lateral radiographs and compare its performance to multiple experienced radiologists and surgeons. On lateral full-spine radiographs of 295 consecutive patients, a two-staged region-based convolutional neural network (R-CNN) was trained to detect anatomical landmarks and calculate thoracic kyphosis (TK), lumbar lordosis (LL), sacral slope (SS), and sagittal vertical axis (SVA). Performance was evaluated on 65 radiographs not used for training, which were measured independently by 6 readers (3 radiologists, 3 surgeons), and the median per measurement was set as the reference standard. Intraclass correlation coefficient (ICC), mean absolute error (MAE), and standard deviation (SD) were used for statistical analysis; while, ANOVA was used to search for significant differences between the AI and human readers. Automatic measurements (AI) showed excellent correlation with the reference standard, with all ICCs within the range of the readers (TK: 0.92 [AI]vs. 0.85-0.96 [readers]; LL: 0.95 vs. 0.87-0.98; SS: 0.93 vs. 0.89-0.98; SVA: 1.00 vs. 0.99-1.00; all p < 0.001). Analysis of the MAE (± SD) revealed comparable results to the six readers (TK: 3.71° (± 4.24) [AI] v.s 1.86-5.88° (± 3.48-6.17)[readers]; LL: 4.53° ± 4.68 vs. 2.21-5.34° (± 2.60-7.38); SS: 4.56° (± 6.10) vs. 2.20-4.76° (± 3.15-7.37); SVA: 2.44mm (± 3.93) vs. 1.22-2.79mm (± 2.42-7.11)); while, ANOVA confirmed no significant difference between the errors of the AI and any human reader (all p > 0.05). Human reading time was on average 139s per case (range: 86-231s). Our AI algorithm provides spinopelvic measurements accurate within the variability of experienced readers, but with the potential to save time and increase reproducibility.

Complete 3D photoelectron momentum vector reconstruction from time-position charged particle imaging

Abstract Many charged particle imaging techniques exist which directly measure, at a detector, the transverse position (x, y) and time-of-flight (t) of individual events in order to obtain a full set of 3D coordinates. Where curved velocity-mapping electric field lines are implemented, as in the case of 3D Velocity Map Imaging (3D VMI) and certain COLTRIMS (Cold Target Recoil Ion Momentum Spectroscopy) instruments, the general transformation of (x, y, t)-data into initial 3D recoil momentum vectors (px , py , pz ) is challenging and has not yet been fully addressed. Here we present a detailed and general method for this transformation, illustrated using our 3D VMI spectrometer and the well-known narrow-band photoionization of nitric oxide, for which we demonstrate quantitative agreement with reported values. We additionally show how to measure and correct (i) small errors in the laser polarization axis alignment at the interaction region of a 3D charged particle imaging spectrometer, and (ii) the spatial variation of gain on a microchannel plate (MCP) detector. Improvements to and characterization of our 3D VMI spectrometer yield an electron time-of-flight resolution of 72 ps across the full 40 mm MCP, in combination with pixel-level spatial resolution.

Single-Step Production of Doubly Re-entrant Microstructures Through Reaction-Diffusion Photolithography for Omniphobic Surfaces.

Omniphobic surfaces, which repel virtually any liquid regardless of its wettability, have been developed using doubly re-entrant microstructures. Although various microfabrication techniques have been explored, these often require multiple complex steps. In this study, reaction-diffusion photolithography (RDP) is used to fabricate micropost arrays with doubly re-entrant geometries through a single-step ultraviolet (UV) exposure process. To create a doubly re-entrant structure consisting of a central, elongated micropost topped with a short ridge, a photomask featuring a circular window surrounded by a narrow ring-shaped window is employed. This configuration is utilized in the RDP process, which relies on radical polymerization. Vertical growth of the structure from the photomask is achieved by introducing strong UV attenuation along the vertical axis, enabled by increasing the photoinitiator concentration. Concurrently, the growth of the ridge is slowed down by designing the ring window with minimal dimensions. This promotes rapid oxygen diffusion into the ring region, where the radicals generated by UV exposure are consumed through reactions with oxygen, thereby delaying the polymerization. This approach enables precise fabrication of full-length central microposts with short ridges in a single step. The resulting doubly re-entrant structures show high contact angles across various liquids and exhibit robust omniphobic performance.

Risk factors for mechanical complications in degenerative lumbar scoliosis with concomitant thoracolumbar kyphosis: does the selection of the upper instrumented vertebra matter?

BackgroundDegenerative lumbar scoliosis (DLS) represents a distinct subset of adult spinal deformity, frequently co-occurring with thoracolumbar kyphosis (TLK) in the sagittal plane. TLK is typically viewed as detrimental in degenerative spinal conditions and has been linked to increased pain severity and a higher prevalence of mechanical complications (MC) as previously reported. The present study aimed to identify the risk factors associated with the development of MC in patients with DLS and concomitant TLK.MethodsThis study retrospectively included 65 DLS patients with a TLK > 20°. During follow-up, MC events were recorded, and patients were categorized into MC and non-MC groups. Spinopelvic parameters were assessed pre- and post-surgery. The locations of the kyphotic apex (KA) and the upper instrumented vertebra (UIV) were documented. Clinical and radiographic data were compared between the two groups. A multivariate logistic regression model was employed to analyze the independent risk factors for MC.ResultsTwenty-nine (44.6%) patients developed at least one MC at final follow-up. At baseline, patients in the MC group exhibited lower bone mineral density (P = 0.002), lower distal lumbar lordosis (DLL, P = 0.025), and higher sagittal vertical axis (SVA, P = 0.005). Post-surgery, the KA shifted cranially with an average vertebral displacement of 2.6 ± 1.8. The proportion of UIV located in the postoperative KA area significantly increased (P < 0.001). The MC group had a higher incidence of Roussouly type mismatch (P = 0.023) and UIV located in the KA area (P = 0.003). Multivariate logistic regression analysis revealed that UIV located in the KA area (OR = 3.798, P = 0.043), increased preoperative SVA (OR = 1.017, P = 0.016) and osteoporosis (OR = 6.713, P = 0.007) were independent risk factors for MC.ConclusionsThe presence of UIV in the KA area, preoperative sagittal imbalance, and osteoporosis were identified as significant risk factors for MC in patients with DLS and concomitant TLK. The spinal morphological characteristics of TLK must be taken into account during surgical planning to prevent placing the UIV within the kyphotic region.

Machine Learning-based Cluster Analysis Identifies Three Unique Phenotypes of Patients With Adult Spinal Deformity With Distinct Clinical Profiles and Long-term Recovery Trajectory: A Development Study.

A retrospective review of a prospective adult spinal deformity data. To identify distinct patient clinical profiles and recovery trajectories in patients with adult spinal deformity (ASD). Patients with ASD exhibit a diverse array of symptoms and significant heterogeneity in clinical presentations, posing challenges to precise clinical decision-making. Accurate patient selection may provide further insight to personalized management strategies. Latent profile analysis (LPA) was performed to determine possible patient phenotype. Goodness-of-fit indices were used to determine the optimal cluster profiles. Outcome differences were evaluated using Analysis of Variance (ANOVA) and subsequent post hoc Tukey's test, while significant predictors of group membership were identified through multinomial logistic regression. A total of 204 ASD patients (mean age of 60.3 ± 11.8 years, comprising 62.3% females) with complete 1-year and 2-year follow-up outcome were included. LPA identified three phenotypes: 51 patients in phenotype 1, 73 patients in phenotype 2 and 80 patients in phenotype 3, respectively. Each phenotype exhibited a unique symptom profile and distinct functional recovery trajectories. Patients in phenotype 3, although demonstrated the worst Scoliosis Research Society-22 questionnaire (SRS-22r) domains at baseline, patients in this cluster exhibited the most substantial Δchange in SRS-22r domains except for self-image at both 1-year and 2-year follow-up. Remarkably, a relative large proportion of patients (58.8%) who were dissatisfied at 1-year follow-up transited to satisfied at 2-year follow-up. Advanced age, longer symptom duration, severe preoperative pelvic incidence-lumbar lordosis (PI-LL) mismatch, higher preoperative sagittal vertical axis (SVA), fusion extending to sacrum/pelvis and grade ≥ 3 osteotomy predicted membership in the phenotype 3. LPA enabled the delineation of three distinct phenotypes among ASD patients, each characterized by unique clinical profiles and distinct long-term recovery trajectories. By pinpointing the crucial variables that uniquely distinguish and predict membership in different phenotypes, the study provides valuable guidance for patient stratification.

MVGNN-PPIS: A novel multi-view graph neural network for protein-protein interaction sites prediction based on Alphafold3-predicted structures and transfer learning.

Protein-protein interactions (PPI) are crucial for understanding numerous biological processes and pathogenic mechanisms. Identifying interaction sites is essential for biomedical research and targeted drug development. Compared to experimental methods, accurate computational approaches for protein-protein interaction sites (PPIS) prediction can save significant time and costs. In this study, we propose a novel model named MVGNN-PPIS. To the best of our knowledge, it is the first to utilize predicted structures generated by AlphaFold3, and combined with transfer learning techniques, for predicting PPIS. This approach addresses the limitations of traditional methods that depend on native protein structures and multiple sequence alignments (MSA). Additionally, we introduced a multi-view graph framework based on two types of graph structures: the k-nearest neighbor graph and the adjacency matrix. By alternately employing a Graph Transformer and Graph Convolutional Networks (GCN) to aggregate node information, this framework effectively captures both local and global dependencies of each residue in the predicted structures, thereby significantly enhancing the model's sensitivity to binding sites. This framework further integrates direction, distances and angular information between the 3D coordinates of side-chain atom centroids to construct a relative coordinate system, generating enhanced edge features that ensure the model's equivariance to molecular translations and rotations in space. During training, the Focal Loss function is employed to effectively address the class imbalance in the dataset. Experimental results demonstrate that MVGNN outperforms the current state-of-the-art methods across multiple PPIS benchmark datasets. To further validate the model's generalization capability, we extended MVGNN to the domain of predicting protein-nucleic acid interaction sites, where it also achieved superior performance.

Exploring chaos and stability: dynamic insights into the stochastic Davey-Stewartson system through advanced sensitivity analysis

In this study, we investigate the stochastic Davey-Stewartson equation in the presence of noise. These two-dimensional integrable equations are higher-dimensional versions of the nonlinear Schrödinger equation. Davey-Stewartson equations are important in plasma physics, nonlinear optics, hydrodynamics, and other disciplines because the solutions they provide are valuable in understanding many complex physical phenomena. We employ a modified version of the G′G2 approach to handle variable-coefficient systems with imaginary components, such as nonlinear Schrödinger systems. We have discovered a wide range of precise traveling wave solutions, including solitons, kink, periodic, and rational solutions. These solutions may have a significant impact in the domains of engineering and plasma physics. The presented techniques effectively achieve a variety of exponential solutions, including bright, dark, single, rational, and periodic solitary wave solutions. We used MATLAB to simulate our findings and provide 3D, 2D, and counter graphs that illustrate the impact of noise on the precise solutions of the stochastic Davey-Stewartson problem. We apply the Galilean transformation to derive the planar dynamical system, which enhances our understanding of the system’s dynamical analysis. We also conduct a sensitivity analysis to observe the systematic response to various initial conditions. This analysis focuses on the symmetrical aspects of the system and includes the illustration of phase portraits with equilibrium points. We also investigate the chaotic behavior of the planer dynamical system by introducing an additional external force. We predict the system’s behavior to increase the value of intensity and frequency. Our analysis reveals periodic, quasi-periodic, and chaotic processes.

Accelerometric assessment of fatigue-induced changes in swimming technique in high performance adolescent athletes

The present study analyzed the kinematic changes under fatigue in highly trained adolescent swimmers during a 50-m all-out front cwal test. Twenty-four girls and fourteen boys aged 12–13 participated in the study. The movement of the hip rim was analyzed using a specialized inertial device equipped with a triaxial gyroscope and accelerometer to measure changes in angular velocity and acceleration. Between the first and second lengths of the pool, the following were observed: a significant (F1.36 = 63.6; p < 0.0001; η2 = 0.64) increase (34%) in maximum pelvic angle, significant (F1,36 = 6.0; p = 0.0193; η2 = 0.14;) increase (12.10%) in angular velocity in rotational motion around a vertical axis, and a significant (F1,36 = 11.29; p = 0.0018; η2 = 0.24) increase (6.86%) in angular velocity in yaw rotation motion around the sagittal axis. Significant (F1,36 = 13.96; p = 0.0006; η2 = 0.28) differences in maximum pelvic angle were observed for lap and side. As unfavourable changes in kinematics are already observed in the second half of the distance, it is therefore suspected that performing frequent high-intensity repetitions may lead to the perpetuation of unfavourable movement patterns. Taking this into account, coaches should limit maximum-speed swimming in adolescent athletes to short distances and an appropriate interval and use training methods to reduce asymmetric work such as training snorkels.

Correlation analysis of global sagittal alignment of the spine in cases of low-grade degenerative lumbar spondylolisthesis.

Disruptions in global sagittal spinal alignment can lead to changes in global sagittal spinal alignment, often manifesting as sagittal malalignment, where the trunk shifts forward. We proposed that these alignment changes are linked to degenerative lumbar spondylolisthesis (DS). The objective was to assess global spinal alignment in low-grade DS using sagittal vertical axis (SVA) classification. The patients with DS were categorized into three groups based on the adult spinal deformity classification: type I, defined by a SVA of less than 40mm; type II, with an SVA ranging from 40mm to 95mm; and type III, where the SVA is 95mm or greater. The study compared age and various sagittal parameters among these groups, including thoracic kyphosis (TK), lumbar lordosis (LL), sacral slope (SS), pelvic tilt (PT), and pelvic incidence (PI). Notable differences were observed between type I and type II, as well as between type I and type III, whereas no substantial variation was detected between type II and type III. Additionally, PI increased with advancing type classification, with a distinct contrast observed between type I and type III. A high PI is a key risk factor for worsening SVA in DS, and it may contribute to the initiation and progression of the condition.

Investigation of the Structural Characteristics of the Gas Diffusion Layer Using Micro-X-Ray Computed Tomography

Due to its low stiffness, the gas diffusion layer (GDL) exhibits significant deformation under a compression service condition, thereby exerting a nonlinear and strong coupling influence on fuel cells’ performance. Therefore, it is of great practical significance to study the structural characteristics evolution of GDLs. The microstructure of the GDLs was obtained using micro-X-ray computed tomography in this study, and their structural properties were analyzed comprehensively and quantitatively. The morphology of GDLs exhibited significant variations across manufacturers due to disparities in the materials and manufacturing processes. The distribution of the pore equivalent diameter and sphericity in GDLs conformed to a normal distribution, with irregular shapes. The fiber length distribution in the unit followed a Gamma distribution, showing a random and uneven distribution in the XY plane. When compressed, the average fiber length was reduced, and a substantial increase in isolated pores was observed. However, the quantity of long fibers and connected and isolated pores decreased after acidification treatment.

Unusual variability of isomers in copper(II) complexes with 1,8-bis(2-hydroxybenzyl)-cyclam.

Copper isotopes and their complexes are intensively studied due to their high potential for applications in radiodiagnosis and radiotherapy. Here, we study the CuII complex of 1,8-bis(2-hydroxybenzyl)-cyclam (H2L), which forms an unexpected variety of isomers differing in the mutual orientation of the substituents on the cyclam nitrogen atoms, the protonation of the phenolate pendant, and the ligand denticity. The interconversion of the isomers is rather slow, which made the isolation, identification and investigation of some of the individual species possible. The most stable and the most common form is the hexacoordinated trans-III isomer. However, several other forms were also observed in solution in the course of HPLC, UV-VIS and electrochemical measurements. The isomers present in solution were identified by comparison with the solid-state structures solved by X-ray diffraction analysis on single crystals and with the help of theoretical calculations. The phenolate pendant is coordinated both in the protonated and deprotonated state; however, the coordination in the axial position of the hexacoordinated trans-III complex is weak, especially in its protonated state. Conversely, the CuII ion is pentacoordinated in the cis-V isomer with only one phenolate strongly coordinated in the basal plane of the distorted tetragonal pyramid. The computational data showed that the phenolate groups might form strong intraligand hydrogen bonds competitive with the metal-phenolate bonds, stabilizing the structure of the complex. In addition, theoretical calculations revealed that several geometries are energetically close to the optimal one, which indicates possible dynamic behaviour of the complex in solution.

Eye lens dosimetry: does the direction of rotation (vertical or horizontal) play a role in type testing?

With the International Commission on Radiological Protection (ICRP) lowering the annual dose limit for the eye lens to 20 mSv, precise monitoring of eye lens exposure has become essential. The personal dose equivalent at a depth of 3 mm, Hp(3), is the measurement method for monitoring the dose to the lens of the eye. Traditional dosimetry methods primarily address lateral radiation exposure scenarios, where radiation approaches from the left or right, necessitating the rotation of the phantom during type testing around the vertical axis. However, these methods do not adequately account for bottom-to-top radiation exposures which are common in real-world situations (such as radiation scattered by the patient reaching medical staff).&#xD;This study examines oblique radiation exposure conditions using a typical eye lens thermoluminescent dosemeter (TLD), Eye-D, placed on a cylindrical phantom to assess dose responses at different angles and exposure energies. The study employs both lower-energy (N-30 radiation quality) and higher-energy (N-100 radiation quality) X-rays at irradiation angles of -60°, 0°, and +60°, measured along the vertical and horizontal rotation axes of the phantom.&#xD;The results show no significant differences between horizontal and vertical (polar and radial) rotation orientations of the dosemeter-phantom setup: recorded relative doses stayed well within ±1%, i.e., by far within the attributed combined uncertainty of ±2%.&#xD.

BoundMPC: Cartesian path following with error bounds based on model predictive control in the joint space

This work introduces the BoundMPC strategy, an innovative online model-predictive path-following approach for robot manipulators. This joint-space trajectory planner allows the following of Cartesian reference paths in the end-effector’s position and orientation, including via-points, within the desired asymmetric bounds of the orthogonal path error. These bounds encode the obstacle-free space and additional task-specific constraints in Cartesian space. Contrary to traditional path-following concepts, BoundMPC purposefully deviates from the Cartesian reference path in position and orientation to account for the robot’s kinematics, leading to more successful task executions for Cartesian reference paths. Furthermore the simple reference path formulation is computationally efficient and allows for replanning during the robot’s motion. This feature makes it possible to use this planner for dynamically changing environments and varying goals. The flexibility and performance of BoundMPC are experimentally demonstrated by five scenarios on a 7-DoF Kuka LBR iiwa 14 R820 robot. The first scenario shows the transfer of a larger object from a start to a goal pose through a confined space where the object must be tilted. The second scenario deals with grasping an object from a table where the grasping point changes during the robot’s motion, and collisions with other obstacles in the scene must be avoided. The adaptability of BoundMPC is showcased in scenarios such as the opening of a drawer, the transfer of an open container, and the wiping of a table, where it effectively handles task-specific constraints. The last scenario highlights the possibility of accounting for collisions with the entire robot’s kinematic chain. The code is readily available at https://github.com/TU-Wien-ACIN-CDS/BoundMPC , inspiring you to explore its potential and adapt it to your specific robotic tasks.

Surface Morphology and Remaining Geometric Parameters of Corroded Members on Bailey Truss

Abstract Bailey truss has been widely used in temporary constructional structures of bridges, and is reusable. In the service duration, Bailey truss is commonly exposed to corrosion threats due to the failure of anti-corrosion coatings, resulting in corrosion damage on members which induces degradation of its structural behavior. This paper presents an investigation on the corrosion damage of a Bailey truss which had been in service for eight years in the Northeast China. A total of 18 member segments were obtained from the chords, diagonals, and verticals of the Bailey truss, and were scanned by a 3D laser scanner after clearing the paint and rust. Then reverse modeling was performed based on the 3D coordinates of the specimen surfaces. The surface topography was discussed for different members on the basis of the separated roughness component, the residual thickness was analyzed for plates, and the residual cross-sectional area and moment of inertia about axes of the members were calculated and discussed. Coupon tests were carried out on corroded specimens from chords, diagonals, and verticals to quantitatively analyze the degradation of corroded Bailey truss. It was found that the corrosion damage on flanges was more severe than that on webs, in terms of the surface roughness and thickness loss. The corrosion status can be influenced by the microstructures and serving location. Upon the true values of the remaining cross-sections, it was concluded that the chords, diagonals, and verticals of the Bailey truss all exhibited the largest loss ratio in moment of inertia about y axis and the smallest loss ratio in cross-sectional area. The vertical member had the largest dispersion of average nominal loss rates, especially for moment of inertia about y axis, whose maximum and minimum values differed by 157.1%. A practical method for estimating the residual cross-sectional area and moment of inertia was validated. In addition, the engineering mechanical parameters (the elastic modulus, yield strength, ultimate strength, and the elongation after fracture) of each member basically show linear degradation. The mechanical parameters of diagonal web are most affected by corrosion. There is 10% thickness loss in chord web with up to 27% loss bearing capability in 8 years, and the factor of safety with respect to a reference parameter is lowered.

Machine learning analysis of cervical balance in early-onset scoliosis post-growing rod surgery: a case-control study

We aimed to analyze the cervical sagittal alignment change following the growing rod treatment in early-onset scoliosis (EOS) and identify the risk factors of sagittal cervical imbalance after growing-rod surgery of machine learning. EOS patients from our centre between 2007 and 2019 were retrospectively reviewed. Radiographic parameters include the cervical lordosis (CL), T1 slope, C2-C7 sagittal vertical axis (C2-7 SVA), primary curve Cobb angle, thoracic kyphosis (TK), C7-S1 sagittal vertical axis (C7-S1 SVA) and proximal junctional angle (PJA) were evaluated preoperatively, postoperatively and at the final follow-up. The parameters were analyzed using a t-test and χ2 test. The machine learning methodology of a sparse additive machine (SAM) was applied to identify the risk factors that caused the cervical imbalance. 138 patients were enrolled in this study (96 male and 42 female). The mean thoracic curve Cobb angle was 67.00 ± 22.74°. The mean age at the first operation was 8.5 ± 2.6yrs. The mean follow-up was 38.48 ± 10.87 months. CL, T1 slope, and C2-7 SVA increased significantly in the final follow-up compared with the pre-operative data. (P < 0.05). The CL and T1 slope increased more significantly in the group of patients who had proximal junctional kyphosis (PJK) compared with the patients without PJK (P < 0.05). The location of the upper instrumented vertebrae (UIV) and single/dual growing rod had no significant influence on the sagittal cervical parameters (P > 0.05). According to the SAM analysis of machine learning algorithms, Postoperative PJK, more improvement of kyphosis, and T1 slope angle were identified as the risk factors of cervical sagittal imbalance during the treatment of growing rod surgery. The growing rod surgery in EOS significantly affected the cervical sagittal alignment. Postoperative PJK and more improvement of kyphosis and T1 slope angle would lead to a higher incidence of cervical sagittal imbalance.

Long-term Postural Stability Changes After Correction of Spinal Deformity: A prospective, controlled pilot study.

Prospective cohort study. This study aimed to investigate the durability of postural stability after ASD correction surgery and its' association with clinical outcomes. The prevalence of symptomatic adult spinal deformity (ASD) necessitates surgical intervention, aiming to correct global spinal balance and spinopelvic parameters. Short-term studies have shown improvements in postural control following surgery, but the long-term impact remains unclear. This single-center prospective cohort study included adult patients undergoing long-segment fusion surgery between November 2019 and July 2021. Preoperative and postoperative balance assessments, radiographic analyses, and patient-reported outcome measures (PROMs) were conducted. Statistical analyses evaluated changes in postural stability and clinical outcomes. Fifteen ASD patients were analyzed. Significant improvements were observed in the early postoperative period in coronal center of pressure (COP) sway (P=0.048) and amplitude (P=0.027), total COP sway (P=0.042), coronal center of gravity (COG) amplitude (P=0.013), total COG sway (P=0.044), and head sway in the coronal plane (P=0.025). These improvements were maintained at the final postoperative visit for all measurements except coronal COG amplitude (early vs. last postoperative visit, P=0.040). Radiographic parameters, including pelvic incidence - lumbar lordosis mismatch (P=0.041) and sagittal vertical axis (P=0.032), also significantly improved postoperatively. PROMs revealed significant enhancements in VAS back pain (P=0.045), RAND SF-36 pain (P=0.016), RAND SF-36 physical functioning (P=0.008), and PROMIS pain interference (P=0.032) scores at the last follow-up. These results demonstrate that the postural stability improvements seen after ASD correction are durable and correlate with enhanced clinical outcomes, such as reduced back pain and improved physical functioning. These findings underscore the clinical importance of achieving sagittal alignment in ASD patients. Further research with larger cohorts and extended follow-up periods is warranted to confirm these associations and establish postural stability assessment as a vital parameter in evaluating patients' quality of life postoperatively. Level 3.

A Graph Neural Network-Based Approach to XANES Data Analysis.

The determination of three-dimensional structures (3D structures) is crucial for understanding the correlation between the structural attributes of materials and their functional performance. X-ray absorption near edge structure (XANES) is an indispensable tool to characterize the atomic-scale local 3D structure of the system. Here, we present an approach to simulate XANES based on a customized 3D graph neural network (3DGNN) model, XAS3Dabs, which takes directly the 3D structure of the system as input, and the inherent relation between the fine structure of spectrum and local geometry is considered during the model construction. It turns out to be faster than the traditional XANES fitting method when the simulation approach and XANES optimization algorithm are combined to fit the 3D structure of the given system. The geometric features of the system are included in the weighted message passing block of XAS3Dabs and their importance is investigated. XAS3Dabs model demonstrates superior accuracy in XANES prediction compared to most machine learning models. By extracting graphs constituted by edges related to the absorbing atom, our model reduces redundant information, thereby not only enhancing the model's performance but also improving its robustness across different hyperparameters. XAS3Dabs model can be generalized to simulate the spectra for the systems with the absorber having the designed absorption edge so as to meet the expectations of online data processing. The method is expected to be the key part of the online 3D structure analysis framework for the XAS-related beamlines of high-energy photon source (HEPS) now under construction.

Paleomagnetic data from volcanic rocks in the southern Central Andes of Argentina and their implications for tectonics and geomagnetic field behavior

Abstract A paleomagnetic study of basaltic lava flows exposed in the northern Neuquén Cordillera, southernmost Central Andes, along the Antiñir-Copahue fault zone (ACFZ), involved 25 sites of the Cola de Zorro Formation (Pliocene–Early Pleistocene) along two different sections. The sites show exclusive normal polarity, corresponding to the Late Pliocene Gauss chron (3.6–2.6 Ma). The angular standard deviation of virtual geomagnetic poles (VGPs; ASD = 14.8°) is consistent with the expected values from recent geomagnetic models, in opposition to anomalously low dispersion found in previous studies in Pleistocene VGPs of reverse polarity from neighboring areas to our study zone. Mean paleomagnetic directions for Bella Vista (Dec = 0.0°, Inc = −50.0°, α₉₅ = 7.6°, K = 36.7, N = 11) and Río Huaraco sections (Dec = 354.9°, Inc = −57.0°, α₉₅ = 7.5°, K = 55.7, N = 8) do not show tectonic rotation around vertical axes. Combining and regrouping our and previous data by area confirmed the absence of tectonic rotations in the Huaraco-Trohunco block and a statistically significant clockwise rotation of 14.4° ± 10.3° of three adjacent tectonic blocks located south of our study locality in Pleistocene times. These results suggest that strike-slip deformation along some sections of the ACFZ was significant in the Pleistocene structural evolution of this region.

Analysis and Applications of Magnetically Coupled Resonant Circuits

Magnetically coupled resonant circuits have been utilized in radio engineering for many years. Recently, these circuits have found new applications, particularly in supplying low- and medium-power devices through medium-range wireless power transmission technology based on magnetic resonance coupling. There is also a growing need to analyze magnetically coupled resonant circuits in the design of metamaterials, which exhibit specific electromagnetic properties within certain frequency bands. This paper provides a coherent and concise overview of the phenomena associated with magnetically coupled resonant circuits. The results encompass numerous established relations as well as new ones. They can be helpful in the design phase of magnetically coupled resonant circuits. The outcomes include equations for determining the coupling resonant frequencies and some parameters of resonance curves. These analytical results are accompanied by 3D and cross-sectional (contour) graphs for better visualization. Moreover, a lumped-element circuit model that includes magnetically coupled resonant circuits is proposed for the resonators used in metamaterials. Formulas for resonant frequencies are derived in the specific case of exciting such resonators. To validate the accuracy of the derived equations, the analytical results are compared with simulations from SPICE (IsSPICE4 ver. 8.1) and COMSOL 5.4 software, which are widely used tools for circuit analysis and electromagnetic simulations. The results of these comparative analyses indicate that the assumptions employed in the analytical solutions introduce only tiny errors.

Artificial Intelligence (AI) and Learning Management Systems (LMS): A bibliometric analysis

The advent of Artificial Intelligence (AI) has transformed Learning Management Systems (LMSs), enabled personalized adaptation and facilitated distance education. This study employs a bibliometric analysis based on PRISMA-2020 to examine the integration of AI in LMSs from an educational perspective. Despite the rapid progress observed in this field, the literature reveals gaps in the effectiveness and acceptance of virtual assistants in educational contexts. Therefore, the objective of this study is to examine research trends on the use of AI in LMSs. The results indicate a quadratic polynomial growth of 99.42%, with the years 2021 and 2015 representing the most significant growth. Thematic references include authors such as Li J and Cavus N, the journal Lecture Notes in Computer Science, and countries such as China and India. The thematic evolution can be observed from topics such as regression analysis to LMS and e-learning. The terms e-learning, ontology, and ant colony optimization are highlighted in the thematic clusters. A temporal analysis reveals that suggestions such as a Cartesian plane and a league table offer a detailed view of the evolution of key terms. This analysis reveals that emerging and growing words such as Learning Style and Learning Management Systems are worthy of further investigation. The development of a future research agenda emerges as a key need to address gaps.